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### Residential Central Air Conditioners and Heat Pumps Preliminary Technical Support
Document The U.S. Department of Energy (DOE) prepared the preliminary technical support document (TSD) for the analyses conducted for its energy conservation standards rulemaking on residential central air conditioners and heat pumps to be published in 2011.

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z Title Page ( PDF 17 KB )

z List of Acronyms and Abbreviations ( PDF 15
KB )

z Executive Summary ( PDF
527 KB )

Chapters

z Chapter 1. Introduction ( PDF 107 KB )

z Chapter 2. Analytical Framework, Comments from Interested Parties, and DOE Responses ( PDF 401 KB )

z Chapter 3. Market and Technology Assessment ( PDF 612 KB )

z Chapter 4. Screening EERE Information Center Programs and Offices Pa g e 1 of 4 A pp liances and Commercial E q ui p ment Standards: Residentia l Central Air Conditioners ...

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_ 031010.ht...Analysis ( PDF 52 KB )

z Chapter 5. Engineering Analysis ( PDF 863 KB )

z Chapter 6. Markups to Determine Equipment Price ( PDF 223 KB )

z Chapter 7. Energy Use Characterization ( PDF 848
KB )

z Chapter 8. Life-Cycle Cost and Payback Period Analysis ( PDF 1.8 MB )

z Chapter 9. Shipments Analysis ( PDF 532 KB )

z Chapter 10. National and Regional Impact Analysis ( PDF 1.8 MB )

z Chapter 11. Life-Cycle Cost Sub-group Analysis ( PDF 29 KB )

z Chapter 12. Preliminary Manufacturer Impact Analysis ( PDF 123 KB )

z Chapter 13. Utility Impact Analysis ( PDF 27 KB )

z Chapter 14. Employment Impact Analysis ( PDF 28
KB )

z Chapter 15.
Environmental Assessment ( PDF 73 KB )

z Chapter 16. Regulatory Impact Analysis ( PDF 25
KB )

z Chapter 17. Regional Standards Impacts on Market Participants ( PDF 826 KB )

Appendices

z Appendix 3A. Utility Rebate Programs ( PDF 696 KB )

z Appendix 6A. Detailed Data for Equipment Price Markups ( PDF 286 KB )

z Appendix 7A. Internal
Loads Schedules and Part-Load Performance Curves ( PDF 127 KB )

z Appendix 7B. Typical Meteorological Year Pa g e 2 of 4 A pp liances and Commercial E q ui p ment Standards: Residentia l Central Air Conditioners ...

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1.1 MB )

z Appendix 7C . Proposed Regions for Regional Standards and Mapping of RECS Observations ( PDF 440 KB )

z Appendix 8A. User Instructions for Life-Cycle Cost Spreadsheet ( PDF 58
KB )

z Appendix 8B. TechnicalAspects of the TariffBased Approach ( PDF 75
KB )

z Appendix 8C. Comparison of Marginal Prices for TOU and Default Tariffs ( PDF 70 KB )

z Appendix 8D. Development of Monthly Allocation Factors for Residential Baseline Energy Use ( PDF 53 KB )

z Appendix 8E. Household
Discount Rate Distributions ( PDF 69 KB )

z Appendix 8F. Detailed Life-Cycle Cost and Payback Period Results ( PDF 391 KB )

z Appendix 9A. Relative Price Elasticity of Demand for Appliances ( PDF 137
KB )

z Appendix 10A. User
Instructions for Shipments and NIA Spreadsheets ( PDF 47
KB )

z Appendix 12A. Preliminary
Manufacturer Interview Guides ( PDF 122 KB )

z Appendix 15A. Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866 ( PDF 752 KB )

Contact Information
Wes Anderson Project Manager (202) 586-7335 Pa g e 3 of 4 A pp liances and Commercial E q ui p ment Standards: Residentia l Central Air Conditioners ...

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## PRELIMINARY TECHNICAL SUPPORT DOCUMENT (TSD): ENERGY EFFICIENCY PROGRAM FOR CONSUMER PRODUCTS AND INDUSTRIAL EQUIPMENT:

Residential Central Air Cond itioners and Heat Pumps

March 2010

U.S. Department of Energy Assistant Secretary Office of Energy Efficiency and Renewable Energy Building Technologies Program Appliances and Commercia l Equipment Standards Washington, DC 20585This Document was prepared for the Department of Energy by staff members of Navigant Consulting, Inc., Lawrence Berkeley National Laboratory, and Pacific Northwest National LaboratoryACRONYMS AND ABBREVIATIONS

AEC Annual Energy Consumption AEO Annual Energy Outlook
AHRI Air-Conditioning, Heating, and Refrigeration Institute ANSI American National Standards Institute ASHRAE American Society of Hea ting, Refrigeration and Air-Conditioning Engineers ASM Annual Survey of Manufacturers BOM bill of materials BT building technologies
BTU British thermal units CAC Central air conditioners and heat pumps CBEC Commercial Building Energy Consumption Survey CEE Consortium for Energy Efficiency CFC chlorofluorocarbons CFR Code of Federal Regulations CIR Current Industry Reports COGS cost of goods sold CMER consumer marginal energy rates CSL candidate standard level DC direct current DOE U.S. Department of Energy DOJ U.S. Department of Justice ECM electronically commutated motors EER energy efficiency ratio EEV electronic expansion valve EIA Energy Information Administration EISA 2007 Energy Independence and Security Act of 2007
EPA U.S. Environmental Protection Agency EPACT 2005 Energy Policy Act of 2005 EPCA Energy Policy and Conservation Act of 1975 °F degrees Fahrenheit
FEMP Federal Energy Management Program FTC U.S. Federal Trade Commission GRIM Government Regulatory Impact Model HCFC hydrocholorofluorcarbon HFC hydrofluorocarbon HSPF heating seasonal performance factor HVAC heating, ventilation, and air conditioning ImSET Impact of Sector Energy Technologies kWh kilowatt hours LCC life-cycle cost LSHX liquid-suction heat exchangers MPC manufacturing production cost MIA manufacturer impact analysis

AA-iMLP manufacturer list price MPC manufacturer production cost MSP manufacturer selling price
MTA market and technology assessment NAECA National Energy Conservation Act of 1987 NAICS North American Industry Classification System NEMS National Energy Modeling System NES national energy savings NIA national impact analysis
NPV net present value NOPR Notice of Proposed Rulemaking OHA Office of Hearings and Appeals
PBP payback period
PPI producer price indices PSI pounds per square inch PSC permanent split capacitor R&D research and development RTTC Refrigeration and Thermal Test Center
RIA regulatory impact analysis SANOPR Supplemental Advanced No tice of Proposed Rulemaking SBA U.S. Small Business Administration SDHV small duct, high velocity SEC U.S. Securities Exchange Commission SEER seasonal energy efficiency ratio SET saturated evaporator temperature SNOPR Supplemental Notice of Proposed Rulemaking SPM shaded-pole motors SPVU single-package, vertical unit SWEF shipment weighted efficiency data TSD Technical Support Document TSL trial standard level TTW through-the-wall
TXV thermostatic expansion valve USC United States Code
W watt WACC weighted-average cost of capital

AA-iiEXECUTIVE SUMMARY

TABLE OF CONTENTS

ES.1 OVERVIEW OF PRELIMINARY ANALYSIS ACTIVITIES

......................................... 1 ES.2 OVERVIEW OF THE PRELIMINARY ANALYSIS AND THE TECHNICAL SUPPORT DOCUMENT

................................................................................................... 3 ES.3 KEY RESULTS OF THE ANALYSIS

.............................................................................. 4 ES.3.1 Market and Technology Assessment

...................................................................... 4 ES.3.2 Screening Analysis

.................................................................................................. 5 ES.3.3 Engineering Analysis

.............................................................................................. 5 ES.3.3.1 Product Classes Analyzed

................................................................................. 6 ES.3.3.2 Manufacturing Cost Assessment

....................................................................... 6 ES.3.4 Markups to Deter mine Product Price

...................................................................... 9 ES.3.5 Energy Use Characterization

.................................................................................. 9 ES.3.5.1 Residential Energy Use

..................................................................................... 9 ES.3.5.2 Commercial Building Energy Use

.................................................................. 11 ES.3.5.3 Regional Analysis

........................................................................................... 11 ES.3.6 Life-Cycle Cost and Payback Period Analyses

.................................................... 15 ES.3.7 Shipments Analysis

............................................................................................... 18 ES.3.8 National Impact Analysis

...................................................................................... 21 ES.3.8.1 National Energy Savings

................................................................................. 22 ES.3.8.2 Net Present Value

........................................................................................... 23 ES.3.9 Preliminary Manufacturer Impact Analysis

.......................................................... 29 ES.4 ISSUES ON WHICH DOE SEEKS PUBLIC COMMENT

............................................. 29

ES-iLIST OF TABLES

Table ES.1 Manufacturer Production Cost Estimates for Three-Ton Split-System Air Conditioners: Coil-Only Systems

........................................................................... 7 Table ES.2 Manufacturer Production Cost Estimates for Three-Ton Split-System Air

Table ES.3 Manufacturer Production Cost Estimates for Three-Ton Split-System Heat Pumps

Table ES.4 Manufacturer Production Cost Estimates for Three-Ton Single-Package Air

Table ES.5 Manufacturer Production Cost Estimates for Three-Ton Single-Package Heat

Table ES.7 Regions Defined for the Central Air Conditioner and Heat Pump Regional

Table ES.8 Split- System Air Conditioners: Average Annual Energy Use by Efficiency

Table ES.9 Split-System Air Conditioners: Average Annual Energy Use by Efficiency

Table ES.11 Single-Package Air Conditioners: Averag e Annual Energy Use by Efficiency

Table ES.13 LCC and PBP Summary: Highest SEER a nd HSPF for Which Mean LCC Savings

Table ES.18 Split-System Air Conditioners: Disc ounted Cumulative NPV Results (3%

Table ES.19 Split-System Air Conditioners: Disc ounted Cumulative NPV Results (7% Conditioners: Blower-Coil Systems

....................................................................... 7

............................................................................................................................... .. 8

Conditioners

............................................................................................................ 8

Pumps

...................................................................................................................... 8 Table ES.6 National Average Markups for Central Air Conditioners and Heat Pumps

........... 9

Analysis

................................................................................................................. 12

Level

⎯ Coil-Only Systems

................................................................................... 13

Level—Blower-Coil Systems

............................................................................... 13 Table ES.10 Split-System Heat Pumps: Average Annual Energy Use by Efficiency Level

.... 14

Level

..................................................................................................................... 14 Table ES.12 Single-Package Heat Pumps: Average Annual Energy Use by Efficiency Level 15

are Positive, and Corresponding Median PBP in Years

....................................... 17 Table ES.14 Split-System Air Conditioners: Cumu lative NES Results (quads)

....................... 22 Table ES.15 Split-System Heat Pumps: Cumu lative NES Results (quads)

.............................. 23 Table ES.16 Single-Package Air Conditioners: Cu mulative NES Results (quads)

................... 23 Table ES.17 Single-Package Heat Pumps: Cumulative NES Results (quads)

.......................... 23

Discount Rate)

...................................................................................................... 25

Discount Rate)

...................................................................................................... 26 Table ES.20 Split-System Heat Pumps: Discounted Cumulative NPV Results

........................ 27 Table ES.21 Single-Package Air Conditioners: Di scounted Cumulative NPV Results

............ 27 Table ES.22 Single-Package Heat Pumps: Discounted Cumulative NPV Results

................... 28

ES-iiLIST OF FIGURES

Figure ES.1 Flow Diagram of Analyses for the Resi dential Central Air Conditioner and Heat Pump Rulemaking Process

..................................................................................... 2 Figure ES.2 Forecasted Shipments (Base Case) for Sp lit-System Air Conditioners, Coil-Only

Figure ES.3 Forecasted Shipments (Base Case) for Split-System Air Conditioners, Blower

- ............................................................................................................................... 19

Coil

........................................................................................................................ 19 Figure ES.4 Forecasted Shipments (Base Case) for Split-System Heat Pumps

....................... 20 Figure ES.5 Forecasted Shipments (Base Case) for Single-Package Air Conditioners

............ 20 Figure ES.6 Forecasted Shipments (Base Case) fo r Single-Package Heat Pumps

................... 21

ES-iiiEXECUTIVE SUMMARY

ES.1 OVERVIEW OF PRELIMINARY ANALYSIS ACTIVITIES

The Energy Policy and Conservation Act, as amended (42 U.S.C. 6291 et seq.; EPCA), directs the U.S. Department of Energy (DOE) to consider amending the energy conservation standards for residential central air conditioners and heat pumps established under EPCA. (42 U.S.C. 6295(d)(3)(B)) Any amended standard mu st be designed to “achieve the maximum improvement in energy efficiency ... which the Se cretary determines is technologically feasible and economically justified.” (42 U.S.C. 6295(o )(2)(A)). This executive summary provides an overview of DOE’s preliminary analysis in consideration of amended energy conservation standards for residential central air conditioners and heat pumps. This summary describes key results from DOE’s analyses and delineates issues about which it seeks comment from interested parties. These issues will be highlighted in the public meeting presentation on this preliminary technical support document (preliminary TSD) and discussed in chapter 2 of the preliminary TSD.

Figure ES.1 presents a summary of the an alytical components of the standards-setting process and illustrates how key results are generated. The focal point of the figure is the center column, labeled “Analyses.” The columns labeled “Key Inputs” and “Key Outputs” show how the analyses fit into the process and how they relate to each other. Key inputs are the types of data and other information that the analyses require. DOE obtains some key information from public databases; it collects othe r inputs from interested parties or persons having special knowledge and expertise. Arrows connecting analyses show the types of information that feed from one analysis to another. Key outputs are anal ytical results that feed directly into the standards-setting process. The issues on which DOE seeks comment derive from the preliminary analysis.

ES-1Framework Document

Figure ES.1 Flow Diagram of Analyses for the Re sidential Central Air Conditioner and Heat Pump Rulemaking Process Utility Impact

A nalysis

Notice of Proposed Rulemaking (NOPR)

Final Rule Market and Technology Assessment

Screening Analysis

Engineering Analysis

Markups fo r Product Price Determination Life

- Cycle Cost and Payback Period Analyses

National Impact Analysis Energy Use

Revise Preliminar y Analysis

Life

- Cycle Cost Sub

- group Analysis

Manufacturer Impact Analysis Shipments Analysis

Employment Impact A nalysis

Revise Analyses • Product Classes

• Technology Options

• Industry Cash Flo w

• Subgroup Cash Flow

• Direct Employment Impacts

• Competitive Impacts

• Cumulative Regulatory Burden • Cost

- Efficiency Relationship

• Life

- Cycle Costs

• Payback Periods

• National Energy Savings

• Net Present Values

• National Employment Impacts

• Revised Results • Market Segmentation

• Non

- Regulatory Programs

• Energy Prices

• Installation Costs

• Maintenance & Repair Costs

• Backcast and Forecast

• Market Saturation

• Stakeholder Comments

• Demographics

• Emission Rates

• National Energy Savings

• Stakeholder Comments • Identify Firms/Products

• Historical Shipments

• Manufacturer Prices

• Average Costs

• Manufacturer Financial Data Design Options Product Classes

Retail Prices Design Energy

Preliminary Analysis • Efficiency/Performance • Manufacturing Cost

Candidate Standard

Levels

Environmental Assessment

Regulatory Impact Analysis Technology Options

• Emission Estimates • Utility Load Factors

• National Energy Savings

• Non

- Regulator y Alternatives • Design Options

• Energy Price Forecasts

• Site

- to

- Source Factors • Energy

- Efficiency Levels

Direct Employment Impacts

• National Energy Savings

• National Product Costs

• National Operating Costs • Utility Impacts • Life

- Cycle Costs

• Payback Periods • Installation Costs

• Maint Costs

• Repair Costs • UEC

• Energy Prices • Annual Energy Use (UEC)

Preliminar y Manufacturer Impact Analysis • Manufacturer Prices

• Average Costs • Conversion Capital Expenditures

• Direct Employment Impacts

• National Energy Savings

• Net Present Values • Trial Standard Levels ( TSLs )

TSLs • Product Prototypes

Energy Efficiency Levels

• Department of Justice Review

ES-2ES.2 OVERVIEW OF THE PRELIMINARY ANALYSIS AND THE TECHNICAL SUPPORT DOCUMENT

This preliminary TSD details each preliminary analysis, inputs, sources, methodologies, and results. Chapter 2 of this preliminary TSD provides an overview of each preliminary analysis, the comments received in response to th e analytical approaches DOE described in the framework document, and DOE’s re sponses to those comments.

The following is a brief description of the chapters in the preliminary TSD that address the preliminary analyses performed by DOE:

• The market and technology assessment (MTA) characterizes the relevant product markets and technology options, including prototype designs (chapter 3).

• The screening analysis reviews each technology option to determine whether it is technologically feasible; is practicable to manufacture, install, and service; would adversely affect product utility or product ava ilability; or would ha ve adverse impacts on health and safety (chapter 4).

• The engineering analysis develops cost -efficiency relationships that show a manufacturer’s cost of achieving increased efficiency. DOE uses manufacturer markups to convert manufacturer production cost (M PC) to manufacturer selling price (MSP) (chapter 5).

• The markups analysis converts the MSPs derived from the engineering analysis to consumer product prices (chapter 6).

• The energy use analysis determines the annual energy use in the field of the considered products (chapter 7).

• The life-cycle cost (LCC) and payback period (PBP) analyses calculate, at the consumer level, the discounted savings in operating co sts throughout the estimated average life of the covered products, compared to any increas e in the product’s installed cost likely to result directly from the imposition of a given standard (chapter 8).

• The shipments analysis forecasts product shipments, which then are used to calculate the national impacts of standards on energy cons umption, the net present value (NPV) of consumer costs and savings, and future manufacturer cash flows (chapter 9).

• The national impact analysis (NIA) assesses the cumulative national energy savings (NES) from standards and the NPV of consum er costs and savings associated with standards at different effici ency levels (chapter 10).

• The preliminary manufacturer impact analysis (MIA) assesses the potential impacts of energy conservation standards on manufacturer s, such as effects on expenditures for

ES-3capital conversion, marketing costs, shipment s, and research and development costs (chapter 12).

The remaining chapters of the preliminary TSD address the analyses to be performed for the NOPR stage:

• The life-cycle cost analysis for subgroups ev aluates the effects of energy conservation standards on various national subgroups of the population (chapter 11).

• The utility impact analysis examines impacts of energy conservation standards on the generation capacity of electric utilities (chapter 13).

• The employment impact analysis examines the effects of energy conservation standards on national employme nt (chapter 14).

• The environmental assessment examines the effects of energy conservation standards on various airborne emissions (chapter 15).

• The regulatory impact analysis examines the national impacts of non-regulatory alternatives to mandatory energy conservation standards (chapter 16).

ES.3 KEY RESULTS OF THE ANALYSIS

The following sections describe in detail the analyses DOE performed in support of the preliminary TSD and present the key results.

ES.3.1 Market and Technology Assessment
When initiating an analysis of potential energy efficiency standards for appliances, DOE develops information on the present and past indus try structure and market characteristics for the products concerned. This activ ity assesses industries and pr oducts both quantitatively and qualitatively based on publicly available information.

DOE generally divides covered products into product classes by the type of energy used, or by capacity or other performance-related features that affect efficiency. Different energy conservation standards may apply to different product classes. (42 U.S.C. 6295(q)) The product classes that DOE is considering in this rulemaking are as follows:

• Split-System Air Conditioners

• Split-System Heat Pumps

• Single-Package Air Conditioners

• Single-Package Heat Pumps

• Small-Duct High-Velocity Systems (SDHV)

• Space-Constrained Air Conditioners

• Space-Constrained Heat Pumps

ES-4For the residential central air conditioner and heat pump products that are covered by this rulemaking, DOE gathered information on (1) manuf acturer market share and characteristics, (2) existing regulatory and non-regulatory initiatives for improving product efficiency, and (3) trends in product characteri stics and retail markets.

DOE reviewed literature and interviewed manufacturers to develop an overall understanding of the residential central air conditioner and heat pump products industry in the United States. Industry publications, including trade journals, as well as literature from manufacturers, government agencies, and tr ade organizations provided the bulk of the information, including (1) manufacturers and thei r market share, (2) shipments by product type, (3) product information, and (4) industry trends. Chapter 3 of the preliminary TSD describes the market analysis and resulting information.

DOE typically uses information about existing and past technology options and prototype designs to determine which tec hnologies and combinations of t echnologies manufacturers use to improve energy efficiency. In consultation with interested parties, DOE developed a list of technologies to consider, for residential central air conditioner and heat pump products, from trade publications, technical papers, and manufacturer literature, and through consultation with manufacturers of components and systems. Produc t literature and direct examination provided additional information, because existing products contain many technologies for improving product efficiency. Before performing the screening analysis, DOE removed from the list those technologies for which the energy consumption could not be adequately measured using the relevant DOE test procedure.

ES.3.2 Screening Analysis
Next, DOE performed a screening analysis to examine whether the technologies DOE identified (1) are technologically feasible; (2) are practicable to manufacture, install, and service; (3) have an adverse impact on product utility or av ailability; and/or (4) have adverse impacts on health and safety. DOE conducts this analysis in consultation with interest ed parties. In the subsequent engineering analysis, DOE further ex amines the technology options that it did not remove from consideration pursuant to the screening analysis.

ES.3.3 Engineering Analysis
In the engineering analysis (chapter 5), DOE established the relationship between the cost of manufacturing residential cen tral air conditioner and heat pumps and their efficiency. This relationship served as the basis for calculating co sts and benefits of modi fied product designs for consumers, manufacturers, and the nation. Chap ter 5 of the preliminary TSD describes the product classes that DOE analyzed, the representa tive baseline units, the efficiency levels DOE considered, the methodology that DOE used to develop the manufacturing production cost model, and the cost-efficiency results.

ES-5ES.3.3.1 Product Classes Analyzed

The engineering analysis directly analyzed the four primary residential central air conditioner and heat pump product classes: (1) split-system air cond itioners; (2) split-system heat pumps; (3) single-package air conditioners; and (4 ) single-package heat pumps. These four product classes represent most of the total shipments of residen tial central air conditioners and heat pumps.

For the other three product classes identif ied in section ES.3.1, DOE found that product offerings and available information were limited. Therefore, in chapter 5 of the preliminary TSD, DOE describes the technical characteristics and potential areas of energy savings for these product classes for the preliminary analysis. DOE intends to fully analyze these product classes for the NOPR if it can obtain enough information to quantify potential areas of energy savings. DOE requests feedback and data on potential areas of energy savings for space-constrained products and SDHV systems. Chapter 5 of the pr eliminary TSD includes additional details on the representative product classes and the cost-efficienc y curves developed as part of the engineering analysis.

ES.3.3.2 Manufacturing Cost Assessment

DOE estimated the manufacturing costs associated with an increase in energy efficiency for each of the residential central air conditi oner and heat pump product classes analyzed using aggregated manufacturer data. The assessment method involved disassembling particular units, analyzing the materials in each unit and the manufacturing processes used to produce it, analyzing the design approaches manufacturers use, and developing a spreadsheet model to evaluate costs. DOE developed a detailed model to estimate the manufacturers product cost (MPC) at various efficiency levels. Chapter 5 of the preliminary TSD includes information on the inputs DOE used to determine the manuf acturing cost, including material, labor, and overhead costs. Chapter 5 also includes inform ation on the various components and features incorporated into designs for residential central air conditioner and heat pump products.

DOE’s engineering analysis produced cost-efficiency curves for the four primary residential central air conditioner and heat pump product classes. The cost -efficiency curves are described by the efficiency levels and the increa se in MPC above the baseline for each level. The split-system air conditioner and heat pump product classes have two different rating methods for determining their seasonal energy efficiency ra tio (SEER), depending on whether the fan blower is included in the rating. If a system is rated as a “coil-only” system, the SEER is calculated using a default fan power. These systems are ge nerally representative of a condensing unit and evaporator coil installed with an existing furnace. If a system is rated as a “blower-coil” system, the SEER is calculated using a specific fan power. In coil-only systems, only the outdoor condensing unit and evaporator coil can be modified to achieve higher system efficiencies; in blower-coil systems, which are generally representa tive of a condensing unit installed with an air handler, the outdoor condensing unit, evaporator coil, and fan blower can all be modified to achieve higher system efficiencies.

DOE assumed that coil-only systems and blower-coil systems are both prevalent in the split-system air-conditioning market, whereas bl ower-coil systems are believed to be the

ES-6overwhelming type of installation in the split-system heat pump market because it is more important to match the indoor a nd outdoor components to obtain proper performance. Therefore, DOE characterized the split-system air conditione r product class by develo ping separate costefficiency curves for coil-only systems and blower-coil systems. DOE characterized the splitsystem heat pump product class using only blowe r-coil systems. DOE requests comment on the market shares of coil-only and blower-coil sy stems for both split-system air conditioners and split-system heat pumps. DOE also requests comment on whether an additional coil-only engineering analysis is necessary to characterize split-system heat pumps. Table ES.1 through Table ES.5 present the key results of the engineering analysis.

Table ES.1 Manufacturer Production Cost Estimates for Three-Ton Split-System Air Conditioners: Coil-Only Systems

Efficiency Level SEER System Cost (without air handler) $
13.0 580
13.5 615
14.0 651
14.5 692
15.0 739
15.5 797
16.0 871
16.5* 957
* Max-tech efficiency level

Table ES.2 Manufacturer Production Cost Estimates for Three-Ton Split-System Air Conditioners: Blower-Coil Systems

Efficiency Level SEER System Cost (with air handler) $
13.0 715
13.5 754
14.0 793
14.5 834
15.0 864
15.5 895
16.0 927
17.0 995
18.0 1,068
19.0 1,147
20.0 1,232
21.0 1,324
22.0* 1,422
* Max-tech efficiency level

ES-7Table ES.3 Manufacturer Production Cost Estimates for Three-Ton Split-System Heat Pumps

Efficiency Level SEER HSPF System Cost (with air handler) $
13.0 7.70 861
13.5 7.85 904
14.0 8.00 951
14.5 8.15 986
15.0 8.30 1,020
15.5 8.45 1,057
16.0 8.60 1,105
17.0 9.10 1,188
18.0 9.60 1,276 19.0 10.10 1,372
19.5* 10.30 1,423
* Max-tech efficiency level

Table ES.4 Manufacturer Production Cost Estimates for Three-Ton Single-Package Air Conditioners Efficiency Level SEER System Cost $
13.0 726
13.5 792
14.0 835
14.5 900
15.0 952
15.5 1,018
16.0 1,097
16.6* 1,209
* Max-tech efficiency level

Table ES.5 Manufacturer Production Cost Estimates for Three-Ton Single-Package Heat Pumps Efficiency Level SEER HSPF System Cost $
13.0 7.7 899
13.5 7.9 940
14.0 8.0 994
14.5 8.0 1,073
15.0 8.0 1,142
15.5 8.5 1,222
16.0 9.0 1,318
16.4* 9.0 1,414
* Max-tech efficiency level

ES-8ES.3.4 Markups to Determine Product Price
In the markups analysis (chapter 6), DOE developed appropriate markups in the distribution chain to convert the estimates of ma nufacturer cost derived in the engineering analysis to consumer prices. In developing markups, DOE estimated markups taken by wholesalers, mechanical contractors, and gene ral contractors, along with sales taxes. DOE calculated markups separately fo r installations in new constr uction and for replacements. DOE also developed separate markups for baseline products (baseline markups) and for the cost increase associated with improvements required to produce more efficient products (incremental markups).

Table ES.6 summarizes the markups develope d for central air conditioner and heat pumps. The markups shown in this table reflect national average values for the given markup. In the subsequent LCC analysis, DOE also deve loped regional markup multipliers to capture regional variation in mechanical contractor markups, general cont ractor markups, and sales tax.

Table ES.6 National Average Markups for Central Air Conditioners and Heat Pumps Baseline Markups Incremental Markups Replacement Market New Construction Market Replacement Market New Construction Market

Wholesaler 1.37 1.37 1.11 1.11
Mechanical 1.38 1.28 1.12 1.04
General

- 1.29

- 1.17

Sales Tax 1.07 1.07 1.07 1.07

Overall 2.02 2.42 1.33 1.45

ES.3.5 Energy Use Char acterization
The energy use characterization provides the basis for developing the energy savings from using higher efficiency central air conditione rs and heat pumps. The energy savings results are incorporated in the LCC and other subseque nt analyses. The DOE test procedure provides standardized metrics that serve as the basis fo r comparing the energy consumption of different product efficiency levels. It provides a standardiz ed estimate of the seasonal efficiency for each air conditioner design. DOE uses the SEER rating to establish an estimate of seasonal cooling efficiency for different product designs. For heat pumps, DOE used the national HSPF rating to establish an estimate of relative heating efficien cy. Since actual usage of central air conditioners and heat pumps in the field varies significan tly as a function of c limate and household use preferences, DOE used other data sources to estimate actual baseline energy consumption.

ES.3.5.1 Residential Energy Use

Residential households form the largest insta lled base of central ai r conditioners and heat pumps. For the residential energy use analysis, DOE used the SEER and HSPF estimates from the engineering analysis to scale baseline energy consumption estimates to reflect higher SEER and HSPF efficiencies. DOE represented the en ergy consumption of the product at each efficiency level using a distribution that account s for variation in usag e and climate conditions based on a representative sample of households across the nation.

ES-9The representative sample of households is a subset of the households from the 2005 Residential Energy Consumption Survey (R ECS) produced by the Energy Information Administration (EIA), the most recent survey available. RECS is a national sample survey that collects statistical information on the consumption of and expenditures for energy in housing units along with data on energy-related character istics of the housing units and occupants. Out of a total of 4,382 households surveyed in the 2005 RECS, 1,854 qualified for the central air conditioner analysis and 339 qualified for the cen tral heat pump analysis. A small number of households reporting use of central air conditione rs were not used in the DOE sample for specific reasons

─ e.g. , for reported non-use of the central air-conditioning system or for concurrent use of anothe r air-conditioning product type in the same household.

For each household in the sample, DOE developed a cooling unit energy consumption (UEC) as well as a heating UEC for homes serv ed by heat pumps. The UEC was based on the reported cooling and heating energy use in RE CS for 2005 and is associated with the stock products (UEC res_stock_non-adj ) used in each household. Based on 1987-2007 cooling degree day data from the National Oceanographic and Atmo spheric Administration National Clima tic Data Center (NCDC), DOE then normalized this UEC data to long-term aver age climate conditions through the use of a weather adjustment factor developed for each census division and applied to all households within the census division. The actual 2005 cooling energy use for each RECS household was multiplied by this weather-adjustme nt factor to generate a weather-normalized UEC res_stock . For heat pumps, DOE carried out a similar weather normalization using 30-year average heating degree day data.

The weather-adjusted UEC is further adjusted to provide base-case energy consumption for 2016 (the start year for LCC analysis) for new central air conditioner and heat pump purchasers. The underlying assumption for the energy use characterization is the same that is used in the LCC analysis, i.e., that the representative samp le of customers will replace or purchase new air conditioners in 2016, the year th at revised central air-conditioning and heat pump standards go into effect. To model a base -case standards scenario for the energy use analysis, DOE first used central air conditioner an d heat pump vintage data in RECS to establish the year that the stock RECS central air conditioner and heat pump unit was installed. It then used data on the historical average efficiency fo r central air conditioners and heat pumps by year to estimate the SEER and HSPF for the products in the RECS household. This stock efficiency is associated with the UEC values for the i ndividual RECS household observations. Because customers are presumed to purch ase air conditioners in 2016, DOE used current estimates of the efficiency distribution for shipments (by produc t class) as shipment efficiency weights appropriate to new purchases in 2016 in the base case. DOE then selected efficiencies for new shipments to each household based on the efficiency distributions. DOE then scaled the weathernormalized UEC res_stock cooling and heating electrical energy use by the ratio of selected replacement efficiency to RECS stock efficiency established for each household. Because stock efficiencies are in general lower than curren t shipped efficiencies, adjusting the weathernormalized stock energy use by the replacement-to-stock efficiency ratio reduces the estimate for household cooling and heating energy consumpti on to reflect the 2016 base case used for the LCC analysis.

ES-10ES.3.5.2 Commercial Building Energy Use

Central air conditioners and heat pumps are also used in many smaller commercial buildings. DOE has estimated the fraction shipped for commercial building applications at approximately 7 percen t based on industry estimates. For commercial buildings, DOE followed the path outlined in the framework document to estimate the energy savings for shipments of higher efficiency products. The framework docu ment used the EnergyPlus building energy simulation software to simulate the energy c onsumption of central air conditioners and heat pumps used to satisfy the cooling, supply fan—an d in the case of central heat pumps, the heating energy—required in a small office building. DOE used an existing small office building model developed for DOE’s energy benchmarking task fo r this analysis. DOE simulated the building in 237 climates corresponding to each of the Typi cal Meteorological Year (TMY2) weather locations within the 50 states. DOE simulated the same building served either by central air conditioners or heat pumps and simulated the pr oduct for each product type using a 13 SEER, 14 SEER, 16 SEER, and max tech level for either central air conditioners (SEER 22) (based on blower-coil ratings) or central heat pumps (SEER 19.5). Product parameters used in the simulation were adjusted to reflect engineering de signs corresponding to each efficiency level.

The simulated building used five individual central air-conditioning and heat pump units. DOE extracted the annual energy consumption for cooling and fan energy use and central heat pump heating from each unit as well as the product capacity from each unit from each simulation run and aggregated these to the whole buildin g level. Using this whole building data, DOE normalized the central air conditioner and heat pu mp energy consumption for each location and efficiency level to reflect that of an average 3-ton central air-conditioning or heat pump unit, for use in the LCC analysis. To estimate the energy consumption for intermediate efficiency levels between those simulated, DOE linearly interpolated the energy use estimates based on the results for the four simulated efficiencies.

DOE used population-based weighting factors de veloped for each climate to represent the relative percentage of customers experiencing each climate in each state, at the national level, and in each of three geographic regions being used to assess regional standards (see below). These weighting factors, in conjunction with the relative weighting between commercial and residential shipments, were used to incorporate the commercial building energy consumption into the overall energy consumption for centr al air conditioners a nd heat pumps at each efficiency level.

ES.3.5.3 Regional Analysis

EPCA allows DOE to consider regional stan dards for central air conditioners and heat pumps. DOE defined two separate geographic regi ons to assess proposed regional standards. One is a hot-humid region, consisting of 12 states in the southeastern United States; the second is a hot-dry region, consisting of four states in the So uthwest. The states comp rising the regions are listed in Table ES.7. Chapter 7 de tails the development of these regions. The remainder of the United States, to which only the national standard will be applicable, was labeled “Rest of Country.” The LCC analysis was conducted both at a national level and at a regional level using residential and commercial custom er populations defined for each region (based on analysis of RECS data for the residential population and the clima te weighting factors developed for the

ES-11commercial analysis). Chapter 7 of the prelimin ary TSD provides more details on the methods, data, and assumptions used for developing the adjusted UECs.

Table ES.7 Regions Defined for the Central Air Conditioner and Heat Pump Regional Analysis
Hot-Humid (Region 1) Hot-Dry (Region 2) Rest-of-Country (Region 0)
Alabama Arizona Alaska Nebraska
Arkansas California Colorado New Hampshire
Florida Nevada Connecticut New Jersey Georgia New Mexico Delaware New York
Hawaii District of Columbia North Dakota
Louisiana Idaho Ohio Mississippi Illinois Oregon
North Carolina Indiana Pennsylvania
Oklahoma Iowa Rhode Island
South Carolina Kansas South Dakota
Tennessee Kentucky Utah
Texas Maine Vermont Maryland Virginia
Massachusetts Washington Michigan West Virginia
Minnesota Wisconsin
Missouri Wyoming
Montana

Table ES.8 through Table ES.12 present th e average annual energy use for the representative product classes at each energy efficiency level DOE considered.

ES-12Table ES.8 Split- System Air Conditioners: Average Annual Energy Use by Efficiency
Level

⎯ Coil-Only Systems

Efficiency Level Annual Energy Consumption kilowatt hours per year (kWh/yr)

National Hot-Humid Hot-Dry Rest of Country

# SEER HSPF * Cooling Heating Cooling Heating Cooling Heating Cooling Heating

1 13.0 N/A 2,407 0 3,564 0 2,176 0 1,378 0
Market Baseline Market Baseline N/A 2,291 0 3,393 0 2,071 0 1,310 0

2 13.5 N/A 2,322 0 3,437 0 2,100 0 1,331 0
3 14.0 N/A 2,243 0 3,318 0 2,029 0 1,287 0

4 14.5 N/A 2,168 0 3,205 0 1,960 0 1,244 0
5 15.0 N/A 2,097 0 3,100 0 1,897 0 1,204 0

6 15.5 N/A 2,031 0 3,002 0 1,836 0 1,166 0

7 16.0 N/A 1,968 0 2,909 0 1,780 0 1,130 0
8 16.5 N/A 1,912 0 2,825 0 1,730 0 1,099 0 *N/A means not applicable.

Table ES.9 Split-System Air Conditioners: Average Annual Energy Use by Efficiency Level—Blower-Coil Systems

Efficiency Level Annual Energy Consumption kWh/yr

National Hot-Humid Hot-Dry Rest of Country

# SEER HSPF* Cooling Heating Cooling Heating Cooling Heating Cooling Heating

1 13.0 N/A 2,433 0 3,584 0 2,172 0 1,365 0
Market Baseline Market Baseline N/A 2,315 0 3,410 0 2,067 0 1,302 0

2 13.5 N/A 2,347 0 3,455 0 2,096 0 1,319 0
3 14.0 N/A 2,267 0 3,336 0 2,025 0 1,275 0

4 14.5 N/A 2,190 0 3,223 0 1,957 0 1,233 0
5 15.0 N/A 2,119 0 3,117 0 1,893 0 1,193 0

6 15.5 N/A 2,052 0 3,018 0 1,833 0 1,155 0

7 16.0 N/A 1,988 0 2,925 0 1,777 0 1,120 0
8 16.5 N/A 1,932 0 2,840 0 1,727 0 1,089 0

9 17.0 N/A 1,878 0 2,760 0 1,679 0 1,060 0
10 18.0 N/A 1,780 0 2,613 0 1,592 0 1,007 0

11 19.0 N/A 1,692 0 2,482 0 1,514 0 960 0

12 20.0 N/A 1,613 0 2,363 0 1,444 0 917 0

13 21.0 N/A 1,541 0 2,256 0 1,380 0 878 0

14 22.0 N/A 1,476 0 2,158 0 1,322 0 842 0 *N/A means not applicable.

ES-13Table ES.10 Split-System Heat Pumps: Average Annual Energy Use by Efficiency Level

Efficiency Level Annual Energy Consumption kWh/yr

National Hot-Humid Hot-Dry Rest of Country

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating

1 13.0 7.70 3,487 1,749 4,275 1,275 4,203 924 1,978 2,968
Market Baseline Market Baseline Market Baseline 3,268 1,687 4,006 1,230 3,937 891 1,857 2,862

2 13.5 7.85 3,363 1,716 4,122 1,251 4,053 906 1,909 2,912
3 14.0 8.00 3,248 1,685 3,980 1,228 3,913 890 1,846 2,859

4 14.5 8.15 3,138 1,654 3,845 1,206 3,780 873 1,784 2,808
5 15.0 8.30 3,035 1,625 3,719 1,184 3,656 858 1,726 2,758

6 15.5 8.45 2,939 1,597 3,601 1,163 3,539 843 1,671 2,711

7 16.0 8.60 2,848 1,570 3,490 1,143 3,430 828 1,620 2,665
8 17.0 9.10 2,688 1,485 3,293 1,081 3,235 783 1,531 2,522

9 18.0 9.60 2,545 1,409 3,117 1,026 3,062 743 1,452 2,395
10 19.0 10.10 2,417 1,341 2,959 976 2,907 706 1,381 2,279

11 19.5 10.30 2,358 1,315 2,886 957 2,835 693 1,348 2,236

Table ES.11 Single-Package Air Conditioners: Average Annual Energy Use by Efficiency Level

Efficiency Level Annual Energy Consumption kWh/yr

National Hot-Humid Hot-Dry Rest of Country

# SEER HSPF * Cooling Heating Cooling Heating Cooling Heating Cooling Heating
1 13.0 N/A 2,376 0 3,602 0 2,170 0 1,363 0
Market Baseline Market Baseline N/A 2,348 0 3,559 0 2,144 0 1,348 0

2 13.5 N/A 2,292 0 3,473 0 2,093 0 1,316 0
3 14.0 N/A 2,214 0 3,353 0 2,022 0 1,273 0

4 14.5 N/A 2,139 0 3,239 0 1,954 0 1,230 0
5 15.0 N/A 2,070 0 3,133 0 1,890 0 1,191 0

6 15.5 N/A 2,004 0 3,033 0 1,831 0 1,153 0

7 16.0 N/A 1,942 0 2,940 0 1,774 0 1,118 0
8 16.6 N/A 1,876 0 2,838 0 1,714 0 1,081 0 *N/A means not applicable.

ES-14Table ES.12 Single-Package Heat Pumps: Average Annual Energy Use by Efficiency Level

Efficiency Level Annual Energy Consumption kWh/yr

National Hot-Humid Hot-Dry Rest of Country

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating

1 13.0 7.70 3,464 1,720 4,295 1,272 4,211 927 1,964 2,953
Market Baseline Market Baseline Market Baseline 3,372 1,698 4,179 1,256 4,098 915 1,914 2,916

2 13.5 7.85 3,341 1,688 4,141 1,248 4,060 910 1,896 2,898
3 14.0 8.00 3,227 1,657 3,999 1,225 3,920 893 1,833 2,845

4 14.5 8.00 3,117 1,657 3,863 1,225 3,787 893 1,772 2,845
5 15.0 8.00 3,015 1,657 3,737 1,225 3,663 893 1,714 2,845

6 15.5 8.50 2,920 1,561 3,618 1,154 3,546 841 1,660 2,682

7 16.0 9.00 2,829 1,476 3,506 1,091 3,436 795 1,609 2,538
8 16.4 9.00 2,763 1,476 3,424 1,091 3,356 795 1,572 2,537

ES.3.6 Life-Cycle Cost and Payback Period Analyses
Stipulating new energy conservation sta ndards for products results in changes in consumer operating expenses—usually a decrease— and changes in consumer price—usually an increase. DOE analyzed the net effect of revised standards on consumers by evaluating the LCCs using the cost-efficiency relationships derived in the engineering analysis, as well as the energy costs derived from the energy use characteri zation. Inputs to the LCC calculation included the installed cost to the consumer (purchase price plus installation cost), operating costs (energy expenses, repair, and maintena nce), the lifetime of the appliance, and a discount rate.

The installed cost of a product typically incr eases while operating cost typically decreases in response to new standards. Therefore, there is a point in time for higher efficiency products when the cumulative net operating-cost savings (in dollars) since the time of purchase is equal tothe increase in the purchase price. The length of time required for products to reach this costequivalence point is known as the payback period (PBP).

DOE conducted the LCC and PBP analyses usin g values that reflect energy consumption in the field. DOE identified several inputs fo r estimating the LCC, including retail product prices, energy prices, discount ra tes, and product lifetimes. DOE used EIA’s energy price data to determine prices for electricity in 2007, and used projections of these energy prices from the April 2009 update to EIA’s Annual Energy Outlook 2009 to estimate future energy prices. DOE developed discount rates from estimates of the finance costs for consumers and commercial businesses that purchase central ai r conditioners and heat pumps.

Because the basis for the lifetime estimates in the literature for air-conditioning products is uncertain, DOE used actual data sources to es timate the distribution of central air conditioner and heat pump lifetimes in the field. DOE estimated the fraction of appliances of a given age still in operation by combining survey results from RECS and the U.S. Census’s American Housing Survey with historical appliance shipments. The resulting survival function, which DOE assumed

ES-15has the form of a cumulative Weibull distributi on, provides an average and median appliance lifetime.

There are number of potential complications concerning the configuration of air conditioning equipment sold in the future marketplace that affect how efficiency can be measured and achieved. For example, efficiency ratings for air conditioning units depend on the configuration in which such units are sold. The vast majority of units on the market are condensing units and indoor coil combinations design ed to be used with furnaces that provide the indoor air handling component. For these products , performance ratings can be provided based on a coil-only rating, in which case a default supply fan power assumption is used to calculate the SEER rating. Higher efficiency, coil-only ratings are achieved through more efficient design of the condensing unit and indoor coil. A small fra ction of the split-system air conditioner market uses dedicated air handlers instead of furnaces. Additional ratin gs of the same condensing unit with specific furnace or air handler blowers can also be provided as blower-coil ratings. Higher efficiency blower-coil ratings can also be obtained by improving the indoor blower or furnace.

Roughly 80 percent of future split-system air conditioner sales are expected to replace failing air-conditioning units (most frequently, th e outdoor condensing unit, while only about 20 percent are expected to be installed in new construction). Most of these systems are integrated with the air-handling system of a natural-gas fi red furnace that provides space heating to the building. Since many of these furnaces were installed at the same time as the failing airconditioning unit, some building owners considering air-conditioning replacement will also replace the aging furnace at the same time, but ot hers will elect to keep the existing furnace and just install a new condens ing unit and indoor coil.

The consumer’s ability to use coil-only systems is also applicable to the new construction market. EPCA does not authorize DOE to require a furnace to be purchased in conjunction with a new split-system air conditioner. In addition, wh ile the Energy Independence and Security Act of 2007 requires DOE to issue furnace fan energy conservation or energy use standards not later than December 31, 2013, DOE does not currently regulate furnace fan performance. In practice, the furnace could be installed prior to the air c onditioner purchase, and a rated efficiency that is the result of a particular furnace fan being used (i.e. the blower-coil efficiency) may be difficult to achieve in the field. Nevertheless, DOE recognizes that a small number of split-system air conditioners are rated using dedicated air handler s only, and a larger fraction are installed in conjunction with a new furnace.

Because of the circumstances described above, DOE has provided an LCC analysis assuming both a coil-only scenario, and a blower-c oil scenario, using the corresponding coil-only and blower-coil engineering curves as appropr iate. DOE developed the life-cycle cost for consumers purchasing coil-only systems and consumers purchasing blower-coil systems assuming that these are independent consumer markets.

To accurately estimate the share of consumers that would be affected by a standard at a particular efficiency level, DOE’s LCC analys is considered the projected distribution of efficiencies for products that consumers would purchase under a base case ( i.e ., absent amended energy efficiency standards). DOE refers to this distribution of product e fficiencies as a base

ES-16case efficiency distributi on. Using the projected distribution of base-case product efficiencies for each product class, DOE assigned a specific base-case product efficiency to each sample household as discussed earlier under energy use characterization. If a household was assigned a product efficiency that is greater than or equal to the efficiency of the standard level under consideration, the LCC calculati on would show that this household is not affected by that standard level.

Table ES.13 summarizes the results for the LCC and PBP analyses, indicating for each product class and region the highest SEER and HSPF level where the average LCC savings is greater than zero and the median PBP in years corresponding to that level.

Table ES.13 LCC and PBP Summary: Highest SEER and HSPF for Which Mean LCC Savings are Positive, and Corresponding Median PBP in Years

Product National Hot-Humid Hot-Dry Rest of Country Class SEER/ HSPF PBP years SEER/ HSPF PBP

years SEER/ HSPF PBP

years SEER/ HSPF PBP

yearsSplitSystem AC Coil Only 13.5/NA 27.8 15.0/NA 17.5 14.5/NA 42.6 13.0/NA NA

SplitSystem ACBlowerCoil 13.5/NA 27.4 19.0/NA 17.9 17.0/NA 30.1 13.0/NA NA

SplitSystem
HP 19.5/10.3 12.0 19.5/10.3 10.0 19. 5/10.3 8.8 15.5./8.45** 12.6

SinglePackage AC 13.0/NA NA 13.0/NA NA 13.0/NA NA 13.0/NA NA

Single– Packag
e HP 14.0/8.0 10.5 14.0/8.0 8.2 14.5/8.0 11.4 13.0/7.7 NA

*NA means not applicable. **SEER 15 and 15.5 show very small LCC savings. Savings are negative at SEER13.5-14.5 and at SEER 16.0 and above.

Figures presented in chapter 8 of the preliminary TSD show the range of LCC savings and PBPs for all of the efficiency levels DOE considered for each product class. Chapter 8 provides more details on the methods, data, and assumptions used for the LCC and PBP analyses.

ES-17ES.3.7 Shipments Analysis
DOE needs shipment forecasts to calculate the national impacts of standards on energy use, NPV, and future manufacturer cash flows for each product being considered. DOE’s shipments model considered ship ments based on sector, market, and region in both residential and commercial sectors. DOE analyzed ship ments to three markets: new construction, replacements, and existing buildings th at do not already contain the product ( i.e ., “new owners”). DOE allocated shipments to the three geographi c regions described in section ES.3.5.3. Rather than simply extrapolating a current shipments tr end, the analysis used driver input variables ( e.g ., new construction forecasts and produc t stock saturations) to forecast sales to each sector, market segment, and region. For units shipped to new construction, annual product shipments are equal to the number of new building units built times th e product purchase rate, which is determined by the market share of the product under c onsideration. To estimate shipments due to replacements, the model used sales in previous years and assumptions about the product lifetime, which determine how long an appliance is likely to remain in use. Shipments to new owners are based on historical rates of a doption. Chapter 9 of the preliminar y TSD provides additional detail on the shipments analysis.

Figure ES.2 through Figure ES.6 illustrate the forecasted base-case shipments for all product classes included in this rulemaking. Shipments are broken down into each of the three regions and designated by market segment ( i.e. , new construction, replacements, and new owners). Shipments to the commercial building sector are estimated to represent only about 7 percent of all product shipments. For clarity, the figures do not differentiate among units going to the residential and commercial sectors.

ES-180 1 2 3 4 5 6

1990 199 4

1 998 2002 2 0 0 6 2010 2014 201 8 2022 2026 2 0 3 0 2034 203 8 2 042 2046

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure ES.2 Forecasted Shipments (Base Case) for Split-System Air Conditioners, CoilOnly

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

1990 199 4

1 998 2002 2 0 0 6 2010 2014 201 8 2022 2026 2 0 3 0 2034 203 8 2 042 2046

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure ES.3 Forecasted Shipments (Base Case) for Split-System Air Conditioners, Blower-Coil

ES-190.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

1990 199 4

1 998 2002 2 0 0 6 2010 2014 201 8 2022 2026 2 0 3 0 2034 203 8 2 042 2046

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure ES.4 Forecasted Shipments (Base Case) for Split-System Heat Pumps

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

1990 199 4

1 998 2002 2 0 0 6 2010 2014 201 8 2022 2026 2 0 3 0 2034 203 8 2 042 2046

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure ES.5 Forecasted Shipments (Base Case) for Single-Package Air Conditioners

ES-200.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50

1 9 9 0 1994 199 8 2 002 2006 2 0 1 0 2014 2018 2 022 2026 2 0 3 0 2034 2038 2 042 2046

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure ES.6 Forecasted Shipments (Base Case) for Single-Package Heat Pumps

ES.3.8 National Impact Analysis
The NIA estimates four national impacts from possible candidate standard levels for residential central air conditioners and heat pumps: (1) national energy savings, (2) monetary value of energy savings to consumers of the cons idered products due to standards, (3) increased total installed costs to consumers of the considered products due to standards, and (4) the NPV of potential standards (the difference between the energy savings and increased total installed costs). DOE prepared an NES spreadsheet mode l to forecast energy savings and national consumer economic costs and savings resulting from new standards.

A key component of DOE’s estimates of NES an d NPV is the trend in energy efficiency forecasted for the base case (without new standa rds) and for each of the standards cases (with new standards). To forecast the base-case effi ciency distribution for each product class, DOE accounted for changes in the market shares of mo re efficient products base d on historical trends. For its determination of standards-case efficiency distributi ons, DOE used a “roll-up + efficiency growth” scenario to establish the distribution of efficiencies for the year that revised standards are assumed to become effective ( i.e ., 2016) and subsequent years. DOE assumed that product efficiencies in the base case that did not meet the standard level under consideration would “roll up” to meet the new standard level in 2016. DOE also assumed that mark et-pull programs (such as ENERGY STAR) would continue to promote efficient applia nces after the introduction of revised standards in 2016, and that this would lead to increased market shares for products with efficiencies above the standard level. DOE a ssumed the growth in more efficient products for

ES-21the base case equaled historical rates of efficiency growth. For the standards cases, DOE developed growth trends for each standard level that maintained the same per-unit average total installed cost difference between the base case and each standards case for the year 2016 over the entire forecast period (2016–2046). Chapter 10 of the preliminary TSD provides additional detail on the development of the ba se case and standards case efficiency trends as well as all the details regarding the NIA.

ES.3.8.1 National Energy Savings

DOE calculated annual NES as the differenc e between national energy consumption in the base case and in each higher efficiency standard case. DOE estimated energy consumption and savings based on site energy (electrici ty directly consumed by the central air conditioner/heat pump) and converted the electricity consumption and savings to source energy (energy needed to produce the site energy) using factors that account for losses in transmission and distribution and in electrici ty generation. Cumulative energy savings are the sum of the annual NES, which DOE deter mined over specified periods.

The NES results shown in Table ES.14 th rough Table ES.17 are cumulative to 2046 and are shown as primary energy savings in quads (quadrillion Btus).

Table ES.14 Split-System Air Conditioners: Cumulative NES Results (quads)

SEER National* Hot-Humid Hot-Dry Rest of Country

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

13.5 0.20 0.18 0.02 0.09 0.08 0. 01 0.03 0.03 0.00 0.06 0.05 0.00

14.0 0.82 0.75 0.07 0.37 0.34 0. 03 0.13 0.12 0.01 0.24 0.22 0.02

14.5 1.46 1.33 0.12 0.65 0.59 0. 06 0.24 0.22 0.02 0.43 0.39 0.04

15.0 2.08 1.90 0.18 0.93 0.85 0. 08 0.34 0.31 0.03 0.61 0.56 0.05

15.5 2.69 2.46 0.23 1.20 1.10 0. 10 0.44 0.40 0.04 0.79 0.72 0.07

16.0 3.23 2.95 0.28 1.44 1.32 0. 12 0.52 0.48 0.04 0.95 0.87 0.08

16.5 3.51 3.18 0.33 1.57 1.43 0. 15 0.57 0.52 0.05 1.02 0.93 0.09

17.0 3.56 0.37 1.59 0.17 0.57 0.06 1.04 0.11

18.0 3.65 0.47 1.64 0.21 0.59 0.08 1.06 0.13

19.0 3.75 0.57 1.68 0.25 0.61 0.09 1.09 0.16

20.0 3.84 0.66 1.72 0.30 0.62 0.11 1.12 0.19

21.0 3.92 0.74 1.76 0.33 0.63 0.12 1.14 0.21

22.0 3.96 0.78 1.78 0.35 0.64 0.12 1.15 0.22

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. ** Total NES for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

ES-22Table ES.15 Split-System Heat Pumps: Cumulative NES Results (quads)

SEER HSPF National* Hot-Humid Hot-Dry Rest of Country

13.5 7.85 0.11 0.07 0.01 0.03

14.0 8.00 0.56 0.34 0.07 0.15

14.5 8.15 1.03 0.63 0.12 0.28

15.0 8.30 1.53 0.93 0.18 0.42

15.5 8.45 2.09 1.26 0.24 0.58

16.0 8.60 2.78 1.66 0.31 0.79

17.0 9.10 3.93 2.33 0.44 1.15

18.0 9.60 4.98 2.94 0.55 1.47

19.0 10.10 5.68 3.36 0.63 1.68

19.5 10.30 5.78 3.41 0.64 1.71

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES.

Table ES.16 Single-Package Air Conditioners: Cumulative NES Results (quads)

SEER National* Hot-Humid Hot-Dry Rest of Country

13.5 0.08 0.04 0.01 0.02

14.0 0.15 0.07 0.02 0.04

14.5 0.24 0.11 0.04 0.07

15.0 0.30 0.14 0.05 0.09

15.5 0.36 0.17 0.06 0.11

16.0 0.41 0.19 0.07 0.12

16.6 0.43 0.20 0.07 0.13

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES.

Table ES.17 Single-Package Heat Pumps: Cu mulative NES Results (quads)

SEER HSPF National* Hot-Humid Hot-Dry Rest of Country

13.5 7.85 0.04 0.02 0.00 0.01

14.0 8.00 0.10 0.06 0.01 0.03

14.5 8.00 0.19 0.12 0.02 0.05

15.0 8.00 0.28 0.17 0.03 0.08

15.5 8.50 0.36 0.22 0.04 0.11

16.0 9.00 0.41 0.25 0.05 0.12

16.4 9.00 0.43 0.26 0.05 0.12

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES.

ES.3.8.2 Net Present Value

DOE calculated NPV as the difference betwee n the present value of operating cost savings and the present value of increased total installed costs. DOE calculated operating cost savings over the life of the products purchased in the forecast period. DOE used discount rates of 7 percent and 3 percent to discount future costs and savings to the present. The NPV results for

ES-23the representative product classes are show n in Table ES.18 through Table ES.22 as the discounted value of the net savings in dollar terms.

ES-24Table ES.18Split-System Air Conditioners: Discounted Cumulative NPV Results (3% Discount Rate)SEERNational*(bill. 2008$)Hot-Humid(bill. 2008$)Hot-Dry(bill. 2008$)Rest of Country(bill. 2008$)Total**CoilOnlyBlowerCoilTotal**Coil-OnlyBlowerCoilTotal**Coil-OnlyBlowerCoilTotal**Coil-OnlyBlowerCoil13.5-0.76-0.760.000.080.060.02-0.04-0.050.01-0.93-0.88-0.0514.0-4.14-4.11-0.030.100.000.10-0.37-0.410.03-4.35-4.14-0.2114.5-9.32-9.25-0.07-0.37-0.530.16-1.07-1.130.06-8.71-8.33-0.3815.0-16.86-16.71-0.15-1.48-1.690.22-2.25-2.330.07-14.27-13.70-0.5715.5-26.88-26.59-0.29-3.28-3.540.26-3.95-4.020.07-21.04-20.25-0.7916.0-38.02-37.53-0.49-5.54-5.810.27-5.89-5.950.06-28.16-27.13-1.0416.5-44.43-43.67-0.76-6.89-7.170.27-7.01-7.050.04-32.18-30.86-1.3217.0-44.77-1.09-6.910.25-7.050.00-32.48-1.6318.0-45.67-1.99-7.010.16-7.17-0.12-33.23-2.3719.0-46.89-3.22-7.19-0.03-7.36-0.31-34.14-3.2820.0-48.41-4.74-7.47-0.30-7.62-0.57-35.19-4.3321.0-50.13-6.46-7.81-0.64-7.92-0.87-36.30-5.4422.0-51.02-7.35-8.00-0.83-8.08-1.03-36.86-6.00*Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES.** Total NPV for 17 through 22 SEER reflects the Coil-Only economic impacts at 16.5 SEER.ES-25Table ES.19Split-System Air Conditioners: Discounted Cumulative NPV Results (7% Discount Rate)SEERNational*(bill. 2008$)Hot-Humid(bill. 2008$)Hot-Dry(bill. 2008$)Rest of Country(bill. 2008$)Total**CoilOnlyBlowerCoilTotal**Coil-OnlyBlowerCoilTotal**Coil-OnlyBlowerCoilTotal**Coil-OnlyBlowerCoil13.5-0.43-0.41-0.02-0.01-0.020.004-0.04-0.040.000-0.42-0.39-0.0314.0-2.20-2.12-0.08-0.17-0.180.01-0.26-0.26-0.001-1.95-1.84-0.1114.5-4.74-4.60-0.14-0.53-0.560.02-0.64-0.64-0.002-3.87-3.67-0.2015.0-8.27-8.06-0.21-1.17-1.200.03-1.22-1.21-0.01-6.29-6.00-0.2915.5-13.06-12.75-0.31-2.16-2.190.03-2.05-2.04-0.01-9.33-8.95-0.3916.0-18.87-18.44-0.43-3.46-3.480.02-3.10-3.07-0.03-12.85-12.35-0.5016.5-22.73-22.14-0.59-4.35-4.360.00-3.80-3.75-0.05-15.13-14.50-0.6317.0-22.91-0.77-4.38-0.02-3.82-0.07-15.27-0.7718.0-23.37-1.24-4.46-0.10-3.89-0.15-15.60-1.1119.0-23.98-1.84-4.57-0.22-4.00-0.25-16.01-1.5120.0-24.71-2.57-4.73-0.37-4.12-0.38-16.47-1.9821.0-25.53-3.40-4.91-0.56-4.27-0.52-16.98-2.4822.0-26.05-3.91-5.03-0.68-4.37-0.62-17.29-2.79*Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES.** Total NPV for 17 through 22 SEER reflects the Coil-Only economic impacts at 16.5 SEER.ES-26Table ES.20Split-System Heat Pumps: Discounted Cumulative NPV ResultsSEERHSPFNational*(bill. 2008$)Hot-Humid(bill. 2008$)Hot-Dry(bill. 2008$)Rest of Country(bill. 008$)3% Disc.Rate7% Disc.Rate3% Disc.Rate7% Disc.Rate3% Disc.Rate7% Disc.Rate3% Disc.Rate7% Disc.Rate13.57.850.340.060.300.080.090.020.01-0.0214.08.001.730.321.550.390.440.130.05-0.0814.58.153.120.572.820.720.810.230.09-0.1615.08.304.310.684.010.971.150.320.06-0.2715.58.455.280.615.141.151.470.38-0.05-0.4516.08.606.270.446.351.301.810.44-0.19-0.6717.09.107.12-0.087.941.412.270.51-0.63-1.0818.09.606.07-1.358.491.122.460.47-1.64-1.7319.010.104.17-2.928.210.592.440.37-2.71-2.4219.510.303.70-3.328.070.432.410.33-2.94-2.59*Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV.Table ES.21 Single-Package Air Conditioners: Discounted Cumulative NPV ResultsSEERNational*(bill. 2008$)Hot-Humid(bill. 2008$)Hot-Dry(bill. 2008$)Rest of Country(bill. 2008$)3% Disc.Rate7% Disc.Rate3% Disc.Rate7% Disc.Rate3% Disc.Rate7% Disc.Rate3% Disc.Rate7% Disc.Rate13.5-0.62-0.33-0.03-0.04-0.07-0.05-0.54-0.2514.0-1.26-0.65-0.10-0.09-0.16-0.09-1.05-0.4714.5-2.32-1.15-0.25-0.19-0.32-0.18-1.82-0.8215.0-3.31-1.62-0.42-0.28-0.49-0.26-2.49-1.1115.5-4.53-2.21-0.66-0.41-0.70-0.36-3.27-1.4716.0-5.67-2.83-0.91-0.56-0.90-0.47-3.97-1.8316.6-6.37-3.27-1.07-0.66-1.02-0.55-4.39-2.08*Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV.ES-27Table ES.22Single-Package Heat Pumps: Discounted Cumulative NPV ResultsSEERHSPFNational*(bill. 2008$)Hot-Humid(bill. 2008$)Hot-Dry(bill. 2008$)Rest of Country(bill. 2008$)3% Disc.Rate7% Disc.Rate3% Disc.Rate7% Disc.Rate3% Disc.Rate7% Disc.Rate3% Disc.Rate7% Disc.Rate13.57.85-0.05-0.050.03-0.0060.010.000-0.05-0.0314.08.00-0.22-0.180.03-0.040.01-0.006-0.16-0.0914.58.00-0.58-0.42-0.04-0.120.00-0.02-0.35-0.2015.08.00-0.94-0.63-0.13-0.20-0.018-0.04-0.51-0.2915.58.50-1.35-0.87-0.27-0.30-0.05-0.06-0.67-0.3716.09.00-1.86-1.18-0.47-0.43-0.10-0.09-0.87-0.4816.49.00-2.16-1.38-0.60-0.52-0.13-0.11-0.99-0.56*Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV.ES-28ES.3.9 Preliminary Manufacturer Impact Analysis
The preliminary MIA focused on manufacturers of residential central air conditioners and heat pumps. Potential impacts include financial effects, both quantitative and qualitative, that might result from new energy conservation standards and consequently lead to changes in manufacturing practices for these products. DOE identified potential impacts through interviews with manufacturers and other interested parties. Chapter 12 of the preliminary TSD includes details on the key issues DOE identified during the preliminary MIA.

DOE identified eight key issues from ener gy conservation standa rds for residential central air conditioner and heat pump manufacturers:

• increased conversion costs,

• impact on U.S. production and jobs,

• cumulative regulatory burden,

• impact on product utility,

• current economic conditions,

• product substitution,

• impacts of regional standards, and

• technical difficulty of ac hieving new standards.

DOE conducted the preliminary MIA by fi rst identifying products, methods, and practices used in the residential central ai r conditioner and heat pump industry. Next, DOE examined how energy efficiency improvement s affect cost, production, and various other manufacturing metrics. Finally, DOE interviewed manufacturers and adjusted the analysis as appropriate, based on manuf acturers’ feedback. In the interviews, DOE examined any additional effects on competition, manufacturing capacity, di rect employment, and the cumulative burden of other regulations affecting manufacturers, as well as several issues raised by individual manufacturers. Chapter 12 of the preliminary TSD provides details on this and other aspects of the preliminary MIA.

ES.4 ISSUES ON WHICH DOE SEEKS PUBLIC COMMENT

DOE is particularly interested in receiving comments and views of interested parties concerning:

1. Effective Date of Standards
DOE previously determined that the final rule in this rulemaking must be published by June 30, 2011 and tentatively decided that the rule would apply to products manufactured 5 years later, in June 2016. Several comments from stakehol ders have been received to date expressing

ES-29concern regarding this compliance date. Specifically, stakeholders are concerned that the implementation of the standard during peak season could re sult in inconsistencies for distributors. DOE seeks further comment on compliance during the peak season. (Reference Chapter 2 of the preliminary TSD for details.)

2. Heat Pump Cooling Efficiency Requirements

Several stakeholders have commented to da te that the same standard should apply for both central air conditioner and heat pump products . This was the case in previous efficiency standards rulemaking, reflecting concerns that different effici ency requirements would cause consumers to switch to the product type subject to lower standards. Current analyses are treating air conditioners and heat pumps as separate pr oducts in order to determine whether separate standards may be warranted. DOE seeks comment regarding whether to implement standards with equal cooling efficiency requirements for air conditioners and heat pumps. (Reference Chapter 2 of the preliminary TSD for details.)

3. Effects of Expiration of Though-the-Wall (TTW) Product Classes
Stakeholders previously stated strong be liefs that TTW split air conditioners and heat pumps should not be included in the space-cons trained product class fo r new installations. According to these manufacturers, inclusion of the products in this class would give TTW producers a significant cost advantage due to the lower efficiency that would be required, resulting in a market shift for new construction applications. The TTW product class is defined to include products manufactured before January 23, 2010. (10 C.F.R. 430.2). As a result, TTW units meeting the definition of space-constrained products are now subject to the standard for those products, while units meeting the definiti on of conventional centra l air conditioners and heat pumps are now subject to the standard for those products. DOE seeks comment on possible shifts in the market due to the expiration of the TTW product classes. (Reference Chapter 2 of the preliminary TSD for details.)

4. Large-Tonnage Products

Comments have been received from stakeholde rs suggesting that 4- and 5-ton units be placed in a separate product class. Currently, DOE maintains that the differences between these large-tonnage units and 3-ton units are not sufficient to require a separate product class, but would consider modifying its analysis in orde r to incorporate these differences. DOE seeks comment regarding methods to account for discre pancies between typical 3-ton units and other large-tonnage products. (Reference Chapter 2 of the preliminary TSD for details.)

5. Replacement Cost of Components of Higher Efficiency Products
Amended efficiency standards are anticipated to increase the cost of new systems, as these units will require larger a nd/or more sophisticated compon ents to meet the efficiency requirements. Several manufacturer s have previously commented that the increased cost of replacing existing systems with new, higher-SEER units will motivate many users to instead repair their current systems. This could include costly repairs that, under current standards, often provide cause for end users to perform system replacement. The result would be a change in the distribution of product lif etimes as well as the estimated num ber of compressor replacements.

ES-30DOE requests comment on the impact of increased efficiency standards on end-user decisions of whether to repair or replace existing installed units. (Reference Chapter 2 of the preliminary TSD for details.)

6. Impact of Amended Standards on Domestic Manufacturers
DOE has performed a preliminary manufacturer impact analysis (MIA) in order to preliminarily quantify the financial impact of higher conservation standards on domestic manufacturers of central air conditioners and heat pumps, as well as the potential impact of these standards on manufacturing capacity and employ ment. The MIA process consists of three phases, incorporating quantitative financial analyses as well as input obtained from manufacturer interviews. MIA information will be reported as part of the preliminary analysis, and DOE seeks comment from involved parties regarding the possi ble impact of increased efficiency standards on domestic manufacturers. (Reference Chapter 2 of the preliminary TSD for details.)

7. Regional Standards
DOE has proposed two regions for establishing regional standards. DOE seeks input on the definition of the regions proposed and the viab ility of regional standards, including likely financial impacts on product dist ribution and manufacturing. (Reference Chapter 2 of the preliminary TSD for details.)

8. Hot-Dry SEER Metric
Based on analysis of climate data, DOE has proposed for consideration a hot-dry SEER metric (SEER hd ) for the hot-dry region to better character ize the seasonal efficiency of products installed in that region, but at this stage has not utilized the metric in the engineering and economic analysis. DOE seeks comment on the development of the SEER hd , on the perceived value of a SEER hd as defined, and whether this metric should be used in place of SEER in the hot dry region. (Reference Chapter 2 of the preliminary TSD for details.)

9. Split-System Air Conditioner Coil-only a nd Blower-Coil Markets and Analysis
DOE has developed the analysis by consid ering two separate markets for coil-only and blower-coil split-system air conditioners. DOE ha s weighted the relative NPV values for both markets together to define the NPV for higher efficiencies for split-syst em air conditioners. DOE believes that higher efficiencies can be obtained with blower-coil systems and higher efficiencies appear to be justified when considering th at market separately. DOE requests comment on whether the differences in costs and other market conditions justify estab lishing separate product classes for coil-only and blower-coil products. (Reference Chapter 5 of the preliminary TSD for details.)

10. Market for Coil-only Heat Pumps
DOE believes that the majority of split-system heat pumps are sold as a matched set of indoor and outdoor units for both the new constr uction and replacement markets and has not provided separate analyses of coil-only and bl ower-coil heat pumps. DOE recognizes, however, that in some instances heat pumps are used in conjunction with gas- or oil-fired furnaces, providing a “dual-fuel” heating capability. DOE requests data on the size of this dual-fuel market

ES-31as well as whether it is strongly regional in natu re. DOE also seeks input on the characterization of the heat pump replacement market and whethe r installations of matc hed sets of indoor and outdoor products should be the basis for DOE’s analysis for all heat pumps. DOE seeks input on whether it should modify the analysis for split-sy stem heat pumps to define separate coil-only and blower-coil markets. DOE also request co mment on how it might modify its energy use characterization analysis for heat pumps to captu re the impact of a home served by two different heating fuels, if that is a large market. (Reference Chapter 5 of the preliminary TSD for details.)

11. Impacts of a Regional Standard on Product Distributors, Dealers, Contractors, and Installers.
Section 325(o)(6)(D)(i) authoriz es the Secretary to establish regional standards only if the regional standards will produce significant energy savings in comparison to a single national standard and are economically jus tified. Further, Section 325(o)(6)(D )(ii) of EPCA states that a regional standard can only be es tablished if the Secretary considers the impact of additional regional standards on consumers, manufacturers , and other market participants, including product distributors, dealers, contractors, and installers. DOE received comment on the framework document that suggest distributors of ce ntral air conditioners and heat pumps to more than one region and general contractors coul d bear disproportionate compliance costs (see section 2.10 in chapter 2 of the preliminary TSD) . DOE believes that data publicly available from EIA and other sources will allow DOE to conduct an LCC analysis and a regional “subgroup analysis” to determine the effects on consumers at the regional level. DOE seeks any additional information on consumer impacts, and in particular se eks information on the potential impacts on distributors, dealers, contractors and installers. DOE specifically seeks quantitative and qualitative information concerning market mechanisms and market circumstances that would be more likely to generate such impacts. DOE is particularly interested in: (1) how common it is for individual distributors and d ealers of central air conditioners and heat pumps to distribute these products to more than one of the proposed regions; (2) what percent of market sales go through multiregional distributors; (3) what effect regional standards would have on the dollar value of inventory carried and carrying charges for that inventory; (4) what effect regional standards would have on sa les and operating costs; and (5) what percent of distributors are small businesses. DOE believes that most contractors and installers are likely to do business in only a few jurisdictions and are unlikely to bear exceptional costs as a result of the central air conditioner and heat pump standards due to operations in more than one region. DOE is interested in information (especially quantitative in formation) that would either support or refute this hypothesis. (Reference Chapter 17 of the preliminary TSD for a preliminary assessment of the impacts of regional standards on market pa rticipants other than manufacturers and consumers.)

12. Enforcement Plan Mechanisms
If regional standards are adopted for this rulemaking, the Energy Independence and Security Act of 2007 (EISA 2007) mandates that an enforcement plan rulemaking be initiated no later than 90 days after the issuance of the sta ndard final rule. (42 U.S.C. 6295(o)(6)(G)) DOE received comment that it should begin to develop the enforcement plan earlier and believes that it is important to do so to understand the impact s of regional standards. DOE requests input on the viability of the enforcement mechanisms disc ussed in section 2.10.3 of chapter 2, as well the

ES-32extent to which these or other proposed mechanis ms would result in add itional financial burdens to consumers, manufacturers, contractors, distributors, dealers, and installers.

13. Off-Mode Energy Consumption

EISA 2007 mandates that DOE consider ame nded test procedures and standards for standby-mode and off-mode energy consumpti on by covered products (such as central air conditioners and heat pumps) for any amended st andard published after July 1, 2010. (42 U.S.C. 6295(gg)(3)) DOE’s test procedure already accoun ts for standby-mode energy consumption in the SEER and HSPF metrics for central air c onditioners and heat pumps, but does not account for off-mode energy consumption. DOE request s comment on the energy consuming components during off-mode as well as the potential to reduce the energy consumption of these components. DOE also requests comment on the potential impacts of separate standard for off-mode energy consumption. (Reference section 2.1.2.8 of chapter 2 for more details.)

14. Combination Standards Rulemaking for Cent ral Air Conditioners and Heat Pumps, Gas Furnaces, and Furnace Fans
DOE is currently pursuing separate standard s rulemakings for three interrelated products: (1) central air conditioners and heat pumps; (2) gas furnaces; and (3) furnace fans. DOE is required by consent decree to publish a final rule for central air conditioners and heat pumps by June 30, 2011. A final rule for gas furnaces pub lished in November 2007 was remanded by the Courts to DOE with the requirement that DOE publish a new final rule by May 1, 2011. EISA 2007 requires that DOE publish a final rule for furnace fans by January 1, 2013. Rather than analyze each set of products separately, DOE is contemplating a combined analysis to examine the first cost and energy savings impacts of th e interaction between the products. If DOE conducts such an analysis and the results indicat e that a combined approach yields additional savings beyond what can be achieved by analyzing each product separately, DOE may decide to pursue a combined standards rulemakings that addresses all three sets of products (or two of the three, i.e., central air conditioners and heat pumps and furnaces) simultaneously. If such a combined rulemaking is pursued, DOE would ne ed to publish a final rule by May 1, 2011; the earliest date for which standards for gas furnaces need to be finalized.

15. Maximum Technologically Feasible Designs
In assessing the viability of maximum technol ogically feasible designs, DOE conducts a screening analysis to determine their viability base d on four criteria: (1) technological feasibility; (2) practicability to manufacture, install, and service; (3) impacts on equipment utility or equipment availability; and (4) adverse impacts on health or safety. The maximum efficiency levels that DOE analyzed for each product cl ass took into account the level’s viability in consideration of the four above criteria. However, DOE is aware of two additional designs that it may consider in this rulemaking: (1) solar assi st technologies and (2) three-stage heat pumps. Solar assisted products are currently available in the market. These products utilize solar energy to supplement the electrical ener gy required for the product to operate. Three-stage heat pumps are also currently available in the market and operate efficiently at low ambient temperatures through the use of additional compressors and com ponents, thereby precluding the need for back up electric resistance heat. DOE believes the bene fits for this technology result primarily in improved heat pump heating, and not cooling, performance. Because both technologies are

ES-33available on the market, DOE requests comment on how the energy conservation standard rulemaking can best address so lar assist and three-stage heat pump technologies. DOE also requests comment on any other technology that is available on the market and could increase maximum technologically feasible efficiency levels.

16. Consensus Agreement
On January 26, 2010, the Air-Conditioning, Heating and Refrigeration Institute (AHRI), American Council for an Energy Efficient Econom y (ACEEE), Alliance to Save Energy (ASE), Appliance Standards Awareness Project (ASAP), Natu ral Resources Defense Council (NRDC), and Northeast Energy Efficiency Partnerships (NEEP) submitted a joint comment to DOE recommending minimum energy conservation standa rds for residential central air conditioners, heat pumps, and furnaces. This consensus agreement is available on DOE’s website, which can be found at: http://www1.eere.energy.gov/buildings/appliance_standards/residential/furnaces_boilers.html

. DOE specifically requests comment on the consensus agreement. In particular, DOE is interested in comments relating to the proposed SEER, HSPF, and EER requirements, the proposed regional divisions, and the proposed compliance date s for residential central air conditioners and heat pumps.

ES-34CHAPTER 1. INTRODUCTION

TABLE OF CONTENTS

1.1 PURPOSE OF THE DOCUMENT

................................................................................. 1-1 1.2 OVERVIEW OF ENERGY CONSERVATION STANDARDS FOR RESIDENTIAL CENTRAL AIR CONDITIONERS AND HEAT PUMPS

............................................. 1-1 1.2.1 Small-Duct, High-Velocity Systems

.................................................................... 1-2 1.2.2 Space-Constrained Products

................................................................................ 1-5 1.2.2.1 Single-Package Vertical Units (SPVUs)

.................................................. 1-5 1.2.2.2 Through-the-Wall Systems

...................................................................... 1-6 1.2.2.3 Single-Package Non-Weatherized Units

.................................................. 1-6 1.2.3 Ductless Split Systems

......................................................................................... 1-7 1.3 PROCESS FOR SETTING ENERGY C ONSERVATION STANDARDS

................... 1-7 1.4 STRUCTURE OF THE DOCUMENT

.......................................................................... 1-10

LIST OF TABLES

Table 1.3.1 Central Air Conditioning Analyses Under the Process Rule

................................... 1-2CHAPTER 1. INTRODUCTION

1.1 PURPOSE OF THE DOCUMENT

This preliminary technical support document (p reliminary TSD) is a stand-alone report that provides the technical analyses and resu lts supporting the information presented in the preliminary notice of public meeting (NOPM) and executive summary for residential clothes dryers and room air conditioners. This preliminary TSD reports on the preliminary activities and analyses conducted in the period preceding the no tice of proposed rulemaking (NOPR) of this rulemaking.

1.2 OVERVIEW OF ENERGY CONSERVATION STANDARDS FOR RESIDENTIAL CENTRAL AIR CONDITIONERS AND HEAT PUMPS

The National Appliance Energy Conservati on Act of 1987 (NAECA) established energy conservation standards for central air conditioners and heat pumps as well as requirements for determining whether these standards should be amended. Specifically, NAECA established energy conservation standards for central air conditioners and heat pumps in the form of minimum limits on the seasonal energy efficiency ratio (SEER) for air conditioners and for heat pumps operating in the cooling mode, and on the heating seasonal performance factor (HSPF) for heat pumps operating in the heating mode. NAECA established the following standards for central air conditioners and heat pum ps: 10.0 SEER/6.8 HSPF for split systems, 1 9.7 SEER/6.6 HSPF for single-package systems. 2 These standards became effective January 1, 1992 for split systems; standards for single-package systems came into effect one year later. See 42 U.S.C. 6295(d)(1)(A)-(B) and (2)(A)-(B). NAECA also required that DOE conduct two cycles of rulemakings to determine if more stringent standards are economically justified and technologically feasible. (42 U.S.C. 6295(d)(3)(A)-(B))

Pursuant to 42 U.S.C. 6295(d)(3)(A), DOE published a final rule in the Federal Register on January 22, 2001 (2001 final rule), amending the energy conservation sta ndards for central air conditioners and heat pumps. 66 FR 7170. The amended standards woul d have increased the minimum SEER to 13 and the minimum HSPF to 7.7. Id. This final rule constituted the first cycle of revised standards for central air conditioners and heat pumps.

Shortly after the publication of the 2001 final rule, DOE postponed the effective date of the rule to take time to reconsider the amended standards for central air conditioners and heat pumps. DOE eventually promulgated a 12 SEER standard in a final rule published May 23,

1 “Split systems” consist of outdoor and indoor units which are “split” from each other and connected via refrigerant tubing. The outdoor unit resides outdoors and consists of a compressor, heat exchanger coil, fan, and fan motor. The indoor unit, consisting of a heat exchanger coil, resides either within a furnace or blower-coil unit, and conditioned air is conveyed to the home via ducts

2 In “single-package systems,” all the components that comprise a split system, including the air circulation equipment, are placed in a single cabinet. The single-package system resides outdoors, and conditioned air is conveyed to the home via ducts.

1-12002 (2002 final rule), 67 FR 36368, but the U.S. C ourt of Appeals for the Second Circuit ruled that DOE had done so improperly. Natural Resources Defense Council v. Abraham , 355 F.3d 179 (2d Cir. 2004). As a result, DOE publis hed a technical amendment on August 17, 2004, which established a 13 SEER standard for all central air conditioners a nd heat pumps, excluding through-the-wall and space-cons trained systems. 69 FR 50997.

EPCA was further amended by the Energy Policy Act of 2005 (EPACT), Pub. L. 109-58. In Section 141 of EPACT, Congress directed DOE to submit an initial report regarding a plan for expeditiously prescribing new or revised standa rds. Pursuant to Section 141 of EPACT, DOE submitted an implementation report 3 to Congress in January 2006. This report specified a schedule for the completion of the second rulemaki ng cycle of revised standards for central air conditioners and heat pumps, requiring DOE to publish a final rule by June 2011, with a standards compliance effective date of J une 2016. In separate court proceedings ( New York v. Bodman , No. 05 Civ. 7807 (S.D.N.Y. filed Sept. 7, 2005) and Natural Resources Defense Council v. Bodman , No. 05 Civ. 7808 (S.D.N.Y. filed Sept. 7, 2005) the resulting consent decree (filed November 6, 2006) adopted the schedule for central air conditioners and heat pumps that DOE published in the January 2006 report to Congress ( i.e. , June 30, 2011).

More recently, EPCA was amended by the Energy Independence and Security Act of 2007 (EISA 2007), Pub. L. 110-140. In Section 306 of EISA 2007, Congress directed DOE to consider regional standards for central air cond itioners and heat pumps (among other products), for one or two regions in addition to a base na tional standard. (42 U.S.C. 6295(o)(6)) EISA 2007 states that in considering regional standa rds, DOE may consider regions made up of contiguous States only. Further, in Sec tion 310 of EISA 2007, Congress directed DOE to consider amended test proce dures and standards for standby-mode and off-mode energy consumption by covered equipment (such as ce ntral air conditioners and heat pumps) for any amended standard published after July 1, 2010. (42 U.S.C. 6295(gg)(3)) Because this energy conservation standards rulemaking for central air conditioners and heat pumps will be completed in 2011, the requirement to incorporate standby-m ode and off-mode energy use into the energy conservation standards analysis is applicable.

1.2.1 Small-Duct, High-Velocity Systems

DOE initially sought to create a separate pr oduct class for small-duct, high velocity (SDHV) systems. DOE reasoned that SDHV syst ems have design considerations (confined installation spaces, high pressure drops, and blower motor power) that warrant special consideration in the analytical and standards- setting process. In the 1999 Supplemental Advance Notice of Proposed Rulemaking (SANOPR) (1999 SANOPR; 64 FR 66306 (Nov. 24, 1999)) for central air conditioners, DOE proposed the creation of a separate class of “space-constrained” products that included SDHV systems and requeste d feedback from stakeholders on the proposal to create a separate product class for SDHV systems. However, DOE received feedback on the 1999 SANOPR that indicated some SDHV units were capable of reaching 12 SEER, and that manufacturers were making investments to produce more efficient SDHV systems.

3 Energy Conservation Standards Activities , January 2006. This document can be downloaded from the DOE website at: http://www.eere.energy.gov/buildings/appliance_standards/2006_schedule_setting.html.

1-2For these reasons, in the October 5, 2000, NOPR (2000 NOPR; 65 FR 59590), DOE proposed not to create a separate SDHV product class, instead requiring SDHV systems to meet the standards for conventional split and single-package systems. 4 However, DOE also proposed to allow SDHV systems the option to test as coil- only products. This additional provision in the test procedure was estimated to provide an additional 1 to 2.5 SEER points for SDHV systems, making it easier for manufacturers to meet the standard. DOE again requested feedback from stakeholders on this proposal.

On January 22, 2001, DOE published the 2001 final rule, establishing a 13 SEER standard for conventional split and single-package systems and reiterating that th e characteristics of available SDHV systems did not warrant the creation of a separa te product class. 66 FR at 7197 DOE explained that revisions to the test proce dure would allow testing as coil-only products, and stated that SDHV systems were, therefore, subj ect to the 13 SEER standards being adopted for all split-system and single-package air conditioners and heat pumps.

On July 25, 2001, in response to a petition for r econsideration and as a result of review under the President’s Regulatory Review Plan, 5 DOE reopened the standards rulemaking and published a Supplemental Notice of Proposed Rule making (SNOPR), in which DOE proposed to withdraw its January 22, 2001 final rule. 66 FR 38822. As a substitute, DOE proposed standards in that SNOPR which would have set a 12 SEER standard for all split-system and single-package air conditioners and heat pumps, thereby resulting in a 20 percent increase in the minimum energy efficiency levels over prior levels. Again, DOE proposed not to establish a separate class for SDHV systems on the grounds that they would be able to meet the 12 SEER standard.

In the subsequent May 23, 2002 final rule, DOE adopted the 12 SEER standard for splitsystem and single-package air conditioners a nd heat pumps, and responded to additional comments from stakeholders on SDHV systems. 67 FR 36368. Further information submitted by stakeholders led DOE to conclude that sepa rate standards for SDHV systems were indeed warranted, and DOE stated it would perform a se parate analysis to determine appropriate standard levels. A new produc t class and definition for SDHV systems were established, and standards were set at the 10 SEER NAECA level until a full analysis could be performed. Further, DOE stated it would consider stakeholde rs’ requests that the DOE test procedure be amended to allow special testin g provisions for SDHV products. At the time of drafting the 2002 final rule, DOE had begun a separate engineer ing and life-cycle cost analysis to determine appropriate standard levels for SDHV products.

However, DOE’s efforts to reopen its rulemaking setting energy conservation standard levels for central air conditioners and heat pum ps were challenged by a number of advocacy groups. In its decision in Natural Resources Defense Council, et al. v. Abraham , the Second Circuit Court concluded that “the May 23, 2002, final rules promulgated by DOE withdrawing the standards it published as a final rule on January 22, 2001, and replacing them with less

4 Standards for conventional systems were proposed at 12 SEER for split and single-package air conditioners and 13 SEER for split-system and single-package heat pumps.

5 The Regulatory Review Plan, which called for agencies to (among other things) withdraw or postpone the effective dates of regulations pending review by the White House, was published in the Federal Register at 66 FR 7702 (Jan. 24, 2001).

1-3stringent standards, were not a valid exercise of DOE's authority under the EPCA,” in light of the “anti-backsliding” provision in 325(o)(1) of EPCA. Section 325(o)(1) of EPCA states that “[t]he Secretary may not prescribe any new or amended standard which increases the maximum allowable energy use...of a covered pr oduct.” 355 F.3d 179, 206 (2d Cir. 2004). Accordingly, DOE published a technical amendment on Augu st 17, 2004 (2004 Technical Amendment; 69 FR 50997). This technical amendment replaced standard levels esta blished by the 2002 final rule (12 SEER) with the 13 SEER standard s established in the 2001 final rule.

Because the 2001 final rule did not establish a separate class or separate standards for SDHV systems, and because SDHV systems are not considered “space constrained” (see discussion in 66 FR at 7197 and 65 FR at 59609-10), they are covered by the 13 SEER/7.7 HSPF standard adopted in that rule. The Court’s ru ling prohibits DOE from adopting a standard of less than 13 SEER for SDHV systems, despite DO E’s more recent conclusion that SDHV systems have a maximum technologically feasib le efficiency of just over 13 SEER. 6

Further, in the test procedures detailed in the October 11, 2005 final rule, DOE stated that test procedure revisions to allow SDHV system s to test as coil-only units would result in unrealistic SEER ratings and would discourage manufacturers from making efficiency improvements to blower motors. 70 FR at 59124. Therefore, DOE did not amend the test procedure to allow testing of SDHV systems as coil-only units, making it more likely that SDHV products would be unable to meet even the 12 S EER standard. DOE advi sed manufacturers of SDHV systems of the procedure available under section 504 of the DOE Organization Act (42 U.S.C. 7194), which allows them to request re lief from hardship or inequity caused by a regulation issued under EPCA.

On May 24, 2004, SpacePak and Unico, Inc., filed a joint application with the Office of Hearings and Appeals (OHA) for exception from th e 13 SEER standard, arguing that they would suffer a “serious hardship and unf air distribution of burdens” if forced to comply with the 13 SEER rule (case nos. TEE-0010 and TEE-0011) The OHA granted the exception to SpacePak and Unico, citing technological constraints (compact indoor coils, hi gh static-pressure losses, and higher fan motor power) that make it more di fficult for SDHV systems to increase energy efficiency. Also cited was the serious hardship to SpacePak and Unico that would result should exception relief not be granted, possibly resulting in “the loss of all sales within the United States.” The OHA further noted that the unavailability of SDHV systems would negatively impact domestic consumers, and that granting exception relief would not have a significant impact upon competition in the air conditioner in dustry. On October 14, 2004, the OHA granted exception relief to SpacePak and Unico, Inc., au thorizing them to manufacture and sell SDHV systems that meet an 11 SEER/6.8 HSPF standa rd. This decision became effective January 23, 2006, and remains in effect until DOE establishe s a different standard for SDHV systems.

On September 28, 2005, Energy Savings Products , Ltd. (ESP), filed its own application for exception relief with the OHA (case no. TEE-0 026). ESP asserted that it would suffer a

6 In 2002, DOE performed a separate engineering analysis for SDHV systems by evaluating the incremental costs and efficiency improvements associated with design changes to blower coil units and pairing of existing SDHV blower coil units with higher-efficiency outdoor units. In that analysis, DOE found that the maximum technologically feasible (“max-tech”) efficiency of SDHV systems was just over 13 SEER. http://eere.energy.gov/buildings/appliance_standards/residential/pdfs/engineering_analysis_112602.pdf

1-4gross inequity, serious hardship, and an unfair dist ribution of burdens if forced to comply with the 13 SEER standard. On December 20, 2005, the OHA granted the exception relief to ESP, citing the same reasons given in the SpacePak/U nico decision and authorizing Energy Savings Products to manufacture and sell SDHV systems that meet an 11 SEER/6.8 HSPF standard. This decision also became effective January 23, 2006, a nd remains in effect until DOE establishes a different standard for SDHV systems.

1.2.2 Space-Constrained Products

In the 1999 SANOPR, DOE first suggested se parate product classes as a way to set standards for space-constrained niche products. 64 FR at 66310. Originally, these products included ductless split systems, SDHV systems, single-package vertical units (SPVU), and through-the-wall (TTW) split systems. In the subsequent 2000 NOPR, through-the-wall packaged and non-weatherized single-package products were also considered space constrained. 65 FR at 59597. DOE’s efforts to establish standards for each of these types of products is explained below.

In the 2004 Technical Amendment, DOE established a separate product class for spaceconstrained systems and required them to meet a 12 SEER/7.4 HSPF standard. Product classes were also set for split-system and single-pack age TTWs, with standards at 10.9 SEER/7.1 HSPF and 10.6 SEER/7.0 HSPF, respectively. The separa te product class for TTW products is set to expire January 23, 2010, which will return those products to the space-c onstrained product class and require them to meet the 12 SEER/7.4 HSPF standard.

Currently, ductless split systems are not considered a space-constrained product and are not given special consideration. They are, ther efore, required to meet the 13 SEER/7.7 HSPF standards for split-system and single-package ai r conditioners and heat pumps. SDHV systems are also not considered space constrained, a nd are required to meet the 13 SEER/7.7 HSPF standards.

In this rulemaking, DOE is reevaluating whet her to give special consideration to these space-constrained products. Below, the history of each type of product is reviewed, and DOE’s approach for how to handle each type in this rulemaking is presented.

1.2.2.1 Single-Package Vertical Units (SPVUs)

In the 2000 NOPR, DOE stated that SPVUs ar e not covered by standards for residential products. 65 FR at 59610. EISA 2007 added definitions 7 and standards 8 for SPVUs. While

7 Section 314 of EISA 2007 codifies definitions for “singl e package vertical air conditioner” and “single package vertical heat pump.” The term “single package vertical air conditioner” means “air-cooled commercial package air conditioning and heating equipment that (A) is factory-assemb led as a single package that (i) has major components that are arranged vertically; (ii) is an encased combinatio n of cooling and optional heating components; and (iii) is intended for exterior mounting on, adj acent interior to, or through an outside wall; (B) is powered by a single- or 3

- phase current; (C) may contain 1 or more separate indoor grilles, outdoor louvers, various ventilation options, indoor free air discharges, ductwork, well plenum, or sleeves; and (D) has heating components that may include electrical resistance, steam, hot water, or gas, but may not include reverse cycle refrigeration as a heating means.” The term “single package vertical heat pump” means “a single pack age vertical air conditioner th at (A) uses reverse cycle

1-5EISA 2007 defined SPVUs as commercial equipmen t, residential single-package TTW products are still considered a part this rulemaking.

1.2.2.2 Through-the-Wall Systems

In the 2000 NOPR, DOE recognized TTW products as being a niche category of products with space constraints, and proposed adopting an 11 SEER standard for them. 65 FR at 59610. However, in light of stakeholders’ concerns that TTW products would not be able to meet the 13 SEER standard, the 2001 Final Rule did not set standards for TTW products, pending completion of later rulemaking proceedings. Prior to the subsequent 2001 SNOPR, DOE performed engineering and life-cycle cost analyses for TTW products to determine appropriate standard levels. Based on those analyses, DOE conc luded that 10.9 SEER/7.1 HSPF and 10.6 SEER/7.0 HSPF were the appropriate standards for sp lit-system and single-package TTW products, respectively, and adopted those standards in the 2002 final rule. 67 FR 36368 In the 2004 Technical Amendment, DOE expl ained that the standards for TTW products, which fall within the definition of “space-constrained product,” would be those set in the 2002 final rule.

The definition of “through-the-wall air conditioner and heat pump” that DOE adopted in 10 CFR 430.2 provides that this product class exis ts only for products manufactured prior to January 23, 2010. After that date, the standards for space-constrained products (12 SEER/7.4 HSPF) will apply to TTW split-system and packag ed air conditioners and heat pumps. Because this “sunset” provision takes place well before the effective date of this rule (2016), DOE will evaluate standards for TTW products based on an assumed baseline of 12 SEER/7.4 HSPF. Manufacturers will have six years between the time TTW products must meet the 12 SEER/7.4 HSPF standard and the time new standards adopted in this ru lemaking become effective.

1.2.2.3 Single-Package Non-Weatherized Units

In the 2000 NOPR, DOE recognized single-package non-weatherized units as having space constraints, but due to the availability of models at the 12 SEER level (the proposed standard level for conventiona l air conditioners in that rulemaking), DOE did not propose a separate product class for them. 65 FR at 59610. Additionally, DOE concluded it would be difficult to define these products in such a way that would avoid the creation of a loophole whereby conventional products coul d take advantage of lower standards. In the 2001 final rule, DOE again made mention of single-package non-w eatherized units, but DOE decided to include them as a type of space-constrained product. The 2001 final rule established a new product class for space-constrained products, but did not set sta ndards in that rule pendi ng completion of later rulemaking proceedings. In the subsequent 2001 SNOPR and the 2002 final rule, no specific mention was made of single-package non-weatherize d units, but DOE still considered them as a type of space-constrained product. In the 2002 final rule, DOE concluded that space-constrained products (excluding TTW products) would be able to meet the 12 SEER standard for conventional products, and did not adopt separate standards for those considered space constrained. Ultimately, in the 2004 Technical Amendment, DOE explained that the ruling by

refrigeration as its primary heat source; and (B) may incl ude secondary supplemental heating by means of electrical resistance, steam, hot water, or gas.’’ (42 U.S.C. 6311(22)-(23))

8 Section 314 of EISA 2007 set standards at 9.0 EER for si ngle-package vertical air conditioners and 9.0 EER/3.0 coefficient of performance (COP) for single-package vertical heat pumps.

1-6the Second Circuit Court of Appeals in Natural Resources Defense Council v. Abraham did not affect the standards established for space-cons trained products in the 2002 final rule, since the 2001 final rule did not establish any standards fo r space-constrained products. Therefore, the 12 SEER standard established in the 2002 final rule was adopted for all space-constrained products, except those with TTW condensers.

1.2.3 Ductless Split Systems

Ductless split systems were included in the revisions to the DOE test procedure in the March 14, 1987 final rule. 53 FR 8304. In the 1999 SANOPR, DOE first suggested separate product classes as a way to set standards for niche products, incl uding ductless split systems. 64 FR at 66310. Since consumers may consider the in terior units of mini- and multi-splits to be more intrusive than ducted systems, manufacturers strive to make them as compact as possible. After receiving stakeholder feedback, DOE deci ded that a separate product class was not warranted, and ultimately in the final rule that set the current standards, ductless split systems were required to meet the 13 S EER standards developed for regu lar split-system air conditioners and heat pumps. 66 FR at 7197.

Prior to the latest revision to the test procedure, manufacturers of ductless split systems applied for and received waivers from the test procedure because of the differences between multi-split systems and traditional split-system air conditioners and heat pumps. In the most recent final rule revising the central air c onditioner and heat pump test procedure, DOE responded to stakeholder comments regarding chan ges to the test procedure for multi-splits. 72 FR at 59906, 59908-11 and 59913-14 (Oct. 22, 2007). Stakeholders asserted that multi-split systems should be rated using EER if those systems compete primarily with room air conditioners and SEER if they compete primarily with ducted residential systems. DOE responded in the October 2007 rule that it believes resi dential-size multi-split systems compete primarily with ducted systems, and that consumers will best be served if multi-split systems are rated using SEER. This will allow consumers to make direct comparisons of efficiency levels when considering system options.

1.3 PROCESS FOR SETTING ENER GY CONSERVATION STANDARDS

Under EPCA, when DOE studies new or amen ded standards, it must consider to the greatest extent practicable the following seven factors:

(1) the economic impact of the standard on the manufacturers and consumers of the products subject to the standard;

(2) the savings in operating costs throughout the estimated average life of the products in the type (or class) compared to any increases in the price, initial charges, or maintenance expense for the products that are likely to result from the imposition of the standard;

(3) the total projected amount of energy savings likely to result directly from the imposition of the standard;

1-7(4) any lessening of the utility or the performance of the products likely to result from the imposition of the standard;

(5) the impact of any lessening of compe tition, as determined in writing by the Attorney General, that is likely to result from the imposition of the standard;

(6) the need for national energy conservation; and

(7) other factors the Secretary considers relevant. (42 U.S.C. 6295(o)(2)(B)(i))

Other statutory requirements are set forth in 42 U.S.C. 6295(o)(1)-(2)(A), (2)(B)(ii)-(iii), and (3)-(4).

DOE considers the participation of interested parties a very important part of the process for setting energy conservation standards. Thro ugh formal public notifications (i.e., Federal Register notices), DOE encourages the participation of all interested parties during the comment period in each stage of the rulemaking. Beginning with the framework document and during subsequent comment periods, in teractions among interested parties provide a balanced discussion of the information that is required for the standards rulemaking.

Before DOE determines whether to adopt a proposed energy conservation standard, it must first solicit comments on the proposed sta ndard. (42 U.S.C 6313(a)(6)(B)(i)) Any new or amended standard must be designed to achieve significant additional conservation of energy and be technologically feasible and economically justified. (42 U.S.C. 6313( a)(6)(A)) To determine whether economic justification exists, DOE must review comments on the proposal and determine that the benefits of the proposed sta ndard exceed its burdens to the greatest extent practicable, weighing the seven factors listed above. (42 U.S.C. 6295(o)(2)(B)(i))

After the publication of the framework docum ent, the energy conservation standards rulemaking process involves thr ee additional, formal public notices, which DOE publishes in the Federal Register. The first of the rulemaking no tices is a NOPM, which is designed to publicly vet the models and tools used in the preliminary rulemaking and to facilitate public pa rticipation before the NOPR stage. The second notice is the NOPR, which presents a discussion of comments received in response to the NOPM and th e preliminary analyses and analytical tools; analyses of the impacts of potential amended energy conservation standards on consumers, manufacturers, and the Nation; DOE’s weigh ting of these impacts of amended energy conservation standards; and the proposed energy conservation standards for each product. The third notice is the final rule, which presents a discussion of the comments received in response to the NOPR; the revised analyses; DOE’s weighting of these impacts; the amended energy conservation standards DOE is adopting for each product; and the effective dates of the amended energy conservation standards.

In June 2008, DOE published a notice of public meeting and availability of the framework document. 73 FR 32243 (June 6, 2008) The framework document, Rulemaking Framework for Residential Central Air Conditioners and Heat Pumps , describes the procedural and analytical approaches DOE anticipated using to evaluate the establishment of energy conservation standards for CAC. This document is available at:

1-8http://www1.eere.energy.gov/buildings/app liance_standards/residential/central_ac_hp_standard s.html.

Subsequently, DOE held a public meeting on June 12, 2008, to discuss procedural and analytical approaches to the rulemaking, and to inform and facilitate st akeholders’ involvement in the rulemaking process. The analytical fr amework presented at the public meeting described different analyses, such as the engineering analysis and the life-cycle cost (LCC) and payback period (PBP) analyses, the methods proposed fo r conducting them, and the relationships among the various analyses. See for all the analyses discussed at the public m eeting to be undertaken in each of the formal public rulemaking documents.

Table 1.3.1 Analyses During Each Rulemaking Stage Preliminary Analyses NOPR Final Rule* Market and Technology Assessment Revised Preliminary Analyses Revised NOPR Analyses

Screening Analysis Life-Cycle Cost Sub-Group Analysis Engineering Analysis Manufacturer Impact Analysis Energy Use Characterization Utility Impact Analysis Markups to Determine Equipment Price Employment Impact Analysis Life-Cycle Cost and Payback Period Analyses Environmental Assessment

Shipments Analysis Regulatory Impact Analysis National Impact Analysis Preliminary Manufacturer Impact Analysis

* During the Final Rule phase, DOE considers the comments submitted by the U.S. Department of Justice in the NOPR phase concerning the impact of any lessening of competition that is likely to result from the imposition of the standard. (42 U.S.C. 6295(o)(2)(B)(v))

As part of the information gathering and sharing process, DOE organized and held interviews with CAC manufacturers. DOE select ed companies that repr esented production of alltypes of CAC equipment, ranging from small to large manufacturers, and including both AirConditioning, Heating and Refrigeration Institu te (AHRI) member companies and non-AHRI member companies. DOE had four objectives for these interviews: (1) solicit feedback on the draft engineering analysis (including methodolog y, production costs, ma nufacturing processes, and findings); (2) solicit feedback on topics related to the preliminary manufacturer impact analysis; (3) provide an opportunity, early in the rulemaking process, to express specific concerns to DOE; and (4) foster cooper ation between the manufacturers and DOE.

There were six general topics related to the preliminary manufacturer impact analysis discussed during each of the interviews: (1) ge neral key issues, (2) CAC shipment projections, (3) capital conversion costs, (4) product mix and profitability, (5) market shares and industry consolidation, and (6) cumulative regulatory burden.

DOE incorporated the information gathered at the meetings into its engineering analysis (see chapter 5) and the preliminary manufacturer impact analysis (see chapter 12). Following the publication of the preliminary analysis and the preliminary analysis public meeting, DOE intends

1-9to hold additional meetings with manufacturers as part of the consultative process for the manufacturer impact analysis conducted dur ing the NOPR phase of the rulemaking.

DOE developed spreadsheets for the LCC, PBP, and national impact analyses. DOE developed an LCC spreadsheet that calculates the LCC and PBP at various energy efficiency levels. DOE also developed a national impact anal ysis spreadsheet that calculates the national energy savings (NES) and national net present values (NPVs) at various energy efficiency levels. This spreadsheet includes a model that forecasts the impacts of amended energy conservation standards at various leve ls on product shipments.

1.4 STRUCTURE OF THE DOCUMENT

This preliminary TSD outlines the analytical approaches used in this rulemaking. The TSD consists of 17 chapters, an environmental assessment, a regulatory impact analysis, and appendices.

Chapter 1 Introduction: provides an overview of the appliance and equipment standards program and how it applies to the CAC rulemaking, and outlines the structure of the document.

Chapter 2 Analytical Framework, Comme nts from Interested Parties, and DOE Responses: describes the rulemaking process step by step, summarizes comments made from interested parties during the framework document comment period, and provides DOE responses to those comments.

Chapter 3 Market and Technology Assessm ent: characterizes the CAC equipment market and the technologies available for increasing equipment efficiency.

Chapter 4 Screening Analysis: determines which technology options are viable for consideration in the engineering analysis.

Chapter 5 Engineering Analysis: discu sses the methods used for developing the relationship between increased ma nufacturer price and increased efficiency.

Chapter 6 Markups to Dete rmine Product Price: discusses the methods used for establishing markups for converting manufacturer prices to customer product prices.

Chapter 7 Energy Use Characterization: discusses the process used for generating energy-use estimates of CAC for a variety of product classes, climate locations, and standard levels.

Chapter 8 Life-Cycle Cost and Payback Period Analyses: discusses the economic effects of standards on individual cust omers and users of the products and compares the LCC and PBP of pr oducts with and without higher efficiency standards.

1-10Chapter 9 Shipments Analysis: discusses the methods used for forecasting shipments with and without higher efficiency standards.

Chapter 10 National Impact Analysis: di scusses the methods used for forecasting national energy consumption and national economic impacts based on annual product shipments and estimates of future product efficiency distributions in the absence and presen ce of higher efficiency standards.

Chapter 11 Life-Cycle Cost Sub-Group Anal ysis: discusses the effects of standards on a subgroup of CAC customers and compares the LCC and PBP of products with and without higher effici ency standards for these customers.

Chapter 12 Preliminary Manufacturer Impact Analysis: discusses the effects of standards on the finances and profitability of product manufacturers.

Chapter 13 Utility Impact Analysis: discusses the effects of standards on the installed generation capacity of electric utilities.

Chapter 14 Employment Impact Analysis: discusses the effects of standards on National employment.

Chapter 15 Environmental Assessment: di scusses the effects of standards on air

borne emissions of electric utilities.

Chapter 16 Regulatory Impact Analysis: discusses the present regulatory actions as well as the impact of non-regulatory alternatives to setting energy efficiency standards.

Chapter 17 Regional Standards Impacts on Mark et Participants: discusses the effects of regional standards on distributors, d ealers, contractors, and installers.

1-11CHAPTER 2. ANALYTICAL FRAMEWORK, COMMENTS FROM INTERESTED PARTIES, AND DOE RESPONSES

TABLE OF CONTENTS 2.1 INTRODUCTION

.............................................................................................................. 1 2.1.1 Overview

................................................................................................................. 1 2.1.2 Miscellaneous Rulemaking Issues

.......................................................................... 3 2.2 MARKET AND TECHNOLOGY ASSESSMENT

........................................................... 7 2.2.1 Product Classes and Scope of Coverage

................................................................. 8 2.2.2 Technology Assessment

........................................................................................ 10 2.3 SCREENING ANALYSIS

............................................................................................... 14 2.4 ENGINEERING ANALYSIS

........................................................................................... 14 2.4.1 Baseline Products

.................................................................................................. 16 2.4.2 Space-Constrained Products

................................................................................. 17 2.5 MARKUPS TO DETERMINE PRODUCT PRICE

......................................................... 17 2.5.1 Distribution Channel Structure

............................................................................. 17 2.5.2 Data Sources for Distribu tion Channel Markups

.................................................. 19 2.5.3 Markups/Price Determination

............................................................................... 20 2.6 ENERGY USE CHARACTERIZATION

........................................................................ 20 2.6.1 Residential Energy Use analysis

........................................................................... 22 2.6.2 Impact of Improved Building Codes

..................................................................... 23 2.6.3 Inclusion of Commercial Energy Use Analysis

.................................................... 24 2.6.4 Use of Rated Performance vers us Degraded Pe rformance

................................... 24 2.6.5 Characterization of Energy Using SEER/HSPF

................................................... 25 2.6.6 Development of Regions for Re gional Standard Analysis

................................... 25 2.7 LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSES

..................................... 29 2.7.1 General Approach for Life-Cycle Co st and Payback Period Analyses

................ 30 2.7.2 Electricity Prices

................................................................................................... 31 2.7.3 Repair Cost

............................................................................................................ 34 2.7.4 Maintenance Cost

.................................................................................................. 35 2.7.5 Discount Rate

........................................................................................................ 36 2.8 NATIONAL IMPACT ANALYSIS

................................................................................. 38 2.8.1 Shipments Analysis

............................................................................................... 38 2.8.2 Efficiency Scenarios and Trends

.......................................................................... 41 2.8.3 National Energy Savings Analysis

........................................................................ 42 2.8.4 Net Present Value Analysis

.................................................................................. 43 2.9 PRELIMINARY MANUFACTURER IMPACT ANALYSIS

........................................ 44 2.9.1 Industry Cash-Flow Analysis

................................................................................ 45 2.9.2 Manufacturer Subgroup Analysis

......................................................................... 45 2.9.3 Competitive Impacts Assessment

......................................................................... 46 2.9.4 Cumulative Regulatory Burden

............................................................................ 46 2.9.5 Preliminary Results for the Manufacturer Impact Analysis

................................. 48 2.9.6 Regional Standards Impact s on Manufacturers

.................................................... 48 2.10 REGIONAL STANDARDS IMPACTS ANALYSIS

...................................................... 49 2.10.1 Impacts on Manufacturers

..................................................................................... 50 2.10.2 Impacts on Distributors, Dealers, a nd Contractors, and Installers

........................ 50

2-i2.10.3 Enforcement

.......................................................................................................... 51 2.11 LIFE-CYCLE COST SUBGROUP ANALYSIS

............................................................. 53 2.12 UTILITY IMPACT ANALYSIS

...................................................................................... 54 2.13 ENVIRONMENTAL ASSESSMENT

............................................................................. 54 2.13.1 Carbon Dioxide

..................................................................................................... 54 2.13.2 Sulfur Dioxide

....................................................................................................... 54 2.13.3 Nitrogen Oxides

.................................................................................................... 55 2.13.4 Mercury

................................................................................................................. 56 2.13.5 Particulate Matter

.................................................................................................. 56 2.13.6 Monetization of Emission s Reduction Benefits

.................................................... 56 2.14 EMPLOYMENT IMPACT ANALYSIS

.......................................................................... 58 2.15 REGULATORY IMPACT ANALYSIS

.......................................................................... 58

LIST OF TABLES

Table 2.1 Energy Conservation Standards for Space-Constrained Products

............................. 2-17

LIST OF FIGURES

Figure 2.1 Distribution Channels for Cent ral Air Conditioners and Heat Pumps

.................... 2-19

2-iiCHAPTER 2. ANALYTICAL FRAMEWORK, COMMENTS FROM INTERESTED PARTIES, AND DOE RESPONSES

2.1 INTRODUCTION

2.1.1 Overview

Section 6295(o)(2)(A) of the Energy Policy and Conservation Act, as amended, 42 USC 6291 et. seq. , requires that when prescribing new or amended energy conservation standards for covered products, the U.S. Depar tment of Energy (DOE) promulgate standards that achieve the maximum improvements in energy efficiency that are technologically feasible and economically justified. This chapter provides a description of the analytical fr amework that DOE is using to evaluate amended energy conserva tion standards for residential ce ntral air conditioners and heat pumps. The chapter sets forth the methodology, an alytical tools, and relationships among the various analyses that are part of this rulemaking.

The analyses performed as part of the accompanying notice and reported in this preliminary technical support document (preliminary TSD) are as follows:

• A market and technology assessment characterizes the relevant products, their markets and technology options for improving their energy efficiency, including prototype designs.

• A screening analysis reviews each tec hnology option and determines if it is technologically feasible; is practicable to manufacture, install, and service; would adversely affect product utility or product ava ilability; or would ha ve adverse impacts on health and safety.

• An engineering analysis develops relationshi ps that show the manufacturer’s cost of achieving increased efficiency. DOE determines the increased cost to the consumer through an analysis of manufacturer markups. The engineering analysis also develops manufacturer markups that convert manufact urer production cost (MPC) to manufacturer selling price (MSP).

• An energy use analysis determines the annual energy use of the considered products.

• A markup analysis develops the distribution channel markups used to determine final customer price starting with MSP.

• The LCC and payback period (PBP) analyses calculate the discounted savings in operating costs (less any increase in maintenanc e and repair costs) at the consumer level throughout the life of the covered products compared with any increase in the installed cost for the products likely to result di rectly from imposition of the standard.

• A shipments analysis forecasts product shipment s, which then are used to calculate the national impacts of standards on energy, net present value (NPV), and future manufacturer cash flows.

2-1• A national impact analysis (NIA) assesses the aggregate impacts at the national level of the NPV of total consumer LCC a nd national energy savings (NES).

• A preliminary manufacturer impact analysis (MIA) assesses the potential impacts of energy conservation standards on manufactur ers, such as impacts on capital conversion expenditures, marketing costs, shipments, and research and development costs.

In the subsequent notice of proposed rulema king (NOPR) stage, DOE will revise the preliminary analyses just described, to the exte nt warranted by comments and new information. In addition, DOE will perform the following analyses:

• An LCC subgroup analysis will evaluate varia tions in customer characteristics that might cause a standard to affect particular c onsumer sub-populations (such as low-income households) differently than the overall population.

• An MIA will estimate the financial impact of standards on manufacturers and calculate impacts on competition, employment, and manufacturing capacity.

• A regional standards impact analysis will examine the impacts of regional standards on distributors, dealers, contract ors and installers. Analysis of potential impacts of regional standards on manufacturers and consumers, as required by EPCA, will be conducted as part of the MIA and LCC and PBP analyses, respectively.

• A utility impact analysis will estimate the effect s of proposed standards on electric, gas, or oil utilities.

• An employment impact analysis will assess the aggregate impacts on national employment.

• An environmental impact analysis will provide estimates of the effects of amended energy conservation standards on carbon dioxide (CO 2 ), sulfur dioxide (SO 2 ), nitrogen oxides (NO x ), and mercury (Hg).

• A regulatory impact analysis (RIA) will evaluate major alternatives to proposed amended energy conservation standards, to assess whether such alternatives could achieve substantially the same regulatory goal at a lower cost.

DOE developed this analytical framework in the Rulemaking Fram ework for Residential Central Air Conditioners and Heat Pumps (June 2, 2008). DOE announced the availability of the framework document in a Notice of Public Meeting and Availability of a Framework Document published in the Federal Register on June 6, 2008. 73 FR 32243–45. DOE presented the analytical approach to interested parties during a public meeting held on June 12, 2008. The framework document is available at http://www1.eere.energy.gov/buildings/applian ce_standards/residential/pdfs/cac_framework.pdf

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In response to the publication of the framewo rk document and to the public meeting, DOE received numerous comments from interested pa rties regarding DOE’s analytical approach. This chapter summarizes the key comments and describes DOE’s responses. In this chapter, DOE also summarizes any significant changes that it has made in the analytical approach described in the framework document and that it has incorporated into its preliminary analyses.

2-2In the executive summary of the preliminary TSD, DOE identifies a number of issues for which DOE seeks public comment. DOE has explained each of those issues in the relevant analysis sections below.

2.1.2 Miscellaneous Rulemaking Issues

2.1.2.1 Retention of the Advanced Noti ce of Proposed Rulemaking

After publication of the framework document, DOE received comments about whether the advanced notice of proposed rulemaking (ANOPR) step should be retained in DOE’srulemaking process. In a joint comment submitted by the American Council for an EnergyEfficient Economy (ACEEE), the Appliance Standards Awareness Project (ASAP), the California Energy Commission (CEC), the Nort hwest Power and Conser vation Council (NPCC), and the Western Cooling Efficiency Center (W CEC) (hereafter “Joint Comment 1”), these interested parties coope ratively expressed a desire for DOE to provide all the analyses traditionally associated with the ANOPR for re view. (Joint Comment 1, No. 25 at p. 9) In addition, Heating, Air Conditioning & Refrigera tion Distributors International (HARDI) stated that the ANOPR process is even more essential for this rulemaking because of the complexity of the standard. Specifically, it mentioned DOE’s unprecedented consideration of regionalizing the standard and, in its opinion, DOE’s need for a be tter understanding of the heating, ventilation, and air conditioning (HVAC) distribution channel, its cost structure, and its role within the industry (HARDI, No. 32 at p. 2). The Southern Company (Southern) also considers the ANOPR an essential part of the rulemaki ng process. (Southern, No. 39 at p. 4) According to Southern, the ANOPR allows “consideration and cr itique of the economic and mark et assumptions to be used in the NOPR without consideration of proposed st ringency levels, and allows the NOPR stage of the rulemaking to focus on stringency levels without excessive questioning of the analysis assumptions.” The National Rural Electric Coope rative Association (NRECA), Trane, Carrier, the Air-Conditioning, Heating, and Refrigerati on Institute (AHRI), the Air Conditioning Contractors of America (ACCA), and the American Supply Association (ASA) also expressed support for DOE’s use of the ANOPR for this rulemaking because it provides an increased level of transparency to the process and an opportunity for interested partie s to provide valuable feedback. (NRECA, No. 35 at p. 2; Trane, No. 16 at p. 5; Carrier, No. 18 at p. 4; AHRI, Public Meeting Transcript, No. 13 at p. 14; ACCA, Publ ic Meeting Transcript, No. 23 at p. 28; ASA, Public Meeting Transcript, No. 13 at p. 32)

Section 307 of the Energy Independence and Security Act of 2007 (Pub. L. 110–140; EISA 2007) amended the Energy Policy and C onservation Act (EPCA) by removing the requirement for DOE to publish an ANOPR when am ending standards for consumer products. DOE agrees, however, that in past rulemaking s, ANOPRs have provided a valuable early opportunity for DOE to vet its assumptions and an alyses and for interested parties to provide comments and data. Therefore, DOE developed an alternative to the ANOPR, consisting of a preliminary analysis and a notice of TSD availa bility to the public. These documents include summaries of, and DOE responses to, comments received at the framework workshop and during the framework comment period. In addition, a public meeting will be held following publication of the preliminary analysis materials. Therefore, the preliminary analysis allows for an expedited rulemaking process that does not sacrifice transparency or feedback opportunities for interested parties.

2-32.1.2.2 Regional Standards

Section 306(a) of EISA 2007 amended EPCA to authorize DOE to consider regional standards for central air conditioners and heat pumps for one or two regions in addition to a base national standard. (42 U.S.C. 6295(o)(6)) In the framework document, DOE requested comment on the potential impacts that regional standards for residential central air conditioners and heat pumps may have on the industry. HARDI comme nted that it was concerned about how the possible adoption of regional standards might affect ENERGY STAR specifications. (HARDI, No. 32 at p. 6) HARDI expressed concern that the ENERGY STAR label could be significantly degraded by forcing the brand to be regionalized or moving to prohibitively expensive efficiency levels in regions with higher minimum standards.

ENERGY STAR creates an incentive for manufact urers to develop and for consumers to purchase higher efficiency products. However, DO E does not have data to determine degradation of the ENERGY STAR label through the impos ition of regional standards, and welcome comments on the issue.

2.1.2.3 Effective Date of Standards

This rulemaking implements the EPCA re quirement for a second amended energy conservation standards rulemaki ng for central air conditioners and heat pumps. (42 U.S.C. 6295(d)(3)(B)) In the framework document, DOE ex plained that pursuant to the consolidated consent decree in New York versus Bodman , No. 05 Civ. 7807 (S.D.N.Y . filed September 7, 2005) and Natural Resources Defense Council versus Bodman , No. 05 Civ. 7808 (S.D.N.Y. filed September 7, 2005), DOE must publish a final ru le in this rulemaking by June 30, 2011. Consistent with the lead time specified in 42 U.S.C. 6295(d)(3)(B) for the second round of amended standards for central ai r conditioners and heat pumps, DOE determined that any such standards would apply to products manufactured on or after 5 years after publication of the final rule. DOE expects to publish a final rule by June 30, 2011 as required by the consent decree, thereby requiring compliance with the standards effective by June 30, 2016.

At the framework public meeting, DOE received several comments about the June 2016 effective date. ACCA stated this date will cause inconsistencies for distributors, because they will have to switch to more expensive products during peak season. (ACCA, Public Meeting Transcript, No. 13 at p. 89) Lennox suggested that the effective date of the standard should be January instead of June 2016 to avoid peak seas on. (Lennox, Public Meeting Transcript, No. 13 at p. 76) ASAP believes that under 42 U.S.C. 6295( d)(3)(B), DOE is not bound to any particular effective date, providing some flexibility to change the date to minimize manufacturing impact. (ASAP, Public Meeting Tr anscript, No. 13 at p. 100)

DOE previously determined that the final rule in this rulemaking must be published by June 30, 2011 and tentatively decided that the rule would apply to products manufactured 5 years later, in June 2016. DOE seeks further comme nt on compliance during the peak season. (Reference Chapter 2 of the preliminary TSD for details.)

2-42.1.2.4 Consensus Negotiations

Efficiency organizations indicated their willingness to participate in developing consensus recommendations but requested regula r DOE communication with interested parties during the preliminary analysis process. They also noted that for consensus negotiations to work, DOE should be willing to consider a standard that might include both performance and prescriptive elements (such as controls and/or interfaces). (Joint Comment 1, No. 25 at p. 5) For residential central air conditioners and heat pumps, DOE lacks the authority to prescribe a standard that consists of a “design requirement ,” i.e., a prescriptive requirement. (42 U.S.C. 6291(6)(B), 6292(a)(3)) Further, generally an ener gy conservation standard must be either a performance requirement or a design requirement , but cannot include both elements. (42 U.S.C. 6291(6))

2.1.2.5 Heat Pump Cooling E fficiency Requirements

NRECA and the Edison Electric Institute (EEI) both stated that final standards for cooling efficiency requirements for central air conditioner and heat pump products should be the same. (NRECA, No. 35 at p. 1; EEI, No. 20 at p. 3)

In the previous energy efficiency standards rulemaking for residential central air conditioners and heat pumps, DOE prescribed th e same cooling-efficiency standard for both types of products. This resulted largely from DOE ’s concern that higher cooling-efficiency ratings for heat pumps might cause consumers to switch to electric resistance furnaces and air conditioners, thereby negating the benefits of higher efficiency levels. 66 FR 7169, 7180-81, 7196 (January 22, 2001)(the 2001 residential central air conditioner and heat pump final rule). In this rulemaking, as reflected in this prelimin ary TSD, DOE is analyzing air-conditioning and heat pump products independently of one another to determine if any am ended standard levels are appropriate. In addition to enabling more precise analysis of each product, these independent analyses will facilitate DOE’s determination as to whether to have the same cooling-efficiency standards for central air conditioners and heat pumps and will facilitate comments on this issue. Based on the analyses it had conducted to date, DOE intends to develop cooling-efficiency standards that are the same for both types of products. However, DOE is still considering this issue and requests comment on whether to set stan dards with the same cooling efficiency for air conditioners and heat pumps.

2.1.2.6 Imported Products

At the framework public meeting, Mitsubishi Electric & Electronics USA, Inc. (MEUS) questioned whether the amended energy conserva tion standard will be applicable to products manufactured before but imported after the effect ive date. (MEUS, Public Meeting Transcript, No. 13 at p. 94)

The amended standards would a pply to all such products. If DOE adopts a single set of national energy conservation standards for ce ntral air conditioners and heat pumps, such standards would apply to products “manufactured ” on or after a specified date. (42 U.S.C. 6295(d)(3)(B)) EPCA defines “ma nufacture" as meaning “to manufacture, produce, assemble or import” and "import" as meaning “to import into the customs territory of the United States.” (42

2-5U.S.C. 6291(10), (11)) In addition, if DOE adopts any regional standards, the companion base national standards would “apply to all products manufactured or imported into the United States on and after the effective date for the standard.” (42 U.S.C. 6295(o)(6)(E)(i)(II)) Any regional standard for a product would apply “to any such pr oduct installed on or after the effective date of the standard.” (42 U.S.C. 6295(o)(6)(E)(ii)) Therefor e, for either a single set of national energy conservation standards or base na tional standards adopted in conjunc tion with regional standards, products imported into the customs territory of the United States on or after the effective date must comply with the standards, regardless of th e date of manufacture. Further, because products would be installed after the da te of manufacture and import, regional standards would be applicable to any products manufactured or importe d before but installed after the effective date of the standards.

2.1.2.7 Test Procedure Issues

DOE received multiple comments at the framewo rk public meeting about revisions to the residential central air conditioner and heat pump test procedure. DOE addressed these comments in a NOPR recently issued to propose revisions to the central air conditi oner and heat pump test procedure. That rulemaking is being conducted in parallel with this st andards rulemaking. The comments apply to the following areas: bench testin g of third-party coils, defaults for fan power in the test procedure, external static pressure in the test, fan time delay relays, incorporation of inverter driven compressors, addition of calcula tion and reporting requireme nts for sensible heat ratio, how to address testing inconsistencies for ductless mini-splits, and incorporation of standby-mode and off-mode energy consumption.

Several of these comments overlap issues surrounding the development of proposed standards, including the possible development of different seasonal energy efficiency ratio (SEER) metrics that would apply regionally and w ould better characterize system efficiency and performance for the defined regions. Consistent with the requirement in EPCA for DOE to express the “efficiency descriptor” for central ai r conditioners and heat pumps as SEER, DOE is considering adoption of revised SEER metrics to reflect regiona l operating conditions. DOE has examined a method of developing a SEER specif ic to a four-state, hot-dry region. DOE believes that the existing SEER ratings sufficiently address performance in hot-humid climates. For the preliminary analysis, DOE did not have sufficient information on how product costs and overall system performance might change if a SEER hot-d ry metric was used. Therefore, DOE used the current SEER rating metric for its energy and economic analysis. DOE will examine comments on the development of the hot-dry SEER and its utility in standards setting in the NOPR stage of the rulemaking.

2.1.2.8 Standby-Mode and Off-Mode Energy Consumption

In Section 310 of EISA 2007, Congress directed DOE to amend test procedures for all covered products to include st andby mode and off mode ener gy consumption unless current procedures already cover such energy consumption or an integrated test procedure is technically infeasible, in which case a separate standby mode and off mode test procedure must be prescribed, if technically feasib le. (42 U.S.C. 6295(gg)(2)) Se ction 310 also required any final rule establishing or revising standards fo r covered products adopted after July 1, 2010 to incorporate standby mode and off mode energy use. (42 U.S.C. 6295(gg)(3)) Because this energy

2-6conservation standards rulemaking for central air conditioners and h eat pumps is scheduled to be completed in 2011, the requirement to incorporat e standby-mode and off-mode energy use into the energy conservation standards analysis is applicable.

DOE considers standby-mode for central air c onditioners and heat pumps to be in effect when the system is on during the cooling and heating seasons, but the compressor is not running. In other words, a system is in standby-mode if it is not actively heating or cooling, but the compressor is primed to be activated by the ther mostat. DOE considers off-mode for central air conditioners and heat pumps to be in effect wh en a system is not set to a heating-mode or cooling-mode. For heat pumps, off-mode is ge nerally characterized by the “shoulder seasons” (i.e., fall and spring), when consumers are not heating or cooling their homes. For air conditioners, off-mode is generally characterized by all non-cooling seasons. DOE determined that standby-mode energy consumption is al ready accounted for in the SEER and heating seasonal performance factor (H SPF) metrics for central air conditioners and heat pumps. DOE cannot, however, incorporate off-mode energy cons umption into the SEER and/or HSPF metrics because by definition, these metrics are seasonal effi ciency descriptors. If DOE were to integrate off-mode energy consumption into the SEER and/or HSPF metrics, these efficiency descriptors would expand beyond the cooling and heating s easons, respectively, and would no longer be seasonal efficiency descriptors as required by EP CA, but rather annual efficiency descriptors. DOE intends to present off-mode energy consum ption in terms of kilowatt hours per year as additional information for consid eration by interested partie s and requests comment on this approach.

2.1.2.9 Federal Preemption

AHRI asserted that a number of local jurisd ictions have mandated efficiency standards for central air conditioners and heat pumps that are more stringent than the Federal standards, in violation of Federal preemption and causing an additional burden on the industry. (AHRI, No. 24 at p. 12)

As AHRI appears to be aware, the DOE standa rds currently applicable to these products, codified at 10 CFR 430.32(c), preempt such state and local standards as provided by EPCA in 42 U.S.C. 6297(c). EPCA allows States to petition DO E for waivers of preemp tion for specific state standards, however, DOE can grant waiver applica tions if statutory criteria are met. (42 U.S.C. 6297(d))

2.2 MARKET AND TECHNOLOGY ASSESSMENT

When DOE begins an energy conservation st andards rulemaking, it develops information that provides an overall picture of the market for the products considered, including the nature of the products, market characteristics, and industr y structure. This activity consists of both quantitative and qualitative efforts based primarily on publicly ava ilable information. The market assessment examined manufacturers, trade associ ations, and the quantities and types of products sold and offered for sale.

DOE reviewed relevant litera ture and interviewed manufact urers to develop an overall picture of the residential central air conditione r and heat pump industry in the United States.

2-7Industry publications and trade journals, governme nt agencies, and trade organizations provided the bulk of the information, including (1) manufac turers and their market shares, (2) shipments by product type and cooling capacity, (3) product information, and (4) industry trends.

Subsequent sections of this chapter descri be the comments DOE received in response to its review of the central air conditioner and heat pump market for the framework document. The analysis developed as part of the market and t echnology assessment is described in chapter 3 of the preliminary TSD.

2.2.1 Product Classes and Scope of Coverage

When evaluating and establishing energy c onservation standards, DOE generally divides covered products into produc t classes by the type of energy us ed, capacity, or other performancerelated features that affect efficiency. Different energy conservation standards may apply to different product classes. (42 U.S.C. 6295(q))

DOE identified seven product classes for this rulemaking: (1) split-system air conditioners, (2) split-system heat pumps, (3) sing le-package air conditione rs, (4) single-package heat pumps, (5) small-duct high-velocity (SDHV) systems, (6) space-constrained air conditioners, and (7) space-constrained heat pumps . DOE directly analyzed the four primary residential central air conditioner and heat pump product classes (the firs t four classes listed above). These four product classes represent most of the total shipments of these products. DOE describes the technical aspects and energy sa vings potential for the three remaining product classes in chapter 5 of the preliminary TSD. DOE intends to conduct a full technical analysis for these three product classes in the NOPR.

DOE received input from interested parties on the product definitions and product classes that DOE included in the framework document. Specifically, DOE received comments on spaceconstrained products; ductless a nd variable refrigerant flow (VRF) split systems; SDHVs; and large-tonnage products.

2.2.1.1 Space-Constrained Products

Carrier expressed opposition to the eventual in clusion of through-the-wall (TTW) split air conditioners and heat pumps in the space-cons trained product class for all but replacement applications. According to Carrier, if DOE allo wed these TTW products to be covered under the space-constrained definition, they would be instal led in new construction applications with the potential to capture a significant share of that market segment. Carrier asserted that this market share shift could occur because manufacturers of TTWs would have an unfair cost advantage as a result of their products being subject to a lower minimum efficiency standard. Carrier suggested that DOE exclude TTW products from th e space-constrained product class or alter the space-constrained definition to ensure that TTW products remain limited to their current replacement niche. (Carrier, No. 18 at pp. 4–5) National Refrigerati on and Air-Conditioning Products (NRACP), a TTW manufacturer, also op poses eliminating the TTW product class. In contrast to Carrier, NRACP asserts that the definition of “space-c onstrained product” is ambiguous and could lead to a market shift in the opposite direction. NRACP claims that manufacturers of non-TTW products would ask to be considered space-constrained products,

2-8allowing their products to compete in the replace ment market segment. (NRACP, No. 34 at p. 1) Joint Comment 1 supports the phase-out of the TTW product class and subse quent application of the more stringent standard for space-constrained products, the class under which TTW products will be covered. (Joint Comment 1, No. 25 at p. 9)

Under DOE’s regulations, the TTW product cla sses are defined to include only products manufactured before January 23, 2010. 10 CFR 430.2 and 430.32(c)(2). On that date, TTWs meeting the definition of “space-constrained pr oducts” will become subject to the 12 SEER/7.4 HSPF energy conservation standard that curren tly applies to “space-c onstrained products.” Any TTWs that do not satisfy DOE’s definition of sp ace-constrained product, but meet the definition of conventional central air cond itioners and heat pumps will beco me subject to the 13 SEER/7.7 HSPF standard that applies to those produc ts. 10 CFR 430.32(c)(2). In addition, while TTW products are primarily installed in replacemen t applications, DOE’s definition for TTW air conditioners and heat pumps does not prevent these products from being installed in new construction applications. DOE requests comment on whether the expiration of the TTW product classes could result in market shifts and the potential magnitude of these shifts.

2.2.1.2 Ductless and Variable Refrigerant Flow Split Systems

During the framework public meeting, intere sted parties discussed the classification of ductless split systems. MEUS stated that ductless mini-splits may warrant a separate product class because they are intended for different a pplications than conven tional split systems and their cooling capacities are about 12,000 British thermal units per hour (Btu/h). A typical central air conditioner system capacity is about 30,000 Btu/h. (MEUS, No. 13 at p. 205) MEUS also suggested a separate class for VRF air conditione r and heat pump systems. (MEUS, No. 19 at p. 2) Like MEUS, Trane recommended that mini-splits be included as an a dditional product class. (Trane, No. 16 at p. 7) Carrier does not support sp ecial classes for duct-free splits, multi-splits, or VRF products, and AHRI commented that no additi onal separate product cl asses are necessary for these products. (Carrier, No. 18 at p. 4; AHRI, Public Meeting Transcript, No. 24 at pp. 4, 6). Further, Lennox recommends that energy re quirements for ductless split systems be set in conjunction with other central air conditioners and heat pumps because both types of products compete for the same sales and inst allations. (Lennox, No. 22 at p. 3)

Like AHRI and Carrier, DOE does not believe ductless or VRF split systems warrant a separate product class. Althoug h some mini-split and multi-split sy stems have capacities as low as 12,000 Btu/h, others reach capacities as high as 42,000 Btu/h according to the AHRI directory. Also, DOE received comments from other manufacturers similar to Lennox’s during development of the test procedure, claiming that ductless split systems compete directly with conventional split systems, and not with room air conditioners. For these reasons, DOE does not intend to create a separate product class for ductless split systems. In addition, DOE believes VRF split systems are a variation of multi-split sy stem products and should be subject to the same standard. Therefore, DOE does not plan to develop a sepa rate product class for VRF split systems.

2-92.2.1.3 Small-Duct, High-Velocity Systems

Joint Comment 1 expressed support for a se parate product class for SDHV systems. (Joint Comment 1, No. 25 at p. 9) Unico also favo rs a separate product class for SDHV with an official minimum standard instead of the curr ent exemption provision. (Unico, No. 13 at p. 170) AHRI commented that the original DOE-propos ed product classes are appropriate, and no additional separate product cla sses are necessary. (AHRI, Public Meeting Transcript, No. 24 at pp. 4, 6) Similarly, Trane asserted that SDHV produc ts should be held to the same standards as mainstream products. (Trane, No. 16 at p. 14)

DOE intends to maintain the existing sepa rate product class for SDHV products. The indoor coil section of an SDHV system is compactly designed to facilitate retrofit installation in tight spaces, resulting in smaller face area and more rows of tubing than conventional systems. The compact fan coil design and small ducts cont ribute to high static-pressure loss that the blower must overcome, requiring greater fan pow er. Greater energy consumption of the blower motors and limited space for installing the fan co ils make it more difficult for SDHV systems to increase energy efficiency. To mitigate the burden on the blowers, designers reduce the required air volume by cooling it more than a conventi onal air conditioner, which offers enhanced humidity removal but increases cost. DOE be lieves these design constraints (confined installation spaces, high pressure drops, and blow er motor power) warrant special consideration in the analytical and standards-setting proce ss. In addition, DOE believes its definition for SDHV products, found in 10 CFR 430.2, is sufficient to prevent any separate standards for these products from becoming a “loop hole.” For these reasons, DOE is considering maintaining a separate product class for SDHV systems. DOE plan s to evaluate whether it is necessary to amend the existing energy conservation standards for these products.

2.2.1.4 Large-Tonnage Products

Trane commented that because of transporta tion and installation challenges, DOE should consider placing 4- and 5-ton units in a sepa rate product class. (Trane, No. 16 at p. 11) AHRI also suggested that a product class for large-tonn age units may be useful. (AHRI, Public Meeting Transcript, No. 24 at p. 4, 6)

DOE believes that the differences between ty pical 3-ton and large-tonnage units are not significant enough to warrant a separate product class. However, DOE will consider expanding its analysis to account for these differences. For instance, the LCC analysis could be modified to account for costs associated with transportation and installation costs of large-tonnage units. DOE requests comment on other methodologies and data to account for the differences between the typical 3-ton and large-tonnage products.

2.2.2 Technology Assessment

As part of the market and technology asse ssment, DOE developed a list of technologies to consider for improving the efficiency of central air conditioners and heat pumps. DOE removed from consideration thos e technology options whose ener gy consumption could not be adequately measured by the existing DOE test procedure. Then DOE removed technologies that do not change or affect the energy efficiency me trics of central air conditioners and heat pumps.

2-10Chapter 3 of the preliminary TSD includes the detailed list of all technology options DOE identified for further consideration in this rulemaking.

In the framework document, DOE presen ted a list of energy-saving technologies identified as relevant to residential central air conditioners and heat pumps. For this rulemaking, DOE is using an efficiency-level approach for th e engineering analysis. As explained in section 2.4, the efficiency-level approach is performed in terms of product efficiency levels rather than design options and particular technologies. DOE has received comments on some of these technologies, namely higher efficiency expansi on valves, micro-channel heat exchangers, liquidto-suction heat exchangers, flat-tube heat exch angers, high-efficiency defrost mechanisms, and evaporative pre-cooled AC systems. For more de tail regarding the technology assessment for this rulemaking, see chapter 3 of the preliminary TSD.

2.2.2.1 Higher Efficiency Expansion Valves

Trane stated that in the ca se of modulated systems ( e.g. , variable speed), the range of refrigerant flow may be broader than a conven tional thermostatic expansion valve (TXV) can handle. Trane asserted that, in these cases, an electronic expansion valve (EEV) may facilitate refrigerant flow control, but by itself offers no efficiency benefit. (Trane, No. 16 at p. 9) AHRI also stated that TXVs and EEVs do not offer any pa rticular efficiency benefits. (AHRI, No. 24 at

p. 5)

TXVs are commonly used in central air conditi oners and heat pumps rated at efficiency levels of 13 SEER or above. TXVs allow for some degree of adjustment of refrigerant expansion and may be more efficient than the capillary tube device under varying conditions. The EEV is similar to the TXV but uses an electronic control system to optimize refrigeration-system performance under all operating conditions. Because it does this with greater flexibility than a TXV, an EEV theoretically allows for increase s in energy efficiency under varying conditions. DOE understands that while the energy savings may be minimal from a TXV or EEV when implemented on its own, they are not negligible. In addition, the energy savings from TXVs and EEVs become more obvious when they are imp lemented with more advanced modulating systems.

2.2.2.2 Micro-Channel Heat Exchangers

Trane commented that micro-channel heat exchan gers offer no efficiency benefit. (Trane, No. 16 at pp. 9–10) It stated that micro-channe l heat exchangers can be used across the efficiency and capacity spectrum, and whether they are employed in any particular design is a matter of cost and other product constraints. Trane further asse rted that micro-channel heat exchangers could be used to remove the space constraint of space-constrained products, which should then be subject to the same efficiency standards as mainstream products. AHRI also stated that micro-channel heat exchangers do not o ffer any particular efficiency benefits. (AHRI, No. 24 at p. 5)

In its 2004 Emerging Technologies and Practices Report, ACEEE estimated that microchannel heat exchangers are generally 15 percent more efficient than conventional fin and tube exchangers. 1 Compared to current fin-tube heat excha ngers, the air passing over a micro-channel

2-11heat exchanger has a longer dwell time, increasing both the efficiency and rate of heat transfer. This increase in effectiveness allows the micro-channel heat exchanger to be smaller yet perform the same as a regular heat exchanger. The smaller size of the micro-channel heat exchanger reduces the refrigerant pressure drop, improving compressor performance. Likewise, a microchannel heat exchanger may achieve better performance in the same volume as a conventional heat exchanger. Micro-channel heat exchangers are an emerging technology in the residential central air conditioner and heat pump industry and manufacturers are still faci ng some challenges with implementing this technology. However, DO E believes that micro-cha nnel heat exchangers have the potential to contribute to energy savings.

2.2.2.3 Liquid-to-Suction Heat Exchangers

Trane stated that there are no benefits of liquid-to-suction heat exchangers (LSHXs) in normal-functioning systems employing the refri gerant R-410A. (Trane, No. 16 at p. 10) AHRI agreed that LSHXs do not offer any particular efficiency benefits. (AHRI, No. 24 at p. 5)

LSHXs are indirect liquid-to-vapor heat tr ansfer devices that evaporate any residual liquid refrigerant that remain in evaporator discharge lines, thereby minimizing the risk of liquid refrigerant entering the compressor suction. Gene rally, LSHXs are installed in air conditioners and heat pumps for proper system operation a nd to improve system performance. Refrigerant type, operating temperature, ambient conditions, and other factors, however, determine how an LSHX will affect the SEER as measured by DOE’s test procedure for residential central air conditioners and heat pumps. Because DOE ha s not found any conclusive evidence of the benefits of LSHXs using R-410A refrigerant, DOE plans to remove this technology from further consideration in this rulemaking.

2.2.2.4 Flat-Tube Heat Exchangers

Both Trane and AHRI commented that flat-tube heat exchangers do not offer any efficiency benefits or savings. (Trane, No. 16 at p. 10; AHRI, No. 24 at p. 5) A flat-tube heat exchanger is similar to a micro-channel heat exchanger in concept, although it implements a different fin design. This technology, however, is under development for central air conditioners and heat pumps, and any possible benefits of its implementation are unknown. Therefore, DOE plans to remove this technology from consideration in this rulemaking.

2.2.2.5 High-Efficiency Defrost Mechanisms

The standard method for defrosting the outdoor coil during the heating operation of a heat pump is to reverse refrigerant flow refrigerant te mporarily. This requires heat from air inside the unit to heat the outdoor coil and melt the frost. In the framework document, DOE listed two defrost mechanisms as alternatives to reversin g the flow of the refrigerant that may reduce energy consumption of the system: frostless h eat pumps and hot water defrost. Trane and NRACP agreed that frostless heat pumps are turned off at low temperatures. As a result, they are not operational during certa in tests and do not meet the require ments of the DOE test procedure for heating performance. (Trane, No. 16 at p. 10; NRACP, No. 34 at p. 3)

2-12DOE is not aware of any frostless heat pumps that turn off at low temperatures. A frostless heat pump retards frost formation by in creasing the temperature of the outdoor coil via added heat to the accumulator. This method of sl owing frost accumulation is effective only when the ambient temperature is above 32 °F. Frost accumulation cannot be prevented when the ambient temperature is below 32 °F and the additional heat is no longer added to the accumulator. At temperatures below 32 °F, the frostless heat pump will rely on typical defrost methods, but it will still be operational. 2 Therefore, DOE believes that a frostless heat pump can still be tested using the DOE test procedure for heating performance. Frostless heat pumps are still being developed, however, and potential energy-saving benefits are uncertain when tested under the DOE test procedure. Therefore, DOE plans to remove this technology from further consideration in this rulemaking.

Trane also stated that hot water defrost raises issues of freezing. It added that if the condensing unit coil is connected to a water syst em, it would presumably permit water heating in cooling mode and would not be ra ted along with the covered product s in this rulemaking. (Trane, No. 16 at p.10)

Hot water defrost systems are still being developed for central heat pumps and any potential energy saving benefits from this technol ogy are still uncertain. Therefore, DOE plans toremove this technology from consideration in this rulemaking. DOE is unaware of any highefficiency defrost mechanisms used in residen tial central heat pumps other than frostless heat pumps and hot water defrost. As a result, DOE plans to remove high-efficiency defrost mechanisms from consideration as a design option in this rulemaking.

2.2.2.6 Evaporative Pre-Cooled Air-Conditioning Systems

Energy Solutions stated that if this rulema king will set regional standards, evaporative pre-cooled AC systems should be considered in the western United States. (Energy Solutions, Public Meeting Transcript, No. 13 at p. 188)

An evaporative cooler is a device that cool s air by passing it over or through an object that is cooled by the evaporation of a liquid. This device is particularly effective in hot-dry climates. While the potential exists for an evapor ative cooler to be used with a conventional central air-conditioning system ( i.e. , evaporative pre-cooled AC system), DOE is unaware of anyevaporative pre-cooled AC systems offered as a complete package by a residential central airconditioning manufacturer. DOE believes that an evaporative pre-cooled AC system can only be achieved through the use of an evaporative cooler as an after-market product. DOE believes that evaporative pre-cooled AC systems are outside the scope of this rulemaking, because the rulemaking only addresses newly manufactured products and not the use of after-market products. DOE lacks the authority to prescribe a sta ndard that consists of a “design requirement,” i.e., requiring the use of an after-market produ ct. (42 U.S.C. 6291(6)(B), 6292(a)(3)) Further, generally an energy conservation standard must be either a performance requirement or a design requirement, but cannot include both elements . (42 U.S.C. 6291(6))Therefore, DOE will not consider evaporative pre-cooled AC systems in its analysis.

2-132.3 SCREENING ANALYSIS

The purpose of the screening analysis is to ev aluate the technologies identified in section 2.2.2 to determine which options to consider fu rther and which options to screen out. DOE consulted with industry, technical experts, and ot her interested parties in developing a list of energy-saving technologies for the technology assessment. DOE then applied the screening criteria to determine which technologies were unsuitable for further consideration in this preliminary rulemaking. Chapter 4 of the preliminary TSD, the screening analysis, contains details about DOE’s screening criteria.

The screening analysis examines whether va rious technologies (1) are technologically feasible; (2) are practicable to manufacture, install, and service; (3) have an adverse impact on product utility or availability; and (4) have adverse impacts on health and safety. In consultation with interested parties, DOE reviewed the list of central air conditioner and heat pump technologies according to these criteria. In the engineering analysis, DOE further considers the efficiency-enhancement technologies that it di d not eliminate in the screening analysis.

2.4 ENGINEERING ANALYSIS

The engineering analysis (chapter 5 of the preliminary TSD) establishes the relationship between the manufacturing production cost and th e efficiency for each residential central air conditioner and heat pump. This relationship serves as the basis for cost-benefit calculations in terms of individual consumers, manufacturers, and the nation. Chapter 5 discusses the product classes analyzed, representative baseline units, incremental efficiency levels, methodology used to develop manufacturing production costs, co st-efficiency curves, impact of efficiencyimprovements on the considered products, and methodology used to extend the analysis to lowshipment-volume product classes.

In the engineering analysis, DOE evaluate s a range of product efficiency levels and associated manufacturing costs. The purpose of the analysis is to estimate the incremental product MSPs that would result from increasing ef ficiency levels above the baseline model in each product class. The engineering analysis considers technologies not eliminated in the screening analysis. The LCC analysis uses the cost-efficiency relationships developed in the engineering analysis.

DOE typically structures its engineering an alysis around one of three methodologies: (1) the design-option approach, which calculates the incremental cost s of adding specific design options to a baseline model; (2) the efficiency-level approach, which calculates the relative costs of achieving increases in energy efficiency leve ls without regard to design options used to achieve such increases; and/or (3) the reverse- engineering or cost-asse ssment approach, which involves a “bottom-up” manufactur ing cost assessment based on a detailed bill of materials derived from tear-downs of the product being analyzed.

In the framework document, DOE stated its intention to use an efficiency-level approach for the engineering analysis. In an efficiency-level approach, analysis is performed in terms of product efficiency levels rather than focusing solely on design options. For each product class,

2-14the engineering analysis estimates MPCs at each potential efficiency level. Hence, in the framework document, DOE requested industry cost-efficiency and shipment data.

EEI and Joint Comment 1 supported DOE’s use of the efficiency-level approach to determine the relationship between MPC and energy efficiency levels. (EEI, No. 20 at p. 5 and Joint Comment 1, No. 25 at p. 10) AHRI and ASAP suggested that DOE review the previous central air-conditioning and heat pump engineering analysis because prior cost efficiency curves were inaccurate. (AHRI, Public Meeting Tran script, No. 13 at p. 196; ASAP, Public Meeting Transcript, No. 13 at p. 197) Although AHRI prov ided industry shipment data, available data does not allow DOE to determine the costs to manufacturers of producing central airconditioning and heat pump products at particular efficiency levels.

For this rulemaking, DOE performed the engineering analysis using an efficiency-level approach that incorporated cost-efficiency data that DOE obtained using the reverse-engineering methodology. In the rulemaking that resulted in the 2001 residential cent ral air conditioner and heat pump final rule, DOE developed its engineer ing analysis by (1) conducting three teardowns; (2) using information obtained from manufacturer interviews; and (3) using manufacturer data submissions, AHRI data submissions, and produc t literature. Because DOE has not received cost-efficiency data during the current rulema king, and because publishe d product literature now provides less detail than at the time of the previous rulemaking, DOE has relied primarily on system teardowns to develop cost -efficiency relationships for the current rulemaking. As a result, DOE has conducted more teardowns for this rule making than the previous rulemaking. This involved selecting and disassembling several central air conditioners and heat pumps, creating bills of materials, and developing a cost model to estimate the MPC of each unit. DOE has also shared its draft cost-efficiency data and assumptions with manufacturers in an attempt to calibrate its cost-efficiency curves and will conti nue to do so throughout th is rulemaking process. Chapter 5 of the preliminary TSD describes th e methodology that DOE used to perform the efficiency level analysis and deri ve the cost-efficiency relationship.

DOE’s engineering analysis produced cost-efficiency curves for the four primary residential central air conditioner and heat pump product classes. The cost -efficiency curves are described by the efficiency levels and the increa se in MPC above the baseline for each level. The split-system air conditioner and heat pump product classes have two differe nt rating methods for determining SEER, depending on whether the fan blow er is included in the rating. If a system is rated as a “coil-only” system, the SEER is calcu lated using a default fan power. These systems are generally representative of a condensing un it and evaporator coil installed with an existing furnace. If a system is rated as a “blower-coil” system, the SEER is calculated using a specific fan power. In blower-coil systems, which are generally representative of a condensing unit installed with an air handler or new construction installations, the outdoor condensing unit, evaporator coil, and fan blower can all be modi fied to achieve higher system efficiencies.

DOE assumed that coil-only systems and blower-coil systems are both prevalent in the split-system air-conditioning market, whereas blow er-coil systems dominate the vast majority ofinstallations in the split-system heat pump market. Therefore, DOE characterized the splitsystem air conditioner product class by developing separate cost -efficiency curves for coil-only

2-15systems and blower-coil systems. DOE character ized the split-system heat pump product class using only blower-coil systems. DOE requests comment on the market shares of coil-only and blower-coil systems for both split-system air conditioners and split-system heat pumps. DOE also requests comment on whether an additional coil-only engineering analysis is necessary to characterize split-system heat pumps.

2.4.1 Baseline Products

The engineering analysis identifies repr esentative baseline products, which are the starting point for estimating the cost of improving the energy efficiency of each product class. For this rulemaking, DOE selected as baseline products a model or mode ls—currently offered for sale—that meet the existing minimum Federal energy efficiency standards. Chapter 5 of the preliminary TSD includes details on the ba seline products for each product class.

2.4.1.1 Representative Capacities

In the framework document, DOE requested comment on typical baseline units for each product class. DOE received seve ral comments on the representa tive capacities for residential central air conditioners and heat pumps. Trane and AHRI recommended that, for split-system and single-package air conditioners and heat pumps , DOE use nominal 2-, 3-, and 5-ton units as representative capacities. (Trane, No. 16 at p. 12; AHRI, No. 24 at p. 6) Carrier agreed that DOE should extend its analysis beyond 3-ton units. (C arrier, No. 18 at p. 6) MEUS commented that central air conditioner and heat pump systems should be analyzed at 30,000 Btu/h, mini-splits at 12,000 Btu/h for one-to-one residential system s, and 24,000 Btu/h for multi-splits and small commercial systems. (MEUS, No. 19 at p. 3)

For the preliminary engineering analysis, DOE used 36,000 Btu/h ( i.e. , 3-ton) cooling/heating capacity systems to develop cost-efficiency relationships for the split-system and single-package product classes because the most shipments tend to be around this capacity DOE acknowledges, however, that residential central air conditioner and heat pump systems tend to reach their optimal efficiency around the 3-ton capacity. For the NOPR, DOE is considering performing additional engineering analyses on 2- and 5-ton capacity products to account for potential capacity-related impacts. Mini-splits and multi-splits fall under the definition of splitsystem air conditioners and heat pumps, so DOE did not consider se parate representative capacities for those products.

2.4.1.2 Refrigerant

DOE also received comments on the assumed re frigerant used in baseline products. Joint Comment 1 stated that adequate consideration of the impact of changing to hydrofluorocarbon (HFC) refrigerant requires a new approach to th e engineering analysis due to the effects on product design and efficiency. (Joint Comment 1, No. 25 at p. 11)

Because hydrochlorofluorocarbon (HCFC) re frigerants were phased out on January 1, 2010, DOE based its engineering analysis on products that use HFC refrigerants ( i.e. , R-410A).

2-162.4.2 Space-Constrained Products

In the framework document, DOE requeste d comment on the appropriate levels to analyze for space-constrained products. DOE al so requested comment on appropriate maximum technologically feasible efficiency levels for space-constrained products. NRACP commented that increasing the SEER for the space-cons trained product classes may not be possible. (NRACP, No. 34 at pp. 2, 4) NRACP stated that achieving a higher energy conservation standard is not possible with components currently available on the market. Therefore, NRACP recommended that SEER requirements for spac e-constrained products remain unchanged.

Table 2.1 provides current energy conservati on standards for space-constrained central air conditioners and heat pumps.

Table 2.1 Energy Conservation Standard s for Space-Constrained Products Space-Constrained Product Energy Standard Air Conditioner 12 SEER Heat Pump 12 SEER/7.4 HSPF DOE anticipates that, as of January 23, 2010, space-constrained air conditioners and heat pumps will include through-the-wall systems.

DOE did not perform a full engineering analysis for the preliminary analysis for spaceconstrained products due to limite d availability of pr oduct data. DOE intends to develop an engineering analysis for space-constrained produc ts for the NOPR. DOE requests feedback and data on space-constrained products to determine potential areas of energy savings. For additional information on space-constrained products and DOE’s methodology for developing an engineering analysis for these product classes, see chapter 5 of the preliminary TSD.

2.5 MARKUPS TO DETERMINE PRODUCT PRICE

DOE used manufacturer-to-consumer markups to convert the MSPs estimated in the engineering analysis to customer prices, which then were used in the LCC, PBP, and manufacturer impact analyses. DOE calculates ma rkups for baseline products (baseline markups) based on the markups at each step in each distri bution channels to obtain the consumer purchase price for the baseline products sold through each channel. DOE similarly calculates incremental markups that relate the change in the manufacturer sales price of higher efficiency models (the incremental cost increase) to the change in the contractor sales price.

To develop markups, DOE must identify how the products are distributed from the manufacturer to the customer (the distributi on channels). After es tablishing appropriate distribution channels for each product class, DOE used economic data from the U.S. Census Bureau, HARDI, ACCA, and other sources to defi ne how prices are marked up as the products pass from manufacturers to customers.

2.5.1 Distribution Channel Structure

Analysis of distribution markups for centra l air conditioners and heat pumps focused on two distribution channels, with markups calcula ted at specific points along those paths. The

2-17distribution channel differs for ne w construction or replacement a pplications (the latter include sales to existing buildings that do not already have a residential central air conditioners and heat pumps). For new construction applications, the manufacturer typically sells the product to a wholesaler-distributor, who sells it to a mech anical contractor, who sells it to a general contractor. Each of these latter three entities a dds a markup or fee to its purchase price before selling the product. DOE understands that virtuall y all central air conditioners and heat pumps installed in new construction follow this distribu tion channel. For replacement applications, the distribution channel is essentially the same, excep t that there is no general contractor markup.

In the framework document, DOE proposed the two distribution channe ls just described, as well as a third (manufacturer to large retaile r to consumer). While MEUS concurred (MEUS, No. 19 at p. 4), DOE received multiple recommendations to combine the three models. HARDI suggested one distribution channel with a c onsistent distribution role. HARDI and CFM Distributors, Inc. (CFM) commented that upon understanding the distribution model, DOE would need only the distribution channel model to provide more accurate costs. (HARDI, No. 32 at p. 2; CFM, No. 13 at p. 287) HARDI, CFM, an d ACCA all commented th at the third channel is nonexistent. (HARDI, No. 32 at p. 2; CFM, No. 13 at p. 287; ACCA, No. 23 at p. 5) Other manufacturers agreed that a single distribution channel would suffice for the analysis. (Trane, No. 16 at p. 18; Carrier, No. 18 at p. 9; Lennox, No. 22 at p. 3; ARI, No. 24 at p. 9) ACEEE commented that DOE’s proposal missed two di stribution channels: a dealer-direct model (merging manufacturing and distribution) and the import model. ACEEE also noted that any retail price survey is difficult to use because of the way different contractors price the markup on the product versus installation. (ACEEE, No. 13 at p. 293) ACEEE suggested that DOE examine manufacturer costs and free on board prices (w hich are equivalent to DOE’s MSP) in conjunction with surveyed retail pri ces to address regional questions.

DOE simplified the distribution channels to only two channels, based on industry comments. HARDI and the manufacturers’ comments imply that a manufacturer that performs its own distribution functions still incurs and charges for those functions. Distribution charges would also have to be added in the case of imports. This results in a similar retail price to that in a situation of a manufacturer that sells into a sepa rate retail distribution process. There is no need to distinguish between these two methods of distribution for calculation of markups.

While DOE recognizes that the theoretical value in using a valid retail price survey directly would avoid the complications associated with calculating individual retail channel markups, DOE agrees with ACEEE’s position that a retail price survey is difficult to administer and interpret in this market because of the way contractors price their goods and services together. Also, current surveyed prices (even if readily available) for high-efficiency products today would reflect prices of premium products, not necessari ly minimally-compliant products under higher standards.

Based on the comments DOE received in response to the framework document and follow-up discussions, DOE determined that distribution channels for new construction units and replacement units should be used to develop distribution channel markups.

2-18Figure 2.1 shows these two distribution ch annels. Chapter 6 of the preliminary TSD provides further descriptions of these channels and details on the fraction of shipments passing through each channel.

New Construction Units: Manufacturer → Distributor → Mechanical Contractor → General Contractor → Customer
Replacement Units: Manufacturer → Distributor → Mechanical Contractor → Customer

Figure 2.1 Distribution Channels for Ce ntral Air Conditioners and Heat Pumps

DOE will continue to seek data concerning the prevalence of different distribution channels, but two channels appear to satisfy the need for estimating representative percentage markups. DOE will index differences in contract or costs and sales ta x as two significant variations.

2.5.2 Data Sources for Distribution Channel Markups

DOE relied on economic data from the U.S. Census Bureau, HARDI, ACCA, and other sources to define how prices are marked up as products pass from manufacturers to consumers. DOE based the wholesaler and mechanical cont ractor markups on company balance-sheet data; DOE based the general contractor markups on U.S. Census Bureau data for the commercial and institutional building construction industry. HARDI and ACCA are trade associations representing wholesalers and mechanical contractors, respectively. DOE obtained the company balance sheets from the HARDI 2008 Pr ofit Planning Re port and ACCA. 3,4 DOE used financial data from the 2002 U.S. Census Bureau for devel oping general contractor markups in the same form as the balance sheet data for wholesalers and mechanical contractors. 5 These balance sheets delineate the components of all costs incurred by firms that supply and install air-conditioning products. Wholesalers and mechanic al contractors to which these reports refer handle multiple commodity lines, including residential central ai r conditioners and heat pumps as well as warmair furnaces. DOE used three key assumptions to estimate markups with these financial data:

(1) The balance sheets accurately represent the various average costs incurred by firms distributing and installing air- conditioning and heating products.

(2) These costs can be divided into two categor ies: (a) costs that vary in proportion to the MSP of the air-conditioning and hea ting products (variable costs), and (b) costs that do not vary with the MSP of air-conditioning or heating products (fixed costs).

(3) Wholesaler and contractor prices vary in proportion to the wholesaler and contractor costs included in the balance sheets.

DOE seeks summary data of distribution marg ins to serve as a baseline for distributor markups on HVAC products, or ot her relevant products, to suppl ement or replace the published data.

2-192.5.3 Markups/Price Determination

DOE received comments on its methods for estima ting retail prices for higher efficiency central air conditioners and heat pumps. CFM argue d that in building a retail price by adding distribution channel markups to MSP, DOE must have a full understanding of the market impact analysis or DOE will not obtain an accurate idea of the price, and the LCC and PBP analyses will be flawed. (CFM, No. 13 at p. 294) CFM also ex pressed concern about overlooking the cost of changes in the standards and product offerings and indicated that the cost of these items would have an effect of the overall markup (presumably because of increased inventory carrying cost). (CFM, No. 13 at p. 34) It is unclear whether the proposed efficiency standards would materially affect inventory turnover rate among elements of the distribution channels or significantly affect operation costs, whether the costs could be passed on to customers, and what the resulting impacts on markups would be. DOE will search for data to determine such relationships. Unless it finds data sources indicating the impact of st andards on markups, DOE would not have a basis to make an adjustment in the ma rkups during the preliminary analysis.

HARDI and Trane commented that the cost estimates DOE used in developing the 2001 residential central air conditioner and heat pump final rule were gr ossly understated and failed to account for the significant costs of getting HVAC products from the point of manufacture to the point of proper installation. They stated that a si mpler approach would be to use retail prices of complete systems at various sizes and SEER levels. (HARDI, No. 32 at p. 3; ARI, No. 24 at p. 5; Trane, No. 16 at p. 12) While DOE agrees, in prin cipal, that selecting product prices from a database of accurately reported retail prices for complete systems at various efficiency levels might be an easier way to get pricing information, DOE knows of no such database and did not receive any price data. It is also unclear that such a database would reflect prices that customers would pay under different efficiency standard s cenarios. Without appropr iate retail price data, DOE will continue to estimate th e retail price using markups in the distribution channel. DOE has modified its approach to markups to exp licitly include transporta tion costs, which were omitted in 2001 (and which account for e ffects of product weight on cost).

HARDI provided two specific comments on the va lues for markups used in the analysis on which DOE based the 2001 residential central air conditioner and heat pump final rule. First, HARDI stated that gross margins must be higher on the more efficient systems, not lower as previously assumed. (HARDI, No. 32 at p. 3) S econd, in assessing current and future product prices, HARDI urged DOE to perform a realistic analysis based on recent material price trends. (AHRI, No. 24 at p. 4) DOE has included in its estimate of retail price, transportation costs that increase with product size, and will increase the pr ice associated with high er efficiency products. DOE already captures recent material price increases in the manufacturer costs and will consider whether and how best to fo recast material prices.

2.6 ENERGY USE CHARACTERIZATION

The energy use characterization assesses the energy savings potential from adopting higher efficiency standards. The characterization provides the basis for the energy savings values DOE uses in the LCC and subsequent analyses . DOE calculated the energy savings for fourclasses of central air conditioner or heat pump products (split-system air conditioners, singlepackage air conditioners, split-system heat pumps, and single-package heat pumps) compared

2-20with a base case that included an estimate of the distribution of efficiencies in 2016 by product class. DOE considered energy use for both reside ntial and commercial user s of these products.

DOE used data from the 2005 Residential Ener gy Consumption Survey (RECS) produced by the Energy Information Administration (EIA), the most recent survey available, to estimate cooling energy use for homes using central ai r conditioner products, and cooling and heating energy use for homes using central heat pump pro ducts, with efficiencies representative of those in the current stock. DOE used 30 years of st ate weather data statistics from the National Climatic Data Center to weather-normalize the 2005 RECS cooling and heating energy use in selected household records to represent long-t erm average cooling and heating energy. DOE assumed that each RECS household had an effi ciency equivalent to the average shipped efficiency for the vintage central air conditione rs or heat pumps identified in RECS, based on historical AHRI ef ficiency data.

To develop estimates for the DOE base-case en ergy use for 2016 (the first year for new standards), DOE used an estimate of the efficien cy distribution in 2016 by product class to select for each RECS observation an efficiency level (SEER for air conditioners and HSPF for heat pumps) that might be purchased in that year in the absence of new standards. This distribution reflects products SEER 13 or higher. DOE then multiplied the weather-normalized cooling energy for the RECS household by the ratio of the historical average SEER to the 2016 SEER value selected for that record in the base case. Similarly, DOE multiplied the weather-normalized heating energy for the RECS household with central heat pumps by the ratio of the vintage-based HSPF to the 2016 HSPF value selected for that record in the base case.

The result of these calculations, carried out over all the selected RECS household records and using the RECS sample weights, is an estimated distribution of annua l cooling and, for heat pumps, heating energy use for residential households . This distribution is provided separately for each climate region and represents the DOE 2016 base case. DOE also used the same RECS observations and similar ratio t echniques to estimate the energy use for each RECS household under a higher SEER/HSPF standa rd, if adopted. DOE uses the difference between the energy use for each household in the base case and the st andards case to calculate the energy savings for that household for each standard level considered.

DOE also developed estimates of energy use for central air conditioners and heat pumps that might be installed in commercial applications. DOE estimated that approximately 7 percent of the central air conditioner or heat pump market is actually in commercial buildings. To develop the commercial estimates, DOE used the EnergyPlus building energy simulation tool to model the energy use of central air conditioners a nd heat pumps in a single small office building served by these products for 238 locations (bas ed on 238 Typical Meteorological Year (TMY2) locations). DOE modeled four efficiency levels for central air conditioners and four for heat pumps (from 13 SEER to the max-tech level) and extracted the annual cooling, heating, and fan energy, as well as the total building cooling cap acity, from each simulation at each efficiency level. Using the total cooling capacity from each simulation, DOE normalized the simulation cooling, heating, and fan energy to that expected for a 3-ton cooling unit. DOE then used interpolation to devel op annual cooling and, for heat pumps , heating energy by climate at intermediate efficiency levels between the base line level and max-tech level. Annual supply fan energy was also calculated and (for the purpose of this analysis) allocated to the cooling or

2-21heating energy for the simulation based on relative energy cooling and heating energy use respectively. DOE used estimates for the fraction of the U.S. population best represented by each TMY2 climate to provide weighting factors for the energy results by climate. As with the residential energy use characterization, DOE se lected locations at random (based on location weighting factors), and a 2016 base-case efficien cy level (based on the estimated efficiency distribution for shipments) for the corresponding LCC analysis. The result is a distribution of commercial energy use within each climate region analyzed in the base case. DOE also used the same commercial building simulation data and interpolation techniques described to estimate energy use for each commercial observation for scenarios in which DOE mandated a higher SEER/HSPF standard level.

In the corresponding LCC analysis, DOE used the RECS household and commercial weights assigned to each TMY2 in conjunction with the 7-percent split between commercial and residential customers to select observations in a Monte Carlo analysis to estimate the distribution of base-case energy use in each DOE climate re gion. In addition, DOE developed the energy use for each household or commercial observation selected for higher efficiency levels corresponding to possible standard levels. The di fference in the resulting distribution of energy use in the base case—and that in each standa rds case for each climate region—is the energy savings from higher standards. Note that in some cases the selected efficiency for a single observation in the base case is higher than the standards case being considered. In those instances, no energy savings are calculated for the observation.

As part of the characterization, DOE made certain implicit assumptions about product application, including how the products ar e operated and under what conditions. Those assumptions are documented in chapter 7 of the preliminary TSD, which also provides more detail about DOE’s approach.

During the framework review process, DOE received comments on various segments of the proposed analysis.

2.6.1 Residential Energy Use analysis

2.6.1.1 Use of RECS Data as Basis of Residential Energy Consumption

DOE based its estimate of the annual space c ooling energy consumption of the stock of installed central air conditioners and heat pumps on data from the 2005 RECS. For each household with a central air conditioner or h eat pump, RECS estimates the product’s annual energy consumption from the household’s utility bills. The estimated annual energy consumption in RECS corresponds to the unit installed in the household, specifically its capacity and efficiency.

In the framework document, DOE stated that it would use the latest available RECS data in the analysis. The latest available RECS data at the time of the public meeting on the framework document (June 12, 2008) was from 2 001. CFM asserted that using 2001 data in 2008-2009 is inadequate. (CFM, No. 13 at p. 269) Tr ane and AHRI also expressed reservations about using RECS data. (Trane, No. 16 at p. 16; ARI, No. 24 at p. 7) They contended that the

2-22vintage of the baseline stock in 2016 would be diff erent from the vintage of the products of even RECS 2005 households and would consequently lead to overestimation of the energy savings.

DOE uses the latest and most practical available data for its analysis. At the time of the public meeting, only the 2001 RECS was availabl e. The 2005 RECS data became available while DOE was developing the preliminary analysis, and DOE used this more recent data. In the current analysis, DOE uses RECS heating and coo ling energy use as a starting point to project baseline energy use in 2016 but accounts for the difference between the 10 SEER standard (the basis of the product stock in th e 2005 RECS) and the 13 SEER standard (the basis of the default base-case purchases in 2016). This is done in th e LCC baseline by scaling the energy use in the 2005 RECS by the ratio of (1) the average SEER (or HSPF) of the vintages of the product stock in the 2005 RECS, to (2) the SEER (or HSPF) of projected products purchased in 2016 (under the current SEER 13 standard).

2.6.1.2 Use of RECS Data Not in the Public Domain

Trane asked if DOE has access to RECS, Commercial Building Energy Consumption Survey (CBECS), and American housing survey data more detailed than what is publically available. (Trane, No. 13 at pp. 270, 284) All of the 2005 RECS data DOE used in its analysis of energy use is publicly available. In developing electricity price data for residential central airconditioning and heat pump applications, however, DOE made limited use of non-publically available data stemming from the 2001 RECS to allocate annual energy savings across months. DOE used this same information in the 2001 residential central air conditioner and heat pump rulemaking and believes that it is an important element of the analysis. For the current analysis, DOE’s use of this data is ba sed on statistics from the data us ed in the 2001 rulemaking. DOE will make the statistics available for parties interested in assessing this electricity price data.

2.6.2 Impact of Improved Building Codes

The impact of improved building codes is a fact or that potentially could impact central air conditioner and heat pump energy use and product sizing. Trane expressed that one of DOE’s national labs, Pacific Northwest National Laborat ory (PNNL), is a center of code development for residential buildings, and asked if PNNL could come up with reasonable estimates for the changes in cooling or heating loads in new c onstruction. (Trane, No. 13 at p. 278) HARDI noted that improved building codes lead to smaller sized products and that properly installed and appropriately sized products might save more energy that improperly installed and oversized high SEER products. (HARDI, No. 32 at p. 5 an d No. 13 at p. 279) Southern suggested that comparing energy consumption of a well insulated building with an old, inefficient building may be instructive. (Southern, No. 13 at p. 279)

Building codes may affect cooling and heating loads in homes but DOE has not incorporated the impact of revised codes into the preliminary analysis due to the difficulty of projecting energy use and product sizing under pote ntial new code scenarios. Even as building codes have improved design, reside ntial buildings have increased in size, which compensates for (and in some cases may overwhelm) any load re ductions due to more efficient design. In

2-23response to HARDI’s comment, DOE agrees that th ere are likely significant energy savings from quality installation and correct si zing; however, these savings would also occur with high SEER products. DOE acknowledges that greater care in si zing could, by reducing first costs, serve to make high SEER products even more cost effective.

2.6.3 Inclusion of Commercial Energy Use Analysis

In the framework document, DOE proposed developing building simulations for a single small office prototype building to extract energy savings statistics for higher efficiency central air conditioner and heat pump products. In res ponse, Carrier commented that a small office building would be the best choice. (Carrier, No. 18 at p. 9) Consequently, DOE opted for using a small office prototype for developing commercial energy consumption statistics. Trane asked if DOE had access to more detaile d data from RECS or CBECS than is available publically. (Trane, No. 13 at pp. 270, 284). DOE responded that it does not have ready access to such data and has not used any finer resolution data for the energy analysis.

2.6.3.1 Fraction of Shipments of Central Air Conditioners and Heat Pumps for Commercial Applications

The preliminary analysis is based on a fixed percentage of product shipments used in commercial buildings. Comments from the 2001 resi dential central air conditioner and heat pump rulemaking requested that DOE set this fra ction at 10 percent. For this rulemaking, DOE requested fresh inputs from intere sted parties about changes to this fraction based on industry statistics. Figures ranged widely, from 3 to 5 percent (Carrier, No. 18 at p. 8), to 7.5 percent (AHRI, No. 24 at p. 8; Trane, No. 16 at p. 17), to 10 to 20 percent. (ACCA, No. 23 at p. 4) Other responses provided estimates that differed across th e product subclasses. Trane indicated that the share of shipments to the commercial segment is higher for packaged systems than for split systems and could be different for other product subclasses ( e.g. , package systems with gas/electric strip heat not covered in this analysis). (Tra ne, No. 13 at p. 283) MEUS commented that the share of the shipments to the commercial segment could be 25 percent for conventional single-package systems, 10 percent for conventional split systems, and 30 to 35 percent for ductless split systems. (MEUS, No. 19 at p. 4)

For the preliminary analysis, DOE set the fra ction of central air conditioner and heat pump systems (all single phase systems) shippe d to commercial buildings at 7 percent. DOE based this percentage on industry estimates pr ovided in the framework document as well as separate comments made from AHRI to the U. S. Environmental Protection Agency (EPA) during the development of revised ENERGY STAR levels for central air conditioners and heat

pumps. a DOE acknowledges variation among the product classes in commercial building installations, but has no detailed data on which to base an individual class assessment for such installations. DOE requests comments on the fracti on of covered products that are shipped to commercial buildings.

2.6.4 Use of Rated Performance versus Degraded Performance

a Stakeholder comments on ENERGY STAR spefications for central air conditioners and heat pumps can be found

at http://www.energystar.gov/index.cfm?c=archives.ac_ashp_spec

.

2-24Degradation of central air conditioner and h eat pump performance over their service life is a concern. Southern observed that DOE’s an alysis assumed no degradation of performance during product lifetimes. (Southern, No. 13 at p. 275) AHRI remarked that if DOE considered degradation of performance for the higher SEER products, DOE should consider the same for base stock. (AHRI, No. 13 at p. 276) In DOE’s analysis, no degradation of performance of the central air conditioner systems is assumed either fo r the base or test case scenarios, thus making consistent the differences among the energy consumption estimates. DOE is unaware of any statistically significant scientific study on this issue that could be factored into the analysis; therefore, DOE used non-degraded efficiencies in its analysis.

2.6.5 Characterization of Energy Using SEER/HSPF

Several commenters questione d SEER’s validity and usefulness as the only energy efficiency metric. ACEEE stated that the actual energy used at high temperature bin hours is higher than the SEER test procedure capture s. (ACEEE, No. 13 at p. 272) Joint Comment 1 stated that as a driver of product development, SEER fails to encourage adequate dehumidification under part load conditions (releva nt to the southeastern United States) and it does not adequately address the need for higher efficiency at higher outdoor temperatures (a concern for the southwestern region). (Joint Comment 1, No. 25 at p. 6) Joint Comment 1 expressed that EER is an essen tial parameter and should be used in conjunction with the SEER. A joint comment from the Northeast Energy Effi ciency Partnerships (NEEP), the Connecticut Office of Policy and Management, the New Ha mpshire Office of Energy and Planning, Efficiency Maine, and the Department of Energy Resources (hereafter “Joint Comment 4”) and a comment from EEI expressed a similar view. (Joint Comment 4, No. 37 at p. 2; EEI, No. 13 at p. 47) Sempra Energy (Sempra) stated that it supports use of the EER metric for properly measuring performance during peak usage. (Sempra, No. 13 at p. 49)

EPCA’s definition of “efficien cy descriptor” at 42 U.S.C. 6291(22) provides that the efficiency descriptor for both cen tral air conditioner and heat pump systems is to be expressed in terms of SEER. Consequently, DOE’s analysis did not consider the use of EER as an additional or alternate descriptor.

2.6.6 Development of Regions for Re gional Standard Analysis

Section 306 of EISA 2007 amended EPCA to au thorize DOE to estab lish a national base level standard and one or two regional standards for central air conditioners and heat pumps, and stipulates that the geographical basis for defining the regions must meet certain specific conditions. (42 U.S.C. 6295(o)(6)) In the framework document, DOE sought input from interested parties on criteria for determining the regions to which the regional standards could apply. DOE received multiple comments on this issue.

Several comments favored setting regional standards. The Pacific Gas and Electric Company (PG&E), Southern California Edison (SCE), Sempra Energy Utilities (Southern California Gas Company and San Diego Gas and Electric Company) (Sempra), Sacramento Municipal Utility District (SMUD), the Nevada Power Company (NPC), and Sierra Pacific Power (SPP) submitted a joint comment (hereafter “Joint Comment 2”) concerning the use of regional standards. Joint Comment 2 asserted th at, because of national climactic variations,

2-25regional standards are necessary and would benefit customers, increase grid reliability, and reduce environmental impacts with minimal negati ve effects on manufacturers, distributors, and contractors. (Joint Comment 2, No. 30 at p. 2) PG&E and Sempra stated that they support regional standards, emphasizing California’s need for a hot-dry climate air cond itioner standard to meet energy efficiency goals. (PG&E, No. 13 at p. 45; Sempra, No. 13 at p. 49) Ice Energy stated that incorporating regional climate factors and time-dependent parameters in the standards would encourage deployment of more efficient cooling systems. (Ice Energy, No. 33 at p. 1) Southern claimed that if the st atutory provisions allowed for a s econd metric like latent capacity, regional standards could addre ss the challenge of adequate dehumidification in hot-humid climates. (Southern, No. 13 at p. 43) NRECA and the Florida Solar Energy Center (FSEC) want economic analysis for different climate zones using appropriate costs. (NRECA, No. 35 at p. 1; FSEC, No. 31 at p. 2)

Some commenters expressed reservations on the merits of setting regional standards. Trane observed that some assertions supporting regi onal standards are inconsistent with the facts. (Trane, No. 13 at p. 62) For example, Trane noted that air conditioners have a remarkable ability to adjust automatically and thermodynamically in response to the load, providing higher latent capacity with high latent load or no latent cap acity when indoor relative humidity is low. CFM expressed that regional standards are unrealistic because climate zones are not aligned with state borders; a better way to address the issue would be to find what meets the specific needs of the hot-dry and hot-humid regions. (CFM, No. 13 at pp. 34, 399) Lennox stated that regional standards should be applied to central air conditione rs and heat pumps only if DOE is certain that the standards will deliver the savings and paybac k forecast projected in the analysis. (Lennox, No. 22 at p. 3)

ACEEE urged completion of the preliminary ec onomic analysis of regional standards before the discussion of enforcement issues . (ACEEE, No. 13 at p. 400) Southern, MEUS, ACEEE, and Sempra suggested holding further co llaborative meetings to discuss criteria for defining the regions. (Southern, No. 13 at p. 391; MEUS, No. 13 at p. 396; ACEEE, No. 13 at p. 400; Sempra, No. 13 at p. 402)

DOE considered these comments and will conduct a regional-leve l detailed economic analysis as provided for under EPCA, as amen ded by EISA 2007. Consequently, DOE studied options from the various criteria. Several comments presented alternative criteria for defining regions to which different performance standards ma y apply. Trane suggested that the regions be defined according to heating degree days (HDDs) and cooling degree day (CDDs), while AHRI stated that the defining criteria should be cooling load hours. (Trane, No. 16 at p. 4 and No. 13 at

p. 393; AHRI No. 24 at p. 3) Carrier urged DO E to evaluate uniform north/south regions to harmonize the heating and cooling standards. (Car rier, No. 18 at p. 2) MEUS suggested using the present ASHRAE climate zones but aggregating the eight climate zones into three regions: 1 and 2; 3 and 4; and 6, 7 and 8. (MEUS, No. 19 at p. 1) CFM commented that while regional standards seem positive, climate does not adhere to state lines. (CFM, No. 13 at p. 34)

NYC and CEC suggested that DOE evaluate re gional standards for hot-humid conditions in the southeast, hot-dry in the west, and temper ate in the north. (NYC, No. 17 at p. 3; CEC, No. 27 at p. 2) Joint Comment 2 suggested defining three standards: a base national standard, a standard for the hot-dry climate, and a standard for the hot-humid climate. (Joint Comment 2,

2-26No. 30 at pp. 1, 20) Joint Comment 1 stated that the two regions most appropriate for regional standards are the west/southwest (representing a hot-dry climate) and the southeast (representing a hot-humid climate). (Joint Comment 1, No. 25 at p. 8) Joint Comment 1 suggested using available state-level population-we ighted CDD and humidity data as criteria for including states in the hot-dry climate region. Joint Comment 1 al so suggested an alternative using the latest TMY3 data to select contiguous states in which the population-weighted bin-hour distribution is systematically hotter and drier than the nationa l average. (Joint Comment 1, No. 25 at pp. 8–9) FSEC suggested using the TMY3 dataset and su pports a regional standard for the hot-humid region. (FSEC, No. 31 at pp. 1–2) Joint Comment 2 suggested developing a hot-dry SEER that could be used as a metric for rating the cent ral air conditioner units in this region. (Joint Comment 2, No. 30 at pp. 1, 20)

ACCA said that while EISA 2007 requires that any regional standard be applied to the entire state, few states could be associated w ith a single region based on CDD, cooling load hours, or other climate criteria. (ACCA, No. 23 at p. 2) Trane observed that few census divisions could be used for defining the boundaries of th e regions over the 50 states. (Trane, No. 13 at p. 350) Trane further contended that while the total cooling capacity of an air conditioner depends on the outdoor dry-bulb temperature and the indoo r wet-bulb temperature, the latent/sensible split depends primarily on the i ndoor conditions. Since neither the total capacity nor the latent split depends on the outdoor relative humidity, it c ould not be used as a valid parameter to distinguish between the hot-dry and hot- humid zones. (Trane, No. 16 at p. 4)

Joint Comment 1 suggested that DOE compare results of two parallel analyses: one with a single national standard and one with up to three regions (hot-dry, hot-humid, and average). Joint Comment 1 asserted that although a national increase in the efficiency standard could be cost effective, it might not achieve maximum cost-effective energy savings, ensure adequate dehumidification or peak load control, or pr ovide manufacturers the be st possible routes for profitable product differentiation. (J oint Comment 1, No. 25 at p. 3)

Some comments suggested coordinating the cu rrent rulemaking process for central air conditioners and heat pumps with other residential products. EEI urged DOE to begin a new rulemaking process for the residential central furnaces and boilers to avoid simultaneous existence of regional standards for central air c onditioners and heat pumps and a single national standard for residential hea ting products. (EEI, No. 20 at p. 2) NRECA advocated quickly implementing the central air conditioner and h eat pump standards, updating the furnace and boiler standards, and ensuring that both have the same effective dates. (NRECA, No. 35 at p. 2)

AHRI and Trane do not believe that DOE has th e authority to establish regional heating standards for heat pumps. (AHRI, No. 24 at p. 4; Trane, No. 16 at p. 4) DOE believes that 42 U.S.C. 6295(o)(6) and other related provisions of EPCA provide aut hority to set regional standards for heat pumps. DOE seeks comment on whether a national standard or regional standards would be appr opriate for heat pumps.

Several commenters also expressed a need for harmonization of the central air conditioner and heat pump standards with future standards for furnaces and boilers. (Carrier, No. 18 at p. 2; EEI, No. 20 at p. 2; NRECA, No. 35 at p. 2) DOE examined various alternative criteria for establishing regions for analysis. Th e current calculations for the labeling of central

2-27air conditioner cooling energy use are based on 1,000 cooling load hours, a representative national average condition. Consequently, DOE propos ed for the preliminary analysis that states with greater than approximate ly 1,000–1,100 cooling load hours be included in a “hot” region (shown in the cooling hour map in the DOE te st procedure). 10 CFR part 430, subpart B, appendix M. DOE considered where populations are centered in the western states, as well as state and regional CDD data.

As DOE proceeded with the preliminary analysis for regional standards, the furnace and boiler final rule from November 2007 ( 72 FR 65136-65170) was remanded to DOE for reconsideration. 6 This rule set standards for residentia l furnaces and boilers. The LCC subgroup analysis performed to support the furnace and boile r rule indicated that positive benefits could be derived if a higher efficiency condensing gas-fired furnace is used in the northern regions of the country. However, before EISA 2007 amended EPCA, DOE could set only a single national standard and therefore, the 2007 furnace and boiler rule was based on a single standard. However, EISA 2007 authorized DOE to establis h one additional regional standard for the gasfired furnaces and consequently DOE was require d by the Second Circuit Court to investigate regional standards for the furnace and boiler rule.

DOE believes that a unified regional defin ition for both central air conditioners/heat pumps and furnaces would have several key benefits, although EISA 2007 does not require a coordinated approach for defining the regions:

• Because similar manufacturers produce furnaces and central air conditioners/heat pumps and the same distribution network is used for both types of products, a unified regional definition would be easier for manufactur ers and distributors to implement.

• A unified boundary would likely result in only one product type (furnace or central air conditioner/heat pump) being subject to a hi gher efficiency regional standard in any given region. Since these appliances are commonly the most expensive appliances purchased in a home, the requirement of high -efficiency units for both types of products could have a large first-cost impact on consumers.

• Regional standards may shift enforcement from the manufacturer to consumer point-ofsale and to installation. A single unified north-south boundary will simplify enforcement for both product types. There will be less po ssible combinations of furnaces and air conditioners, less motivation fo r non-compliance as the price differential between the base-case options on either side of a regional boundary are lower.

Upon further examination, DOE realized that the hot-humid and hot-dry regions being considered in this rulemaking corresponded to states with less than 4,500 HDD65 (heating degree days base 65 o F), and that this 4,500 HDD65 boundary is close to the 5,000 HDD65 boundary already analyzed in the furnace-rule se nsitivity study. DOE examined individual states with an average HDD65 between 4,500 and 5,000, a nd tentatively concluded that they would benefit more from higher furnace standards than higher air conditioner standards. Consequently, DOE is considering a regional boundary that co rresponds roughly to 4,500 HDD65 so that states with 4,500 or more heating degree days form th e northern region, to which the baseline national standard developed in this rule making would be applicable. The remaining states would form the southern region, where two regional central air co nditioner standards (eastern hot-humid and the

2-28western hot-dry) would be developed. Chapter 7 of this preliminary TSD discusses the development of analysis regions.

2.7 LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSES

The effect of amended standards on individua l customers usually includes a reduction in operating cost and an increase in purchase cost, which together determine the economic impact of standards on individual customers. This chap ter describes the following two metrics, which DOE used in the analysis to measure this impact:

• LCC is the total customer cost of an applia nce or product, generally over the life of the appliance or product, including purchase a nd operating costs. The latter consist of maintenance, repair, and energy costs. Futu re operating costs are discounted to the time of purchase and summed over the lifetime of the appliance or product.

• PBP measures the amount of time it takes cu stomers to recover the assumed higher purchase price of a more energy-efficient product through reduced operating costs.

New or amended energy conservation sta ndards typically affect product operating expenses and purchase prices. DOE evaluated the net LCC to analyze the net effect of amended central air conditioner and heat pump standards on consumers. DOE used the cost-efficiency relationship derived from the engineering analysis, along with the energy costs derived from the energy use characterization. Inputs to the LCC calcu lation include the installed consumer cost of a product (consumer purchase price plus installati on cost), operating expenses (energy, repair, and maintenance costs), the lifetime of the unit, and a discount rate.

Because the installed cost of a product typical ly increases while operating cost typically decreases in response to amended standards, ther e is a time in the life of products with higherthan-baseline efficiency when the net reduction in operating costs (in dollars) since the time of purchase is equal to the increase in the purchase price of the higher efficiency product. The length of time required for products to reach th is cost-equivalence point is known as the PBP.

DOE conducted the LCC and PBP analyses using typical values to reflect energy consumption in the field. DOE identified several input values for estimating the LCC, including retail prices; electricity prices; discount rate; maintena nce, repair, and installation costs; and product lifetimes.

DOE developed discount rates fro m estimates of the interest ra te (finance cost) applied to residential product purchases. Following accepted prin ciples of financial theory, the finance cost of raising funds to purchase such products can be interpreted as either (1) the financial cost of any debt incurred to purchase products (interest charges on debt), or (2) the opportunity cost of any equity used to purchase products (interes t earnings on household or business equity).

The LCC and PBP model was developed usin g Microsoft Excel spreadsheets combined with Crystal Ball, a commercially available add-in. The LCC and PBP analyses explicitly model the uncertainty and variability in the model’s inputs using Monte Carlo simulation and probability distributions.

2-29The LCC analysis estimated energy use for each central air conditioner or heat pump unit as described in chapter 7 of the preliminary TSD. Energy use of central ai r conditioners and heat pumps is sensitive to climate, so it varies by location. An important feature of the LCC and PBP analyses is that it has been conducted at both th e regional and national levels. Aside from energy use, other important factors influencing the anal yses include energy prices, installation costs, product distribution markups, and sales tax. At the national and regional levels, the LCC spreadsheets explicitly model the uncertainty and variability in the model’s inputs using probability distributions based on the shipment of products to different regions of the country.

As mentioned, DOE generated LCC and PBP results as probability distributions using a simulation based on Monte Carlo analysis met hods in which certain key inputs consist of probability distributions rather than single-point values. Therefore, the outcomes can be expressed as probability distributions. As a result, the Monte Carlo analysis produces a range of LCC and PBP results. A distinct advantage of this type of approach is that DOE can identify the percentage of customers achieving LCC savings or attaining certain PBP values, in addition to identifying the average LCC savings or average PBP for a particular efficiency level.

DOE received a number of comments from stak eholders on the LCC and PBP analysis methods and proposed sources of data.

2.7.1 General Approach for Life-Cycle Co st and Payback Period Analyses

Joint Comment 1 stated that DOE should es timate uncertainty ba nds in product and operating costs (derived from uncertainty in mate rials costs and in energy costs to consumers) and document its methods. DOE should also present methods to examine asymmetries in risks of under- versus over-investments in efficiency. (J oint Comment 1, No. 25 at p. 11) Joint Comment 1 noted that when the LCC analysis gives a rather flat-bottomed curve, DOE must move toward maximum feasible efficiency to meet the legal requirements. (Joint Comment 1, No. 25 at p. 11) Joint Comment 1 stated that the value of energy during peak load conditions needs to be accounted for in the LCC analysis. (Joint Comme nt 1, No. 25 at pp. 4-5) ACCA asked whether the LCC and PBP analyses consider rebates, tax incentives, and other benefits available to the consumer to encourage the purchase of more efficient products. (ACCA, No. 13 at p. 277)

With respect to uncertainty bands, DOE cons iders costs of materials and services and uses a distribution of the costs of such items across the nation. The MSP already accounts for the uncertainty of prices of products in the manufac turing process due to uncertainty in materials prices. The analysis also considers differences in energy prices across the nation and over time (see chapter 7 of the preliminary TSD). DOE’s LC C savings results include the percentages of consumers at each efficiency level for whom the LCC savings are positive and negative, and those who are not affected (because they already buy products that are more efficient than the standard), thus demonstrating the relative risks fo r consumers from higher efficiency levels (see chapter 8 of the preliminary TSD). In addition, the national impact analysis shows the present value of net economic savings to the nation at each efficiency level, thus showing the risks to the nation of under- and over-i nvestment in efficiency (see chap ter 11 of the preliminary TSD). As for energy value during the peak load, the LCC analysis uses marginal prices for energy savings that account for the prices of residential and commercial energy during the peak periods. With respect to meeting legal require ments, DOE considers the LCC at each efficiency level along

2-30with the impact on manufacturers (from the manufacturer impact analysis in chapter 12 of the preliminary TSD) and the nation (from the nati onal impact analysis in chapter 11 of the preliminary TSD), as well as the other factors se t forth in 42 U.S.C. 6295(o)(2)(B) to determine whether a given standard level achieves the maximum improvement in energy efficiency that is both technically feasible and economically justified.

DOE’s basic analyses calculate the LCC and PBP without rebates, tax incentives, and other methods to “buy down” the installed costs of products. The regulatory impact analysis calculates the impact of market incentives of rebates and tax incentives (chapter 18 of the preliminary TSD).

2.7.1.1 Uncertainties in Assumptions

ACEEE noted DOE’s tendency to use the LCC analysis as the driving agent to make its determination when there is significant uncertainty in all its assumptions ( i.e. , from service life to the trajectory of electricity prices). (ACEEE, No. 13 at p. 343)

DOE does estimate LCC at each efficiency le vel but, as mentioned above, balances LCC along with impacts on manufacturers and the nation, as well as the other required factors, when determining whether a given standard level achieves the maximum efficiency improvement that is technically feasible and economically justified.

2.7.1.2 Treatment of Non-Compliant In stallations in the Analysis

CFM asked if the LCC model has a degrada tion factor to account for sub-performing noncompliant installations. CFM has had experience with SEER 13 units being installed on improperly matched evaporators, especially in multi-family housing units. (CFM, No. 13 at p. 337)

The LCC analysis assumes that energy c onsumption is the amount calculated in the energy analysis, which in turn assumes that th e products at each efficiency level achieve the relative efficiency that corresponds to the incr ease in SEER or HSPF for that level. DOE currently has no data that would show an y systematic deviation from this pattern.

ACCA asked about the availabilit y of the LCC analysis assumptions so that they could be reviewed. (ACCA, No. 13 at p. 336)

All assumptions for the LCC model are discussed in chapter 8 of the preliminary TSD. Additional details on retail ma rkup assumptions are discussed in chapter 6, engineering assumptions and manufacturer selling price in chapter 5, and energy consumption in chapter 7.

2.7.2 Electricity Prices

Electricity price information is required to cal culate the dollar benefits to consumers who purchase and operate more efficient central air conditioners and heat pumps. The electricity cost savings comprise the benefit side of the cost-benefit analysis used to estimate the LCC impacts of more efficient central air conditioners and heat pumps. To value the electricity cost savings, DOE developed marginal electricity prices. The marginal electricity price for a given consumer

2-31is the cost of the next increment of electricity use on their utility bill, and is the correct estimate of the value of savings that a cons umer would see in the real world.

DOE developed residential marg inal electricity prices from tariffs collected in 2008 from a representative sample of elect ric utilities throughout the United States. DOE collected over 150 residential tariffs from a samp le of about 90 electric utilitie s. As described earlier, DOE developed household samples using central ai r conditioners and heat pumps from the 2005 RECS. The location of each household can be id entified within broad geographic regions ( e.g. , Census Divisions). As a result, each household is assigned to a utility within a region. In turn, DOE developed a weighted-average marginal elec tricity price for each household from all the possible utility tariffs that could be assigned to that household.

DOE also developed commercial marginal electricity prices from tariffs for those commercial building applications that use reside ntial central air conditioners and heat pumps. DOE used tariffs collected in 2004. Because cent ral air conditioner and heat pump shipments to commercial applications are es timated to be low, DOE did notupdate its co mmercial tariff collection. Rather, DOE adjusted the prices fro m the 2004 tariffs with scaling factors based on the increase in average electrici ty prices from 2004 to 2008 based on data from EEI Typical Bills reports 7 and a summary report on rate increases publis hed by Regulatory Research Associates. 8 Similar to the residential tariffs, DOE collected over 260 commercial tariff s from a sample of 90 electric utilities. For the commercial buildings characterized and simulated in the Energy Use Characterization analysis, DOE assigned all po ssible tariffs to each building based on its geographic location. As with the residential household sample, DOE developed a weightedaverage marginal electricity price for each commercial building from the utility tariffs that could possibly be assigned to that building.

AHRI and Trane questioned the use of margin al electricity prices given that past standards rulemakings found only slight differen ces between average and marginal electricity rates. (AHRI, No. 24 at p. 9; Trane, Public Meeting Transcript, No. 13 at pp. 308–309) Carrier and Sempra noted that the projected effective da te of the standards is relatively distant (2016), which makes it difficult to estimate electricity prices. Carrier also stated that due to the uncertainty of electricity pricing in the future , the focus of the analysis should not be on the development of electricity prices. (Carrier, Public Meeting Transcript, No. 13 at pp. 314-315; Sempra, Public Meeting, No. 13 at pp. 310-311) In contrast, PG &E and EEI believe there are likely to be significant differences in average and marginal prices. (PG&E, Public Meeting Transcript, No. 13 at p. 309; EEI, Public Me eting Transcript, No. 13 at pp. 311-312) Although the marginal electricity prices DOE developed for some prior standards rulemakings demonstrated little to no difference between average and marginal prices, there is reason to believe that marginal prices differ significantl y from average prices for highly seasonal and peak-coincident end uses such as air conditioning . For example, in a rulemaking on standards for commercial unitary air conditioners (CUAC), the DOE-developed marginal electricity prices differed substantially from average prices. 9 Therefore, DOE developed marginal electricity prices for this rulemaking to ensure that it accurately calculated the value of electricity savings due to more efficient central air conditioners and heat pumps. DOE’s current method of determining electricity prices based on tariffs allows the calculation of either average or marginal electricity prices with little difference in effort.

2-32A joint comment from the National Resour ces Defense Council (NRDC), the National Consumer Law Center, Inc. (NCLC), and Enterpri se Community Partners (ECP) stated that DOE should develop time-of-use (TOU) rates for the en tire country (hereafter “Joint Comment 3”). (Joint Comment 3, No. 36 at pp. 2–3) Ice Energy stated that the analysis should account for electrical generation costs based on TOU. (Ice En ergy, No. 33 at p. 3) As described above, DOE collected residential tariffs to characterize marginal electricity prices for central air conditioners and heat pumps. These tariffs are based on electricity use charges (in dollars per kilowatt hour ($/kWh)) that are a function of the overall househol d electricity use (in kW h). For example, for tariffs with increasing block ra tes, households will be charged a higher price once electricity consumption exceeds defined threshold levels. This type of pricing structure does not necessarily reflect the cost to a utility of providing electrical service at different times of the day. Many utilities offer optional TOU tariffs that generally charge consumers more for electricity duringpeak periods when it presumably costs the utility more to provide electrical service. During offpeak periods, TOU tariffs are also structured to charge consumers less than they would normally be charged under a non-TOU tariff. To determin e the effect of TOU pricing structures on residential consumers, DOE collected TOU tariffs for those utilities in the sample (50 percent) that offered optional TOU tariffs to their custom ers. This represents a larger percentage of potential customers because TOU tariffs are typica lly offered by larger utilities. Coupling hourly energy savings derived from typical residentia l household and central ai r conditioner/heat pump load profiles with TOU tariffs, DOE was able to derive TOU-based marginal electricity prices. Appendix 8-D of this preliminary TSD describes this analysis, which compares marginal prices developed from TOU tariffs with marginal prices developed from non-TOU tariffs. For commercial prices, existing tariff structures alread y account for the effect that an end use, such as central air conditioning, has on marginal electricity prices. Because utilities bill their commercial consumers with dema nd charges (in $/kWh) in addition to energy charges, the resulting marginal prices reflect the contribution that air conditioning has on peak demand.

Joint Comment 3 stated that the electricity prices that DOE uses do not reflect the full costs to the utility system of providing electri city to meet air-cond itioning demand. (Joint Comment 3, No. 36 at pp. 2-3) In the analysis of CUAC efficiency standards, DOE conducted a comprehensive analysis of the real marginal cost of serving peak loads, and compared it to the marginal price utilities charge their customers through commercial tariffs. While CUAC is a different appliance serving a different customer sector, the technical analysis of peak impacts for residential and commercial air conditioning is essentially the same. The analysis for CUAC accounted for the diversity of CUAC loads and their coincidence with utility system loads. Electric utility capacity costs were determined at a regional level (in $/kWh) and applied to the CUAC peak load savings to calculate the capacity component of the real ma rginal cost. The real marginal cost calculation included operating, capacity, and other costs incurred to serve customers, and so represented the price the utility would have to charge to cover all of its costs at the margin. The results of this analysis showed that on a national average basis, the real marginal cost and the tariff-based marginal price were nearly equal, with a value of approximately 10¢/kwh in 2002$. Across the industry, utilities appear to recover through their tariffs the real cost of serving peak loads. At the national level, there are no subsidies. Overall, it seems unlikely that a peak impact that does not appear sign ificant for commercial air conditioning would be significant for residential central air conditioners. In regions where the total electric load peaks in summer, commercial air conditioning tends to be mo re peak-coincident than residential, because the overall system peak is driven by the standa rd 9:00-to-5:00, 5-day work week schedule that

2-33most commercial buildings follow. Therefore, DOE believes that the conclusions of the price analysis for CUAC also apply to central air c onditioners and heat pumps, and that on the average current utility tariffs capture the true marginal cost of providing electricity for peak-coincident end uses.

DOE used projections of electricity pr ices from EIA’s Annual Energy Outlook 2009 ( AEO 2009 ) to estimate future energy prices. 10 Joint Comment 1 recommended that DOE perform appropriate sensitivity analyses for broad ranges of energy costs. (Joint Comment 1, No. 25 at p. 4) DOE conducts sensitivity analyses using alternative AEO forecasts in addition to the AEO reference forecast. These alternative foreca sts reflect different assumptions about economic growth and other factors. In general, the range of AEO forecasts bracket the long-run energy price forecasts made by other organizations. Jo int Comment 3 stated that DOE should not rely solely on the AEO forecasts, but should consider relevant factors that occur after the AEO publication date. It also suggested that DOE shoul d examine futures contracts for natural gas and adjust its electricity price forecasts accordingl y. (Joint Comment 3, No. 36 at pp. 3, 6) The AEO forecast of electricity and other energy prices is a widely accepted, thoroughly documented, and transparent benchmark analysis. AEO price forecasts are recalibrated each year. DOE has consistently relied on AEO price forecasts and ha s used other forecasts, including the various AEO scenarios, to delimit the energy prices used in standards analyses. DOE believes this is the best approach for forecasting prices. EEI commented that currently 26 states have renewable portfolio standard (RPS) mandates and four have R PS goals, and that DOE should take these into account in its analysis. (EEI, Public Meeting Transcript, No. 13 at p. 394) The AEO forecasts account for all state RPS mandates and thei r impact on future electricity prices.

Earthjustice stated that DOE’ s forecast of electricity prices should account for the high probability of a nationally applicable mandatory regime to limit CO 2 emissions. (Earthjustice, No. 29 at pp. 3-4) Until any cap and trade legislati on is enacted, analysis of its impacts would be speculative. DOE uses the most recent AEO forecas ts to estimate future electricity prices. If a carbon cap and trade regime is enacted, the AEO is likely to incorporate the projected impacts of the regime in its forecast.

2.7.3 Repair Cost

2.7.3.1 Replacement Cost of Components of Higher Efficiency Products

DOE received several general comments on re pair costs. ACCA noted that while maintenance costs may be only slightly more for higher efficiency products, the cost of repair and installation increases are enough to warrant consideration as part of the LCC and PBP analyses. (ACCA, No. 23 at p. 5) Unico comment ed that the product lifetime should include a factor for product warranty and coverage. (Unic o, No. 13 at p. 342) Unico observed that some repairs are so expensive that owners replace the w hole unit rather than repair the original and this calls into question the assumption of one compressor change-out in a lifetime. Danfoss commented that in the replacement industry (two-t hirds of the total market), the consumer can choose to replace the compressor or put in a ne w and more efficient unit. Danfoss and Lennox both commented that the higher cost of higher SEER products drives homeowners toward repair and this trend will continue w ith lower SEER products. (Danfoss, No. 13 at p. 343; Lennox, No. 13 at p. 338)

2-34DOE plans to scale the cost of repair to th e efficiency and cost of the products. DOE seeks comment and data on whether increased standard levels will affect the decision to repair rather than replace the product enough to signif icantly affect the distri bution of pr oduct lifetimes and the estimated number of compressor replacements.

Lennox commented that while the use of mic ro-channel heat exchangers resulted in smaller units with R-22, it is unclear whether th is size reduction is possible with R-410A. A leak in a micro-channel would likely require replacing the entire coil, leading to higher replacement costs. (Lennox, No. 13 at p. 339)

Trane commented that it will be using electronically commutated motors (ECMs) on blowers, fans, and possibly compressors. Trane urged DOE to obtain estimates for replacement part costs of induction motors versus ECM moto rs and for conventional contacts (relays) for an electro-mechanical system versus the electronic control board. (Trane, No. 13 at p. 339) Trane asserted that an elect ronic control board cannot be serviced at the same cost as an electromechanical system. Trane also commented that if the standard level leads to a requirement for multi-speed outdoor units and the variable speed indoor/outdoor motors, this would inevitably lead to significantly higher maintenance and repair costs due to the complexity of the diagnosis, the prospect of higher failure rates fo r more complex systems, and higher repair parts costs. (Trane, No. 16 at p. 20)

DOE has modeled the cost of re pair proportional to the relativ e initial cost of the products as efficiency increases. Thus, as efficiency levels increase, the cost of repair will also increase, consistent with these industry comments.

DOE plans, at the notice of proposed rulemaki ng (NOPR) stage, to address the consumer repair versus replace decision in the LCC chapte r (chapter 8) by conducting sensitivity analyses to identify the effects of increased repair costs versus new purchase costs on LCC. However, DOE does not plan to carry this sensitivity analysis through to the national impact analysis. DOE plans to address the effects of regional standards on low-income consumers within the subgroup analysis (chapter 12) by conducting LCC analyses for these subgroups at the regional level, also at the NOPR stage of the rulemaking. However, DOE does not plan to carry either of these analyses through to the national impact analysis.

2.7.4 Maintenance Cost

DOE received multiple comments concerning the effects of the technical complexity of higher efficiency products on maintenance costs. HARDI commented that a greater emphasis on planned maintenance must be gi ven to higher efficiency products to maintain the installed efficiency. (HARDI, No. 32 at p. 4) According to HARDI, the high potential price of the R-410A refrigerant would make a noticeable difference in maintenance costs, especially when higher efficiencies require larger charge sizes. The cost of the refrigerant could exceed the value of the warranty on the product. (HARDI, No. 13 at p. 333)

Trane commented that if the minimum efficiency level leads to a requirement for multispeed outdoor units and the variable speed indoor/outdoor motors, significantly higher maintenance and repair costs would be expected due to the complexity of the diagnosis, the

2-35prospect of higher failure rates for more complex systems, and higher repair part costs. (Trane, No. 16 at p. 20)

AHRI and Lennox commented that DOE cannot as sume that the main tenance repair and installation costs will be negligible for more efficient products. Lennox noted that higher efficiency products have much larger coils a nd clogged coils have a bigger effect (implying higher maintenance costs). (AHRI, No. 24 at p. 10; Lennox, No. 13 at pp. 338–339)

PG&E commented that based on extensive st udy of its field experience, a higher efficiency product maintains its actual field perf ormance better over a range of charge, reducing maintenance cost. (PG&E, No. 13 at pp. 334–335)

ACEEE commented that for those manufactur ers not adopting micro-channel heat exchangers, it is unclear whether new technologie s will lead to higher maintenance costs. The new technologies include a great deal of forego ne advanced and automated diagnostics. These improvements should lead to smarter machinery th at will be self-correc ting and will notify the maintenance technician what to bring and do when conducting maintenance. (ACEEE, No. 13 at

p. 332)

DOE acknowledges that although some mainte nance costs may not increase in higher efficiency products, other component s likely would cost more to maintain, such as cleaning of larger coils and conducting mo re complex diagnostics of components such as multi-speed compressors and variable-speed motor systems and setting of more complex controls. DOE assumed that maintenance cost will increase for hi gher efficiency products in the analysis and will scale maintenance cost to th e product selling price, which is a proxy for the complexity of the mechanical components, elect ronics, and size of the coils.

2.7.5 Discount Rate

As described below, DOE de veloped discount ra tes separately fo r residential and commercial purchasers of central ai r conditioners and heat pumps.

2.7.5.1 Residential Rates

DOE derived discount rates for the LCC analysis from estimates of the cost to finance the purchase of the considered products. Following fi nancial theory, the financial cost of raising funds to purchase appliances can be interpreted as (1) the financial cost of any debt incurred to purchase a product, or (2) the opportunity cost of any equity used to purchase a product.

Carrier, AHRI, CFM, and Trane stated that DOE should use a discount rate for residential consumers equal to the prevailing credit card rate. (Carrier, No. 18 at p. 10; AHRI, No. 24 at p. 9; CFM, Public Meeting Transcript, No. 13 at p. 328; Trane, Public Meeting Transcript, No. 13 at p. 329) Carrier and Trane also commented that over 70 percent of unit sales are for replacement and that these would not be included in mortgages. (Carrier, No. 18 at p.10; Trane, No. 16 at p. 19) Energy Solutions suggested that DOE factor in default rates on credit cards as a negative interest rate when determining the rates associated with credit cards. (Energy Solutions, Public Meeting Transcript, No. 13 at p. 329)

2-36For replacement purchases, households use va rious methods to finance the purchase of major appliances. The frequency with which each financing vehicle is used to purchase an appliance is unknown, however. DOE identifies all possible debt or asset cl asses that might be used to purchase the considered appliances or that might be affected indirectly. DOE then estimates the average percentage shares of the various types of debt and equity for the average U.S. household using data from the Federal Reserve Board’s Survey of Consumer Finances (SCF) for a number of years. Using the SCF and other sources, DOE then develops a distribution of rates for each type of debt a nd equity to represent the rates that may apply in the year in which amended standards would take effect. For the purchase of products for new homes, which are included in the sales price of the home, DOE uses finance costs base d on a distribution of mortgage rates. Based on data from RECS, DOE determined that new home purchases represent approximately 30 percent of residential sales.

2.7.5.2 Commercial

DOE developed commercial discount rates based on cost of capital calculated for commercial businesses expected to occupy small commercial buildings. For the commercial cost of capital data, DOE relied on financial data for industries found in the Damodaran website for 2009. DOE received a comment on co mmercial discount rates.

EEI suggested that DOE use discount rates a ssociated with small businesses most likely to use central air conditioners a nd heat pumps, rather than using discount rates from all types of commercial businesses that woul d use other products. (EEI, No. 20 at p. 7; No. 13 at p. 327)

For commercial rates, DOE uses discount ra tes only for businesses that would be expected to occupy small commercial buildings. DOE will investigate whether it is possible to identify small businesses that would use central air conditioners and heat pumps and whether there is likely to be a significant difference in di scount rates for such businesses. See chapter 8 in the preliminary TSD for further di scussion of discount rates.

2.7.5.3 Product Lifetime

Product lifetime is the age at which the central air conditioner or heat pump is retired from service. In the prior standards rule making for these products, DOE conducted a comprehensive analysis on produc t lifetime showing that the average lifetime for central air conditioners and heat pumps was 18.4 years. That analysis also demonstrated that compressors failed and were replaced on average in year 14 of the system’s life. AHRI and Trane stated that the central air conditioner and heat pump lifetimes are 10 and 12 years, respectively. (AHRI, No. 24 at p. 10; Trane, No. 16 at p. 21) Trane also suggested that DOE use data provided by the Census Bureau and/or RECS to deduce central air conditioner and heat pump lifetime. (Trane, Public Meeting Transcript, No. 13 at p. 340) ACCA conducted an informal survey of its members and determined that central air cond itioner and heat pump lif etime is less than 18.4 years. (ACCA, No. 23 at p. 5)

DOE based product lifetimes for its prior centr al air conditioner and heat pump standards rulemaking on a consumer survey from the late 1980s commissioned by electric utilities. Although the survey was robust and accurate, it may no longer be representative of current

2-37product lifetimes. As a result, DOE conducted an analysis of actua l product lifetime in the field using a combination of shipment s data and responses in RECS on the age of household central air conditioner and heat pump products. By co mbining the results of RECS with the known history of appliance shipments, DOE estimated the percentage of central air conditioner and heat pump products of a given age still in operation. Th is survival function, which DOE assumed has the form of a cumulative Weibull distribution, provides an average and a median appliance lifetime. As described in chapter 8, this analysis yielded an estimate of mean life of 19 years for central air conditioners and 16.3 years for heat pumps.

HARDI stated that product lifetimes decrease fo r higher efficiency products due to their complexity. (HARDI, No. 32 at p. 4) Contrary to HARDI, MEUS stated that higher efficiency products should have a longer life expectancy . (MEUS, No. 19 at p. 5) DOE’s method of developing product lifetimes does not account for th e efficiency or complexity of the product. DOE is unaware of data that clearly demonstrates that more efficient or sophisticated products have longer or shorter lift imes than more conventional products. Without such data, DOE assumed that lifetime was not a function of either efficiency or product complexity.

2.8 NATIONAL IMPACT ANALYSIS

The NIA assesses the NES and the NPV from a national perspective of total appliance consumer costs and savings expected to result from standards at specific efficiency levels. DOE determined both the NPV and NES for the performance levels considered for the product classes analyzed. To make the analysis more accessible and transparent to all interested parties, DOE prepared a Microsoft Excel spreadsheet model to forecast NES and the national consumer economic costs and savings resulting from new standards. The spreadsheet model uses typical values (as opposed to probability distributions) as inputs. To assess the effect of input uncertainty on NES and NPV results, DOE has developed its spreadsh eet model to conduct sensitivity analyses by running scenar ios on specific input variables.

DOE conducted its NIA to assess impacts for the hot-humid region, the hot-dry region, and the remaining parts of the country that ar e neither hot-humid nor hot-dry (to which the national standard would be applicable). Although the sum of the regional impacts does provide the impact on the entire Nation, DOE also conducted its NIA for the Nation as a whole without consideration of regional impli cations. This national analysis provided NES and NPV results different from those determined by summing the regional impacts. Because inputs to the NIA, such as product total installed cost, product annual energy cons umption, and product repair and maintenance costs, have regi onal dependencies in addition to being a function of product efficiency, the regional level impacts when summed will differ from the impacts that are determined at the national level. If DOE pr oposes regional standards in the NOPR, DOE will consider whether to present the national impacts as a sum of the regional results.

2.8.1 Shipments Analysis

DOE uses forecasts of product shipments to calculate the national impacts of standards on energy use, NPV, and future manufacturer cash flows. DOE developed shipment forecasts based on an analysis of key market drivers fo r each considered product. In DOE’s shipments model, shipments of products ar e driven by new construction, replacement of the existing stock

2-38of installed products, and existing households or buildings that do not already own the product (referred to hereafter as new owners). DOE accounted for shipments to commercial buildings as well as residential households. The industry pr ovided estimates of the percentage of annual central air conditioner and heat pump sales shi pped to commercial building applications. These estimates ranged from 3 to 10 percent. (Trane, No. 16 at p. 17; Carrier, No. 18 at p. 8; MEUS, No. 19 at p. 4; AHRI, No. 24 at p. 8) Based on industry input, DOE assumed 7 percent of central air conditioner and heat pump shipments were to commercial applications and accounted for this in the shipments model.

The shipments model takes an accounting approach, tracking market shares of each product class and the vintage of units in th e existing stock. Stock accounting uses product shipments as inputs to estimate the age distributi on of in-service product stocks for all years. The age distribution of in-service pr oduct stocks is a key input to NES and NPV calculations because operating costs for any year depend on the age di stribution of the stock. DOE used historical product shipments to assist in calibrating the shipments model. AHRI and other parties provided historical product shipments information. (AHRI, Public Meeting Transcript, No. 13 at p. 352) AHRI provided historical shipments for each of the four primary produc t classes—split-system air conditioners, single-package air conditioners, split-system heat pumps, and single-package heat pumps—but did not disaggregate the shipment s data regionally. As a result, DOE relied on historical regional product stock saturation data from past RECS surveys as well as past U.S. Census Bureau American Housing Surveys ( AHS). Put simply, DOE disaggregated AHRI’s historical product shipments regionally by calibra ting the resulting product stock saturations to the values specified by the RECS and AHS da ta. DOE used this ca libration technique for residential shipments only. Commercial shipme nts were allocated regionally based on the percentage allocations determined for residential shipments.

MEUS stated that it would provide historical shipments data for ductless split systems. (MEUS, Public Meeting Transcript, No. 13 at p. 34) For SHDV systems, Unico noted that SDHV manufacturers sell only the indoor half of the system, and therefore do not know which condenser model installa tion contractors use for outdoor units . As a result, SDHV shipments data are not available. As noted in section 2.2.1.2, DOE considers ductless split systems within the product class of split systems and does not anal yze ductless systems separately. The analyses conducted for this preliminary TS D have not addressed the non- primary product classes that include space-constrained products and SDHV sy stems. DOE requests shipment data from interested parties for non-pr imary products (e.g., SDHV system s, space-constrained products, ductless split systems), as well as suggestions on how to treat these product classes in the NOPR.

To estimate the impact that standards have on product shipments, DOE analyzed the impact that purchase price, operating costs, and household income have had on historical central air conditioner and heat pump shipments. From this analysis, DOE derived a relative price elasticity that estimates shipments impacts as a function of the increase in purchase price, operating cost savings, and household income . Although the correlation among historical shipments and the above three para meters is not strong, there is enough evidence to suggest a connection. Of the three parameters, purchase pr ice has the most significant impact on product shipments; an increase in product purchase price will lead to a decrease in product shipments.

2-39Several interested parties remarked that the increase in purchase price due to higher efficiency standards would lead to decreased central air conditioner and heat pump shipments. Specifically, EEI and Rheem commented that some consumers may switch from central systems to room air conditioners when faced with higher product purchase prices. (EEI, No. 20 at p. 8; Rheem, Public Meeting Transcript, No. 13 at p. 376) MEUS stated that central heat pump consumers may switch to either electric resistance heating systems or hybrid systems if standards significantly increase product purchase price. (M EUS, Public Meeting Transcript, No. 13 at pp. 358–359) Several partie s remarked that consumers may choose to repair their products rather than replace it if standards lead to significantl y higher product purchase pr ices. (Danfoss, Public Meeting Transcript, No. 13 at pp. 274, 359; Trane, Public Meeting Transcript, No. 13 at p. 360; HARDI, Public Meeting Transcript, No. 13 at p. 24; CFM, Public Meeting Transcript, No. 13 at

p. 35; MEUS, No. 19 at p. 5) DOE acknowledges th at a significant increase in central air conditioner and heat pump purchase prices could ca use some potential new owners to forego or delay a central air conditioner or heat pump pur chase. As described above, DOE developed a relative price elasticity to quantify the potentia l drop in central air conditioner and heat pump sales from an increase in purchase price due to standards.

DOE considered shipments decreases only in the replacement and new owner markets. Because most new construction is now routinely e quipped with either a central air conditioner or heat pump, DOE assumed that any increase in purchase price caused by standards would not affect the decision to install a central air conditioner or heat pump system in new construction. In the case of the replacement market, DOE assumed that any drop in shipments would be caused by consumers deciding to repair rather than replace their products. DOE estimated that the extended repair would last 6 year s, after which time the products would be replaced. In the case of new owners of central air conditioners, DOE assumed that any consumers forgoing a central air conditioner purchase would instead buy a room air conditioner. In the case of new owners of central heat pumps, DOE assumed that any cons umers forgoing a heat pump purchase would instead purchase a combination central air conditioner and electric resistance furnace system.

ACEEE noted that in 2010, products will need to transition to a new refrigerant—R-410a. ACEEE stated that R-410a-based syst ems require a very different cl ass of refrigerant lubricants. Consequently, for split systems, DOE should pay attention to the feasibility of componentreplacements rather than system replacements when consumers are required to move from an R22 system to an R-410A system that uses diff erent lubricants and controls. (ACEEE, Public Meeting Transcript, No. 13 at p. 362) As described in section 2.4.1.2. DOE did not account for the impact of switching to R- 410a in determining manufacturer costs. For modeling the replacement of split systems in the shipments analysis, DOE assumed that all consumers would replace both the outdoor unit and the indoor coil. Although consumers today may replace only the outdoor unit and retain the indoor coil, w ith the transition to R-410a, DOE assumed all consumers would replace both components in order to avoid refrigerant and lubricant incompatibility issues. Although not explicitly ac counting for the effects of R-410A as described above, DOE estimated the impact of higher product prices on a consumer’s decision to repair or replace a failed unit.

2-40Chapter 9 of the preliminary TSD provides additional details on the shipments analysis and the impact that higher purchase prices, operating costs, and household income due to standards have on product shipments.

2.8.2 Efficiency Scenarios and Trends

Several of the inputs for determining NES and NPV depe nd on product efficiency. DOE developed efficiency trends for the base case without new standards and the standards case. These trends specify the average annual historical and forecasted shipments-weighted product efficiencies.

In the framework document, DOE proposed to use a “roll-up” efficiency scenario in developing its forecasts of efficiency trends afte r standards take effect. Under this scenario, all products that perform at levels below a prosp ective standard are moved, or rolled up, to the minimum performance level allowed under the standa rd. The distribution of products that meet the higher efficiency standard levels is unaffected.

Joint Comment 1 stated that prior rulemakings suggest that the early response to standards is a “roll-up” but that eventually, the market begins to shift. Joint Comment 1 suggested that DOE should attempt to incorpor ate a blended scenario in the NIA. (Joint Comment 1, No. 25 at p. 11) Danfoss also suspected that an initial roll-up and eventual efficiency spread are likely. Danf oss stated that the standards th at took effect in the early 1990s indicate that a roll-up phenomenon occurred immedia tely, followed a year or two later with the sale of products with higher efficiencies. (Danfo ss, Public Meeting Transcript, No. 13 at p. 372) AHRI stated that over the last 3 years, shipme nts have included higher product efficiencies. AHRI’s expects this trend will continue as energy costs escalate. AHRI suggested forecasting an increasing efficiency trend to the effective da te of the standard (2016) and using a roll-up scenario to estimate the impact from new standards. (AHRI, No. 24 at p. 11) EEI suggests reviewing historical efficiency data between 1992 and 2006 to estimate the probable impact from new standards. EEI also suggests adding a “time lag” effect once the new standards become effective ( i.e. , accounting for product sales with efficienci es lower than the new standard because of manufacturer and distributor inventories). NRDC noted that new legislation and enhanced market-pull programs will likely lead to the sa le of more efficient products. (NRDC, Public Meeting Transcript, No. 13 at p. 375)

AHRI provided historical shipment-weighted effi ciency (SWEF) data for each of the four primary product classes between 1992 to 2008, which included new standards for central air conditioners and heat pumps in 1992 and 2006. After the 1992 standards took effect, SWEFs increased for each product class on average 1 SEER between 1992 and 2005, which is an efficiency growth rate of approximately 0.077 SEER per year. After the 2006 standards took effect, SWEFs increased in 2007 and 2008, but w ith limited data, it is di fficult to assess the growth. After reviewing the historical data from AHRI, DOE believes that new standards will cause baseline models to roll up to the standard efficiency level, but that some fraction of shipments will remain above the minimum. DOE calculated the SWEF from this resulting efficiency distribution. In the years following the standard, DOE estimated that SWEFs for the base case will continue to grow at the rate observed between 1992 and 2005 ( i.e. , 0.077 SEER per year) until the max-tech efficiency level is attained, at which point the SWEF was held

2-41constant. To develop standards case forecasted SWEFs, DOE developed growth trends for each standard level that maintained the same per-unit average total installed cost difference for the between the base case and each standards case for the year 2016 over the entire forecast period (2016–2046).

HARDI and Trane commented on the effect that market-pull programs such as ENERGY STAR can have on the sale of high-efficiency products. HARDI claimed that higher efficiency standards could actually hinder the effectivene ss of market-pull progra ms to improve overall building performance. For example, higher product costs due to standards can be an issue in qualifying for sustainable building credits and initiatives. (HARDI, No. 32 at p. 8) Trane noted that manufacturers run off-season rebate programs to promote the sale of high-efficiency products. The method described above for forecastin g SWEFs after a standard becomes effective assumes the continued existence of market-pull programs to encourage the adoption of more efficient products. Because DOE used the same efficiency growth rate as the growth rate between 1992 and 2005, the effectiveness of future market-pull programs is implicitly assumed to be the same as the effectiveness of programs between 1992 and 2005. Chapter 10 of the preliminary TSD details the approach DOE used to forecast product efficiencies.

2.8.3 National Energy Savings Analysis

The inputs for determining the national energy savings for each product analyzed are: (1) annual energy consumption per unit; (2) shipme nts; (3) product stock; (4) national energy consumption; and (5) site-to- source conversion factors. DOE calculated the national energy consumption by multiplying the number of units (stock) of each product (by vintage or age) by the unit energy consumption (also by vint age). DOE calculated a nnual NES based on the difference in national energy consumption for th e base case (without new efficiency standards) and for each higher efficiency standard. DOE estimated energy consumption and savings based on site energy and converted the electricity consumption and savings to source energy. Cumulative energy savings are the sum of the NES for each year over the timeframe of the analysis.

In the framework document, DOE stated th at it would consider a rebound effect in its analyses. A rebound effect occurs when the increa sed energy efficiency and reduced consumer costs of higher efficiency products causes the c onsumer to alter their behavior resulting in an increase in energy consumption. Based on limite d research, DOE found that the rebound effect for residential space-cooling produ cts appears to be highly variable, ranging from 0 to 50 percent ( i.e. , consumers may activate more efficient air-conditioning products 0 to 50 percent more frequently than baseline products). AHRI and Trane st ated that the rebound effect is not likely to be significant for more efficient central air c onditioners and heat pumps. (AHRI, No. 24 at p. 8; Trane, No. 16 at p. 17) Joint Comment 1 suggested that DOE review the available literature on the rebound effect. (Joint Comment 1, No. 25 at p. 11) DOE found no new literature on the subject since the publication of the framework document. Becaus e industry experience indicates that it is very unlikely that increase product effi ciencies will result in a rebound effect, DOE did not include this effect in its analysis.

2-42AHRI commented that the analysis period for the national energy savings should not exceed the period during which the rule is likely to be in effect before being superseded by a subsequent rule. The analysis horizon should be on the order of 10 years. (AHRI, No. 24 at p. 8)

DOE calculates the NPV of new or amended standards to estimate the impacts of standards on the nation. In performing the NPV analysis for the first energy conservation standards rulemakings, DOE selected a 30-year anal ysis period beginning on the effective date of the standard because it closely matched the lifetime of the longest-lived products considered for standards. Matching the lifetime of the longest-lived products a llows for a full turnover of the stock. For the next few rulemakings on different products, DOE used the same analysis end date but the appropriate start-of-standa rd date that resulted in a shorter analysis period for those products. By the 1990s, DOE found that using the same analysis end date would result in rulemaking that could not capture the full imp act of amended standards. As a result, DOE determined it was necessary to change the analysis end date. DOE settled on the 30-year analysis, which allows the full-life capture of an y product shipped in the first year a standard becomes effective. Because products have vary ing lifetimes, DOE uses a 30-year period to maintain a consistent timeframe to compare th e energy savings and economic impacts from all standards rulemakings.

DOE believes that using a 30-year analysis period is appropriate. To compare energy savings for residential or commercial equipment classes across varying lifetime appliance rulemakings, DOE must use the lifetime of the longest-lived product or equipment type because the annual energy consequences of improving the longest-lived residential products or commercial equipment would re main unknown until all of the ma rket consisted of improved units. That scenario would not occur until the last of the pre-standard equipment is retired. Thirty years is a practical estimate for that event fo r short- and long-lived equipment. The NOPR for beverage vending machines discusses th is point in further detail. 74 FR 26040–41.

To compare economic costs and savings using discounted present value, it is common in economics to use the stream of benefits and costs over the lifetime of the equipment. In DOE energy conservation standards rulemakings, th e outer limit for economic benefits and costs is established in the NPV analysis as the last year of life of the oldest equipment purchased during the 30-year period used for energy savings comparisons.

2.8.4 Net Present Value Analysis

The inputs for determining NPV are: (1) tota l annual installed cost; (2) total annual savings in operating costs; (3) a discount factor; (4 ) present value of costs; and (5) present value of savings. DOE calculated net savings each ye ar as the difference between the base case and each standards case in total savings in operating costs and total increases in installed costs. DOE calculated savings over the life of each product , accounting for differences in annual energy rates. DOE calculated NPV as the difference between the present value of operating cost savings and the present value of total in stalled costs. DOE used a discount factor based on real discount rates of 3 and 7 percent to discount futu re costs and savings to present values.

2-43DOE calculated increases in total installed costs as the difference in total installed cost between the base case and standards case ( i.e. , once the standards take effect). Because the more efficient products bought in the standards case us ually cost more than products bought in the base case, cost increases appear as negative values in the NPV.

DOE expressed savings in operating costs as decreases associated with the lower energy consumption of products bought in the standards case compared to the base efficiency case. Total savings in operating costs are the product of savings per unit and the number of units of each vintage that survive in a given year.

The national impacts analysis examines the potential economic impacts of alternative standard levels on consumers who purchase the cons idered products. Joint Comment 3 stated that DOE should quantify the effect of the standard on electricity prices and the value of reduced electricity bills to all consumers. (Joint Comment 3, No. 36 at p. 5) DOE investigated the possibility of estimating the impact of specific standard levels on electricity prices in its rulemaking for general service fluorescent lamps and incandescent reflector lamps. 11 While natural gas markets exhibit a simple chain of agents from producers to consumers, the power industry is a complex mix of fuel suppliers, producers, and distributors. Even though the distribution of electricity is regulated everywhere, its institutional structure varies. Upstream components are more complicated and generation is priced using different methods across the country. For these and other reasons, accurate mode ling of the response of electricity prices to a decrease in residential-sector demand due to standards is problematic. Thus, DOE does not plan to estimate the value of potentially reduced electricity costs associated with revised standards for all consumers.

Chapter 10 of the preliminary TSD provides additional details on the national impacts analysis.

2.9 PRELIMINARY MANUFACTURER IMPACT ANALYSIS

DOE performed a preliminary MIA to estimate the financial impact of higher energy conservation standards on reside ntial central air conditioner and heat pump manufacturers, and to calculate the impact of such standards on employ ment and manufacturing capacity. The MIA has both quantitative and qualitative aspects. The quantitative part of the MIA relies on the government regulatory impact model (GRIM), an industry-cash-flow model customized for these three industries. The GRIM inputs are information on the industry cost structure, shipments, and revenues. This includes information from many of the analyses described above, such as manufacturing costs and prices from the engineerin g analysis and shipments forecasts. The key GRIM output is the industry net present value (INP V). Different sets of assumptions (scenarios) will produce different results. The qualitative part of the MIA addresses factors such as product characteristics, characteristics of particular firms, and market and product trends, and includes assessment of the impacts of standards on manufacturer subgroups. Chapter 12 of the preliminary TSD describes the complete preliminary MIA.

DOE conducts each MIA in three phases and w ill further tailor the analytical framework for each MIA based on comments from interested pa rties. In Phase I, DOE creates an industry profile to characterize the industry and identify im portant issues that require consideration. In

2-44Phase II, DOE prepares an industry cash-flow model and interview questionnaire to guide subsequent discussions. In Phase III, DOE inte rviews manufacturers and assesses the impacts of standards quantitatively and qua litatively. DOE assesses industry and subgroup cash flow and NPV using the GRIM. DOE then assesses impacts on competition, manufacturing capacity, employment, and regulatory burden based on manu facturer interview feedback and discussions.

Until recently, DOE reported MIA results in its standards rulemakings only during the NOPR phase of the rulemaking. However, DOE is now evaluating and reporting preliminary MIA information in this preliminary analysis. DOE gathered this information during the preliminary manufacturer interviews conducted fo r the engineering analysis. See chapter 12 of the preliminary TSD for a summary of manufacturers’ concerns regarding the impacts of amended energy conservation st andards for this rulemaking.

As part of the NOPR, DOE will seek comments from manufacturers about their potential loss of market share, changes in the efficiency distribution within each industry, and the total reduction in product shipments at each amended energy conserva tion standard level. DOE will then estimate the impacts on the industry quantita tively and qualitatively. DOE seeks further comment from interested par ties about the impact of amended standards on domestic manufacturers. See the issues for which DOE seeks comment in the executive summary.

The following is an overview of the information DOE will collect and the analysis it will conduct during the preliminary MIA (chapter 12 of the preliminary TSD).

2.9.1 Industry Cash-Flow Analysis

The industry cash-flow analysis relies primarily on the GRIM. DOE uses the GRIM to analyze the financial impacts of more stringen t energy conservation standards on the industry that produces the products covered by the standa rd. The GRIM analysis uses many factors to determine annual cash flows from a new standard: annual expected revenues; manufacturer costs, including cost of goods sold, depreciation, research and development, selling, general, and administrative expenses; taxes; and conversion capital expenditures. DOE compares the results against base-case projections that involve no new standards. The financial impact of new standards is then the difference between the two sets of discounted annual cash flows. Other performance metrics such as return on invested capital are available from the GRIM. For more information on the industry cash-flow analysis, refer to chapter 12 of the preliminary TSD.

2.9.2 Manufacturer Subgroup Analysis

Industry cost estimates are not adequate to assess differential impac ts among subgroups of manufacturers. For example, small and nich e manufacturers, or manufacturers whose cost structure differs significantly from the industry aver age, could be more negatively affected by the imposition of standards. Ideally, DOE would cons ider the impact on every firm individually; however, since this usually is not possible, DOE typically uses the results of the industry characterization to group manufacturers exhibiting similar characteristics.

DOE outlined the process it uses to establis h manufacturer subgroups in the framework document and sought comment from interested parties on any potential subgroups within the

2-45industry. Joint Comment 1 suggested that DOE should address impacts on other market participants (distributors, dealers, etc.) as an extension of DOE’s usual analyses. (Joint Comment 1, No. 25 at p. 9) HARDI argued that increases in efficiency standards do not guarantee significant energy savings and can negatively imp act small businesses if all factors and market realities are not taken fully into account. ( HARDI, No. 32 at pp. 1, 3) AHRI commented that DOE should examine the impact of the rule on a ll manufacturers of diff erent product classes. AHRI stated that DOE should also assess th e impact on component suppliers, dealers, distributors, contractors, and the manufacture d housing industry. (AHRI, No. 24 at p. 12)

DOE has characterized the impacts on the re sidential central air conditioner and heat pump industry. DOE did not identify any manufacturer subgroups within the industry other than small manufacturers. DOE will consider the possible effects of amended energy conservation standards for residential centr al air conditioners and heat pumps on small businesses. DOE identified a few small businesses within the industr y in chapter 3 of the preliminary TSD. During the manufacturer interview pro cess conducted as part of th e NOPR, DOE will discuss the potential subgroups and subgroup members it has id entified for the analysis. DOE will encourage manufacturers to recommend subgroups or characte ristics appropriate for the subgroup analysis. DOE will also attempt to contact component supp liers, dealers, distribut ors, and contractors during the manufacturer interview process c onducted for the NOPR. For more detail on the manufacturer subgroup analysis, see chapter 12 of the preliminary TSD.

2.9.3 Competitive Impacts Assessment

DOE must consider whether a new standard is likely to reduce industry competition, and the Attorney General must determine the impact s, if any, of reduced competition. DOE will make a determined effort to gather and report firm-specific financial information and impacts. The competitive impacts assessment will focus on assessing the impacts on smaller manufacturers. DOE will base this assessment on manufacturing cost data and information collected from interviews with manufacturers. The interviews will focus on gathering information to help assess asymmetrical cost increases to some manufacturers, increased proportion of fixed costs potentially increasing business risks, and potential barriers to market entry ( e.g. , proprietary technologies). The NOPR will be submitted to the Attorney General for a review of the impacts of standards on compe tition. The Attorney General’s comments on the proposed rule will be considered in preparing the final rule.

2.9.4 Cumulative Regulatory Burden

DOE recognizes and seeks to mitigate the overlapping effects on manufacturers of new or revised DOE standards and other regulatory actions affecting the same products. DOE will analyze and consider the impact on manufacturer s of multiple, product-sp ecific regulatory actions. DOE outlined the cumulative regulatory burden process in the framework document and sought comment on any additional regulations faci ng the residential central air conditioner and heat pump industry.

2-462.9.4.1 Refrigerant Phase-Out

In the framework document, DOE discussed how the EPA HCFC phase-out beginning on January 1, 2010 could impact the central air conditioner and heat pump industry. 68 FR 2820. Joint Comment 2 stated that the current standard -setting process for resi dential cooling products is complicated by many new factors, including the mandatory shift away from R-22 (HCFC) to HFC or other refrigerants in 2010, unprecedented increases in raw material pricing, and sizable increases in electricity cost. (Joint Comment 2, No . 30 at p. 3) ACCA stated that the cost of R-22 has doubled in the last few years as a result of regulatory phase-outs and increased demand. (ACCA, No. 23 at p. 3) ACCA suggested that DO E should periodically assess the price of R-22 throughout the rulemaking to ensure that the en gineering analysis is using a proper value. EEI stated that manufacturers will ha ve switched over most, if not all, of their products to R-410A by 2010. Because this rule does not go into effect until 2016, the only impact of the reduced availability of R-22 will be on the retrofit market. EEI concluded that the impacts on this rule will therefore be minimal. (EEI, No. 20 at p. 6)

Because production of R-22 central air conditioner and heat pump products will discontinue by 2010, any issues regarding the avai lability of R-22 will be related to the retrofit market. The reduced availability of R-22 may result in price increases relative to retrofit products. While retrofit products are outside the scope of this rulemaking, any OEMs that also deal with retrofit products could face an additional cumulative regulatory burden. DOE will consider the potential impact of refrigerant price increases on the retrofit market as part of the MIA analysis in the NOPR.

HARDI commented that the potential for increased refrigerant costs (due to reduced availability, shorter lifetimes, and increased charge sizes) poses a significant threat to manufacturers. (HARDI, No. 32 at p. 7) HARDI stated that combined with lengthening manufacturer warranties on higher efficiency pr oducts, the liability may potentially exceed the affordability or availability of HFC refrigerants. HARDI also stated that increased speculation about the affordability and availability of HFC refr igerants could further hinder already sluggish sales of new products. HARDI commented that DOE should consider the refrigerant ramifications of residential central air conditione r and heat pump regulations that could increase the demand for HFC refrigerants. HARDI stated concerns about R-410A av ailability in addition to slow acceptance of new replacement refrige rants in product manufacturer warranty terms, which adds to concerns of long-term refrige rant supplies/options. (HARDI, No. 32 at p. 8)

Emerson, Trane, and Carrier also expressed concern about the centr al air conditioner and heat pump industry’s transition to R-410A, stating th at the supply of the new refrigerant might be in question. (Emerson, Public Meeting Transcript , No. 13 at p. 257; Trane, No. 16 at p. 14; and Carrier, No. 18 at p. 7) AHRI and Lennox recomm ended that DOE carefully study the impact of climate change legislation on the availability and price of HFC refrigerants, as there is a possibility that prices will dramatically increase and that not enough refrige rant will be available to meet the new energy conservation standards (AHRI, No. 24 at p. 7; Lennox, Public Meeting Transcript, No. 13 at p. 383) HARDI commented that its members have prepared for the transition from R-22 to HFC refrigerants such as R-410A. They also said that any regulatory efforts to change this to control GHG emissions would adversely impact the industry. (HARDI, No. 32 at p. 7) Lennox commented that given th e uncertainties around climate change legislation

2-47and potential regulation, the industry could be goin g through another refrigerant change at the same time that the new rulemaking becomes effective. (Lennox, Public Meeting Transcript, No. 13 at p. 363)

DOE used HFC refrigerant R-410A as the basi s for its analysis. While pending climate change legislation might result in a phase-out or production caps for HFC refrigerants over the course of this rulemaking, any analysis of pot ential impacts before such legislation is enacted would be speculative. During interviews with manufacturers, DOE was unable to obtain any data that would quantify HFC refrigerant price increases. DOE requests data or information on projected HFC cost increases and the basis for such projections. DOE also seeks comment on the extent to which interested parties expect projected HFC costs to increase, the timing of these increases, and the certainty of the increases.

2.9.4.2 Additional Regulations

In addition to the HCFC refrigerant phase-out , the industry identified other regulations or pending regulations that should be considered in the cumulative regulatory burdens analysis. MEUS said that DOE should consider AS HRAE standard 90.1-2007 for economizer and ventilation air requirements; AS HRAE Draft Standard 189 for advanced energy designs; and International Codes Council (I CC) building and energy codes. (ICC 2009 codes) (MEUS, No. 19 at p. 6)

DOE identified several regulati ons relevant to central air conditioners and heat pumps, including energy conservation standards and re gional standards for other products made by central air conditioner and heat pump manufacture rs, the EPA phase-out of HCFCs, and building codes. DOE will examine the potential impacts of these regulatory burdens in greater detail in the MIA conducted for the NOPR.

2.9.5 Preliminary Results for the Manufacturer Impact Analysis

As part of the preliminary MIA, DOE discussed potential impacts of amended energy conservation standards with manuf acturers responsible for a majori ty of central air conditioner and heat pump sales. These discussions occurred during the interviews DOE conducted for the engineering analysis. The interviews provided valu able information that DOE used to evaluate the impacts of amended energy conservation standards on manufacturers’ cash flows, manufacturing capacities, and employment levels. DOE discusses its findings from the preliminary MIA interviews in the executive summary and in chapter 12 of the preliminary TSD.

2.9.6 Regional Standards Impacts on Manufacturers

For the preliminary analysis, DOE conducte d limited interviews with manufacturers regarding the potential impacts of regional standards as they relate to residential central air conditioners and heat pumps.

Manufacturers stated that the implementati on of regional standards would generally complicate their production proce sses, decrease their economies of scale, and complicate product distribution. Any additional testin g, certification, rating, or la beling would increase costs, and

2-48could have a harmful impact, particularly on small manufacturers. Manufacturers stated that margins across the industry have decreased in past years, and that imposing region-specific standards would likely further this decline. Ma nufacturers were also concerned that more stringent regional standards may impact consumers’ decisions to repair rather than replace units, as well as possible consumer switching to alternative products (i .e., multiple room air conditioners). Manufacturers asserted that this would be especially evident in low-income regions. Some manufacturers also stated that cost increases resulting from regional standards may cause them to stop selling products in certain regions.

As required by EPCA, DOE plans to evaluate any differential impacts regional standards may have on manufacturers. DOE will tailor its MIA interview guides to include questions exploring the quantitative and qualitative impacts of regional standards on manufacturers. Potential impacts could include additional compliance, inventory, or marketing costs associated with the promulgation of regional standards. To the extent appropria te, DOE may evaluate subgroups of manufacturers that are differentially impacted by regional standards. One possible subgroup, for example, may be manufacturers that own distribution networks. DOE will include any differential financial impacts if it determines appropriate in its GRIM analysis. DOE seeks further comment regarding the potential impact of regional standards on manufacturers of residential central air conditioners and heat pumps . In addition, DOE is seeking market data that will assist in the identification and analysis of the impacts of regional standards on manufacturers.

2.10 REGIONAL STANDARDS IMPACTS ANALYSIS

During the framework public meeting, several interested parties indicated that there could be additional impacts on product distributors and contractors if DOE establishes regional standards. Several interested parties commented that there would be enforcement issues with regional standards. In establishing a framework for regional standards, EISA 2007 appears to recognize that DOE has not dealt with these issues previously, as the appliance standards programs historically set only nati onal standards, and states that DOE shall consider the impact of additional regional standards on consumers, manufacturers, a nd other market participants, including product distributors, dealer s, contractors, and installers.

DOE addresses impacts on consumers in chapter 8 and chapter 11 of the preliminary TSD. DOE plans to analyze the impacts of re gional standards on consumers within these chapters by calculating consumer LCCs and su bgroup LCCs on a regional basis. For the NOPR, DOE plans to analyze the impacts of regional standards on manufacturers as part of the manufacturer impact analysis (chapter 12 of th e preliminary TSD), as described in section 2.9.6. To address concerns regarding impacts of regional standards on distributors, dealers, contractors and installers, DOE intends to develop a new regional standards impacts analysis as a separate TSD chapter at the NOPR stage that identifies specific impacts of concern and examines the significance and scale of these impacts on the affected parties. If necessary, the analysis will also propose how the energy and economic analyses mig ht be adjusted to reflect the impacts. See chapter 17 of the preliminary TSD for a preliminary assessment of the impacts of regional standards on market participants othe r than manufacturers and consumers.

2-492.10.1 Impacts on Manufacturers

DOE will analyze the impacts of regional standards on manufacturers in the MIA. See section 2.9.6 for more detail.

2.10.2 Impacts on Distributors, Dealers, and Contractors, and Installers

HARDI stated that regional standards will increase non-compliance and would create a major competitive disadvantage for contractors that seek to comply. (HARDI, No. 32 at p. 5) This situation already exists in California after implementation of Title 24 requirements. Kent & O’Connor stated that splitting a metropolitan ar ea with regional standards would have a significant competitive impact, particularly if a price difference exists between the higher efficiency and the national standard units. (K ent & O’Connor, No. 13 at p. 231) The National Association of Home Builders (NAHB) commented that a general contractor usually will not have any special HVAC expertise. If regional standards are implemented, a builder is likely to use more time and effort double-checking that units are compliant. The extra cost of this effort should be included in the payback analysis, th e cumulative regulatory burden, the employment impact analysis, and the regulatory impact an alysis. NAHB also commented that regional standards would affect home builders, most of wh ich are small businesses; as such, a regulatory flexibility analysis would be necessary. (NAHB, No. 21 at pp. 1, 2).

For the preliminary analysis, DOE conducted limited interviews with distributors and contractors, and sought comment regarding the potential impacts of regional standards as they relate to residential central ai r conditioners and heat pumps.

Distributors had concerns regarding the imp lementation of regiona l standards and the potential impact of those standards on their busine ss. Distributors were concerned that possible disparities between the regional boundaries for standards and existing distribution boundaries may prove problematic. Distributors stated that regional standards may be defined based on geographic boundaries composed of state lines, wh ich are usually different than the boundaries that affect the composition of markets for central air conditioners and heat pumps. These market boundaries are determined by several factors, such as utility service areas, composition of existing building types within an area, and the delineation of natural climatic regions.

Additionally, distributors were concerned about the possible impact of regional standards on the efficiency of the distribution chain, and ultimately, their ability to control costs. Similar to manufacturers, national and regional distributors stated that they would face decreases in their economies of scale, which current ly benefit manufacturers of products that can be stocked and sold nationwide. Specifically, if certain products could not be sold throughout the entire country, then the cost of those products in the regions where they could be sold would be driven up. Distributors also stated that climates within a specific geographic region may vary, and certain areas within a geographic region may have mo re limited cooling demand than the surrounding areas. As a result, sales in those areas, where hi gh-efficiency cooling equipment would not be as well justified, would likely be de pressed. Distributors that service areas that lay on borders between regions would be particularly affected, as their costs would increase due to the more complex and diverse inventories. This would also limit the growth of distributors into neighboring areas which fall into a different climate region. DOE seeks further comment

2-50regarding the potential impact of regional standa rds on distributors, deal ers, contractors, and installers of residen tial central air conditioners and heat pumps. In addition, DOE is seeking market data that will assist in the identification and analysis of the impacts of regional standards on distributors, dealers, cont ractors, and installers.

DOE plans to address the issues raised in the interviews as well as the comments on regional standards. DOE plans to perform a sensitivity analysis of the effects of additional inventory costs and carrying charges on firm profitability of typical heating, air-conditioning, and refrigeration distributors at the national and regional levels. To conduct this analysis, DOE plans to use detailed sample industry data on income statem ents and balance sheets from HARDI’s Profit Reports. Because this source contains data by region and size of firm, DOE plans to examine the effects of firm size and region on the profitability calculations. DOE will investigate using enterprise sales data from Bureau of the Census County Business Patterns . and Bureau of the Census Geographical Area Series for 2002 on border counties for the regions of interest to determine the location and net fraction of distributors likeliest to be affected by selling in multiple regions. Distribution of air-conditioning w holesalers by size of sales also is available in the Bureau of the Census publication Establishment and Firm Size -2002. If similar questions concerning elements of the balance sheets and income statements are later raised for contractors and installers, similar detailed establishment financial and geographic area data series are also available in the 2002 Economic Census for mechanical and general contra ctors and would allow DOE to conduct similar analyses of c ontractors and installers.

DOE intends to develop an enforcement plan for regional standards as stated in section 2.10.3. DOE may also analyze (quantitatively or qualitatively, as data allow) the impacts that regional boundaries would have for distributors and dealers. DOE currently does not have data available on the potential impact of record-keeping and other administrative compliance costs for regional standards on the part of general contractors or other part s of the central air conditioner and heat pump distribution channels that would allow DOE to address NAHB’s concern. If such data become available, DOE plans to use 2002 Cens us data identified in this section to analyze the effects of such costs on firm profitability in the new chapter on the impacts of the regional standards on the distribution channels.

2.10.3 Enforcement

As noted above, several comme nts expressed concerns about enforcement of regional standards. HARDI indicated that it has serious co ncerns that regionalization strategy for central air conditioner and heat pump energy conservation standards will be unenforceable. (HARDI, No. 32 at p. 5) AHRI also believes that regional standards may be impractical and unenforceable. (AHRI, No. 24 at p. 3) ACCA stated their ag reement and further commented that regional standards will result in confusion to consumers in the marketplace. (ACCA, No. 23 at p. 2) Kent & O’Connor stated that when regional boundaries are being drawn, the willingness of a state to enforce the standard should be considered. (Kent & O’Connor, No. 13 at p. 240) Trane also commented that code officials may be the only entities that could effectively enforce regional standards, especially in areas close to regional boundaries. (Trane, No. 16 at p. 5)

Carrier posed a number of questions for DOE to consider, including: (1) what the enforcement mechanism will be; (2) if states will be responsible for enforcing the regional

2-51standard; (3) what regulations cover cross stat e-line transfers of non-compliant products; (4) how distributors will supply multiple regions addressed in the enforcement process; and (5) how enforcement regulations will address the issue of certain OEM systems that alone cannot meet a higher efficiency in one region but may be eligib le for sale if an inde pendent manufacturer’s coil is used. (Carrier, No. 18 at p. 3)

ACCA urged DOE not to wait for a regional standards decision before developing an enforcement plan, stating that the practicality and feasibility of enforcement should be part of the general evaluation of regional st andards. (ACCA, No. 23 at p. 2) Lennox agreed that regional standards are useless unless the enforcement issu es are resolved. (Lennox, No. 13 at p. 395) Joint Comment 1 suggested that DOE should consult with industry groups such as HARDI (distributors), ACCA, SMACNA, and MCA (contractors) as well as building code officials (ICC) and the National Association of State Energy Officials in the development of enforcement plans. (Joint Comment 1, No. 25 at p. 9) Carri er suggested that DOE hold sessions with state regulators to determine their willingness and ability to enforce regional energy standards. (Carrier, No. 18 at p. 4) ACCA encourages DOE to hold another collaborative meeting to discuss regional standards enforcement. (ACCA, No. 13 at p. 397) HARDI commented that the U.S. Department of Housing and Urba n Development was unable to form ulate regional criteria due to enforcement issues and that en forcement proposals should be made available for public debate. (HARDI, No. 13 at p. 398)

If regional standards are adopted for this rulemaking, EISA 2007 mandates that an enforcement plan rulemaking be initiated no later than 90 days after the issuance of the standard final rule. 42 U.S.C. 6295(o)(6)(G)(ii)(I). DOE has not yet determined the enforcement mechanism for regional standards; however DOE believes that an effective enforcement plan will likely be composed of multiple enforcement mechanisms. Among mechanisms DOE is considering are:

1) appropriate modifications to a ppliance labels to indicate in which regions of the country specific equipment is allowed to be installed;

2) requirements that marketing literature for systems clearly indicate in which regions a product could be le gally installed;

3) encouraging state and local entities to adopt these regional standards in building codes and to provide reference to the required minimu m efficiencies in required mechanical or electrical permits;

4) encouraging states who have regional app liance standards to adopt and codify the appropriate regional stan dards enacted by DOE;

5) clearly indicating in law that installations that don’t meet regional standards could result in installers being subject to fines for each occurrence;

6) requirements to certify compliance of installa tions through warranty registration or other registration means;

2-527) an informational program so that consumers are made aware of any regional standards, what to look for in purchasing equipment, and what implications there would be for improper installation; and

8) competitively-driven enforcement where manufacturers/distributors/contractors report other manufacturers/distributor s/contractors whose actions re sult in installations not in compliance with Federal standards.

Certain features of any enforcement plan w ould be that it not unduly regulate interstate commerce or otherwise constrain where a product may be manufactured or through which states a product can be transported and that it not place undue financial burden on consumers, manufacturers, contractors, distri butors, dealers or installers. Wh ile DOE believes that much of the liability for proper installation will inevitably lie with the installer, it believes that manufacturers and distributors can play a role in enforcement through labeling and possibly providing data, such as ongoing statistics, regarding non-complying products sold for final installation in a given region.

For the NOPR, as part of its analysis of regional impacts on distributors, dealers, contractors, and installers, DOE will analyze California’s Title 24 requirements and other extant state-level standards and consider the issues that have developed concerning their enforcement. DOE will also seek industry input on the viabilit y of the above enforcem ent mechanisms, other mechanisms DOE should consider, and the extent to which these mechanisms would result in additional financial burdens to consumers, manufacturers, c ontractors, distribut ors, dealers, and installers. DOE will consider and note all comments related to enforcement of regional standards submitted before the issuance of an enforcement plan rulemaking.

2.11 LIFE-CYCLE COST SUBGROUP ANALYSIS

The LCC subgroup analysis evaluates economic impacts on selected consumers groups who might be adversely affected by a change in the national energy conservation standards for the considered products. DOE evaluates impacts on pa rticular subgroups of consumers in part by analyzing the LCC impacts and PBP for those particular consumers.

DOE will use the LCC spreadsheet model to evaluate impacts on consumer subgroups. DOE can analyze the LCC for any subgroup by applying the LCC spreadsheet model to only that subgroup. DOE is particularly sensitive to increas es in the consumer price of the considered products, wishing to avoid a negative economic impact on any identified consumer subgroup.

Joint Comment 3 stated that DOE should fully analyze the energy savings potential of regional standards. (Joint Comment 3, No. 36 at p. 2) Low-income consumers will be disproportionally affected by standard levels unsuited to their region.

DOE will conduct a regional LCC and PBP an alysis that will sample low-income households and determine the potential for the proposed standards to disproportionately affect them. Low-income households may be dispropo rtionally affected because they may use a costlier-than-average mix of debt instruments to pay for first costs.

2-532.12 UTILITY IMPACT ANALYSIS

The utility impact analysis includes an analysis of the effect of ne w energy conservation standards on the electric and the gas utility indus tries. For this analysis, DOE adapted National Energy Modeling System (NEMS), a large multi-sectoral, partial-equilibrium model of the U.S. energy sector that the EIA developed throughout the past decade primarily for preparing EIA’s AEO. In previous rulemakings, a variant of NEMS (currently termed NEMS-BT, BT referring to DOE’s Building Technologies Program) was devel oped to address the specific impacts of an energy conservation standard.

Available in the public domain, NEMS produ ces a widely recognized baseline energy forecast for the United States through 2030. Th e typical NEMS outputs include forecasts of electricity sales, prices, a nd electric generating capacity. DOE conducts the utility impact analysis as a scenario that departs from the latest AEO reference case. In other words, the energy savings impacts from amended energy conserva tion standards are modeled using NEMS-BT to generate forecasts that deviate from the AEO reference case.

2.13 ENVIRONMENTAL ASSESSMENT

The intent of the environmental assessment is to quantify and consid er the environmental effects of amended energy conservation standard s for central air conditioners and heat pumps. The primary environmental effects of these stan dards would be reduced power plant emissions resulting from reduced consumption of electricity. DOE will assess these environmental effects by using NEMS-BT to provide key inputs to its analysis. The portion of the environmental assessment that will be produced by NEMS-BT considers carbon dioxide (CO 2 ), nitrogen oxides (NO X ), and mercury (Hg). The environmental assessment also considers impacts on SO 2 emissions. After a brief discussion of general methodology, this s ection will address each of the relevant emissions. This section then explains how DOE plans to monetize the benefits associated with emissions reductions.

2.13.1 Carbon Dioxide

In the absence of any Federal regula tion of power plant emissions of CO 2 , a DOE standard is likely to result in reductions of these emissions. The CO 2 emission reductions likely to result from a standard will be estimated using NEMS-BT and national energy savings estimates drawn from the NIA spreadsheet model. The net benefit of the standard is the difference between emissions estimated by NEMS-BT at each standard level considered and the AEO Reference Case. NEMS-BT tracks CO 2 emissions using a deta iled module that provides results with broad coverage of all sector s and inclusion of interactive effects.

2.13.2 Sulfur Dioxide

DOE has preliminarily determined that SO 2 emissions from affected Electric Generating Units (EGUs) are subject to nationwide and regional emissions cap and trading programs that are likely to eliminate the standards’ impact on SO 2 emissions. The costs of meeting such emission cap requirements are integrated in the electricity prices used in DOE’s analysis of the standards. Title IV of the Clean Air Act sets an annual emissions cap on SO 2 for all affected EGUs. SO 2 emissions from 28 eastern States and the Distri ct of Columbia (DC) are also limited under the

2-54Clean Air Interstate Rule (CAIR, published in the Federal Register on May 12, 2005. 70 FR 25162 (May 12, 2005)), which creates an allowance- based trading program that will gradually replace the Title IV program in those States a nd DC. (The recent legal history surrounding CAIR is discussed below.) The attain ment of the emissions caps is flexible among EGUs and is enforced through the use of emissions allowances and tradable permits. Under existing EPA regulations, any excess SO 2 emission allowances resulting from the lower electricity demand caused by the imposition of an efficiency standard could be used to permit offsetting increases in SO 2 emissions by any regulated EGU. However, if the standard resulted in a permanent increase in the quantity of unused emission allowances , there would be an overall reduction in SO 2 emissions from the standards. While there remains some uncertainty about the ultimate effects of efficiency standards on SO 2 emissions covered by the existin g cap and trade system, the NEMSBT modeling system that DOE plans to use to forecast emissions reducti ons currently indicates that no physical reductions in power sector emissions would occur for SO 2

.
Even if there is no significant redu ction in the overall emissions of SO 2 that results from the standard, there may still be some ec onomic benefit from reduced demand for SO 2 emission allowances that is not fully reflected in the co st savings experienced by individual consumers. Electricity savings that decrease the overall demand for SO 2 emissions allowances could lower allowance prices and thereby result in some econo mic benefits for all electricity consumers, not just those that reduced their electricity use as a result of an efficiency standard. DOE does not plan to monetize this particular benefit because the effect on the SO 2 allowance price from any single energy conservation standard is likely to be small and highly uncertain.

2.13.3 Nitrogen Oxides

NEMS-BT also has an algorithm for estimating NO X emissions from power generation. The impact of these emissions, however, will be affected by the CAIR, which the Environmental Protection Agency (EPA) issued on May 12, 2005. CAIR will permanently cap emissions of NO X in 28 eastern states and the District of Columbia. 70 FR 25162 (May 12, 2005).

Much like SO 2 emissions, a cap on NO X emissions means that the amended central air conditioner and heat pumps standards may have little or no physical effect on these emissions in the 28 eastern States and the DC covered by CAIR. Although CAIR has been remanded to the EPA by the DC Circuit, it will remain in effect until it is replaced by a rule consistent with the Court’s July 11, 2008, opinion in North Carolina v. EPA. 531 F.3d 896 (DC Cir. 2008); see also North Carolina v. EPA, 550 F.3d 1176 (DC Cir. 2 008). Because all States covered by CAIR opted to reduce NO X emissions through participation in cap-and-trade programs for electric generating units, emissions from these sources are capped across the CAIR region.

Standards may produce an envir onmental-related econo mic benefit in the form of lower prices for emissions allowance credits. As with SO 2 allowance prices, DOE does not plan to monetize this particul ar benefit because the effect on the NO X allowance price from any single energy conservation standard is likely small and highly uncertain.

Accordingly, DOE plans to use NEMS-BT to estimate the emissions reductions from possible standards in the 22 States where emissions are not capped.

2-552.13.4 Mercury

Similar to emissions of SO 2 and NO X , future emissions of Hg would have been subject to emissions caps. In May 2005, EPA issued th e Clean Air Mercury Rule (CAMR). 70 FR 28606 (May 18, 2005). CAMR would have permanently capped emissions of mercury for new and existing coal-fired power plants in all States by 2010. However, on February 8, 2008, the DC Circuit issued its decision in New Jersey v. Environmental Protection Agency, in which the DC Circuit, among other actions, vacated th e CAMR. 517 F.3d 574 (DC Cir. 2008). EPA has decided to develop emissions standards for pow er plants under the Clean Air Act (Section 112), consistent with the DC Circ uit’s opinion on the CAMR. See http://www.epa.gov/air/mercuryr ule/pdfs/certpetition_withdrawal.pdf . Pending EPA's forthcoming revisions to the rule, DOE is excluding the CAMR from its Environmental Analysis. In the absence of CAMR, a DOE sta ndard would likely reduce Hg emissions and DOE plans to use NEMS-BT to estimate these emission reductions.

2.13.5 Particulate Matter

DOE acknowledges that particulate matter (PM) impacts are of concern due to human exposures that can impact health. But impacts of PM emissions reduction are much more difficult to estimate than other emissions reductions due to the complex interactions between PM, other power plant emissions, meteorology, and atmospheric chemistry that impact human exposure to particulates. Human exposure to PM us ually occurs at a significant distance from the power plants that are emitting particulates and particulate precursors. When power plant emissions travel this distance, they undergo highly complex atmospheric chemical reactions. Although the EPA does keep inventories of direct PM emissions of power plants, in its source attribution reviews, the EPA doe s not separate direct PM emissions from power plants from the sulfate particulates indirectly produced through complex atmos pheric chemical reactions. The great majority of PM emissions from power plan ts are of these seconda ry particles (secondary sulfates). Thus, it is not useful to examine how the amended standard impacts direct PM emissions independent of indir ect PM production and atmospheric dynamics. Therefore, DOE is not planning to assess the impact of these standa rds on particulate emissions. Further, even the cumulative impact of PM emissions from power plan ts and indirect emissions of pollutants from other sources is unlikely to be significant.

2.13.6 Monetization of Emissi ons Reduction Benefits

For those emissions for which real nationa l emission reductions are anticipated (CO 2 , Hg, and NO X for 22 states), only ranges of estimate d economic values base d on environmental damage studies of varying quality and applicability are available. Therefore, DOE plans on reporting estimates of monetary benefits derived using these values and plans to consider these benefits in weighing the costs and benefits of each of the st andard levels considered. In accordance with U.S. Office of Management and Budget (OMB) guidance, DOE will conduct two calculations of the monetary benefits derived using each of the economic values used, one using a real discount rate of 3 percent and another using a real discount rate of 7 percent.

In order to estimate the monetary value of benefits resulting from reduced emissions of CO 2 emissions, it is DOE’s intent to use in its an alysis the most current Social Cost of Carbon

2-56(SCC) values developed a nd/or agreed to by interagency reviews. The SCC is intended to be a monetary measure of the incremental damage resulting from greenhouse gas (GHG) emissions, including, but not limited to, net agricultural productivity loss, human health effects, property damage from sea level rise, and changes in ecosy stem services. Any effort to quantify and to monetize the harms associated with climate change will raise serious questions of science, economics, and ethics. But with full regard for the limits of both quantifi cation and monetization, the SCC can be used to provide estimates of the social benefits of reduc tions in GHG emissions.

DOE uses the most recent interagency estimates of the potential global benefits resulting from reduced CO 2 emissions. At the time of this notice, these estimates are $4.7, $21.4, $35.1, and $64.9 per metric ton of CO 2 (in 2007 dollars). These values are then adjusted to 2009$ using the standard GDP deflator value of 2008 and 2009 . For emissions (or emission reductions) that occur in later years, these values grow in real terms over time.. . . Additionally, the interagency group determined that a range of values from 7 per cent to 23 percent should be used to adjust the global SCC to calculate domestic effects, although preference will be given to consideration of the global benefits of reducing CO 2 emissions.

DOE recognizes that scientific and economic kno wledge continues to evolve rapidly as to the contribution of CO 2 and other GHG to changes in the fu ture global climate and the potential resulting damages to the world economy. Thus, these values are subject to change.

DOE also intends to estimate the potential monetary benefit of reduced NO X , and Hg emissions resulting from the standard levels it considers. For NO X emissions, available estimates suggest a very wide range of monetary values for NO X emissions, ranging from $370 per ton to $3,800 per ton of NO X from stationary sources, measured in 2001$ (equivalent to a range of $447 to $4,591 per ton in 2009$).). Refer to the OM B, Office of Information and Regulatory Affairs, “2006 Report to Congre ss on the Costs and Benefits of Federal Regulations and Unfunded Mandates on State, Local, and Trib al Entities,” for additional information.

For Hg emissions reductions, DOE has previous ly determined that the impact of mercury emissions from power plants on humans is c onsidered highly uncertain. However, DOE identified two estimates of the environmental damage of mercury based on two estimates of the adverse impact of childhood exposure to methyl mercury on intelligence quotient (IQ) for American children, and subsequent loss of life time economic productivit y resulting from these IQ losses. The high-end estimate is based on an estimate of the current aggregate cost of the loss of IQ in American children that results from ex posure to mercury of U.S. power plant origin ($1.3 billion per year in year 2000$), which wo rks out to $33.7 million per ton emitted per year (in 2009$). Refer to L. Trasande et al., “Applying Cost Analyses to Drive Policy that Protects Children,” 1076 Ann. N.Y. Acad. Sci. 911 (2006) for additional information. The low-end estimate is $0.66 million per ton emitted (in 2004$) or $0.749 million per ton in 2009$, which will be updated to 2009$. DOE deri ved this estimate from a publis hed evaluation of mercury control using different methods and assumptions from the first study but also based on the present value of the lifetime earnings of ch ildren exposed. See Ted Gayer and Robert Hahn, “Designing Environmental Policy: Lessons from the Regulation of Mercury Emissions,” Regulatory Analysis 05–01, American Enterprise In stitute-Brookings Joint Center for Regulatory Studies, Washington, DC (2004). A version of th is paper was published in the Journal of

2-57Regulatory Economics in 2006. Th e estimate was derived by ba ck-calculating the annual benefits per ton from the net present value of benefits reported in the study.

For more detail on the environmental assessment, refer to the environmental assessment report in the preliminary TSD.

2.14 EMPLOYMENT IMPACT ANALYSIS

The imposition of standards can affect employ ment both directly a nd indirectly. Direct employment impacts are changes in the number of employees at plants that produce the covered products and at the affiliated distribution a nd service companies. DOE evaluated direct employment impacts in the manufacturer impact analysis. Indirect employment impacts may result from consumers shifting expenditures between goods (the substitution effect) and from changes in income and overall expenditure levels (the income effect). DOE will use PNNL’s impact of sector energy technologies (ImSET) mo del to investigate the combined direct and indirect employment impacts. The ImSET model, which was de veloped for DOE’s Office of Planning, Budget, and Analysis, estimates the employment and income effects energy-saving technologies produce in buildings, industry, and transportation. Compared with simple economic multiplier approaches, ImSET allows for more comp lete and automated anal ysis of the economic impacts of energy conservation investments.

2.15 REGULATORY IMPACT ANALYSIS

In the NOPR, DOE will prepare an RIA pursuant to Executive Order 12866, Regulatory Planning and Review, 58 FR 51735, October 4, 19 93. The RIA is subject to review under the Executive Order by the Office of Information and Regulatory Affairs at the Office of Management and Budget. The RIA addresses th e potential for non-regulatory approaches to supplant or augment energy conservation standards in order to improve the energy efficiency or reduce the energy consumption of the pr oducts covered under this rulemaking.

DOE recognizes that non-regulatory efforts by manufacturers, utilities, and other interested parties can substantia lly affect energy efficiency or reduce energy consumption. DOE will base its assessment on the actual impacts of any such initiatives to date, but also will consider information presented by interested parties on the impacts existing initiatives might have in the future.

2-58REFERENCES

1. ACEEE. Emerging Technologies and Practices. 2004. (Last accessed May 18, 2009.) http://www.aceee.org/pubs/a042_h13.pdf

2 . Oak Ridge National Laboratory. 2002. Frost-less Heat Pump.

3. Heating, Air Conditioning & Refrigera tion Distributors International. 2008. 2008 Profit Report (2007 Data).

4. Air Conditioning Cont ractors of America. 2005. Financial Analysis for the HVACR Contracting Industry

.

5. U.S. Census Bureau. 2002. Commercial and Institutional Building Construction: 2002

. Report EC02-231-236220.

6. U.S. Court of Appeals for the Second Circuit, voluntary remand, State of New York, et al.

v. Department of Energy, et al., April 15, 2009.

7. Edison Electric Institute, EEI Typical Bills and Average Rates Report

. < http://www.eei.org/products_and_services/descriptions_and_access/typ_bills_report.htm >

8. Regulatory Research Associates, Inc., Average Regulated Retail Price of Electricity, 2007 & Comparative Historical Data , 2008. Jersey City, NJ.

9. U.S. Department of Energy–Office of Energy Efficiency and Renewable Energy. Technical Support Document: Energy Efficiency Program for Commercial and Industrial Equipment: Commercial Unitary Air Conditioners and Heat Pumps . July 2004. Chapter 8.

< http://www1.eere.energy.gov/buildings/appliance_standards/commercial/cuac_tsd_06090 4.html >

10. U.S. Department of Energy–E nergy Information Administration. An Updated Annual Energy Outlook 2009 Reference Case Reflecting Provisions of the American Recovery and Reinvestment Act and Recent Changes in the Economic Outlook . April 2009. Report #: SROIAF/2009-03.

< http://www.eia.doe.gov/oiaf/servicerp t/stimulus/index.html?featureclicked=1 & >

11. U.S. Department of Energy–Office of Energy Efficiency and Renewable Energy, Energy Conservation Program: Energy Conservation Standards for General Service Fluorescent Lamps and Incandescent Reflector Lamps; Proposed Rule. Federal Register 2009 74(69): 16920–16968.

2-59CHAPTER 3. MARKET AND TECHNOLOGY ASSESSMENT

TABLE OF CONTENTS

3.1 INTRODUCTION

............................................................................................................ 3-1 3.1.1 Definitions

............................................................................................................. 3-1 3.1.2 Product Classes

...................................................................................................... 3-2 3.1.3 Test Proce dures

..................................................................................................... 3-3 3.2 MARKET ASSESSMENT

............................................................................................... 3-3 3.2.1 Trade Associations

................................................................................................ 3-4 3.2.2 Manufacturers and Ma rket Share

.......................................................................... 3-5 3.2.3 Regulatory Programs

............................................................................................. 3-8 3.2.4 Non-Regulatory Programs

................................................................................... 3-10 3.2.5 Industry Cost Structure

........................................................................................ 3-15 3.2.6 Equipment Lifetime

............................................................................................. 3-16 3.2.7 Market Performan ce Data

................................................................................... 3-17 3.2.8 Historical Shipments and Efficiencies

................................................................ 3-27 3.2.9 Saturations in U.S. Households

........................................................................... 3-30 3.3 TECHNOLOGY ASSESSMENT

................................................................................... 3-31 3.3.1 Compressor Improvements

.................................................................................. 3-31 3.3.2 Fan System Improvements

.................................................................................. 3-32 3.3.3 Expansion Valve Improvements

......................................................................... 3-33 3.3.4 Heat Exchanger Technologie s and Improvements

.............................................. 3-34 3.3.5 Designs Relevant Only to Heat Pumps

............................................................... 3-37

3-iLIST OF TABLES

Table 3.2.1 AHRI Directory of Cer tified Product Performance Classifications for Residential Central Air Conditioners and Heat Pumps

................................................................................... 3-5 Table 3.2.2 Manufacturer Brand Names Found in th e AHRI’s Directories of Certified Product

Table 3.2.3 Current Federal Energy Conservati on Standards for Resi dential Central Air

Table 3.2.4 Canadian Energy Conservation Standa rds for Residential Ce ntral Air Conditioners

Table 3.2.5 ENERGY STAR Levels for Split System and Single Package Re sidential Central Air

Table 3.2.8 Rebate Programs Offered by Local Utilities for Residential Central Air Conditioners

Table 3.2.9 Rebate Programs Offered by Local Ut ilities for Residential Ce ntral Air-Cooled Heat

Table 3.2.10 Air Conditioning and Warm Air He ating Equipment Industry Employment and

Table 3.2.12 Industry Cost Stru cture Developed from SEC Data Error! Bookmark not defined. Table 3.2.13 Types of Models Listed in the AHR I Directory of Certified Product Performance.... Performance for Residential Central Ai r Conditioners and Heat Pumps

.................................... 3-6

Conditioners and Heat Pumps

.................................................................................................... .. 3-9

and Heat Pumps

................................................................................................................. ........ 3-10

Conditioners and Heat Pumps

.................................................................................................... 3-11 Table 3.2.6 CEE Tiers for Residential Centra l Air Conditioners and Heat Pumps

................... 3-12 Table 3.2.7 Federal Tax Credits fo r Residential Central Air Cond itioners and Heat Pumps

.... 3-12

............................................................................................................................... ..................... 3-13

Pumps

.......................................................................................................................... ............... 3-14

Payroll Data

................................................................................................................... ............ 3-15 Table 3.2.11 Air Conditioning and Warm Air Heating Equipment Industry Cost Data

.......... 3-16

............................................................................................................................... ..................... 3-17

LIST OF FIGURES

Figure 3.2.1 2007 Market Shares for Unitary Air Conditioners and Heat Pumps

...................... 3-7 Figure 3.2.3 SEER Ratings for Single Package Ce ntral Air Conditioners in the AHRI Certified

Figure 3.2.4 SEER Ratings for Single Packag e Heat Pumps in the AHRI Certified Product

Figure 3.2.5 SEER Ratings for Split System Cent ral Air Conditioners in the AHRI Certified

Figure 3.2.6 SEER Ratings for Split System Heat Pumps in the AHRI Directory of Certified

Figure 3.2.7 SEER Ratings for SDHV Systems in the AHRI Directory of Certified Product

Figure 3.2.8 HSPF Ratings for Single Package He at Pumps in AHRI’s Directory of Certified

Figure 3.2.9 HSPF Ratings for Split System Heat Pumps in AHRI’s Directory of Certified

Figure 3.2.10 HSPF Ratings for SDHV Heat Pump s in AHRI’s Directory of Certified Product

Figure 3.2.11 Average SEER Ratings at Each Cooling Capacity for Single Package Air Product Performance Directory

................................................................................................. 3 -18

Performance Directory

.......................................................................................................... ..... 3-18

Product Performance Directory

................................................................................................. 3 -19

Product Perfo rmance

............................................................................................................ ...... 3-19

Performance

.................................................................................................................... ........... 3-20

Product Perfo rmance

............................................................................................................ ...... 3-21

Product Perfo rmance

............................................................................................................ ...... 3-21

Performance

.................................................................................................................... ........... 3-22

Conditioners in AHRI’s Directory of Certified Product Performance

...................................... 3-23

3-iiFigure 3.2.12 Average SEER Ratings at Each Cooling Capacity for Split System Air Conditioners in AHRI’s Directory of Certified Product Performance

...................................... 3-23 Figure 3.2.13 Average SEER Rating at Each Coolin g Capacity for Single Package Heat Pumps

Figure 3.2.14 Average SEER Rating at Each Coolin g Capacity for Split System Heat Pumps in

Figure 3.2.15 Average SEER Rating at Each Cooling Capacity for SDHV Systems in the AHRI

Figure 3.2.16 Average HSPF at Each Cooling Cap acity for Single Package Heat Pumps in the

Figure 3.2.17 Average HSPF Rating at Each Cooling Capacity for Split System Heat Pumps in

Figure 3.2.18 Average HSPF Rating at Each Cooling Capacity for SDHV Heat Pumps in the in the AHRI Directory of Cer tified Product Performance

......................................................... 3-24

the AHRI Directory of Certif ied Product Performance

............................................................. 3-24

Directory of Certified Product Performance

.............................................................................. 3-25

AHRI Directory of Certified Product Perfo rmance

................................................................... 3-26

the AHRI Directory of Certif ied Product Performance

............................................................. 3-26

AHRI Directory of Certified Product Perfo rmance

................................................................... 3-27

3-iiiCHAPTER 3. MARKET AND TECHNOLOGY ASSESSMENT

3.1 INTRODUCTION

This chapter details the market and technolog y assessment that the U.S. Department of Energy (DOE) has carried out in support of the ongoing energy conservation standards rulemaking for residential central air conditioners and heat pumps. It consists of two sections: the market assessment and th e technology assessment.

The goal of the market and technology assessment is to de velop a qualitative and quantitative characterization of the residential ce ntral air conditioner and heat pump industry and market structure, based on publicly available information and data and information submitted by manufacturers and other stakeholde rs. Publicly available information includes the equipment certification directory from the Air-Conditioning, Heating and Refrigeration Institute (AHRI), as well as Current Industry Reports (CIR) and A nnual Survey of Manufactures (ASM) from the U.S. Census Bureau. Issues addressed include: manufacturer characteristics and market shares; existing regulatory and non-regulatory efficien cy improvement initiatives ; product classes; and trends in the equipment markets and characteristics. The technol ogy assessment is a preliminary list of technologies that can improve the efficiency of residential central air conditioners and heat pumps. These technologies are consid ered in the screening analysis.

Residential central air conditioners and heat pum ps are products that are used to centrally heat and/or cool residential buildings. These pr oducts, also called unitary air conditioners and heat pumps, are limited to cooling capacities of less than 65,000 Btu/hr (5.4 tons) and do not include room air conditioners a or packaged terminal air conditioners and heat pumps. b

3.1.1 Definitions

The Energy Policy and Conservation Act (EPCA) defines a “central air conditioner” as “a product, other than a packaged terminal air c onditioner, which is powered by single-phase electric current, air cooled, rated below 65,000 Btu per hour, not contained within the same cabinet as a furnace, the rated capacity of wh ich is above 225,000 Btu per hour, and is a heat pump or a cooling only unit.” (42 U.S.C. 6291(21)(A )-(E)) DOE has incorporated this definition into its regulations at 10 CFR 430.2.

a “Room air conditioner” is defined in 10 CFR 430.2 as “a consumer product, other than a ‘packaged terminal air conditioner,’ which is powered by a single phase electric cu rrent which is an encased assembly designed as a unit for mounting in a window or through the wall for the purpose of providing delivery of conditioned air to an enclosed space. It includes a prime source of refrigeration and may include a means for ventilating and heating.” For more information on room air conditioners, see http://www.eere.energy.gov/buildings/appliance_standards/residential/room_ac.html

. b “Packaged terminal air conditioner” is defined in 10 CFR 430.2 as “a wall sleeve and a separate unencased combination of heating and cooling assemblies specified by the builder and intended for mounting through the wall. It includes a prime source of refrigeration, separable outdoor louvers, forced ventilation, and heating availability energy.” “Packaged terminal heat pump” is defined in 10 CFR 430.2 as “a packaged terminal air conditioner that utilizes reverse cycle refrigeration as its prime heat source and should have supplementary heating availability by builder’s choice of energy.” For more information on package terminal air conditioners and heat pumps, see http://www.eere.energy.gov/buildings/appliance_standards/commercial/packaged_ac_hp.html

.

3-1EPCA defines a “heat pump” as “a product, other than a packaged terminal heat pump, which consists of one or more assemblies, powered by single-pha se electric current, rated below 65,000 Btu per hour, utilizing an indoor conditioni ng coil, compressor, and refrigerant-tooutdoor air heat exchanger to provide air heating, and may also provide air cooling, dehumidifying, humidifying circulating, and air cleaning.” (42 U.S.C. 6291(24)(A)-(E)) DOE has incorporated this definition into its regulations at 10 CFR 430.2.

3.1.2 Product Classes

Residential central air conditioners and heat pumps are divided into nine product classes based on physical characteristics of the produc t that affect performance. Key physical characteristics include product ty pe (i.e., air conditioner or heat pump), whether the unit is a single package or has individual indoor and outdoor sections, and space constraints that relate to product utility.

3.1.2.1 Existing Product Classes

The existing Federal energy conservation standa rds for residential central air conditioners and heat pumps went into effect on January 23, 2006. 10 CFR Part 430.32(c)(2) lists the nine product classes of residential cen tral air conditioners and heatpumps and their corresponding energy conservation standards. The existing product classes are:

• Split-system air conditioners

• Split-system heat pumps

• Single-package air conditioners

• Single-package heat pumps

• Through-the-wall air conditioners and heat pumps – split system

• Through-the-wall air conditioners and heat pumps – single package

• Small duct, high velocity systems

• Space-constrained air conditioners

• Space-constrained heat pumps

3.1.2.2 Rulemaking Product Classes

For this residential central air conditioner and heat pump rulemaking, DOE maintained the existing product classes. However, two of th e existing product classes, through-the-wall air conditioners and heat pumps – split system and th rough-the-wall air conditioners and heat pumps

–

single package, no longer exist c , which is subsequent to the eff ective date of this rulemaking. Therefore, DOE did not consider those two product classes separately (instead DOE considered them to be space-constrained products), and ex amined only seven product classes for this residential central air conditioner and heat pump rulemaking. The se ven product classes DOE examined are:

c As defined in 10 CFR 430.2, the through-the-wall product class applies only to products manufactured prior to January 23, 2010. This provision eliminates through-the-wall units as a separate product class after this date.

3-2• Split-system air conditioners

• Split-system heat pumps

• Single-package air conditioners

• Single-package heat pumps

• Small duct, high velocity systems

• Space-constrained air conditioners

• Space-constrained heat pumps

3.1.3 Test Procedures

The test procedures for central air conditione rs and heat pumps are codified in 10 CFR 430, Subpart B, Appendix M. Most aspects of the existing test procedure for central air conditioners and heat pumps date back to its original publication in the Federal Register on December 27, 1979. 44 FR 76700. DOE modified the test procedure on March 14, 1988, to cover variable-speed central air conditioners and he at pumps, to address te sting of split non-ducted units, and to change the method used for cred iting heat pumps that provide a demand defrost capability. 53 FR 8304.

A further revision of the test procedure for central air conditioners and heat pumps was published as a final rule on October 11, 2005 and became effective on April 10, 2006. 70 FR 59122. Generally, the October 2005 final rule added new sections, revised several sections, and re-organized the test procedure in order to eliminate the need for several test procedure waivers and to make the test procedure more chronological in its progression. The revisions to the test procedure did not alter the minimum energy cons ervation standards in effect for central air conditioners and heat pumps. On July 20, 2006, DOE published a proposed rule to consider further changes to the test procedure in response to issues raised by stakeholders prior to the publication of the October 11, 2005, final rule . 71 FR 41320. DOE determined that it was appropriate to consider additional modifications to the test procedure for the following reasons: (1) to implement test procedure revisions that are needed because of new energy conservation standards for small-duct, high-velocity (SDHV) systems; (2) to better address test procedure waivers for multi-split systems; and (3) to address sampling and rating issues that have been raised since new minimum energy conservation standards for these products became effective on January 23, 2006. Id . at 41321-22 A final rule adopting additional amendments to the central air conditioner and heat pump test pr ocedures related to these issues was published on October 22, 2007, which became effective on April 21, 2008. 72 FR 59906. Subsequent waivers granted for residential modulating mu lti-split systems terminated on the eff ective date of the latest test procedure final rule. 72 FR at 59906-07.

3.2 MARKET ASSESSMENT

The following market assessment identifies manufacturer trade associations, domestic and international manufacturers of residential ce ntral air conditioners and heat pumps and their corresponding market shares, regulatory and non -regulatory programs. The market assessment also describes the cost structur e for the residential central air conditioner and heat pump industry, and summarizes relevant ma rket performance data.

3-33.2.1 Trade Associations

DOE identified AHRI as the only trade group that supports, or has an interest in, the residential central air conditioner and heat pump industry.

AHRI is a national trade association of manuf acturers of residential, commercial, and industrial appliances and equipment, components, and relate d products. AHRI was established in January of 2008 when the Air-Conditioning and Refrigeration Institute (ARI) merged with the Gas Appliance Manufacturers Association (GAMA) . AHRI’s member companies are responsible for over 90 percent of the residential and co mmercial air conditioning and space heating equipment sold in North America. 1 AHRI develops and publishes technical standards for residential and commercial equipment using rati ng criteria and procedures for measuring and certifying equipment performance. AHRI also par ticipates in developing international standards and has established a policy of a dopting international standards for use in the United States when technologically and economically feasible.

AHRI administers the ARI Performance Certified programs that test and certify the performance of cooling equipment. AHRI mainta ins the AHRI Directory of Certified Product Performance that lists all produc ts that have been certified by the AHRI. AHRI maintains certified performance directories for both air conditioners and heat pumps rated below 65,000 Btu/h. The AHRI directories subdivide these products based upon certain defining characteristics, such as single package or split system and coil only or coil and blower combinations. Table 3.2.1 shows the AHRI classifi cations where products are available in the AHRI directories of certified products, along with the corresponding DOE product classes for this rulemaking.

3-4Table 3.2.1 AHRI Directory of Certified Pr oduct Performance Classifications for Residential Central Air Conditioners and Heat Pumps
DOE Product Class AHRI Classifications* Split system air conditioners RCU-A-C RCU-A-CB RCU-A-CB-O RCUY-A-CB RCUY-A-CB-O RC-A Split system heat pumps HRC-A-C HRC-A-CB HRCU-A-C HRCU-A-CB HRCU-A-CB-O HORC-A-C HORCU-A-C HORCU-A-CB Single package air conditioners SP-A SPY-A Single package heat pumps HSP-A Small duct, high velocity systems SDHV-RCU-A-CB SDHV-HRCU-A-CB SDHV-HORCU-A-CB Space constrained products – air conditioners** TTW-RCU-A-C TTW-RCU-A-CB Space constrained products – heat pumps** TTW-HRCU-A-C TTW-HRCU-A-CB *The classifications listed are only those with products available in the AHRI Directories of Certified Product Performance for central air conditioners and heat pumps. For more information on AHRI classifications and their definitions, visit www.ahridirectory.org/ahriDirectory/pa ges/fieldHelp.aspx?program=AC&controlID=ariType for air conditioners, or www.ahridirectory.org/ahriDirectory/ pages/fieldHelp.aspx?program=HP&controlID=ariType for heat pumps. **The AHRI Directory of Certified Performance did not list any space constrained products as of March 16, 2009. However, after January 23, 2010 (which is after the effective date for this rulemaking) the Through-the-wall equipment classes will expire, at which time, they will become part of the space constrained product classes.

3.2.2 Manufacturers and Market Share

DOE examined AHRI’s Directory of Cer tified Product Performance for residential central air conditioners and heat pumps to identify residential central air conditioner and heat pump manufacturers. DOE identifie d 45 separate companies that manufacture and market air conditioner and heat pump systems and coils. Th e manufacturers found in the AHRI Directories of Certified Pr oduct Performance for residential central air conditioners and heat pumps are listed in Table 3.2.2, along with their parent company in parentheses, if applicable.

3-5Table 3.2.2 Manufacturer Brand Names Found in the AHRI’s Directories of Certified Product Performance for Residential Central Air Conditioners and Heat Pumps 2

Aaon, Inc. Lennox International National Coil Company

Aire-Flo Friedrich Air Conditioning Co. (US Natural Resources, Inc.) National Comfort Products (National Refrigeration and Air Conditioning Products, Inc.)

Airquest Fujitsu General America, Inc. (Fujitsu General Group) Nutone

Airwell-Fedders North America,
Inc. GD Midea Commercial AirConditioning Equipment Co., Ltd. Quietside

Bard Manufacturing Company Goodman/Amana (Goodman Global, Inc.) Rheem/Ruud (Paloma Global)

Beutler Corporation Grandaire Style Crest Products

Broan Haier America (Haier Group) Summit Manufacturing, Inc.
Century (Heat Controller) Heat Controller, Inc. Texas Furnace, LLC
Cold Point Corp. Intertherm Thermo Products, Inc. (Burnham Holdings, Inc.) Dayton Electric Manufacturing Company (WW Grainger, Inc.) Kenmore (Sears Holdings Corpora tion) Trane/American Standard (Ingersoll Rand)

Eair LLC LG Electronics, Inc. Unitary Products Group (York/Johnson Controls)
Ecotemp Mammoth, Inc. (Thomas H. Lee Partners, LP) United Refrigeration Distributors,
Inc.
Enviromaster International (ECR International, Inc.) McQuay International (Daikin Industries, Ltd.) V-Aire

Espitech, LLC Mitsubishi Electric and Electronics USA, Inc. Whirlpool

International Comfort Products ­ Carrier/UTC Nordyne Xenon

Figure 3.2.1 displays the 2007 market shares for the residential central air conditioner market. The 7 largest residential central air c onditioner and heat pump ma nufacturers controlled 97 percent of the market. The seven largest ma nufacturers for the year 2007 are UTC/Carrier, Goodman, American Standard (Trane) d , Lennox, Rheem, York and Nordyne.

d Prior to 2007, Trane was a subsidiary of American Standard Companies. On November 28, 2007 Trane separated from the two other branches of American Standard Companies. On June 5, 2008, Ingersoll Rand acquired Trane. For more information, visit www.trane.com/Corporate/About/history.asp.

3-6Figure 3.2.1 2007 Market Shares for Unitar y Air Conditioners and Heat Pumps 3

3.2.2.1 Small Businesses

DOE considers the possibility of small businesses being particularly impacted by the promulgation of minimum energy conservation sta ndards for residential ce ntral air conditioners and heat pumps. The Small Business Admin istration (SBA) defines small business manufacturing enterprises for resi dential central air conditioners and heat pumps as having 750 employees or fewer. 4 SBA lists small business size standard s that are matched to industries as they are described in the North American I ndustry Classification System (NAICS). A size standard is the largest that a for-profit concern can be and still qualify as a small business for Federal Government programs. These size standard s are generally the average annual receipts or the average employment of a firm. For residen tial central air conditioners and heat pumps, the size standard is matched to NAICS code 333415, Air-Conditioning and Warm Air Heating Equipment and Commercial and I ndustrial Refrigeration Equipmen t Manufacturing, which has a size standard of 750 employees.

DOE further studied the potential impacts on these small businesses in detail and presented the results in manufacturer impact anal ysis (MIA) (Chapter 12 of this TSD). DOE has identified the following as small business residential central air conditioner and heat pump manufacturers:

• Aire-Flo

• Airquest

• Bard Manufacturing Company

• Beutler Corporation

• Heat Controller

• Cold Point Corporation

• Eair, LLC

• Enviromaster International

3-7• Espitech, LLC

• National Coil Company

• National Comfort Products

• Quietside

• Style Crest Products

• Summit Manufacturing, Inc.

• Texas Furnace, LLC

3.2.2.2 Mergers and Acquisitions

A trend in the residential central air conditi oning and heat pump industry over the past decades has been the consolidation of major manufacturers. In the last ten years or so, the seven major manufacturers (i.e., Goodm an, Lennox, Carrier, York, Rheem, Nordyne, and Trane) have gone through various mergers and acquisitions, and have materialized as differentiated leaders in the air conditioning and heat pump manufacturing industry. A brief summary of the recent history of each of the seven largest manufacturers is as follows:

• Goodman Global, Inc. was founded and purchased Janitrol in 1982. In 1997, Goodman acquired the Amana brand.

• Lennox Industries is a subsidiary of Lennox International, Inc., a holding company that was created in 1984. Lennox Internati onal acquired Armstrong Air Conditioning Inc. in 1988. In 1999, Lennox International co mpleted an Initial Public Offering and became a public company.

• Carrier has been a wholly-owned subsid iary of United Tec hnologies Corporation since 1979. In 2004, Carrier Corpora tion acquired Linde Refrigeration.

• York Unitary Products Group and York Inte rnational are subsidiaries of Johnson Controls, Inc. Johnson Controls, Inc. purchased York in 2005.

• Rheem is a privately held firm that was acquired by Paloma I ndustries of Japan in 1987. Paloma Industries also acquired Rheem Australia (Solahart) in 2002.

• Nordyne is a subsidiary of the privately held Nortek, Inc. It introduced the Frigidaire, Tappan, and Philco brands as potential repl acement HVAC brands in 1998. It also added the Gibson and Kelvinator bra nds in 1999. In 2002, the firm added the Westinghouse brand as a residential produc t line. The Mammoth commercial line was introduced as a part of Nordyne in 2003. Most recently, Nordyne added the Broan brand of products in 2005.

• Trane Inc. was acquired by American Standard Companies in 1984. In 2007 Trane separated from American Standard and was subsequently bought by Ingersoll-Rand in 2008.

3.2.3 Regulatory Programs

The following section details current regula tory programs mandating energy conservation standards for residential central air conditi oners and heat pumps. Section 3.2.3.1 discusses current Federal energy conservation standard s. Sections 3.2.3.2 and 3.2.3.3 review standards in both Canada and Mexico that may impact the companies servicing the North American market.

3-83.2.3.1 Current Federal Energy Conservation Standards

Part A of Title III of EPCA addresses the energy conservation standards for consumer products other than automobiles, which include residential centr al air conditioners and heat pumps. (42 U.S.C. 6291-6309) The most recent Fe deral standards for residential central air conditioners and heat pumps went into effect on January 23, 2006 and are codified in? 10 CFR Part 430.32. Table 3.2.3 presents the current Fe deral energy conservation standards for residential central air conditioners and heat pumps as presented in part (c)(2) of 10 CFR Part 430.32.

Table 3.2.3 Current Federal Energy Conservation Standards for Residential Central Air Conditioners and Heat Pumps e Product class SEER* HSPF** (i) Split system air conditioners 13.0

- (ii) Split system heat pumps 13.0 7.7 (iii) Single package air conditioners 13.0

- (iv) Single package heat pumps 13.0 7.7 (v)(A) Through-the-wall air conditioners and heat pumps-split system*** 10.9 7.1

(v)(B) Through-the-wall air cond itioners and heat pumps-single package*** 10.6 7.0

(vi) Small duct, high velocity systems 13.0 7.7 (vii)(A) Space constrained pr oducts-air conditioners 12.0

- (vii)(B) Space constrained products-heat pumps 12.0 7.4 *SEER is seasonal energy efficiency ratio. **HSPF is heating seasonal performance factor for Region IV. ***As defined in 10 CFR Part 430.2, this product class applies to products manufactured before January 23, 2010.

3.2.3.2 Canadian Energy Conservation Standards

The Natural Resources Canada (NRCan) Office of Energy Efficiency regulation mandates minimum energy conserva tion standards for residential central air conditioners and heat pumps. These standards apply to single p ackage and split system air-source air conditioners and heat pumps with a cooling capacity less than 65,000 Btu/h. The current standards went into effect November 2006, and are shown in Table 3.2.4.

e Current Federal energy conservation standards for residential central air conditioners taken from 10 CFR 430.32(c)(2).

3-9Table 3.2.4 Canadian Energy Conservation St andards for Residential Central Air Conditioners and Heat Pumps 5

Product Minimum Energy Performance Standard Air Conditioners – single package & split-system – cooling SEER = 13 Heat Pumps – single package & split–system – cooling SEER = 13 Heat Pumps – single package & split system – heating HSPF V* = 6.7 AC & HP – through–the–wall, coolin g – (until January 22, 2010) SEER = 10.9 AC & HP – through–the–wall, cooling – (after January 23, 2010) SEER = 12 Heat pumps – through–the–wall – heatin g – (until January 22, 2010) HSPF V = 6.2 Heat Pumps – through–the–wall – heatin g – (after January 23, 2010) HSPF V = 6.4 AC & HP – space–constrained – cooling SEER = 12 Heat pumps – space–constrained – heating HSPF V = 6.4 AC & HP – small duct, high velo city (SDHV) – cooling SEER = 11 *HSPF V is the Heating Seasonal Performance Factor – Region V. U.S. energy conservation standards specify HSPF as HSPF IV (i.e. HSPF – Regi on IV). HSPF V = HSPF IV/1.15.

3.2.3.3 Mexican Energy Conservation Standards

The National Commission for Energy Saving (CONAE) f is the agency responsible for developing, updating, and imple menting Mexican official standards of energy efficiency. CONAE published NOM-011-ENER-2006 (which update d previous standard effective in 2002) in June 2007. The standards prescribe minimum e fficiencies for central, package, and split system central air conditioners with cooling capacities between 30,000 and 65,000 Btu/h g at a minimum of 13 SEER. h

Table 3.2.5 Mexican Energy Conservation St andards for Residential Central Air Conditioners 6

Product Minimum Energy Performance Standard Air Conditioners – single package & split-system – cooling SEER = 13

3.2.4 Non-Regulatory Programs

DOE identified several non-regulatory programs aimed at improving the energy efficiency of residential central air conditioners and heat pumps. DOE reviewed two programs based on voluntary efficiency targets for residen tial central air conditioners and air-source heat pumps: the ENERGY STAR program and the Consortium for Energy Efficiency (CEE) initiative. In addition, DOE identif ied rebate programs for resi dential purchasers of higherefficiency central air conditione rs and heat pumps, DOE also identified Federal and State tax

f For more information visit www.conae.gob.mx/wb/CONAE/english/_rid/6600?page=1

. g Cooling capacity is specified in the standard as 8,800W to 19,050W.

h Mexican efficiency standards for central air conditioners are specified in terms of Relación de eficiencia energética estacional (REEE). NOM-011-ENER-2006 mandates a minimum efficiency of 3.81 REEE, which is equivalent to 13 SEER.

3-10credits for residential consumers of higher-effici ency central air conditioners and heat pumps. DOE reviewed Federal procurement specifi cations for these products as well.

3.2.4.1 Voluntary Energy Efficiency Targets

Energy Star

ENERGY STAR i is a voluntary labeling program conducted by the U.S. Environmental Protection Agency (EPA) and DOE that identifie s and promotes energy-efficient products. To qualify, a product must usually exceed federal mi nimum standards by a specified amount, or if no federal standard exists, it must meet minimum efficiency levels set by the program and/or exhibit selected energy saving features. ENERGY STAR creates minimum energy efficiency specifications for various products, including split system and single package air conditioners and heat pumps. ENERGY STAR originally set specifications for central air conditioners and heat pumps in 1995, followed by revisions in 2002, 2006, and 2009. The current (2009) ENERGY STAR levels are shown in Table 3.2.5.

Table 3.2.5 ENERGY STAR Levels for Split Sy stem and Single Pa ckage Residential Central Air Conditioners and Heat Pumps 7

Product Class SEER Rating EER Rating* HSPF Rating Split system air conditioners 14.5 12.0

- Split system heat pumps 14.5 12.0 8.2 Single package air conditioners 14.0 11.0

- Single package heat pumps 14.0 11.0 8.0 *EER is energy efficiency ratio.

Consortium for Energy Efficiency

The CEE Residential Central Air Conditioner and Heat Pump Initiative promotes the use of high-efficiency residential central air c onditioners and heat pumps, along with proper installation and sizing of these products. CEE identifies three tiers of efficiency for split system central air conditioners, and two tiers of efficiency for split system heat pumps and single package central air conditioners and heat pumps. For split system central air conditioners and package central air conditioners and heat pumps, the CEE Tier 1 levels are the same as the ENERGY STAR levels. The CEE tier requirements are shown in Table 3.2.6.

i For more information, visit www.energystar.gov.

3-11Table 3.2.6 CEE Tiers for Residential Cent ral Air Conditioners and Heat Pumps 8

Product Class CEE Tier SEER Requirement EER Requirement HSPF Requirement Split System Central Air Conditioners Tier 1 14.5 12.0

- Tier 2 15.0 12.5

- Tier 3 16.0 or higher 13.0 or higher

- Single Package Central Air Conditioners Tier 1 14.0 11.0

- Tier 2 14.0 or higher 12.0 or higher

- Split System Heat Pumps Tier 1 14.5 12.0 8.5
Tier 2 15.0 or higher 12.5 or higher 8.5 or higher Single Package Heat Pumps Tier 1 14.0 11.0 8.0
Tier 2 14.0 or higher 12.0 or higher 8.0 or higher

3.2.4.2 Consumer Rebate Programs

DOE has identified numerous reba te programs that are available to purchasers of new residential central air conditioners or heat pumps. These rebates are offered by electric utility companies or other agencies to residential consumers who purchase higher-efficiency units.

Appendix 3-A provides a listing of rebates for residential centr al air conditioners and heat pumps identified by DOE.

3.2.4.3 Consumer Tax Credits

Federal Tax Credits

DOE reviewed the Federal tax credit that provides consumers a credit toward their Federal income tax if they purchase qualifying re sidential central air conditioners or heat pumps. These tax credits apply only to products being in stalled in existing homes; they do not apply to central air conditioners and heat pumps for new housing construction. This Federal tax credit is 30 percent of the installation cost (equipment and labor) to the consumer of the new air conditioner or heat pump, with a maximum limit of $1500. To qualify for the Federal tax credit, products must meet varying levels of efficiency depending on the product class. Table 3.2.7 shows the required efficiency level for each produ ct class, along with the amount of the Federal tax credit available.

Table 3.2.7 Federal Tax Credits for Residentia l Central Air Conditioners and Heat Pumps 9

Product EER Requirement SEER Requirement HSPF Requirement Available Tax Credit

Central Air Conditioners – Split Systems ≥ 13.0 ≥ 16.0 N/A 30% of cost, up to $1,500

Central Air Conditioners – Single Package ≥ 12.0 ≥ 14.0 N/A 30% of cost, up to $1,500

Air Source Heat Pumps – Split Systems ≥ 12.5 ≥ 15.0 ≥ 8.5 30% of cost, up to $1,500

Air Source Heat Pumps – Single Package ≥ 12.0 ≥ 14.0 ≥ 8.0 30% of cost, up to $1,500

3-12State Tax Credits

DOE also identified four states that have tax credits for central air conditioners and heat pumps: Montana, Oregon, Indiana, and Kentucky.

Montana has had an Energy Conservation Tax Credit for residential energy conservation

measures since 1998. 10

, 11 The tax credit covers a variety of residential energy and water efficiency installations, including ENERGY ST AR heating/cooling equipment. The amount of the credit increased in 2002 from 5 percent of e quipment costs (up to $150) to 25 percent (up to $500 per taxpayer). The Energy Conservation Tax Credit can be used for equipment installed in new construction or rem odeling projects, with the tax credit allowed only for the portion of the cost and materials above “establis hed standards of construction.”

Oregon’s Residential Energy Tax Credit (R ETC) was created in 1977 to encourage the use of renewable resources in households. The Oregon legislature expanded the RETC program in 1997 to include residential refrigerators, clothes washers, and dishwashers; participation in the program increased significantly after they beca me eligible. The prog ram subsequently added credits for high-efficiency heat pump systems, air conditioners, and water heaters (2001); furnaces and boilers, (2002),and other equipm ent and measures. For HVAC, residential appliances, and water heating, the credit is $0.40/ kWh saved in the first year, or 25% of net purchase price, whichever is less. The credit limit for energy efficient appliances and heating and cooling systems is $1,000 per calendar year; excess credit may be carried forward for five

12

, 13 years.

To qualify, a central air conditioning or h eat pump system must have a performance verification test by a tax credit-certified technicia n. For this verification test there is a separate tax credit of 25% of the cost of the test and an y needed repairs, up to $250. Purchasers of highefficiency central air conditioners or heat pumps who have pre mium efficiency ducts qualify for an additional $150 tax credit.

Central air conditioning split-system units mu st have EER of 13.0 or higher. The tax credit for qualifying central air conditioning systems is the amount listed in Table 3.2.8 or 25 percent of the net purchase price, whichever is less.

Table 3.2.8 Oregon Tax Credit for Central Air Conditioners
Tier Minimum Efficiency EER Maximum Tax Credit Amount

RAC4 13.0 $160

RAC5 14.0 $225

RAC6 15.0 $300

Air-source heat pump split-system equipment must have HSPF of 9.0 or higher and EER of 12 or higher. Table 3.2.9 shows the heat pum p tax credit levels by system efficiencies.

3-13Table 3.2.9 Oregon Tax Credits for Heat Pumps

HSPF EER
12 12.5 13
9.0 $300 $320 $340

9.5 $300 $360 $380

10.0 $300 $360 $430

Indiana offers a tax credit beginning in 2009 to individuals and small businesses for the costs associated with purchasing ENERGY STAR -qualified central air conditioners,and other appliances. The credit may be claimed against the state income tax, insurance premium tax, or financial institutions tax. The amount of the ta x credit is set at 20% of the expenditures for qualified heating and cooling e quipment up to $100 per taxable year. The credit is for expenditures in 2009 and 2010 and there is no carryover. 14

, 15

Kentucky offers a 30% state income tax credit beginning in 2009 for taxpayers who install certain energy efficiency measures on their principal residence or residential rental property. These energy efficiency measures in clude “Qualified Energy Property Installation,” which includes heat pumps and central air conditi oners, among others. Eq uipment must meet the efficiency guidelines specified in the Federal tax credit for residential energy property (see Table 3.2.7). The total annual tax credit for this equipm ent may not exceed $250. These credits apply to equipment purchased in taxable years 2009-201 5 and may be carried forward for one year. 16

, 17

3.2.4.4 FEMP Procurement Guidelines

DOE reviewed the Federal Energy Management Program (FEMP) procurement guidelines for Federal governme nt equipment purchasing. Fe deral constructi on requirements include these guidelines for installing or replacing equipment. Table 3.2.10 shows the FEMP performance requirements for residential cent ral air conditioners and Table 3.2.11 shows the requirements for air source heat pumps. 18

, 19

Table 3.2.10 FEMP Performance Requirements fo r Residential Central Air Conditioners System Type SEER EER Split 14.5 or greater 12.0 or greater Packaged 14.0 or greater 11.0 or greater

Table 3.2.11 FEMP Performance Requirements for Air Source Heat Pumps System Type HSPF EER SEER Split 8.0 or greater 11.0 or greater 13.0 or greater Single Package 7.6 or greater 10.5 or greater 12.0 or greater

3-143.2.5 Industry Cost Structure

DOE developed an industry cost structure for residential central air conditioners and heat pumps from publicly available information from the Census Bureau’s ASM and the SEC 10-K reports filed by publicly owned manufacturers.

The Census Bureau collects industry-wide em ployment data based on NAICS codes. As stated previously, manufacturers of residentia l central air conditioners and heat pumps are grouped into the Air-Conditioning and Warm Air Heating Equipment and Commercial and Industrial Refrigeration Equipment Manufactur ing category, which is NAICS code 333415. Table 3.2.12 presents the commercial air cond itioning and warm air heating equipment manufacturing employment levels and earnings from 1997 to 2005 according to the NAICS.

Table 3.2.12 Air Conditioning and Warm Air Heating Equipment Industry Employment and Payroll Data 20,21

Year Production Workers All Employees Payroll for All Employees ($1000)

2006 74,909 98,097 4,019,813

2005 76,011 102,354 3,942,808

2004 73,106 99,035 3,691,029

2003 77,488 104,668 3,776,417

2002 80,417 108,274 3,815,747

2001 88,978 118,876 3,950,483

2000 97,978 127,384 4,267,872

1999 95,904 123,962 4,043,064

1998 91,994 120,011 3,844,667

1997 90,968 119,386 3,678,996

The statistics illustrate a steady decline in both the number of production and nonproduction workers in the industry after the year 2000, with the only exception being in 2005, when the number of employees increased. The overall decline in employment may be a result of industry consolidation, increased automation in production, or manufacturers moving their facilities outside of the United States to reduce labor costs. The increase in employment in 2005 may have resulted from manufactur ers of residential central ai r conditioners in heat pumps augmenting the number of production workers to d eal with the increased demand for central air conditioners and heat pumps that occurred prior to the most recent Federal standards becoming effective in 2006 (as shown by the sharp increase in residential central air conditioner and heat pump shipments in 2005).

Table 3.2.13 presents the costs of materials and industry payroll as a percentage of value of shipments from 1997 to 2006.

3-15Table 3.2.13 Air Conditioning and Warm Air Heating Equipment Industry Cost Data 10,11

Year Cost of Materials as a percent of value of shipments (percent) Cost of Payroll for production workers as a percent of value of shipments (percent) Cost of Total Payroll (production + admin.)

as a percent of value of

shipments (percent)

2006 53.2 8.9 13.8

2005 53.8 8.5 13.8

2004 51.1 8.8 14.2

2003 50.6 9.5 15.4

2002 49.4 9.8 15.9

2001 52.6 9.8 15.8

2000 53.0 10.1 16.0

1999 53.4 9.8 15.4

1998 54.9 9.9 15.4

1997 54.2 10.1 16.0

The cost of materials as a percentage of valu e of shipments has fluctuated slightly over the 10-year period. Fluctuations in raw material costs are common from year to year. The cost of payroll for production workers as a percentage of value of shipments has followed a declining pattern since 1998, with the exception of only the year 2006, during which the cost of payroll increased from the previous year. Finally, the cost of total payroll as a percentage of value of shipments has generally declined since 2000, illu strating a reduction in industry non-production or administrative employees, possibly the product of selling, general, and administrative (SG&A) cost-cutting measures.

A detailed financial analysis of the manufacturers of each of the product types covered by this rulemaking is presented in the manufacturer impact analysis (MIA) (Chapter 12 of this TSD). This analysis identifies key financial i nputs including cost of capital, working capital, depreciation, capital expenditures, etc.

3.2.6 Equipment Lifetime

The lifetime of residential central air conditioners and heat pumps can vary greatly depending on how often the system is used (whi ch is dependent upon the climate of the region where the product is installed and the personal pr eferences of the consumer) and how regularly it is maintained and serviced. DOE reviewed available literature to determine the appropriate lifetime for residential central air conditioners and air-sour ce heat pumps. Generally, most sources estimate the lifetime of re sidential central air conditioners and heat pumps to be in the range of 10 to 20 years. Appliance Magazine pub lishes an Annual Portrait of the U.S. Appliance Industry, in which it estimates low, high, and av erage lifetimes for a range of home appliances, including unitary air conditioners and heat pum ps, based on input from appliance experts and many additional sources. Appliance Magazine estimates the average lifetime of a residential central air conditioner as 11 years and the average lifetime of a residential air-source heat pump as 12 years. AHRI estimates the average lifetime of a central air conditioner as 12 to 15 years, and the average lifetime of a heat pump as 14 years. 22 DOE used national survey data, along with manufacturer shipment data, to calculate the distribution of air conditioner and heat pump lifetimes. The mean central ai r conditioner and heat pump lifetimes from the distributions were

3-16determined to be 19.0 and 16.2 years, respectiv ely. Additional information about equipment lifetimes is contained in the Life-Cycle Cost and Payback Period Analysis chapter (Chapter 8) of this TSD.

3.2.7 Market Performance Data

DOE examined the AHRI Directory of Cer tified Product Performance for residential central air conditioners and heat pumps to determine the characteri stics of residential central air conditioners and heat pumps currently available on the market. By defin ition, residential central air conditioners and heat pumps are products w ith a cooling capacity below 65,000 Btu/h and are air-cooled, and therefore DOE did not examine any products that did not meet these criteria. In addition, DOE excluded from its analysis any pro ducts that were manufactured for Canada or export only, and any products in the AHRI Direct ory of Certified Product Performance that were not labeled as “active,” meaning that they are currently being manufactured. Table 3.2.14 shows the number of the models in the AHRI Directory of Certified Product Performance for each equipment class. As the table shows, the large ma jority of residential ce ntral air conditioners and heat pumps are split system products, and th ere are relatively few space constrained ( i.e. through-the-wall) models.

Table 3.2.14 Types of Models Listed in the AHRI Directory of Certified Product Performance
Product Class Number of Models Listed in the AHRI Directory of Certified Product Performance Split system air conditioners 281,184 Split system heat pumps 153,397 Single package air conditioners 8,479 Single package heat pumps 2,876 Small duct, high velocity system 4,468 Space constrained – air conditioners 12* Space constrained – heat pumps 12* *Currently there are no space constrained air conditioners or space constrained heat pumps in the AHRI Directory of Certified Performance. However, the AHRI Directory of Certified Performance does list through-the-wall products that will be classified as space constrained products prior to the effective date of this rulemaking.

DOE examined the efficiency of residentia l central air conditioners and heat pumps currently available on the market in AHRI’s Certified Product Performance Directory. DOE divided the products into bins based on their effi ciency and counted the number of models in each efficiency bin. The efficiency ratings were se parated into efficiency bins of one SEER each, and the SEER ratings are calculated to two d ecimal points. Figure 3.2.2 through Figure 3.2.6 show histograms of the efficiency data for split system and single package central air conditioners and heat pumps, as well as for SDHV systems.

3-17Figure 3.2.2 SEER Ratings for Single Package Central Air Conditi oners in the AHRI Certified Product Performance Directory

Figure 3.2.3 SEER Ratings for Single Package He at Pumps in the AHRI Certified Product Performance Directory

3-18Figure 3.2.4 SEER Ratings for Split System Central Air Condition ers in the AHRI Certified Product Performance Directory

Figure 3.2.5 SEER Ratings for Split System Heat Pumps in the AHRI Directory of Certified Product Performance

3-19Figure 3.2.6 SEER Ratings for SDHV Systems in the AHRI Directory of Certified Product Performance

Figure 3.2.2 through Figure 3.2.6 show that the SEER Ratings for split system and single package air conditioners and heat pumps are mostly concentrated in the 13 to 14.99 SEER range, although split systems cover a much higher range of efficiencies. The ma jority of SDHV systems are concentrated in the 11 to 12.99 SEER rang e. The through-the-wall products in the AHRI Directory of Certified Product Pe rformance all had a SEER rating of either 10.9 (9 central air conditioners and 8 heat pumps were rated 10.9 SEER) or 11.0 (3 central air conditioners and 4 heat pumps were rated 11.0 SEER).

DOE also examined the HSPF ratings of the heat pumps in AHRI’s Directory of Certified Product Performance. Figure 3.2.7 through Figure 3.2.9 shows the number of single package, split system, and SDHV heat pumps models in the directory that fall into the specified HSPF bins.

3-20Figure 3.2.7 HSPF Ratings for Single Package Heat Pumps in AHRI’s Directory of Certified Product Performance

Figure 3.2.8 HSPF Ratings for Split System Heat Pumps in AHRI’s Directory of Certified Product Performance

3-21Figure 3.2.9 HSPF Ratings for SDHV Heat Pumps in AHRI’s Directory of Certified Product Performance

For single package heat pumps, the HSPF ratings are concentrated in the 7.5 to 8.49 range. Split system heat pumps cover a greater range of HSPF ratings, and are concentrated in the 7.5 to 8.99 range. For SDHV heat pumps, a signi ficant number of models fall into the range between 6.5 and 8.49. All 12 Through-the-wall heat pump models listed in AHRI’s directory had an HSPF rating of 7.1.

In reviewing the efficiency of residentia l central air conditioners and heat pumps currently available on the market, DOE also examined the relationship between efficiency and equipment capacity. Figure 3.2.10 through Figure 3.2.14 show the average SEER ratings at each equipment capacity available for single packag e and split system air conditioners and heat pumps, as well as for SDHV systems in AHRI’s Directory of Certified Product Performance.

3-22Figure 3.2.10 Average SEER Ratings at Each Cooling Capacity for Single Package Air Conditioners in AHRI’s Directory of Certified Product Performance

Figure 3.2.11 Average SEER Ratings at Each Cooling Capacity for Split System Air Conditioners in AHRI’s Directory of Certified Product Performance

3-23Figure 3.2.12 Average SEER Rating at Each C ooling Capacity for Single Package Heat Pumps in the AHRI Directory of Certified Product Performance

Figure 3.2.13 Average SEER Rating at Each C ooling Capacity for Split System Heat Pumps in the AHRI Directory of Certified Product Performance

3-24Figure 3.2.14 Average SEER Rating at Each C ooling Capacity for SDHV Systems in the AHRI Directory of Certified Product Performance

The average SEER ratings for single pack age air conditioners and heat pumps are concentrated generally in the 13 to 15 SEER range for the entire range of cooling capacities. Split system air conditioners and heat pumps displa y a greater range of average SEER ratings at lower cooling capacities, and then appear to be come concentrated between 13 and 15 SEER at the higher cooling capacities. Split system air conditioners and heat pumps appear to have “sweet spots” near the two and three ton cooling capacities (i.e. 24,000 and 36,000 Btu/h cooling capacities) where a greater range of average efficiencies occurs, and where the highest average SEER ratings occur. SDHV systems appear to have an average SEER value in the range of 11 to 13 SEER for the entire range of cooling capacities.

DOE also examined the average HSPF ratings at each equipment capacity for heat pumps listed in AHRI’s Directory of Certified Pr oduct Performance. Figure 3.2.15 through Figure 3.2.17 show the average HSPF at each available ca pacity rating in AHRI’s directory for single package, split system, and SDHV heat pumps.

3-25Figure 3.2.15 Average HSPF at Each Cooling Capa city for Single Package Heat Pumps in the AHRI Directory of Certified Product Performance

Figure 3.2.16 Average HSPF Rating at Each C ooling Capacity for Split System Heat Pumps in the AHRI Directory of Certified Product Performance

3-26Figure 3.2.17 Average HSPF Rating at Each C ooling Capacity for SDHV Heat Pumps in the AHRI Directory of Certified Product Performance

The HSPF ratings for single package heat pumps are consistently between 7.7 and 8.2 HSPF for the entire range of cooling capacities. Split system heat pumps appear to have a greater range of average HSPF ratings at lower cooling capacities, and a smaller range of average HSPF ratings at higher cooling capacities. The averag e HSPF ratings peak near 3 tons (36,000 Btu/h) and 5 tons (60,000 Btu/h). The average HSPF ratings of SDHV heat pumps are between 6.8 and 8 for the entire range of capacities.

3.2.8 Historical Shipments and Efficiencies

3.2.8.1 Historical Shipments

The Air-Conditioning, Heating, and Refrigeration Institute (AHRI) provided historical shipments data over the 1990- 2007 time-period disaggregated in to the four primary product classes. 23 Historical shipments from 1972-1989 were also provided by AHRI from previous data submittals to the Lawrence Berkeley National Laboratory (LBNL). 24 The data for 1972­ 1989 included some shipments of 3- phase as well as single-phase central air conditioners and heat pumps, whereas the data for 1990-2007 included only single-phase central air conditioners. DOE disaggregated the shipments for single-phase and 3-phase central ai r conditioner and heat pump equipment in the earlier data and incl uded only single phase units. Table 3.2.14 summarizes the historical shipments data.

3-27Table 3.2.15 Central Air Conditioner and Heat Pump Shipments

Year Split CAC
thousands Single Package CAC
thousands Split HP
thousands Single Package HP
thousands
1972 1,489 257 28 52
1973 1,742 318 35 52
1974 1,503 289 49 48
1975 888 159 83 45
1976 1,219 231 177 74
1977 1,364 218 329 89
1978 1,546 253 389 97 1979 1,428 248 376 107
1980 1,233 134 293 61 1981 1,293 122 348 66 1982 1,037 111 267 49 1983 1,558 192 455 82
1984 1,857 189 535 98
1985 1,784 203 619 107 1986 1,876 203 680 106
1987 2,204 237 714 103 1988 2,334 247 649 91
1989 2,516 267 650 91 1990 2,241 334 643 104
1991 2,388 306 615 96
1992 2,254 330 647 101 1993 2,474 346 718 107
1994 3,087 387 825 118 1995 3,221 384 834 120
1996 3,635 418 936 139 1997 3,364 395 917 142
1998 4,010 406 1,019 148
1999 4,317 429 1,044 147
2000 4,280 437 1,073 159
2001 3,931 361 1,180 165
2002 4,381 380 1,229 165
2003 4,281 390 1,350 174
2004 4,561 414 1,584 190
2005 5,461 455 1,810 213
2006 4,038 330 1,807 190
2007 3,582 338 1,570 199
Source: Air-Conditioning, Heating, and Refrigeration Institute (AHRI)

3.2.8.2 Historical Efficiencies

AHRI provided historical shipment-weighted efficiency data (SWEF) data spanning the years 1992 to 2008. 28 Between 1992, the year in which the first set of standards for central air conditioners and heat pumps became effective, and 2006, when an updated set of standards became effective, the SWEFs fo r central air conditioners grew by approximately one SEER point. Figure 3.2.18 shows the SWEFs for split system and single package central air

3-28conditioners. The figure also presents the linear fit to each product class’ SWEF data series. The linear fits have high coefficients of deter mination, i.e., linear fits provide a good estimate of the SWEF growth rate. Table 3.2.15 provides a summary of the SWEF growth rates for each product class.

Split A/C SEER = 0.0703 * year - 129.65
R2 = 0.9633

Package A/C
SEER = 0.0 778 * year - 144.78
R2 = 0.9455

10.0 10.2 10.4 10.6 10.8 11.0 11.2 11.4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

YearShipment-Weighted SEER Split A/C Package A/C Linear (Split A/C) Linear (Package A/C)

Source: Air-Conditioning, Heating, and Refrigeration Institute (AHRI) Figure 3.2.18 Central Air Conditi oner Historical Shipment-Weigh ted Efficiencies with Linear Fits

Table 3.2.16 Central Air Conditioner Shipmen t-Weighted Efficiency Growth Rates

SWEF Growth Rate

Product Class SEER increase per year Split System Air Conditioners 0.0703 Single Package Air Conditioners 0.0778

For heat pumps, between 1992 and 2006, the S EER-based also grew by approximately one SEER point. Figure 3.2.19 shows the SEER -based SWEFs for split system and single package heat pumps. The figure also presents the linear fit to each product class’ SWEF data series. The linear fits have high coefficients of determination, i.e., lin ear fits provide a good estimate of the SWEF growth rate. Table 3.2.16 provides a summary of the SEER-based SWEF growth rates for each product class. AHRI did not provide historical SWEF data for heat pump HSPFs.

3-29Split HP SEER = 0.0739 * year - 136.55
R2 = 0.9594

Package HP SEER = 0.0736 * year - 136.03
R2 = 0.8886

10.2 10.4 10.6 10.8 11.0 11.2 11.4 11.6 11.8

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

YearShipment-Weighted SEER Split HP Package HP Linear (Split HP) Linear (Package HP)

Source: Air-Conditioning, Heating, and Refrigeration Institute (AHRI) Figure 3.2.19 Heat Pump Historical Shipment-Weig hted Efficiencies ba se on SEER with Linear Fits

Table 3.2.17 Heat Pump Shipment-Weigh ted Efficiency Growth Rates

SWEF Growth Rate

Product Class SEER increase per year Split System Heat Pumps 0.0739 Single Package Heat Pumps 0.0736

3.2.9 Saturations in U.S. Households

Saturation refers to the percentage of the housing stock with a given product. The American Housing Survey (AHS) provides historical stoc k saturations for central air conditioning and heat pump equipment for every other year between 1991

− 2007. 25 Table 3.2.17 summarizes the saturations for central air conditioners, heat pump, and both types of equipment. Central air conditioerns and heat pump satura tion has grown from 38.6 percent to 64.6 percent from 1991 to 2007.

3-30Table 3.2.18 Central Air Conditioner Heat Pump Historical Housing Stock Saturations

Year CAC HP Total
1991 30.8% 7.8% 38.6%
1993 32.0% 8.5% 40.5%
1995 33.9% 9.1% 43.0%
1997 36.3% 12.0% 48.3%
1999 41.4% 11.4% 52.8%
2001 45.0% 11.3% 56.3%
2003 46.5% 11.7% 58.2%
2005 50.2% 12.7% 62.9%
2007 51.8% 12.8% 64.6%

3.3 TECHNOLOGY ASSESSMENT

The purpose of the technology assessment is to develop a preliminary list of technologies that could potentially be used to improve the ef ficiency of central air conditioners and heat pumps. The following assessment provides descripti ons of technologies and designs that apply to subsystems within all product classes of centr al air conditioners and heat pumps, as well as innovations that apply to heat pumps only.

3.3.1 Compressor Improvements

Several technologies exist to increase the effici ency of the compressors used in central air conditioner and heat pump systems. High effi ciency reciprocating and scroll compressors, sometimes incorporating variable-speed motors, all have higher efficiencies than the traditional reciprocating compressors commonly used in air conditioners.

Scroll compressors compress gas in a fundamentally different manner from traditional compressors—between two spirals, one fixed and one rotating. High efficiency reciprocating compressors are as efficient, or more effici ent, than scroll compressors. However, these compressors are often considered to present some drawbacks exist including noise, cost and reliability, compared to scroll compressors.

Variable-speed compressors are implemented through the use of an electronic control on the compressor motor, which allows the motor to operate at different speeds. Variable-speed compressors reduce energy consumption in three ways (but it should be noted that it typically increases efficiency over a broad operating ra nge but does not inherently increase maximum efficiency at the comp ressor rating point):

1. When refrigerant flow is reduced duri ng part-load operation, the condenser and evaporator (designed for full flow conditions) ar e more effective and thus more efficient. Temperature drops decrease, resulting in reduced pressure rise across the compressor, which also improves efficiency. 2. Close matching of load eliminates the cycling that occurs with single-stage compressors. Maintaining a constant pressure is more effi cient because losses at higher pressure rise are greater than gains at lower pressure rise.

3-313. During the off-cycle, the pressure in the system equilibrates. At the intermediate pressure, refrigerant vapor will condense in the cold evaporator rather than the condenser. Essentially, some of the heat rejection load is rejected to the evaporator during this time, reducing overall system performance. Variable speed operation would eliminate or significantly reduce compressor off-time and the related inefficiencies.

3.3.2 Fan System Improvements

3.3.2.1 Higher Efficiency Fan Motors

Fan motors are fractional horsepower in size , are responsible for moving air across the indoor and outdoor coils, and typically run at one speed. The manufacturer will match the motor size and blade to the coil to meet the expect ed cooling load under most conditions. Higher efficiency fan motors reduce energy consumption by requiring less electrical power to generate motor shaft output power.

Electric motors operate based on the interaction between a field magnet and a magnetic rotor. In a brushed motor, the field magnets are permanent magnets and the rotor is an electromagnet; the situation is reversed in a brushless motor. The electromagnetic interactions between these two magnets cause the rotor to rotate.

Nearly all fan motors for standard central air conditioners and heat pumps are of the permanent split capacitor (PSC) variety. In PSC motors, the electromagnet consists of windings of electrical wire through which current is driv en. A smaller, start-up winding is present in addition to the main winding. The start-up winding is electrically connected in parallel with the main winding and in series with a capacitor. At start up, the interactions between the magnetic field generated by the start up winding and that generated by the main winding induce rotation. Because of the capacitor, however, the current to the start-up winding is cut off as the motor reaches steady state. This makes PSC motors more energy efficient, with motor efficiencies ranging from 50 to 70 percent. PSC motors are produced in large quantities and are relatively inexpensive.

Another type of electric moto r, the brushless direct curr ent (DC) (i.e., electronicallycommutated motor (ECM), is more energy-efficient than PSC motors of comparable size and capacity. Brushless DC motors, which are sold in high volumes, are three-phase electric motors with efficiencies ranging from 70 to 80 percent. However, brushless DC motors can weigh twice as much as equivalent PSC motors. In addition, brushless DC motors are complex, and can cost from two and a half to five times as much as a PSC motor.

A way to further improve the efficiency of motors used for central air conditioner and heat pump applications is to make the critical components of an induction motor's rotor (e.g., conductor bars and end rings) out of copper instead of aluminum. Due to difficulties with casting copper, making these components out of alumi num is the common current practice. However, the greater conductivity of copper results in lower resistance heating losses in the rotor, and thus lower losses in the motor when compared to traditional aluminum motor parts. Recently, the creation of copper dies made fro m special alloys has allowed for the advancement of copper

3-32casting techniques. Additional imp rovements in the design and fabrication of copper motors, such as optimization of the steel laminations, c ould further increase the efficiency of copper motors over aluminum motors.

3.3.2.2 Fan Motor Controllers

Fan motor controllers allow fan motors to run at variable speed to match changing load conditions. During periods of frost build-up in heat pumps, fan motor power requirements increase; during the post-defrost period, power requ irements decrease. Matching the fan speed to all conditions ensures more stab le discharge air temperatures and improves coil performance. Fan motor controllers would also allow both centr al air conditioners and heat pumps run more efficiently at varying ambient humidity and temperature levels. Because of practical limitations on efficiency, variable speed systems dominate the market over 14 SEER, and it is unusual to find a system over 13 SEER that does not inco rporate a variable speed indoor blower.

3.3.2.3 Higher Efficiency Fan Blades

High efficiency fan blades move air more efficiently, yielding energy consumption savings by reducing the required fan shaft power . The fans typically used in central air conditioners and heat pumps have stamped, curved sheet metal blades. The blades are typically supplied by a fan blade manufacturer and mounted to the motor by the manufacturer, and may not be optimized for the particular central air co nditioner or heat pump that they are installed on. Fans may have lower efficiencies due to the higher required pressure drops, for which sheet metal fans are not well suited. Requi red fan shaft power could be reduced if the fan blades were optimized for each given application.

3.3.3 Expansion Valve Improvements

Expansion valves are refrigerant metering de vices whose purpose is to control the amount of refrigerant flowing to the evaporator coil. In doing so, they simultaneously decrease the temperature and pressure of the refrigerant, creating a cold liquid-vapor mixture. The low temperature of the refrigerant leaving the expansion valve creates the driving force to move heat out of the refrigerated space and into the evaporator.

The most basic type of expansion device is a capillary tube, which may be found in older, less efficient air conditioners and heat pumps. The capillary tube is a long, thin piece of pipe that creates a pressure drop in the refrigerant through frictional losses. Capillary tubes must be sized to the particular application and cannot adjust for variations in load or ambient operating conditions. They are often oversized for worst- case conditions, and therefore may operate at reduced efficiency during normal operation.

The thermostatic expansion valve (TXV) is common in air conditioners and heat pumps rated at an efficiency level of 13 SEER or above. This device uses an orifice to reduce the pressure of the entering refrigerant and a sens ing bulb to monitor and maintain the temperature of the superheated vapor leaving the evaporator. Because the TXV allows for some degree of adjustment of refrigerant expansion, it may be so mewhat more efficient than the capillary tube device under varying conditions.

3-33The electronic expansion valve (EEV) is similar to the TXV, but uses an electronic control system to optimize refrigeration-syst em performance under all operating conditions. Because it does this with greater flexibility than that allowed by a TXV, an EEV theoretically allows for further increases in energy efficiency under varying conditions.

3.3.4 Heat Exchanger Technologies and Improvements

3.3.4.1 Baseline Technology

Most central air conditioners and heat pumps currently on the market utilize traditional tube-and-fin heat exchangers for both the evaporator and condenser coils. These coils are refrigerant-to-air heat exchangers composed of metals with hi gh thermal conductivity, usually aluminum and copper, with the tubes generally being composed of copper and the fins of aluminum.

The evaporator coil is responsible for evaporating and superheating the entering refrigerant liquid-vapor mixture while extracting heat from the air in the conditioned space. The internal heat-exchanging surfaces in contact with refrigerant are commonly referred to as “refrigerant-side” while the external heat-exchanging surfaces in contact with the air are referred to as “air-side.” Because a temperature difference is necessary to drive heat from the air into the refrigerant, the saturated evaporator temperature must be considerably colder than the evaporator’s discharge air temperature. The magnitude of this driving force is directly related to the total cooling load and the thermal characteristics of the evaporator. Increasing the area of the coil decreases the necessary temperature difference and therefore decreases the required saturated evaporator temperature. This results in an increased compressor energy efficiency ratio (EER) and lower compressor energy consumption.

The condenser coil is responsib le for condensing and sub-cooling the entering refrigerant vapor while rejecting heat from the refrigerant to the ambient air. As with evaporator coils, increasing the area of the condenser coil will decrease the necessary change in temperature across the coil, resulting in increased compressor efficiency (increased EER).

The majority of evaporator and condenser coils used in central air cond itioners and heat pumps currently on the market are of the traditiona l tube-and-fin heat exchanger design. Many manufacturers utilize a similar process in buildin g coils, and this methodology has remained fundamentally the same over the long period during which these products have been in use. The actual techniques utilized in this process vary by company, a nd proprietary methods are often utilized by specific manufacturer s in the production of coils. Manuf acturing of coils in-house is a process which requires high capital investments in machinery and line setup. As a result, manufacturers have been hesitant to move aw ay from the traditional method of coil production, as doing so would require large new investments. Instead, companies have historically focused on improving the performance of their existing coil designs.

3.3.4.2 Improvements to Baseline Coils

Increasing the overall size of the coil in one or more dimensions tends to be the most cost-effective way to increase the system efficiency. However, many applications limit the amount of coil size increase in or der to maintain overall cabinet dimensions. Most approaches to

3-34increasing the coil surface area also result in an increase in required fan motor power and an increase in refrigerant pressure drop. Enhancements to the refrigerant-side surface area of both evaporator and condenser coils typically include rifled or diamond-pattern tubing and increased number of tube passes. Enhancements to the ai r side surface area include increased fin pitch (decreased fin spacing), fin patterns (wavy or zi g-zag), and increased numbers of tube passes. The size constraints facing manufacturers who have already maximized the size of their units make it necessary for these companies to cons ider alternative methods to improving heat exchanger performance.

3.3.4.3 Alternative Coil Technologies

3.3.4.4.1. Liquid Suction Heat Exchangers

The goal of a liquid suction heat exchanger is to further cool the flow of liquid refrigerant entering the expansion valve using the flow of gaseous refrigerant leaving the evaporator, thus providing sub-cooling for the entering liquid by super-heating the exiting suction vapor. Hotter suction vapor is less susceptible to heat gains in the return piping to the compressor rack. The compressor work is increased, however, because the suction vapor has greater enthalpy. In addition, the possibility of compressor overheating problems, brought on by the combination of increased compressor work and hotter vapor, limits the use of this method in some situations. The possibility for these problems and the potential gains of liquid suction heat exchangers depend on the several factors, including evaporator temperature, type of refrigerant used, and system pressures.

3.3.4.4.2 Microchannel Heat Exchangers

Several companies produce microchannel heat ex changers, which are mainly used in the automobile industry. Unlike a conventional round-tube plate-fin heat exchanger, the microchannel has a rectangular cross-section cont aining several small channels through which refrigerant passes. Fins pass between the tubes an d are brazed to the tubes, and all components are aluminum. The resulting microchannel coil transfers more heat per unit of face area than does a round-tube plate-fin coil of co mparable capacity. It does so with a lower airside pressure drop, yielding reduced fan power consumption. These benefits can improve system EER and SEER ratings in residential air conditioners when comp ared to a condenser coil of the same face area. This would allow manufacturers to improve the rated SEER without fu rther increasing the size of the units. Because the microchannel fin arrangem ent prevents natural condensate drainage, their use in heat pump and evaporator coil applications is not forthcoming.

Although the microchannel heat exchanger co sts more to produce than a conventional round-tube plate-fin coil, this product offers particular opportunities to reduce the size and weight of the heat exchanger. Those advantages le d to the rapid and almost total transition of the automobile air conditioner market to microchan nel technology. Microchannel heat exchangers also offer significant reductions in refrigerant charge, which suggests that they may reduce the rate of compressor failures caused by refrigerant slugging.

Even after several years of dominance in the automobile market, the microchannel heat exchanger has not penetrated the building air conditioning markets where size and weight

3-35constraints are not as important. The cost advantages of reduci ng the size and weight of the condenser or the capacity of the system have not sufficiently outweighed the added costs and risk associated with the microchannel technology for these systems to attain widespread use in building applications to date. A dditionally, given the fact that most manufacturers produce coils in-house, and that setting up a coil production line is an extremely capital-intensive process, manufacturers are generally hesitant to make the large investments needed to move away from the production of traditional tube -and-fin heat exchangers. Mo reover, several limitations and uncertainties are particularly hindering the large-scale adoption of microchannel heat exchangers. First, microchannel construction makes condensate re moval much more challenging than traditional tube-and-fin heat exchangers. This poses a serious barrier to the adoption of the technology in evaporators and in heat pump condensers. Some manufacturers may decide not to adopt the new technology if they cannot offer it in all of their products, including both air conditioners and heat pumps. Second, there are con cerns whether residential heat exchangers are proven to perform well under wide variations in ambient temperatures given that they are considerably larger than automobile heat ex changers and are configured differently. Third, compressor lubrication is entrained in the re frigerant, and residen tial microchannel heat exchangers must display a proven ability to consistently return lubricant to the compressor to avoid costly damage. Fourth, manufacturers are concerned that contractors will not be able to repair coil leaks effectively because of the difficulty of successfully brazing aluminum in the field.

3.3.4.4.3 Flat-Tube Heat Exchangers

Flat-tube, louver-fin heat exchangers offer various advantages over traditional roundtube, plain-fin heat ex changers. The flat-tube design reduces wake region, which decreases heat transfer downstream of round tubes. The design improves fin efficiency, and creates a lower profile drag as a result of the smaller tube projected area. Serpentine louvered-fin, flat-tube heat exchangers have already been utilized in automotive applications because of their ability to produce the same amount of heat transfer with much more compact designs than the plain-fin, round-tube variety heat exchangers. In laborator y tests, the louver-fin, fl at-tube heat exchanger was found to produce heat transfer coefficients th at were 90% higher than those produced by a plain-fin, round-tube heat exchanger. The significan t increase in heat transfer coefficient resulted in a size reduction factor of two to three for a residential absorption heat pump system. The more efficient flat-tube heat ex changers would be able to provide th e same amount of heat transfer and reduce the amount of airflow needed from the fa ns, thus reducing the amount of electricity consumed by the fan motors and increasing system efficiency.

Like the microchannel technology, the flat-t ube heat exchangers still have not broken through into the air conditioner and heat pump market, where the size of the unit is not as much of a concern. The extra cost of developing th ese systems and investing the large amounts of capital needed to produce them in-house has not ye t been offset by the potential advantages to using flat-tube heat exchangers. Also, condensate removal is a concern in louvered-fin, flat-tube heat exchangers because of water “bridges” that get into the louve r gaps and reduce heat transfer.

3-363.3.5 Designs Relevant Only to Heat Pumps

The following technologies, defrost mechan ism and defrost cycle control, are two examples of defrost-related improvements applic able to heat pump designs, and it should be noted that they are not intended to comprise an exhaustive list of viable technologies.

3.3.5.1 Defrost Mechanism

As the outside air passes over the outdoor coil of a heat pump operating in heating mode, its heat is absorbed by the refrigerant inside the coil, which lowers the temperature of the ambient air. When the temperature of the surrounding air is reduced to less than 32°F, the moisture in the air will condense and freeze on th e outdoor coil, forming a layer of frost. The frost reduces performance by increasing the thermal resistance to heat transfer from the coil to the air, and by obstructing airflow. Both the met hod in which defrost is pe rformed and control of the defrost cycle can lead to increased energy savings.

The standard method of defrosting the outdoor coil during the heating operation of a heat pump is to temporarily reverse the flow of the refrigerant. This will use some of the heat from air inside to heat the outdoor coil and melt the frost. At the same time the i ndoor coil is cooled, and it becomes necessary to heat the house using an auxiliary heating system (typically electric resistant heaters).

“Frost-less” heat pump defro st technology slows frost accumulation on the outdoor coil while also increasing the heating capacity by adding an accumulator to the heat pump cycle. The accumulator traps heat from the condensed liquid from the condenser, and this causes an increase the suction pressure of the compressor. This addition of heat to the accumulator increases the outdoor coil temperature by several degrees and th us reduces the frost accumulation on the coil. Also, much of the heat added to the accumulator is still brought inside by increased heat pump supply air temperature since the suction pressure of the compressor was increased. The frostless heat pump still may accumulate frost, however, if the heat pump is operated for a long period of time at low ambient temperatures, creating the need for a cycle reversal for defrosting. During the reverse cycle, the indoor blower is shut off and the refrigerant flows to the accumulator, making the accumulator take over the function of the evaporator. This allows for reverse cycle defrosting while also preventing cool air from being blown inside, and reduces the need for resistance heaters. When the surrounding te mperature drops below 32°F, increasing the temperature of the outdoor coil a few degrees will not prevent frost accumulation, and heat input to the accumulator becomes useless. Therefor e, the accumulator should only be used at temperatures between 32°F and 41°F, when frost is most likely to collect on the coil and the use of the accumulator will be able to reduce the amount of frost.

Another mechanism for reducing the number and duration of defrost cycles is hot watersource defrosting. In heat pumps equipped with hot water defrost, a specifically designed system of valves and conduit allow the heat pump to sele ctively send the refrigerant to the various heat pump components, depending on which heat pump functions are being performed. These heat pumps use components and valves arranged in such a way that they are able to cool a space, heat a space, heat a liquid without affecting the temp erature of the conditioned space, cool a space while heating a liquid, and defrost the outdoor coil using only the previously heated water as a

3-37heat source. During the defrost mode, hot water that is held in a storage tank is used to defrost the outdoor coil, without degrading the overall pe rformance of the heat pump. A refrigerant-towater heat exchanger is used to provide energy to the refrigerant and allow it to melt the frost on the outdoor coil. This can be done without any degradation to heat pump performance, and the energy taken from the hot water in the system is easily and inexpensively replaced when the heat pump switches back into normal heating mode.

3.3.5.2 Defrost Cycle Control

During a conventional heat pump defrost cycl e some form of supplemental heating is needed to compensate for the reversal of the heat pump cycle. Usually electric resistance heaters are used to heat air inside the house while the de frost cycle occurs, and this type of heating is much less efficient than heating using the heat pump. Since the alternate heat sources are much less efficient, the efficiency of a heat pump can be increased by reducing the frequency and duration of the defrost cycles.

Defrost cycle control involves management of the initiation and termination of defrost cycles, and thereby the frequency and duration of defrost cycles. In conventional heat pumps defrost cycles are typically scheduled, and initiation and termination are timer-controlled. For this type of defrost cycle control, cycles are initiated at regular intervals, and terminated after a fixed amount of time. Cycle frequency and duration are unrelated to actual frost conditions, and are just based on estimations by the manufacturer. Under timer control, the frequency of defrost cycles is determined by the amount of time the manufacturer expects it to take for a large frost layer to develop in the worst-case scenario, a nd the cycle duration long enough to ensure complete defrost in the worst-case scenario. Timer-based defrost can lead to unnecessarily frequent and long defrost cycles.

Demand-based defrost cycles eliminate unnecessa ry defrost cycles. Demand-defrost heat pumps use sensors to measure outdoor coil and out door ambient conditions to determine when to initiate and terminate defrost cycles. A microprocessor examines and analyzes the compressor run time, ambient air temperature, and outdoor coil temperature, all of which determine the environment under which a defrost cycle should o ccur. The microprocessor is then able to determine when the defrost cycle should be initia ted and when it should be terminated, reducing the overall number and duration of cycles, and improving the efficiency of the heat pump.

3-38REFERENCES

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3-41CHAPTER 4. SCREENING ANALYSIS

TABLE OF CONTENTS

4.1 INTRODUCTION

........................................................................................................... 4-1 4.2 SCREENED-OUT TECHNOLOGIES

............................................................................ 4-2 4.2.1 High-Efficiency Expa nsion Valves

...................................................................... 4-2 4.2.2 Condenser Fan Motor Controllers

....................................................................... 4-2 4.2.3 Liquid-Suction Heat Exchangers

......................................................................... 4-2 4.2.4 Defrost Cycle Controls

........................................................................................ 4-3 4.2.5 Defrost Mechanisms

............................................................................................ 4-3 4.3 REMAINING TECHNOLOGIES

................................................................................... 4-3CHAPTER 4. SCREENING ANALYSIS

4.1 INTRODUCTION

This chapter addresses the screening analysis that the U.S. Department of Energy (DOE) conducted in support of the ongoing energy conservation standards rulemakings for residential central air cond itioners and heat pumps. This rulemaking is mandated by the National Appliance Energy Conservation Act of 1987 (NAECA), and is effective for products manufactured five years after the date of publication of a final rule establishing energy conservation standards.

In the market and technology assessment (c hapter 3), DOE presented an initial list of technologies that can reduce the energy consumption of central air conditioners and heat pumps. The goal of the screening analysis is to screen out technologies that will not be considered further in the rulemaking analys es. Some of the technologies considered in chapter 3 can reduce annual energy consum ption under real-world conditions, but may not increase the seasonal energy efficiency ratio (SEER) or heating seasonal performance factor (HSPF) as calculated using the DOE test procedure. DOE removed from consideration those technologies that do not increase SEER or HSPF. DOE evaluated the remaining technologies using the screening cr iteria set forth in the Energy Policy and Conservation Act (EPCA). (42 U.S.C. 6311–6317)

Section 325(o) EPCA esta blishes criteria for prescribing new or amended standards that are designed to achieve the maximum improvement in energy efficiency. Further, EPCA directs the Secretary of Energy to determine whether a standard is technologically feasible and economically justified. (42 U.S.C. 6295(o)(2)(A), as directed by 42 U.S.C. 6316(a)(1)–(3)) EPCA also establishes guidelines for determining whether a standard is economically justified. (42 U.S.C. 6295(o)(2)(B)) In view of the EPCA requirements for determining whether a standard is technologically feasible and economically justified, DOE applies the following set of screening criteria to determine which design options are unsuitable for further consideration in the rulemaking (Title 10 of the Code of Federal Regulations, Part 430, Subp art C, Appendix A at 4(a)(4) and 5(b)):

Technological feasibility. Technologies incorporated in products or in working prototypes will be considered technologically feasible.

Practicability to manufacture, install, and service. If mass production of a technology in products and relia ble installation and servicing of the technology could be achieved on the scale necessary to serve the relevant market at the time of the effective date of the standard, then that technology w ill be considered practicable to manufacture, install, and service.

Adverse impacts on product utility or pro duct availability. If DOE determines that a technology has significan t adverse impact on the utility of the product to significant subgroups of consumers, or result in the unavaila bility of any covered product type with performance characteristics (including reliability), features, sizes,

4-1capacities, and volumes that are substantially the same as products generally available in the United States at the time, it will not be considered further.

Adverse impacts on health or safety. If DOE determines that a technology will have significant adverse impacts on health or safety, it will not be considered further.

In sum, if DOE determines that a particular technology, or combination of technologies, fail to meet one or more of the four criteria, it will be screened out. Section 4.2 below documents the reasons for eliminating any technology.

4.2 SCREENED-OUT TECHNOLOGIES

As stated above, technologies that do not increase SEER or HSPF are not considered beneficial in the context of th is rulemaking. Therefore, DOE removed the following technologies from consideration: higher efficiency expansion valves, condenser fan motor controllers , liquid-suction heat exchange rs (LSHXs), defrost cycle controls, and defrost mechanisms.

4.2.1 High-Efficiency Expansion Valves

In actual operating conditions, high-efficiency expansion va lves such as electronic expansion valves (EEVs) can reduce the a nnual energy consumption of central air conditioners and heat pumps by adapting to varying loads and ambient conditions. However, because each test within the DOE test procedure is a steady-state test ( i.e., tests are conducted at a single, specified temp erature and relative humidity), there is no opportunity for high-efficiency expansion valves to reduce SEER or HSPF. Consequently, DOE did not consider high-efficiency expansion valves as a design option in the engineering analysis.

4.2.2 Condenser Fan Motor Controllers

Under actual operating conditions, condens er fan motor controllers can adapt condenser operation to changing ambient te mperatures and thereby reduce annual energy consumption of central air conditioners and heat pumps. However, because each test within the DOE test procedure is a steady-state test ( i.e., tests are conducted at a single, specified temperature and relative humidity), there is no opportunity to account for the effect of a condenser fan motor controller on SEER or HSPF. Consequently, DOE did not consider condenser fan motor controllers as a design option in the engineering analysis.

4.2.3 Liquid-Suction Heat Exchangers

An LSHX is a heat exchanger that serves to cool liquid refrigerant entering the expansion valve by utilizing some of the gaseous refrigerant from the evaporator coil. The purpose of this is to sub-cool the inco ming liquid through superheating of the suction vapor. In general, LSHXs are installed in re frigeration systems to ensure proper system operation and can potentially improve system performance under actual field operating

4-2conditions. However, the performance of an LSHX is dependent upon a number of factors, including refrigerant type, operatin g temperature, and ambient conditions, and thus DOE does not have enough information to suggest that an LSHX would consistently increase SEER or HSPF as rated using the DOE test procedure. Consequently, DOE did not consider LSHXs as a design option in the engineering analysis.

4.2.4 Defrost Cycle Controls

A defrost cycle control system is set up to adapt from previous defrost cycles to attain improved defrost system operation at various outdoor temperature conditions. This technology can save energy annually by usin g a computer to run the defroster at the optimum time and optimum temperature based on the ambient temperature range. However, this system adds efficiency because it helps account for outdoor temperature variation. The static nature of the DOE test procedure am bient conditions does not allow for increases in SEER or HSPF due to impleme ntation of such a system. As a result, DOE did not consider defrost cycle controls as a design option in the engineering analysis.

4.2.5 Defrost Mechanisms

Several mechanisms exist which may be used to aid in defrosting heat pump heat exchanger coils. One of these is the “frost-less” heat pump coil, which adds an accumulator to the heat pump cycle, trapping heat from the condenser liquid and using it to increase the temperature of the outdoor co il by several degrees. This reduces the buildup of frost on the coil, but is only effective within a small range of ambient temperatures at and above the freezing point of water. Additionally, such systems increase compressor work, and thus do not appear to have any positive benefit on rated SEER or HSPF values as measured using the DOE test procedure.

A second defrost mechanism which currently exists is hot-water defrosting. This system uses an additional circuit of valves and tubing which allows for some of the refrigerant to be used to heat water, which is then stored and used to defrost the coil by being sent through additional tubing around the coil. However, such a system would make no impact on the values of SEER or HSPF determined using the DOE test procedure. Consequently, DOE did not consider either of these defrost mechanisms as design options in the engineering analysis. DOE is not aware of any defrost mechanisms other than frost-less heat pum ps or hot-water defrost that are currently in use on the market or in development that could have a potential benefit to ra ted SEER or HSPF.

4.3 REMAINING TECHNOLOGIES

After eliminating those tec hnologies that do not increase SEER and do not meet the four screening criteria described in S ection 4.1, DOE is considering the following technologies:

• higher efficiency fan motors

• higher efficiency fan blades

4-3• improved evaporator coils

• improved condenser coils

• higher efficiency compressors

• microchannel heat exchangers

• flat-tube heat exchangers

4-4CHAPTER 5: ENGINEERING ANALYSIS

TABLE OF CONTENTS

5.1 INTRODUCTION

........................................................................................................... 5-1 5.2 METHODOLOGY OVERVIEW

.................................................................................... 5-1 5.3 PRODUCT CLASSES

..................................................................................................... 5-2 5.4 BASELINE UNITS

......................................................................................................... 5-2 5.5 TEARDOWN ANALYSIS

.............................................................................................. 5-3 5.5.1 Selection of Units

................................................................................................. 5-3 5.5.2 Generation of Bill of Materials

............................................................................ 5-5 5.6 COST MODEL

................................................................................................................ 5-6 5.6.1 Cost Model Overview

.......................................................................................... 5-7 5.6.2 Cost Model Assumptions

..................................................................................... 5-8 5.6.3 Manufacturer Selling Price Estimates

................................................................ 5-11 5.6.4 Downstream An alyses

....................................................................................... 5-12 5.7 NICHE PRODUCTS

..................................................................................................... 5-12 5.7.1 Small Duct High Velocity

.................................................................................. 5-12 5.7.2 Space-Constrained

............................................................................................. 5-15 5.7.3 Future Analyses

................................................................................................. 5-17 5.8 INDUSTRY COST-EFFICIENCY CURVES

............................................................... 5-18 5.8.1 Split-System Air Conditioners: Blower-Coil

..................................................... 5-18 5.8.2 Split-System Air Conditioners: Coil-Only

......................................................... 5-22 5.8.3 Split-System Heat Pumps

.................................................................................. 5-23 5.8.4 Single-Package Air Conditioners

....................................................................... 5-24 5.8.5 Single-Package Heat Pumps

.............................................................................. 5-25 5.9 MISCELLANEOUS SYSTEM CHARACTERISTICS

................................................ 5-25 5.9.1 Investigation of the Relationshi p Between SEER and HSPF

............................ 5-25 5.9.2 Calculation of System Weights

.......................................................................... 5-30 5.10 RESULTS

...................................................................................................................... 5- 32 5.11 REFERENCES

.............................................................................................................. 5-38LIST OF TABLES

Table 5.6.1: Summary of Ra w Material Prices

............................................................................ 5-9 Table 5.6.2: Purchased Central Air Conditioner and Heat Pump Components

........................... 5-9 Table 5.6.3: Factory Parameter Assumptions

............................................................................ 5-10 Table 5.9.1: Comparison of Proposed HSPF Sta ndard Levels with Available Products

.......... 5-28 Table 5.9.2: Prevalence of HSPF ratings by SEER level for 3-ton Split Heat Pumps with Impacts of Suggested HSPF Standards

.............................................................................. 5-29 Table 5.9.3: Calculated Typical Split-System Air Conditioner Unit Weights

.......................... 5-30 Table 5.9.4: Calculated Typical Split-System Heat Pump Unit Weights

.................................. 5-31 Table 5.9.5: Calculated Typical Packag ed Air Conditioner Unit Weights

................................ 5-31 Table 5.9.6: Calculated Typical Packaged Heat Pump Unit Weights

....................................... 5-32 Table 5.10.1: Cost-Efficiency Data for Split-Sy stem Air Conditioners: Blower-Coil

.............. 5-33 Table 5.10.2: Cost-Efficiency Data for Split- System Air Conditioners: Coil-Only

.................. 5-34 Table 5.10.3: Cost-Efficiency Data for Split-System Heat Pumps

............................................ 5-35 Table 5.10.4: Cost-Efficiency Data for Single-Package Air Conditioners

................................ 5-36 Table 5.10.5: Cost-Efficiency Data for Single-Package Heat Pumps

....................................... 5-37

LIST OF FIGURES

Figure 5.2.1: Engineering Analysis Methodology

....................................................................... 5-2 Figure 5.5.1: Nominal Efficiencies of Se lected Split-System Outdoor Units

............................. 5-4 Figure 5.5.2: Illustration of System Combinations for Split Systems

......................................... 5-4 Figure 5.5.3: Example of BOM Spreadsheet

............................................................................... 5-6 Figure 5.6.1: Cost Model Categories

........................................................................................... 5 -7 Figure 5.6.2: Cost Model Methodology

....................................................................................... 5-8 Figure 5.6.3: Components of Manufacturer Selling Price

......................................................... 5-11 Figure 5.8.1: Illustration of the Absolute Cost versus SEER Relationship

............................... 5-19 Figure 5.8.2 Illustration of System Cost Translation Process

................................................ 5-20 Figure 5.8.3: Illustration of Cost Trends

.................................................................................... 5-21 Figure 5.9.1: Relationship Betwee n HSPF and SEER in Availa ble 3-Ton Split-System Heat Pumps

.................................................................................................................... 5-27 Figure 5.10.1: Cost-Efficiency Data for Split- System Air Conditioners: Blower-Coil

............. 5-33 Figure 5.10.2: Cost-Efficiency Data for Split- System Air Conditioners: Coil-Only

................ 5-34 Figure 5.10.3: Cost-Efficiency Data for Split-System Heat Pumps

.......................................... 5-35 Figure 5.10.4: Cost-Efficiency Data for Single-Package Air Conditioners

............................... 5-36 Figure 5.10.5: Cost-Efficiency Data for Single-Package Heat Pumps

...................................... 5-37CHAPTER 5. ENGINEERING ANALYSIS

5.1 INTRODUCTION

The engineering analysis establishes the relationship between manufacturer selling price (MSP) and seasonal energy efficiency ratio (SEE R), measured in British thermal units per hour per watt (Btu/h/W), for the residential central ai r conditioners and heat pumps covered in this rulemaking. In this analysis, a relationship is also developed for heat pumps between SEER and heating seasonal performance factor (HSPF), meas ured in British thermal units per hour per watt (Btu/h/W). The cost-efficiency relationship serv es as the basis for subsequent cost/benefit calculations for individual customers, manufacturers, and the Nation. In determining this relationship, the U.S. Department of Energy (DOE) estimates the increase in the manufacturer selling price associated with technological chan ges that reduce the energy consumption of the baseline models.

The primary inputs to the engineering analysis are data from the market and technology assessment (chapter 3 in the TSD), input fro m manufacturers, baselin e specifications and production cost estimates de veloped using a cost model. The primary output of the engineering analysis is a set of cost-efficiency curves th at represent the average incremental cost of increasing efficiency levels above the baseline levels. In the subsequent markups analysis (chapter 6 in the TSD), DOE determines customer prices by applying distribution markups, sales tax, and contractor markups to the manufact urer sales prices (MSPs) developed in the engineering analysis. After applying these markup s, the data serve as inputs to the energy use characterization (chapter 7 in the TSD) and th e life-cycle cost and payback period analyses (chapter 8 in the TSD).

In this chapter, DOE discusses the identification of representative baseline units for each class, the methodology used to develop bill of materials and MSPs, the process for constructing the cost-efficiency curves, develops an engine ering examination of ni che product classes, and presents cost-efficiency curve outputs.

5.2 METHODOLOGY OVERVIEW

This section describes the analytical methodol ogy used in the engineering analysis. In this rulemaking, DOE is adopting an efficiency-level approach, which estimates the incremental cost of increasing product efficiency. This es timate is based on a reverse engineering analysis validated by manufacturer input. First, DOE us ed information gathered from manufacturers and data from the market and technology assessment to identify baseline units and select a set of units for teardown analysis. The baseline unit serves as a starting point for the analysis and the selected units that span a range of functionality, cooling capacity and efficiency ranges for commercially available products. DOE developed a unit cost estimate for the selected products by reverse engineering each, developing a bill of materials and inputting the results into a manufacturing cost model. To determine the MSP of a machine at each efficiency level, DOE added a typical profit to the fully absorbed cost of production. The resu lting MSP estimates were

5-1used to verify information provided by manufacture rs. The results of the engineering analysis are a set of cost-efficiency curves, in the form of MSP versus SEER, for each product class. The methodology for the engineering analysis is a lo gical, concise, and reproducible process, as illustrated in Figure 5.2.1.

Identification

of Baseline (5.4) Teardown Analysis ( Error! Reference Cost Model (5.6) CostEfficiency

Curves

( 5

. 8 ) Baseline BOM Cost Downstream Analysis

(5.6.4) MSP

vs. SEE R

Figure 5.2.1: Engineering Analysis Methodology

5.3 PRODUCT CLASSES

As discussed in the MTA (chapter 3 of th e TSD), DOE identified the following product classes for its analysis.

• Split-system air conditioners

• Split-system heat pumps

• Single-package air conditioners

• Single-package heat pumps

• Small duct, high velocity systems

• Space-constrained air conditioners

• Space-constrained heat pumps

Conventional products include th e first four classes (split-system air conditioners, splitsystem heat pumps, single-pack age air conditioners, and single -package heat pumps). Niche products include the last three cl asses (small duct, high velocity systems, space-constrained air conditioners, and space-constrained heat pumps ). The space-constrained product classes are assumed to include most through-the-wall air conditioners and heat pumps (both split and single package), since through-the-wall products will no longer exist after January 23, 2010 a , which is subsequent to the effective date of this rulemaking. Therefore, DOE did not consider those two product classes separately. Instead, DOE considered them as space-constrained products. The niche product classes are disc ussed separately and in fu rther detail in section 5.7.

5.4 BASELINE UNITS

The identification of baseline units required establishing both a minimum efficiency level (minimum SEER rating) and capacity which best represented the span of capacities of commercially available products . Currently, the standards for conventional central air

a As defined in 10 CFR 430.2, the through-the-wall product class applies only to products manufactured prior to January 23, 2010. This provision eliminates through-the-wall units as a separate product class after this date.

5-2conditioners and heat pumps (split-system air conditioners, split-system heat pumps, singlepackage air conditioners, and single-package h eat pumps) are set at 13 SEER/7.7 HSPF. Thus, conventional units that attain only the minimum efficiency rating of 13 SEER/7.7 HSPF will be considered baseline units for those product classes. DOE selected a model or models meeting the existing minimum Federal energy efficiency standards that are currently offered for sale as baseline products.

Regarding the representative capacity, this rulemaking applies to units with capacities below 65,000 Btu/h. For conventional product classes, 36,000 Btu/hour ( i.e. , 3-tons) was selected as the representative capacity for analys is because units at this capacity are ubiquitous across manufacturers, have high sales volumes, and span a relatively large range of efficiencies. DOE acknowledges, however, that manufacturers tend to optimize residential central air conditioner and heat pump systems around the 3-ton capacity. For the NOPR, DOE is considering performing additional engineering an alyses on 2- and 5-ton capacity products to account for potential capacity-related impacts on th e cost-efficiency relationship. Baseline units serve as a starting point for the engineering analysis and guide the selection process for the teardown analysis.

5.5 TEARDOWN ANALYSIS

Other than obtaining detailed manufacturing co sts directly from a manufacturer, the most accurate method for determining the production co st of a product is to disassemble it piece-by

piece, compile a bill of materials (BOM), and es timate the material and labor cost of each component. DOE refers to this practice as a physical teardown. A supplementary method, called a catalogue teardown, uses published manufact urer product literature and supplementary component data to estimate the major physical differences between the catalog teardown unit and a similar physical teardown unit.

Units selected for physical teardowns were dismantled, and each part was characterized according to weight, manufacturing processes, dimensions, material, and quantity, in order to facilitate the creation of a co mplete BOM for the product. Bills of materials for catalog teardowns are generated by modifying the BOM of a similar unit that has been physically torn down to reflect major physical differences. These modifications are ba sed on data taken from manufacturer specification sheets a nd supplementary component data.

5.5.1 Selection of Units

The teardown analysis performed for this engineering analysis includes a total of 24 physical teardowns, including 13 outdoor units (see Figure 5.5.1), 8 indoor units, and 3 evaporator coils. It also included 7 catalog teardowns for indoor units.

5-3Figure 5.5.1: Nominal Efficiencies of Selected Split-Sys tem Outdoor Units

The collection of products selected for teardown is intended to closely represent the market and expose the incremental cost of increasing product efficiency. To accomplish this, DOE selected the products for physical teardown and catalog teardown based on the following guidelines:

1. The selected products, taken together, cover the full range of efficiency levels considered in the analysis with emphasis placed on efficiencies in the 13-16 SEER range. Figure 5.5.2 illustrates how indoor and outdoor units from a single manufacturer can be combined to provide multiple ratings.

OUTDOOR UNIT SEER INDOOR UNIT

OUTDOOR UNIT-A

OUTDOOR UNIT-B

OUTDOOR UNIT-C INDOOR UNIT-A

INDOOR UNIT-C INDOOR UNIT-B 13

14

16

18

20

Figure 5.5.2: Illustration of System Combinations for Split Systems

2. From most manufacturers, DOE selected at least one low-efficiency product and one high-efficiency product, preferably sharin g similar characteristics (e.g., same product line).

3. The selected products are produced by manufacturers that have relatively large market shares in the residential central air conditi oning market, and thus are representative of typical design approaches.

4. The selected products have min imal product features or opti ons that add cost without affecting product efficiency.

5-45. For split-systems, indoor products were sele cted based on universality (ability to be paired with selected outdoor units) to maxi mize the number of systems that could be modeled.

5.5.2 Generation of Bill of Materials

The end result of each teardown was a structured BOM, describing each product component and its relationship to the other parts, in the estimate d order in which manufacturers assembled them. The BOMs describe each fabrication and asse mbly operation in detail, including the type of product needed (e.g., presses, drills) and the process cycle times. The result is a thorough and explicit model of the production process. The BO Ms incorporate all materials, components, and fasteners classified as either raw materials or purchased parts and assemblies. The classification into raw mate rials or purchased parts is ba sed on DOE’s previous industry experience, recent information in trade publica tions, and discussions with high- and low-volume original equipment manufacturers (OEMs). DOE al so visited several manu facturing plants to reinforce its understanding of the industry’s cu rrent manufacturing practices. Information was gathered to account for product designs specific to central air conditioners and heat pumps and ensure that the teardown analysis methodology an d pricing were accurate. For purchased parts, the purchase price is an estimate based on high-v olume price quotations and detailed discussions with suppliers. For fabricated parts, the price of intermediate materials (e.g., tube, sheet metal) and the cost of transforming them into finished parts is an estimate based on current industry pricing. For a continued discussion of the cost details and assumptions , refer to section 5.6.2.

The BOM for a catalog teardown is identically structured and provides a description in equal detail to the BOM of a ph ysical teardown. However, it is generated using a slightly different methodology. As stated previously, bills of materi als for catalog teardowns are generated by modifying the BOM of a similar unit that has been physically torn down. These modifications reflect the major physical differences between the units. Specific to this engineering analysis, the catalog teardown methodology was employed to generate bills of materials for evaporator coils and air handlers. DOE physically tore down 3 evaporator coils and 8 air handlers. Based on these physical tear downs, DOE executed 4 supplementary evaporator coil catalog teardowns and 7 supplemen tary air handler catalog teardowns.

Figure 5.5.3 below shows an example of a section of a BOM spreadsheet. Each row of the spreadsheet represents a single part of th e unit assembly, and include s a description of the part, a material type, initial and final dimensions, and weight. These rows also include placeholders for the type and number or duration of fabrication processes (stamping, drilling, etc.) required to create that part. From this information, a part cost is generated, and the part costs are summed across the sheet to create a cost estimate for the entire unit.

5-5Figure 5.5.3: Example of BOM Spreadsheet

5.6 COST MODEL

The cost model is a detailed, component-focus ed, activity-based tool for estimating the manufacturing cost of a product. Once teardowns were completed, DOE implemented a cost model that could translate the phy sical information from the BOMs into manufacturing costs. The cost model is based on production activiti es and divides factory costs into materials, labor, depreciation, and overhead. DOE defines the cost inputs of these broader categories in Figure 5.6.1.

5-6Major Category Sub-Category Description

Material Costs Direct Raw materials (e.g., coils of sheet metal) and purchased parts (e.g., fan motors, compressors)

Indirect Material used during manufacturing (e.g., welding rods, die oil, release media) Assembly Part/unit assembly on manufacturing line

Manufacturing Labor Fabrication Conversion of raw material into parts ready for assembly

Indirect Fraction of overall labor not associated directly with product manufacturing (e.g., forklift drivers, quality control) Supervisory Fraction of indirect labo r that is paid a higher wage

Depreciation Equipment, Conveyor, Building Straight line depreciation over expected life

Tooling Cost is allocated on a per-use basis or obsolescence, whichever is shorter

Utilities A fixed fraction of all material costs meant to cover electricity and other utility costs Other Overhead Maintenance Based on installed e quipment and tooling investment Property Tax and
Insurance A fixed fraction based on total unit costs

Figure 5.6.1: Cost Model Categories

DOE fed the cost data from all the BOMs—whet her they were obtained through physical teardowns or catalog teardowns—into the cost model. The cost model analysis created cost estimates for each of the central air conditioners analyzed in the teardown analysis. The cost model uses specific assumptions to provide cost estimates; the following sections describe these assumptions.

5.6.1 Cost Model Overview

This section provides a general overview of the process by which the cost model converts the physical information in each product’s BOM into cost information. After gathering component information through physical tear downs and organizing it to form BOMs, the resulting data were used as inputs for the cost model spreadsheet. To determine the costs, DOE could follow two different paths, depending on whether a subassembly was purchased (out

sourced) or produced in-house. For purchased part s, DOE gathered price quotations from major suppliers at different production volumes. Fo r parts produced in-house, DOE reconstructed manufacturing processes for each part using modeli ng software based on internal expertise. For example, for an access panel, DOE estimated th e time required for setup, handling, changeover, and punching holes, as well as the number of holes and hits. By repeating this process, DOE was able to assign labor time, equipment utilization, and other important factors to each subassembly in each of the units considered for this analysis. The last step was the conversion of all this information into dollar values. To perform this task, DOE collected information on such factors as labor rates, tooling depreciation, and costs of purchased raw material s. DOE assumed values

5-7for these parameters using internal expertise and confidential information available to its contractors. Figure 5.6.2 provides an illust ration of the cost model methodology.

Purchased Parts Bill of Materials Fabrication Processes Assembly Processes Finished Materials Raw Materials

Figure 5.6.2: Cost Model Methodology

In sum, DOE assigned costs of labor, materials, and overhead to each part, including coils, whether purchased or produced in-house. DOE th en aggregated single-part costs into major assemblies (e.g., cabinet assembly, condensing unit, evaporat or unit, controls, packaging, condenser coil assembly, evapor ator coil assembly, and compressors) and summarized these costs in a spreadsheet. DOE repeated this same process for each unit in the engineering analysis,representing a specific efficiency level at the chosen capacity, and mapped the resulting costefficiency points to use as a basi s for the cost-efficiency curves.

5.6.2 Cost Model Assumptions

Assumptions about manufacturer practices and co st structure play an important role in estimating the final cost of the products. DOE used assumptions regarding the manufacturing process parameters, e.g., equipmen t use, labor rates, tooling depr eciation, and cost of purchased raw materials, to determine the value of each component. It then summed the values of the components into assembly costs and, finally, th e total product cost. The product cost includes the material, labor, deprecia tion, and overhead costs associated with the manufacturing facility. The material costs include both raw materials and purchased part costs. The labor costs include fabrication, assembly, and indirect and overhead (burdened) labor rates. The depreciation costs include equipment depreciation, tooling depreci ation, and building depreciation. The overhead costs include indirect process costs, utilities, equipment and building maintenance, and rework. The following sections describe the cost model as sumptions related to material prices, purchased parts and factory parameters.

5.6.2.1 Material Prices

DOE determined the cost of raw material s by using prices for copper, steel, and aluminum from the American Metals Market. 1 DOE noted that there have been drastic fluctuations in metal prices ove r the last few years. To account for these large fluctuations, DOE used prices of metals that reflect a five-year average of the Bureau of Labor Statistics Producer Price Indices (PPIs) spanning 2004 to 2009. 2 DOE used the PPIs for steel mill products and copper rolling, drawing, and extruding, and ad justed to 2009$ using the gross domestic product implicit price deflator. 3 For non-metal materials, such as pl astics, DOE uses current PPIs as opposed to a five-year average. Table 5.6.1 below lists a selection of the raw material cost values used in the cost model.

5-8Table 5.6.1: Summary of Raw Material Prices Metal Type Five Year Cost Average. ($/lb 2004-2009) Cold Rolled Steel (CRS) $.39
Aluminized CRS $.55
Galvanized CRS $.54
Pre-Painted CRS $.70
Textured CRS $.61
Pre-Painted Textured CRS $.86
Fin Aluminum $1.23 Cu Tube – Plain for Refrigeration $2.11 Cu Tube – Rifled for Refrigeration $2.84

5.6.2.2 Fabricated Parts and Purchased Parts

DOE characterized parts based on whether manufacturers fabricated them in-house or purchased them from outside suppliers. For fabricated parts, DOE estimated the price of intermediate materials (e.g. tube, sheet metal) and the cost of forming them into finished parts. For purchased parts, DOE estimated the purchase price for OEMs based on discussions with the manufacturers. Whenever possible, DOE obtained price quotes directly from suppliers of the manufacturers of the units being analyzed. DOE assumed that the components in Table 5.6.2 below were purchased from outside suppliers.

Table 5.6.2: Purchased Central Air Condi tioner and Heat Pump Components Assembly Purchase d Sub-Assemblies

Condensing Unit Compressor Condenser Fan Blade
Condenser Fan Motor Filter/Dryer
Hi/Low Pressure Switch
Accumulator Reversing/Shutoff Valve
Plastic Parts

Evaporating Unit Evaporator Blower Evaporator Fan Motor TXV/EEV/Orifice
Plastic Parts

Controls Control Boards Capacitors, transformers, contactors, etc.

As previously stated, variability in the co sts of purchased parts can account for large changes in the overall MPC values calculated. Purc hased part costs can vary significantly based on the quantities desired and the co mponent suppliers chosen. The pur chased part prices utilized in this study were typical values based on estimated production volume and other factors. In actuality, there would be variability in these prices. The role of purchase part prices in the MPC

5-9calculation is further magnified because these parts comprise roughly 50-60 percent of these systems by cost. Additionally, some parts, such as molded plastic components, may be produced in-house by some manufacturers and purchased by others. The choice between these options would result in changes to the calculated overall system costs.

5.6.2.3 Factory Parameters

Certain factory parameters, such as fabrication rates, labor rates and wages also affect the cost of each unit produced. DOE factory pa rameter assumptions were based on internal expertise and manufacturer feedback. Table 5.6.3 below lists the factory parameter assumptions used in the cost model. These factory parameters are independent of the efficiency level of the unit produced and do not vary between the fo ur major product classes analyzed in the engineering analysis. This assumption is consistent with the fact that all major manufacturers produce units in all of these produc t classes, and across a range of efficiency levels. Additionally, these assumptions are generalized to represent typical production and are not intended to model a specific factory.

Table 5.6.3: Factory Parameter Assumptions

Parameter Estimate
Actual Annual Production Volume (units/year) 1,250,000 Work Days Per Year (days) 250 Assembly Shifts Per Day (shifts) 2 Fabrication Shifts Per Day (shifts) 2.5 Fabrication Labor Wages ($/hr) 16 Assembly Labor Wages ($/hr) 16 Assembly Worker Hours Per Year 3,600
Fabrication Worker Hours Per Year 4,500 Length of Shift (hrs) 8 Units Per Day 6,000 Average Equipment Installation Co st (% of purchase price) 10% Fringe Benefits Ratio 50%
Indirect to Direct Labor Ratio 33% Average Scrap Recovery Value 30% Building Cost ($/ft 2 ) 100 Worker Downtime 15% Building Life (in years) 30 Burdened Assembly Labor Wage ($/hr) 24 Burdened Fabrication Labor Wage ($/hr) 24 Supervisor Span (workers/supervisor) 25 Supervisor Wage Premium (over fabrication and assembly wage) 30%

5-10‐ 5.6.3 Manufacturer Selling Price Estimates

The output of the cost model is the manufacturer selling price, or MSP, which includes all production and non-production cost s, as well as profit. The MSP is related to the MPC (manufacturer production cost) by the manufacture r mark-up. The MPC includes all direct costs including production-related labor , materials, depreciation and overhead costs (as defined in section 5.6). The manufacturer markup is a multiplier that scales MPC to the MSP, and covers non-production cost elements, including sales, general and administrative, research and development, other corporate ex penses and profit. The components of MSP are shown in Figure 5.6.3.

Manufacturer Selling Price

Full Cost of

Product

Manufacturer Production Cost

Direct Labor Direct Material Overhead

Indirect Labor

Indirect Material

Maintenance

Depreciation

Taxes

Insurance related

to assets Non Production
Cost

Selling

Market Research

Advertising

POS Promotion

Salesperson Comp & Travel

Logistics (Warehousing, Delivery, Record

‐ Keeping, Order

Processing) General & Admin.

Costs of
Service & Staff Units

General Corporate

Costs (Comp, etc) R & D

Costs associated with finding new

and improved

products or
processes

Code Compliance

Modernization Interest

Cost of borrowing

funds Profit

Figure 5.6.3: Components of Manufacturer Selling Price

The law requires publicly owned companies to disclose financial information on a regular basis by filing forms with the U.S. Securities and Exchange Commission (SEC). The SEC form 10-K, filed by companies annually, provides a comprehensive overview of the company’s business and financial conditions . The 10-K report includes the co mpany’s revenues and direct and indirect costs. In the preliminary analysis , DOE used 10-Ks from publicly owned residential heating product companies to estimate manufacture r markups. The income statement section of the 10-K often lists the figures necessary for ca lculating the manufacturer markup—the net sales, costs of sales, and gross prof it. After calculating the markup fo r each manufacturer with 10-K data, DOE then calculated a single market-share weighted manufacturer markup to represent the

5-11industry. DOE applied a manufacturer markup of 1.32 to the MPC to arrive at a final manufacturer selling price.

5.6.4 Downstream Analyses

The MSPs derived in the engineering analysis are important inputs to the life-cycle cost analysis (LCC) and the manufacturer impact analysis (MIA). In the LCC, the MSPs are necessary to calculate the total installed cost of each unit. In the MIA, DOE constructs a number of scenarios that analyze how different pricing schemes impact manufacturers financially. In the MIA, both MSP and the direct production cost components of MSP are important drivers of results. DOE discusses how the engineering analysis is used in the other analyses in chapters 8 and 12 of the TSD.

5.7 NICHE PRODUCTS

For this preliminary analysis, DOE has conduc ted a basic review of the information available regarding products in the niche (s mall-duct, high-velocity and space-constrained) product classes. This consisted of gathering and analyzing public ly available documentation and product specification sheets, as well as interviewing some manufacturers directly. At this point, however, it should be noted that no formal engine ering analysis has been performed, no physical or catalogue teardowns have been conducted, a nd cost-efficiency curves have not yet been developed. DOE seeks to perform a full engineering analysis in later stages of the rulemaking, including teardowns and cost modeling of units throughout the available efficiency levels, as well as modeling of system designs to develop cu rves depicting theoretical incremental costs of efficiency increases.

5.7.1 Small Duct High Velocity

Small-duct, high-velocity (SDHV) systems ar e intended for applications that require special design constraints, primari ly retrofit applications in olde r homes and residential buildings where the original construction limits the use of conventional ductwork. In these situations, SDHV units often serve as the preferred alte rnative to operating multiple window units or installing obtrusive conventional ducting systems. SDHV systems are designed with the intent of allowing for simple installation and preserving the appearances of the existing buildings. These systems are also utilized in new construction applications, where building designs that would not be possible if traditional ductwork, and the require d space associated with it, were used. 10 CFR 430.2 defines “small-duct high-velocity system” as:

“...a heating and cooling product that contains a blower and indoor coil combination that (1) Is designed for, and produces, at least 1.2 inches of external static pressure when operated at the certified air volume rate of 220-350 CFM per rated ton of cooling; and (2) When applied in the field, uses high velocity room outlets generally greater than 1000 FPM which have less than 6.0 square inches of free area.”

5-125.7.1.1 Identification of the Baseline

Currently, the 13 SEER efficiency level ma ndated by the 2004 technical amendment (69 FR 50997) to the 2002 final rule applies to all SDHV products. Howeve r, all three major domestic manufacturers of SDHV units have been granted exceptions to this standard by the Office of Hearings and Appeals (OHA), allowing these units to instead adhere to an 11 SEER efficiency level. The decisions applying to these manufacturers went into effect on January 23, 2006 and remain in effect until DOE establishes an independent standard for SDHV systems. Therefore, DOE has selected 11 SEER as the current market baseline. Due to the ducting constraints mandated by the system size requirements, elevation of system performance to high levels is difficult in practice, and manufacturers have stated that they believe the maximum technologically feasible efficiency level to be just over 14 SEER. This is in agreement with the distribution of efficiency levels of products in the AHRI Certified Directory b , as roughly 74% of the units listed have rated efficiencies between 11 and 12 SEER, while only 5% of units are rated at 13 SEER or above. The highes t listed efficiency of a matched unit in the AHRI Directory is 14.5 SEER.

5.7.1.2 Product Description

SDHV air conditioners and heat pumps currently sold in the U.S. are similar to traditional split-system air conditioners and heat pumps, incorporating an outdoor unit with an indoor blower-coil unit. What differentiates SDHV syst ems from conventional split systems is the use of compact ductwork and specialized diffusers designed to accommodate high air velocities, combined with a specially designed indoor unit. Since these space constraints only affect the indoor portion of the system, the outdoor portion of an SDHV system is a conventional splitsystem model, selected from a manufacturer ba sed on the desired performance specifications of the system. The inherent system design constr aints prevent SDHV systems from achieving the same efficiencies as conventiona l split-system air conditioners a nd heat pumps w ithout placing a disproportionate burde n on consumers and manufacturers.

Three domestic manufacturers of SDHV systems, SpacePak, Unico, and Energy Saving Products, Ltd. (trade name: Hi-Vel ocity), certify their systems in the AHRI Certified Directory. Currently, the AHRI Certified Directory lists 4,469 actively produced mix-match system combinations with rated SEER values ranging from 11 SEER to 14.5 SEER. The majority of these units are rated between 11 and 12 SEER . The number of distinct SDHV indoor units produced by the three manufacturers is quite sma ll compared to the number of choices available for the condensing unit, as any conventional condensing unit can be connected to an SDHV indoor unit. Additionally, system performance will be constrained by e ither the condensing unit or the blower-coil unit, since the two componen ts are not matched by the manufacturer. Based on an examination of the AHRI Certified Directory, for any given SDHV indoor unit, variation of the condensing unit can change the syst em SEER value by up to 3.5 points.

b This refers to the AHRI Certified Directory information as of October 2, 2009, for SDHV air conditioning and heat pump units of all residential capacities.

5-13SDHV indoor units, along with the return air ducts and supply plenums, are designed to fit into confined spaces (e.g., attics, closets, and crawl spaces), within structures that were often not originally built with provisions for central ai r conditioning systems. The design of the SHDV unit varies by manufacturer. Spacepak produces packaged blower-coil combination units, while Energy Saving Products offers the fan mounted in a housing unit with a space to accommodate the evaporator coil, with the coil selectable by the user or installer ba sed on the application. Unico produces a modular system, where the blow er, evaporator coil, and optional heating coil are sold separately and are bolted together by the installer in the desired position, allowing for multiple configurations to fit different installation arrangements.

SDHV ducts possess very small cr oss-sectional profiles, not more than a few inches in diameter. This allows them to be installed in spaces that could not accommodate larger conventional ductwork. In other cases , the ductwork is concealed in ba seboards or molding, or is simply installed visibly along the edge of a wall when no space for concealment exists. In the case of new construction, SDHV ducts are often routed between studs in walls and through ceilings without requiring the large clearances necessitated by conv entional ductwork. These systems produce air velocities on the order of four to five times those of conventional systems, and as a result, blower motors must be capable of producing high static pressures. However, constraints on the maximum velocity of the air through the ductwork and vents exist, imposed by the onset of undesirable effects at very high ai r velocities including noise and drafts within rooms. As a result, the maximum volume of air that can be moved per unit time is constrained as well. To partially compensate for this limited flow volume, SDHV systems generally operate with higher temperature differentials across the evaporator coil in order to achieve the desired cooling capacities while moving less air than a conventional split-system air handler. This requires that SHDV units utilize evaporator coils with very high efficiencies; however, this efficiency gain resulting from the more effective co il is more than offset by the increased power consumption of the indoor blower.

5.7.1.3 Design options

Based on interviews with SDHV system manuf acturers, evaluation of previous analyses, and an assessment of SDHV systems currently ava ilable, DOE developed a list of design options that should be considered in its analysis. Th is list includes technologies considered to be technologically feasible and will serve to estab lish the maximum technologically feasible (max

tech) design. Due to the aforementioned technolog ical similarities that i nherently exist between the SDHV and conventional split-system product cl asses, DOE is currently considering the options previously listed for application in sp lit-system air conditioners and heat pumps as potential methods for increasin g SDHV product efficiency.

DOE has preliminarily concluded that the ability of manufacturers to implement these design options may be limited by the dimens ional restrictions imposed upon the systems. Namely, the necessity that the indoor unit be compact constrains the maximum possible dimensions of the coil. The result is that coil improvements must take the form of improved materials and fin designs, or the addition of coil rows to increase effective surface area while maintaining the necessary profile. However, increases in coil depth also result in a higher pressure drop across the coil, requiring more fa n energy to move the air. Manufacturers have claimed that they feel additional increases in the size of evaporator coils will not prove to be cost

5-14effective. Additionally, the overall rating of an SDHV unit is largely dependent upon the condensing unit to which the syst em is matched. Certain technolog ies (e.g., high-efficiency fan motors and compressors) are required in the conde nsing unit in order for the whole system to achieve the higher efficiency levels. Manufactur ers have claimed that a 12 SEER system rating generally requires a two-speed compressor on the condensing unit, while a 13 SEER system rating can only be attained through the use of a variable-speed compressor. Since the design of these condensing units is beyond the control of the SDHV system manufacturer, mandating efficiency levels which would require consumers to purchase mo re costly products from other manufacturers could lead to negativ e consequences for the industry.

5.7.1.4 Cost of Efficiency Improvements

Due to constraints on the implementation of the design options available to manufacturers, increases in system efficiency would come at a high cost, and improvements would meet with diminishing returns beyond a certain point. Increases in coil size would likely incur corresponding increases in coil cost, as mate rial costs are the bigg est contributor to the pricing of coils. Additionally, imp roved fin designs or other desi gn features would come at a high cost as well. Moreover, since overall system performance is highly dependent upon the efficiency of the outdoor unit, which is produced by a different manufacturer altogether, costs passed on to the consumer in upgrading to a hi gher-efficiency system would be greater than those encountered by the SDHV system manufacturers.

5.7.2 Space-Constrained

Certain types of central air conditioners and heat pumps are manufactured for applications with space constraints and, theref ore, have features that distinguish them from the majority of products available. Sometimes these products are not able to meet standards designed for conventional split-syst em air conditioners a nd heat pumps, or are able to, but, in doing so, place a disproportionate burden on manufacturers and consumers. This product class covers the products that DOE has determined to fit the definition of space constrained. 10 CFR 430.2 defines “space-constr ained product” as:

“...a central air conditioner or heat pump:

(1) That has rated cooling capacities no greater than 30,000 BTU/hr;

(2) That has an outdoor or indoor unit having at least two overall exterior dimensions or an overall displacement that: (i) Is substantially smaller than those of other units that are: (A) Currently usually installed in site-built single family homes; and (B) Of a similar cooling, and, if a heat pump, heating capacity; and

(ii) If increased, would certainly result in a considerable increase in the usual cost of installation or would certainly result in a significant loss in the utility of the product to the consumer; and

(3) Of a product type that was available for purchase in the United States as of December 1, 2000.”

5-155.7.2.1 Identification of the Baseline

In the 1999 SANOPR, DOE first suggested se parate product classes as a way to set standards for these niche products. 64 FR at 66310. Originally, these products were believed to include through-the-wall (TTW) split systems, single-package vertical units (SPVU), ductless split systems, and SDHV systems. As ofthe 2000 NOPR, TTW single-package and nonweatherized single-package system s were also added to this product class. In the 2004 Technical Amendment, DOE established a se parate product class for space- constrained systems, requiring them to meet a 12 SEER standa rd. TTW systems were made their own product class, and were required to meet a 10.9 SEER standard; however , this is set to expire on January 23, 2010. Within the scope of this rulemaking, SDHV units have been granted consid eration as a separate product class, and ductless split sy stems are being considered as part of the conventional splitsystem air conditioner and heat pump product classes. SPVU’s are considered to be commercial equipment, and thus do not fall under the scope of this rulemaking. Additionally, there currently appears to be no major manufacturer of domestica lly-sold single-package non-weatherized units. As a result of these changes since the last rule making, DOE is currently unaware of any products which would fall within the cl assification of space-constraine d products aside from TTW units. For this reason, DOE is considering TTW products as the basis for its study of this product class. DOE seeks feedback regarding this decision and any other existing products that may be considered space-constrained.

5.7.2.2 Product Description

There are two main types of TTW products: (1) TTW split systems and (2) TTW singlepackage systems. TTW products were popular in new multi-story residential construction in the 1960s and 1970s. Major OEMs have since abandone d the replacement market, providing an opportunity for lower-volume manufacturers, su ch as First Company, National Comfort Products, and EnviroMaster Intern ational .The replacement market is now dominated by these lower-volume manufacturers. Most TTW products ar e in the 1-1/2 to 2-1/2 ton (18,000 Btu/h to 30,000 Btu/h) capacity range. Residents and buildin g owners are particularly sensitive to any increase in price, especially the cost of enlarging the wall opening to accommodate a larger product. As a result, new TTW products for retrof it applications must f it within the same wall opening as the original units. Since repair is the only other cost-effective alternative to replacement, a new standard that increases cabinet size or results in a significant price increase could be counter-productive, preventing the turnov er of old, inefficient products and instead encouraging users to repair those existing units.

5.7.2.3 Design Options

DOE uses information about existing and pa st technology options and prototype designs as input in identifying technologies manufactur ers could use to meet and/or exceed energy conservation standards. In consu ltation with interested parties, DOE is developing a list of technologies that should be considered in the anal ysis. This list consists of all those technologies considered to be technologically feasible and w ill serve to establish the max-tech design. Due to the technological similarities th at inherently exist betwee n the space-constrained and conventional split-system product cl asses, DOE is currently considering the options previously

5-16listed for application in split-system air conditi oners and heat pumps as potential methods for increasing space-constrained product efficiency.

DOE conducted preliminary MIA interviews a nd various engineering evaluations to investigate the technology options available to space-constrained product manufacturers to increase the energy efficiency of their units. Based on this investiga tion, DOE has preliminarily concluded that unique factors may prevent TTW products from realizing the full potential of many energy saving design options. Typically, increased condenser coil surface area is the most cost-effective energy saving measure. Howeve r, manufacturers of these products are limited in their ability to implement this option by the appa rent constraints upon coil size inherently present in this product class, and so me manufacturers have expresse d concern that the available condenser coil surface area may have already been maximized in order to reach the 10.9 SEER standard. Similarly, manufacturers have claimed that the number of coil rows has also been maximized to the point at which the addition of further rows would provide insignificant returns. Other coil improvements, such as micro-channel tubing, have not yet proven effective during research and development testing. Specificall y, manufacturers have been unable to solve defrosting issues, calling into question the technolog ical feasibility of this design option. If coil improvements are insufficient to increase product efficiency, TTW manufacturers must explore more costly design options, such as high-effic iency compressors and fan motors and controls. According to certain manufacturers, variable-speed motors are unavailable for the lower capacities of TTW split systems, and higher-efficiency compressors are already in products on the market, having been implemented to m eet the 10.9 SEER standa rd. As lower-volume producers of a niche product, TTW manufacturers ma y not have the resources or the influence on component suppliers to make adva ncements in motor or compressor technology that could make them cost-effective energy saving design options for TTW products.

5.7.2.4 Cost of Efficiency Improvements

Based on manufacturer feedback, DOE estimates the MPC of a typical 10.9 SEER splitsystem TTW air conditioner to be between $700 and $800. According to certain TTW manufacturers, compliance with the 12 SEER st andard for space-cons trained products comes with an estimated increase in material costs of 15-20%, resulting in cost increases throughout the distribution chain. To surpass the 12 SEER sta ndard, TTW manufacturers would have to utilize very efficient components purchased from outside suppliers, such as variable-speed fan motors and inverter-driven compressors that could greatly increase the MPC. Since the cost of these components would be entirely dependent upon the suppliers, TTW manufacturers claim that they would be unable to control the costs incurred in procuring these purchased parts, and would be forced to pass those costs on to their dist ributors and, ultimately, consumers.

5.7.3 Future Analyses

For this preliminary analysis, DOE did not conduct physical or catalog teardowns on these niche products, nor has it developed an engi neering model to evaluate the performance of the included products. DOE also has not determined what the values of the max-tech SEER levels are for these products, due to the scarcity of quantitative data. However, for future stages of the rulemaking, DOE has deve loped a suggested analytical me thodology to study these niche product classes.

5-17Since SDHV manufacturers only produce the indoor portions of these systems, DOE proposes an approach similar to that used with blower-coil split air conditioning systems (described in section 5.8.1). As the ratings of specific indoor SDHV systems vary across different condensing units, teardowns of a few models from different manufacturers should be sufficient to facilitate the development of a cost-efficiency curve across the entire range of possible efficiencies, from baseline to max-tech.

The space-constrained (TTW) air conditione rs and heat pumps differ from the SDHV systems and other product classes in that all the products currently manufactured are rated at an efficiency level of 12 SEER. Therefore a conve ntional teardown analysis alone will not yield sufficient information regarding the cost and effectiveness of incremental efficiency improvements. For these products, DOE proposes that information and specifications for baseline units be gathered from teardowns of pr oducts currently on the market. This baseline information will then be used as inputs into models and simulations which will be used to explore the possible options that could be used to product incremental increases in efficiency. DOE seeks input from interested parties regarding this analytical methodology for the niche product classes.

5.8 INDUSTRY COST-EFFICIENCY CURVES

5.8.1 Split-System Air Conditioners: Blower-Coil

In new construction applications, a complete system is always installed. In replacement applications for split-system air conditioners, consumers are presented with two options: (1) replace a portion of their system, or (2) repl ace the entire system. For the first option, if a consumer has a furnace installed and a portion of the air conditioning system (i.e., condensing unit or evaporator coil) fails, the consumer may choose to only replace the air conditioning portion of the system. This scenario involves the replacement of a condensing unit and an evaporator coil used with the existing fan blower in the furnace. In these applications, manufacturers are constrained by the fan blower in the installed furnace, they only have the ability to modify the condensing unit or evaporator coil to achieve the desired efficiency. These systems are referred to as coil-only systems, and are tested and rated using the combination of a specific condensing unit and evaporator coil with default fan specifications identified in the test procedure.

For the second option, if the entire system is replaced, the consumer has the ability to select a combination of indoor and outdoor units that can achieve any efficiency within the commercially available range of efficiencies fo r split-system air conditioners. Since the systems are sold as specific combinations of indoor and outdoor units, manufactur ers have the ability to modify all portions of the syst em (i.e., condensing unit, evapor ator coil, and evaporator fan blower) to achieve the desired efficiency. These systems are referred to as blower-coil systems and are tested and rated using the combination of a specific condensing unit, evaporator coil, and evaporator fan blower. Since manufacturers have more options to improve the efficiency of a blower-coil system, the cost-effi ciency relationship is inherent ly different than for coil-only systems. Both types of systems are prevalent in the marketplace, and DOE characterized split

5-18system air conditioners with a separate cost -efficiency curve for blower-coil and coil-only systems.

DOE first developed an industry cost-efficiency curve for blower-coil, split-system air conditioners using the process listed below. These products span the largest efficiency range and are the highest-selling product class of all central air conditioners and heat pumps. Creating the industry cost-efficiency curve for split-system air conditioners was a four-step process that consisted of: (1) plotting the raw data points as absolute system cost versus efficiency, (2) translating the absolute system costs by manufacturer to common normalized system costs, (3) trending system and subsystem costs, and (4) aggregating the cost data to develop a costefficiency curve representative of the industry. Th e details of these steps are described in this section.

5.8.1.1 Plotting Absolute System Cost Versus Efficiency

The cost model analysis developed cost estimates for each of the teardowns, as detailed in section 5.6. The output from the model incl udes all manufacturing co sts, which includes corporate overhead expenses. DOE developed system costs for blower-coil, split-system air conditioners by summing the costs of specific matched pairs of conde nsing units and air handlers. DOE selected matched pairs from manufacturer spec ification sheets and the AHRI database to span the entire efficiency range fo r split-system products. The combined cost, called “absolute system cost” for purposes of this analysis, is the cost to manufacture each system—it is not the final cost to the end-user, because it doe s not include the manufacturing and distribution channel markups.

The absolute system cost from the model is plotted as a function of each product’s efficiency—given as SEER. Manufacturers publis h SEER values for each of their products, according to AHRI specifications. DOE does not present any absolute costs in this document, because doing so could expose sensitive financia l information about i ndividual manufacturers’ products. Figure 5.8.1 illustrates how DOE plotted absolute system cost versus efficiency

Figure 5.8.1: Illustration of the Absolute Cost vers us SEER Relationship

5-195.8.1.2 Translating Absolute System Cost to Normalized System Cost

For the next step in the process of creating the industry cost-efficiency curves, DOE normalized the absolute system costs from each manufacturer. DOE shifted system costs for products made by the same manufact urer equally, but shifted syst em costs for products made by different manufacturers independently.

As illustrated in Figure 5.8.2, the cost translation process shifted the absolute system costs of each manufacturer’s products so that the cost of the baseline system (i.e., 13 SEER) is consistent across all manufacturers. By ensuring that all manufacturers shared a common baseline system cost, DOE was able to compare manufacturers’ data points directly while maintaining each manufacturer’s incremental costs as efficiency increases, allowing for a direct analysis of the cost of efficiency improvement s regardless of baseline costs. To do this, DOE first identified the lowest cost 13 SEER system and the manufacturer that produced that system. DOE then shifted other manufacturers’ absolu te system cost data points down until each manufacturer’s lowest-cost 13 SEER system ma tched the overall lowest-cost 13 SEER system. DOE realizes that other methods of normalizing the data are available, such as shifting the cost values to center the curves at a market-weighted average rather than the lowest cost, and such methods could be considered for use in further analyses.Normalized Cost

SEER Figure 5.8.2 Illustration of System Cost Translation Process

In analyses downstream of the engineering analysis, DOE accounted for the fact that in replacement applications, some consumers will not replace their entire air conditioning system. For this scenario, DOE assumed that the consumer will only replace the condensing unit and the evaporator coil. For more detail on these replacement scenarios, see chapter 8 of the preliminary TSD. In order to model these scenarios, DOE estimated costs for different portions of the central air conditioning system. Therefore, DOE simplif ied the output from the cost model into five subsystems for each split-system air conditione r analyzed. The five subsystems were: (1) condensing unit, (2) indoor unit casing (sheet me tal and insulation), (3) evaporator coil, (4) evaporator fan blower, and (5) balance of indoor unit.

In addition to normalizing system costs, DOE also normalized the subsystem costs that were estimated from cost m odel data. This step was necessary in order to ensure that the sum of

5-20the subsystem costs equated to the normalized ove rall system costs developed previously. To do this, for each absolute system cost, DOE calculated the percentage that each absolute subsystem cost accounted for in the total. DOE then applied these same percentages, specific to each system cost, to the normalized system cost to estimate the normalized subsystem costs. As a result, the normalized subsystem costs were scaled propor tionally to the normalized system costs.

5.8.1.3 Trending System and Subsystem Costs

It is rare that a single manufacturer produces a system at every efficiency level throughout the entire operating efficiency range of central air conditioners and heat pumps. In addition, some manufacturers produ ce multiple systems in different product lines that achieve the same rated efficiency. These variations in product offerings across different manufacturers introduce complications to the analysis which must be addressed through trending of the data. Trending by manufacturer ensures that there is data at every efficiency level for each manufacturer studied, allowing for aggregation ac ross all manufacturers at every data point. If the data were not trended, certain efficiency levels would contain more models from some manufacturers than others, or perhaps no models at all from some manufacturers. This would introduce an undesired weighting effect into the da ta once the aggregated curves were developed, with some manufacturers’ products at certain e fficiency levels essentially being represented more than others. Therefore, DOE developed trends to estimate each manufacturer’s production costs at all efficiency levels. Figure 5.8.3 illustrate s the type of trends that DOE developed, first showing trend lines produced from normalized da ta for each manufacturer, then showing an overall trend line created using ag gregated normalized data.

Figure 5.8.3: Illustration of Cost Trends

According to discussions with manufacturers, examination of manufacturer specification sheets, and conducting physical teardowns, DOE found that system costs generally increaselinearly with respect to efficiency from 13-14 SEER. At these lower efficiencies, the most costeffective method for manufacturers to achieve effici ency gains is to increase the surface area of the heat exchangers. Wit hout strict constraints on the size of the heat exchangers , the efficiency gains resulting from their increased size are relatively proportional to the additional material, and thus cost. As air conditioners b ecome more efficient, it becomes increasingly difficult and costly to increase efficiency to the next higher level. Th is is partly because traditional lower-cost design changes, such as increasing heat exchanger surface area, may not suffice. This relationship

5-21becomes increasingly evident at efficiencies gr eater than 14 SEER. Therefore, DOE derived the system cost-efficiency curve for each manufacturer using a linear line-fit from 13-14 SEER, and an exponential curve-fit for effi ciencies greater than 14 SEER.

DOE also developed trends for the five subsystems described above. When examining the normalized subsystem costs, DOE found that each manufacturer used different methods to increase system efficiency. While each manufacturer’s system costs exhibited a similar trend as efficiency increased, the differences in the subsystem trends between different manufacturers were masked since all of the subsystem costs summed to the system cost. Therefore, DOE analyzed every subsystem from each manufacturer on an individual basis when developing trends to estimate subsystem costs for the operating efficiency range of split-system air conditioners.

5.8.1.4 Aggregating System and Subsystem Costs

To develop the industry cost-efficiency cu rve for split-system air conditioners, DOE aggregated the manufacturer cost-efficiency curves at both the system and subsystem level. Since DOE only developed curves for four manufactur ers, it adjusted market shares of those four manufacturers to represent the entire industry. DOE then used those adjusted market shares to weight each manufacturer’s cost-efficiency data. The result was a cost-efficiency curve that represented the MPC at each efficiency level fo r the industry, as well as five subsystem costefficiency curves.

Since DOE evaluated the subsystems indivi dually for each manufacturer, there were small discrepancies between the sum of the aggregated subsystem cost-efficiency curves and the aggregated system cost-efficiency curve. Therefore, DOE calibrated the subsystem costs such that their sum at each efficiency level was consistent with the system cost at each level.

5.8.2 Split-System Air Conditioners: Coil-Only

Since coil-only, split-system air conditioners rely on a default evaporator fan power to achieve their SEER rating, DOE’s cost-efficien cy curve consisted of only two subsystems, a condensing unit and an evaporator coil. Because a coil-only system is constrained by the default evaporator fan power in the test procedure, the system faces additional limitations in the maximum achievable (i.e., max-tech) SEER level compared to blower-coil systems. Referring to the AHRI Certified Directory, DOE determined that the max-tech for coil-only systems was roughly 16.5 SEER. Upon review of these system s, DOE found that this max-tech level was achieved using a condensing unit similar to a cond ensing unit used in a 19-20 SEER blower-coil system. DOE also found that at lower efficiencies (i.e., 13-14 S EER), the condensing units and evaporator coils were very similar to blower-coil systems of the same SEER level. Due to theparallels between coil-only and blower-coil systems, DOE used its estimated blower-coil costefficiency curve as the basis for the coil-only cost-efficiency curve.

As a starting point for the coil-only cost-effi ciency curve, DOE eliminated the indoor unit casing, evaporator fan blower, and balance of in door unit subsystems from the blower-coil costefficiency curve. Using manufacturer specification sheets and the AHRI Certified Directory, DOE then compared the SEER ratings of the sa me condensing unit when rated as a blower-coil

5-22and a coil-only system. DOE found that through 14 SEER, the condensing units were generally consistent between blower-co il and coil-only systems. Above 14 SEER, higher-efficiency condensing units were typically required in coil-only systems to achieve the same SEER levels as blower-coil systems.

When assessing the differences between the ev aporator coils in coil-only and blower-coil systems, DOE found that above the baseline, high er-efficiency evaporator coils were typically required for coil-only systems to achieve the same SEER levels as blower-coil systems. As the system efficiencies increase, the disparity between the complexity and cost of evaporator coils used in blower-coil and coil-only systems also increases.

5.8.3 Split-System Heat Pumps

To develop a split-system heat pump cost-efficiency curve, DOE used manufacturer specification sheets and limited heat pump teardowns to modify the blower-coil, split-system air conditioner cost-efficiency curve. DOE maintained the breakdown of system costs into the five subsystems used for blower-coil, split-system air conditioners. DOE firs t examined manufacturer specification sheets to identify any differences in the indoor units used in air conditioners and heat pumps. DOE found that the indoor units us ed in 13 SEER split-system heat pumps are generally the same indoor units that are used in 13.5 SEER split-system air conditioners. This 0.5 SEER offset between the indoor units used w ith heat pumps and air conditioners existed throughout the entire efficiency range. Therefor e, DOE shifted all split-system air conditioner subsystem costs relating to the indoor unit (i.e., indoor unit casing, evaporator coil, evaporator fan blower, and balance of indoor unit) c down by 0.5 SEER to modify the cost-efficiency curve to be applicable to split-system heat pumps.

Next, DOE compared the condensing units (i .e., outdoor units) used in split-system air conditioners and heat pumps. To do this, DOE compared the estimated system cost (based on teardowns) of a 13 SEER heat pump with a 13 SEER air conditioner from the same manufacturer. DOE calculated the percentage increase in cost of the system for that manufacturer. DOE then applied this percentage increase to the estimated industry cost of a 13 SEER split-system air conditioner to estimate the industry cost of a 13 SEER split-system heat pump. From this, DOE used the estimated industry cost of the indoor unit of a 13 SEER heat pump to back out the industry cost of an outdoor unit for a 13 SEER heat pump. DOE then calculated the percentage increase in the industr y cost of an outdoor unit for a 13 SEER heat pump compared to a 13 SEER air conditioner. DO E applied this percentage increase to the industry costs of outdoor units for split-system ai r conditioners to estimate the costs of outdoor units for split-system heat pumps throughout the entire efficiency range.

DOE determined that the max-tech level for split-system heat pumps was 19.5 SEER using the AHRI Certified Directory. Since this max-tech level fell between two split-system air conditioner SEER levels that were used to estimate the cost of the indoor and outdoor portions of

c For heat pump products (split-system and single-package), DOE refers to the heat exchangers and associatedsystem components with respect to their functionality while the system is in cooling mode. For example, in a splitsystem heat pump, the outdoor heat exchanger is referred to as the condenser coil and the indoor heat exchanger is referred to as the evaporator coil.

5-23the system, DOE interpolated between the two levels. DOE then examined manufacturerspecification sheets for high-efficiency systems to validate the costs estimated using the blowercoil, split-system air conditioner cost-efficiency curve. DOE did not develop a separate coil-only cost-efficiency curve for split-syst em heat pumps as it did for ai r conditioners. DOE believes that the majority of split-system heat pumps are sold as a matched set of i ndoor and outdoor units for both the new construction and replacement markets. However, DOE recognizes that in some instances heat pumps are used in conjunction with gas- or oil-fired furnaces today providing a “dual-fuel” heating capability. DOE seeks input on the characterization of the heat pump replacement market and whether installations of ma tched sets of indoor and outdoor products should be the basis for DOE’s analysis for all heat pumps.

5.8.4 Single-Package Air Conditioners

The basic system components of a single-package air conditioner are very similar to a split-system air conditioner. However, the system configurations differ enough that incremental costs cannot be estimated based s imply on the incremental costs of a split-system air conditioner, as was done for split-system heat pumps. Rather, DOE used manufacturer specification sheets and information from manufacturer interviews to determine the sizes and complexity of components in the baseline system. DOE relied on the cost estimates from split-system air conditioners to estimate the costs for various single-package air conditi oner components for the baseline system. To estimate component cost s for single-package air conditioners, DOE separated the condensing unit costs for split-syst em air conditioners into individual component costs (i.e., unit casing, condensing coil, condensin g fan, compressor, sealed system components, and a balance of the condensing unit). DOE then considered the costs of individual components at each efficiency level when developing cost estimates for a baseline single-package air conditioner.

To estimate the cost of the baseline casing , DOE used the sum of the indoor unit and outdoor unit casings for a 13 SEER split-system air conditioner. DOE found that the baseline condensing coils in single-package air conditioners are typically about 10-percent larger than those used in 13 SEER split-system air conditione rs. Therefore, DOE estimated the baseline cost for the condensing coil as 1.1 times the cost of a 13 SEER split-system air conditioner condensing coil. DOE also found that variable-s peed evaporator fan blowers are typically implemented in single-package air conditioners at 13.5 SEER, compared to 14.5 SEER in splitsystem air conditioners. So, DOE estimated that the baseline cost of the evaporator fan blower was approximately the same as a 14 SEER split- system air conditioner ev aporator fan blower. DOE assumed that the baseline costs of the remain ing system components were identical to those estimated for a 13 SEER blower-co il, split-system air conditioner.

Once DOE established the component costs for a baseline single-package air conditioner, DOE examined the AHRI Certified Database to determine that the max-tech level was 16.6 SEER. Using information from discussions with manufacturers and product specification sheets, DOE estimated the incremental costs of ea ch component from 13-16 SEER in 0.5 SEER increments as well as for the 16.6 SEER max-tech level. For simplicity, DOE then grouped the component costs into two subsystems: (1) eva porating, and (2) condensing. The evaporating subsystem consisted of the evaporator coil a nd the evaporator fan blower. The condensing

5-24subsystem consisted of all th e remaining components in the system. The sum of these two subsystems at each efficiency level pr ovides the system MPC for that level.

5.8.5 Single-Package Heat Pumps

DOE derived the single-package heat pump cost-efficiency curve using a similar methodology as was used to develop the split-syst em heat pump cost-efficiency curve. However, DOE used the single-package air conditioner cost-efficiency curve as the basis rather than the split-system air conditioner cost-e fficiency curve. DOE retained the two subsystems used for single-package air conditioners. To develop the cost-efficiency curve for single-package heat pumps, DOE first examined manufacturer specification sheets to identify any differences in the evaporator coils and evaporator fan blowers us ed in air conditioners and heat pumps. DOE found that the baseline heat pumps typically used a va riable-speed evaporator fan blower. DOE also found that the evaporator coils used in 13 SEER h eat pumps were about the same size those used 13.5 SEER air conditioners. This 0.5 SEER offset between the indoor units used with heat pumps and air conditioners existed throughout the entire e fficiency range. Therefore, DOE shifted the evaporating subsystem costs for the single package air conditioners down by 0.5 SEER to modify the cost-efficiency curve to be appli cable to single-package heat pumps. Next, DOE increased the condensing subsystem cost for si ngle-package air conditioners by the same percentage used to estimate the cost of the outdoor unit for split-system heat pumps. This was done for all efficiencies.

DOE determined that the max-tech level for split-system heat pumps was 16.4 SEER using the AHRI Certified Directory. For the c ondensing subsystem, this max-tech level fell between two single-package air conditioner SEER levels that were used to estimate its cost. So, DOE interpolated between the two SEER levels to estimate a corresponding cost for 16.4 SEER. For the evaporating subsystem, the air conditione r costs were shifted down by 0.5 SEER, but the max-tech level for heat pumps was only 0.2 SEER less than air conditioners. Therefore, DOE trended the evaporating subsystem costs using a line of best fit to estimate the subsystem cost at 16.4 SEER. The sum of these two subsystems at e ach efficiency level provides the system MPC for that level.

5.9 MISCELLANEOUS SYSTEM CHARACTERISTICS

5.9.1 Investigation of the Relation ship Between SEER and HSPF

Energy efficiency standards for heat pumps must establish minimum values for HSPF as well as SEER. However, this analysis thus far has only been performed in terms of rated SEER values, with no trending or aggr egation of data with regard to HSPF. In past rulemakings, analyses performed in terms of SEER were used as grounds for determination of HSPF standards. As part of this analysis, DOE inves tigated whether the relationship between HSPF and SEER is substantial enough to allow a SEER standa rd to serve as a basis for an HSPF standard as well.

5-255.9.1.1 Split-System Heat Pumps

Since SEER and HSPF are calculated values and incorporate factors other than the physical properties of the system, no direct rela tionship between the two would be expected. As Figure 5.9.1 illustrates, a survey of available sp lit-system heat pump products, procured from the AHRI Certified Directory, supports this hypothesis. Each band in the Figure represents 20 percent of the products available at the stated SEER level. Although HSPF generally increases with SEER, the statistical correlation is rather low (0.626). However, the relationship between SEER and HSPF is fairly close over the majority of the SEER values studied, with the middle 60 percent of the HSPF values falling within a range of +/-0.45 points of the median at SEER values of 17 and below.

To set energy efficiency standards for heat pumps, DOE must determine both an HSPF level and a SEER level. This complicates the an alysis since each SEER level corresponds to a range of varied HSPF ratings. To provide a rationale for selecting SEER-HSPF pairs, DOE examined plots based on Figure 5.9.1 that showed the number of models possessing each HSPF at each SEER level. Table 5.9.2 lists the results. A proposed minimum HSPF requirement was determined based on the distribution of the produc ts currently available throughout the range of efficiency levels. Median (50 th percentile) HSPFs are generall y well above the minimum HSPF level proposed, except at the higher SEER levels, where closer to 40 percent of units studied fall above these values. This is due to the perceive d ability of high-SEER products to attain higher HSPF values as well, and follows relationships us ed in past CAC rulemakings. DOE realizes that a number of different methodologies could be u tilized in setting the relationship between SEER and the required corresponding HSPF. One of these methods could be to construct a line which follows the median of the existing data, then offset it so that a chosen percentage of the products currently on the market would remain above this line. Such an alternative method could be considered in studying the SEER-HSPF relationshi p during later phases of this rulemaking.

5-26Source: 2008 AHRI Directory of Certified Product Performance d Figure 5.9.1: Relationship Betw een HSPF and SEER in Availa ble 3-Ton Split-System Heat Pumps

After examining the distribution data, DOE plotted the relationshi p between HSPF and SEER for all 3-ton split-system heat pumps currently listed as active in the AHRI Certified Directory. At the baseline efficiency of 13 SEER, the difference between the minimum HSPF (6.7) and the median (8.0) is 1.3 HSPF. However, the existing standard is 7.7 HSPF, and for this reason, DOE chose not to include any units below this level in its analysis. From this base point of 7.7 HSPF at 13 SEER, DOE then defined a line that generally followed the median HSPF at each SEER level while passing through the 13 SEER, 7.7 HSPF point:

Equation 5.9.1

Equation 5.9.2

The proposed minimum HSPF requirements are derived by inserting the minimum SEER requirements into the formula. Even though DO E does not have information on the distribution of heat pump sales by HSPF at each SEER level, it is apparent that the market currently favors products that exceed the minimum allowable HSPF le vel. This is due both to the correlation between HSPF and SEER and the preference in the market for higher HSPF heat pumps in cooler

d The AHRI Directory contains some models listed as currently produced which fall below the minimum current
HSPF value.

5-27climates. DOE believes that establishing an HSPF standard well above the current median at a given SEER level would impose an undue design c onstraint on manufacturers, adding to the cost and burden of designing, producin g, testing, and qualifying the product without resulting in a significant increase in the average HSPF of products sold. Table 5.9.1 summarizes the selection of HSPF standard levels:

Table 5.9.1: Comparison of Proposed HSPF St andard Levels with Available Products

Efficiency/Standard Level (SEER) 13 14 15 16 17 18 19

Recommended Minimum HSPF 7.7 8 8.3 8.6 9.1 9.6 10.1

Median HSPF in Available Products 8 8.3 8.6 9 9.2 9.25 9.05

Offset from Median (HSPF) -0.30 -0.30 -0.30 -0.40 -0.10 0.35 1.05

Fraction of Available Products Below Recommended HSPF Level <10% <10% <40% <20% <30% <70% <70%

Source: 2008 AHRI Directory of Certified Product Performance

Table 5.9.2 provides a more de tailed breakdown of the models available at each efficiency level as well as the total number of models at each efficiency level.

5-28Table 5.9.2: Prevalence of HSPF Ratings by SEER Level for 3-Ton Split-System Heat Pumps with Impacts of Suggested HSPF Standards

Decile Efficiency Level (SEER)

13 14 15 16 17 18 19
Selected HSPF

7.7 8 8.3 8.6 9.1 9.6 10.1
0% 6.7 6.7 6.7 6.7 7.1 7.4 8.05 10% 7.7 8 7.8 8.5 8.5 8.35 8.47 20% 7.9 8.1 8.1 8.7 9 8.9 8.62 30% 8 8.2 8.2 8.9 9.1 9 8.73 40% 8 8.2 8.5 9 9.1 9.25 8.94 50% 8 8.3 8.6 9 9.2 9.25 9.05 60% 8.1 8.5 8.6 9.1 9.25 9.5 10.05 70% 8.2 8.5 8.8 9.1 9.5 9.64 10.25 80% 8.3 8.6 9 9.2 9.7 10 10.35 90% 8.5 8.85 9.2 9.5 9.9 10.23 10.43 100% 9.45 10 10 10.65 10.75 10.6 10.55
No. Models 14939 12211 4892 2024 1517 285 23

Source: 2008 AHRI Directory of Certified Product Performance

5.9.1.2 Single-Package Heat Pumps

The current study of the relation between HSPF and SEER for single-package heat pumps, performed as part of this preliminary analysis, is based off of the fit of an equation directly to the AHRI Certified Directory data for this product class. However, for use in future analyses, DOE also investigated the applicability of the results obtained for split-system heat pumps to the single-package heat pump product class. The single-package heat pump product class contained a much lower number of product m odels (623) than the split-system heat pump product class, constituting only 0.3 percent of the total heat pump models represented in the AHRI Certified Directory. When the products we re categorized by SEER rating, it became evident that the variation present within the HSPF values at each SEER level was much smaller than was the case with split-system heat pumps. Whereas the HSPF values for a given SEER could vary by as much as 3.95 HSPF within the split-system products, the largest variation observed for the single-package products at a spec ific SEER was 0.2 HSPF. This suggests that there is a strong correlation for these product s between SEER and HSPF, and that an HSPF standard would likely have a similar effect on all manufacturers. Additionally, when the proposed HSPF equation discusse d above was compared against the single-package heat pump data, a strong agreement was visible. From this it appears that the general, median trend in the HSPF/SEER relationship exhibited for split-system products is also followed by single-package products. As a result, for the NOPR, DOE propos es that the SEER/HSPF correlation proposed for split-system products be extended to apply to single-package heat pumps as well.

5-295.9.2 Calculation of System Weights

Representative system weights for units at all SEER levels were required as an input to downstream analyses, including the life-cycle cost calculations and other analyses performed as part of this investigation. The basis for this calculation of typical system weight was weight information obtained from manufactur er specification sheets. For e ach of the four conventional product classes (split-system ai r conditioners, split-system he at pumps, single-package air conditioners, single-package heat pumps), data were collected across a number of manufacturers and across the entirety of the range of applicable rated SEER levels. The br eadth of data included served to ensure as accurate a view of the market as possible would be obtained. Separate calculations were performed for the indoor units and outdoor units for the split-system product classes, and for packaged units for the single-package product class. For all of these units, the data across the various manufacturer s were consistent enough to a llow for direct trending of unit weight. Therefore, system weights as listed by the manufacturers were plotted against rated SEER for all manufacturers and SEER levels, and a best fit curve was fit to the data. From this curve fit, typical unit weights were estimated for e ach applicable SEER level. This trending and calculation allowed for a single typical unit weight corresponding to a given SEER value to be used for the systems in each product class. Table 5.9.3 through Table 5.9.6 give the calculated typical weights by SEER level for each product class examined.

Table 5.9.3: Calculated Typical Split-S ystem Air Conditioner Unit Weights Split AC Typical Weights (lbs)
SEER Outdoor Unit Weight Indoor Unit Weight
13 178 110
13.5 189 114
14 199 117
14.5 209 120
15 220 124
15.5 230 127
16 240 130
16.5 250 132
17 261 134
18 282 140
19 302 144
20 323 148
21 344 152
22 364 156

5-30Table 5.9.4: Calculated Typical Spli t-System Heat Pump Unit Weights Split HP Typical Weights (lbs)
SEER Outdoor Unit Weight Indoor Unit Weight
13 225 114
13.5 237 117
14 248 120
14.5 258 124
15 269 127
15.5 279 130
16 288 134
17 307 140
18 324 144
19 341 148
19.5 349 152

Table 5.9.5: Calculated Typical Pack aged Air Conditioner Unit Weights

SEER Packaged AC Typical Weights (lbs)
13 333
13.5 349
14 366
14.5 382
15 398
15.5 414
16 431
16.6 450

5-31Table 5.9.6: Calculated Typical Pa ckaged Heat Pump Unit Weights

SEER Packaged HP Typical Weights (lbs)
13 379
13.5 395
14 411
14.5 427
15 443
15.5 460
16 476
16.4 489

5.10 RESULTS

The final result of the engineering analysis is a set of cost-efficiency curves. DOE developed curves representing the four c onventional product classes using the reverseengineering and cost modeling methodology descri bed above. The four cost-efficiency curves are shown in Figures 5.10.1 through 5.10.5 below and in tabular form in Tables 5.10.1 through 5.10.5 in the form of SEER versus MPC. More deta iled results, including the design options used at each design option level, are provided in appendix B.

As stated above, DOE used the cost-efficiency curves from the engineering analysis as an input to the life-cycle cost (LCC) analysis to determine the price of central air conditioning and heat pump units to the customer (see chapter 8 of the TSD).

5-32Table 5.10.1: Cost-Efficiency Data for Sp lit-System Air Condit ioners: Blower-Coil Efficiency Level Outdoor Unit Indoor Unit System

SEER Condensing Unit [$] Indoor Unit Casing [$] Evaporator Coil [$] Evaporator Fan Blower [$] Balance of Indoor Unit [$] MPC [$]

13 475.32 56.69 104.89 59.27 19.09 715.26
13.5 495.04 57.72 113.91 64.89 22.37 753.93
14 514.76 58.75 124.59 71.02 23.47 792.59
14.5 534.48 59.78 125.16 91.13 23.38 833.92
15 554.38 60.81 125.86 94.88 27.90 863.84
15.5 576.72 60.81 128.34 99.55 29.45 894.87
16 599.95 60.81 130.87 104.44 30.99 927.06
16.5 624.13 60.81 133.45 109.58 32.50 960.46
17 649.27 60.81 136.08 114.96 33.99 995.11
18 702.65 60.81 141.49 126.55 36.87 1,068.36
19 760.41 60.81 147.11 139.30 39.58 1,147.21
20 822.92 60.81 152.96 153.34 42.10 1,232.12
21 890.56 60.81 159.05 168.79 44.35 1,323.56
22 963.77 60.81 165.37 185.79 46.30 1,422.04

Figure 5.10.1: Cost-Efficiency Data for Split-System Ai r Conditioners: Blower-Coil

5-33Table 5.10.2: Cost-Efficiency Data for Sp lit-System Air Condit ioners: Coil-Only Efficiency Level Outdoor Unit Indoor Unit System

SEER Condensing Unit [$] Evaporator Coil [$] MPC [$]
13 475.32 104.89 580.21
13.5 495.04 119.53 614.57
14 514.76 136.35 651.11
14.5 555.55 136.91 692.46
15 599.95 139.48 739.43
15.5 649.27 147.83 797.10
16 712.01 159.16 871.17
16.5 782.27 174.55 956.82

0.00 200.00 400.00 600.00 800.00 1,000.00 1,200.00 1,400.00 1,600.00MPC [$]

12 13 14 15 16 17 SEER

Figure 5.10.2: Cost-Efficiency Data for Split-System Ai r Conditioners: Coil-Only

5-34Table 5.10.3: Cost-Efficiency Data for Split-System Heat Pumps Efficiency Level Outdoor Unit Indoor Unit System

SEER Condensing Unit [$] Indoor Unit Casing [$] Evaporator Coil [$] Evaporator Fan Blower [$] Balance of Indoor Unit [$] MPC [$]

13 601.67 57.72 113.91 64.89 22.37 860.56
13.5 626.63 58.75 124.59 71.02 23.47 904.47
14 651.59 59.78 125.16 91.13 23.38 951.04
14.5 676.55 60.81 125.86 94.88 27.90 986.01
15 701.75 60.81 128.34 99.55 29.45 1,019.90
15.5 730.02 60.81 130.87 104.44 30.99 1,057.13
16 759.43 60.81 136.08 114.96 33.99 1,105.27
17 821.86 60.81 141.49 126.55 36.87 1,187.57
18 889.42 60.81 147.11 139.30 39.58 1,276.23
19 962.54 60.81 152.96 153.34 42.10 1,371.74 19.5 1,002.10 60.81 156.01 161.06 43.22 1,423.20

Figure 5.10.3: Cost-Effici ency Data for Split-System Heat Pumps

5-35Table 5.10.4: Cost-Efficiency Data fo r Single-Package Air Conditioners Efficiency Level Subsystems System

SEER Condensing [$] Evaporating [$] MPC [$]
13 550.42 175.91 726.33
13.5 575.28 216.29 791.57
14 608.88 226.52 835.40
14.5 661.67 238.00 899.67
15 702.39 249.71 952.10
15.5 751.43 267.05 1,018.49
16 811.79 285.46 1,097.25
16.6 904.63 304.67 1,209.31

Figure 5.10.4: Cost-Effi ciency Data for Single-P ackage Air Conditioners

5-36Table 5.10.5: Cost-Efficiency Data for Single-Package Heat Pumps Efficiency Level Subsystems System

SEER Condensing [$] Evaporating [$] MPC [$]
13 682.31 216.29 898.60
13.5 713.79 226.52 940.30
14 756.32 238.00 994.32
14.5 823.14 249.71 1,072.85
15 874.68 267.05 1,141.73
15.5 936.76 285.46 1,222.21
16 1,013.16 304.67 1,317.83
16.4 1,091.51 322.46 1,413.96

Figure 5.10.5: Cost-Efficien cy Data for Single-Package Heat Pumps

5-375.11 REFERENCES

1 American Metals Market, http://www.amm.com/.

2 U.S. Department of Labor, Bureau of Labor Statistics, Producer Price Indices

, http://www.bls.gov/ppi /.

3 U.S. Department of Commer ce, Bureau Economic Analysis, Gross Domestic Product Implicit Price Deflator

, https://bea.gov/bea/dn/nipaweb/TableView.asp#Mid

.

5-38CHAPTER 6. MARKUPS TO DETERMINE EQUIPMENT PRICE

TABLE OF CONTENTS

6.1 INTRODUCTION

.............................................................................................................. 6-1 6.2 MARKUP CALCULATION PROCEDURE

..................................................................... 6-2 6.2.1 Baseline Markups

................................................................................................. 6-3 6.2.2 Incremental Markups

........................................................................................... 6-4 6.2.3 Overall Markups

.................................................................................................. 6-4 6.3 ASSUMPTIONS USED TO ESTIMATE WHOLESALER AND CONTRACTOR MARKUPS

........................................................................................................................ . 6-5 6.4 ESTIMATION OF WHOLESALER MARKUPS

............................................................. 6-6 6.4.1 Estimation of Wholesaler Markup Probability Distribution

................................ 6-8 6.5 ESTIMATION OF MECHANICAL CONTRACTOR MARKUPS

.................................. 6-8 6.5.1 Markups for Mechanical Contract ors in the Replacement and New Construction Markets

........................................................................................... 6-9 6.5.2 Estimation of Mechanical Contractor Markup Probability Distribution

........... 6-11
6.6 ESTIMATION OF GENERAL CONTRACTOR MARKUPS

........................................ 6-12 6.6.1 Estimation of General C ontractor Markup Probability Distribution

................. 6-13
6.7 SALES TAX

..................................................................................................................... 6 -14 6.8 OVERALL MARKUPS

.................................................................................................... 6-15 REFERENCES

..................................................................................................................... ..... 6-17

LIST OF TABLES

Table 6.4.1 Wholesaler Expenses and Markups

..................................................................... 6-7 Table 6.5.1 Baseline Markup, All Mechanical Contractors

.................................................... 6-9 Table 6.5.2 Baseline Markups for the Replacemen t and New Construction Markets, All Mechanical Contractors

............................................................................... 6-10 Table 6.5.3 Mechanical Contractor Expenses and Baseline Markup, Residential and Light Commercial

.............................................................................................. 6-10 Table 6.5.4 Mechanical Contractor Expenses a nd Markups Based on Census Bureau
Data

.................................................................................................................... 6-11 Table 6.6.1 General Contractor Expe nses and Markups

....................................................... 6-13 Table 6.7.1 State Sales Tax Rates (Percent)

......................................................................... 6-15 Table 6.8.1 Average Overall Ba seline Markups

................................................................... 6-15 Table 6.9.2 Average Overall Incremental Markups

.............................................................. 6-15

6-iLIST OF FIGURES

Figure 6.1.1 Distribution Channels for CAC Equipment

......................................................... 6-1 Figure 6.4.1 Wholesaler Baseline Markup Probability Distribution

........................................ 6-8 Figure 6.4.2 Wholesaler Incremental Markup Probability Distribution

.................................. 6-8 Figure 6.5.1 Residential a nd Light Commercial Mechani cal Contractor Relative Markup Probability Distribution

........................................................................ 6-12 Figure 6.6.1 Residential Genera l Contractor Relative Markup Probability Distribution

....... 6-14 Figure 6.6.2 Commercial General Contractor Relative Markup Probability Distribution

..... 6-14

6-iiCHAPTER 6. MARKUPS TO DETERMINE EQUIPMENT PRICE

6.1 INTRODUCTION

To carry out the life-cycle cost (LCC) calcu lations described in Chapter 8, the U.S. Department of Energy (DOE) needed to determin e the cost to the customer of a residential central air conditioner or heat pump (CAC) product. This cost was determined for both baseline equipment and more-efficient equipment th e customer would purchase following the promulgation of new energy conservation standards. However, the customer price of baseline or higher-efficiency equipment is not known and can be determined based on how the equipment is purchased. For the central air conditioner and h eat pump rulemaking, direct information on the incremental markup on equipment costs for higher efficien cy units is not readily available. This is partially due to the fact that such units ar e often included in the c onstruction costs of new housing or as a package that includes installati on. In addition, because higher efficiency units may have different markups than baseline units at minimum efficiency and higher efficiency units are not produced at the same volume as ba seline units, current incremental equipment costs observed in the market may not be representativ e of the incremental costs under a new standard. The manufacturing selling price (MSP) can be determined for both baseline equipment and the more-efficient equipment as desc ribed in the engineering analysis (Chapter 5). Therefore, by applying a multiplier called a “markup” to the MSP, DOE was able to estimate the customer price of equipment purchased through various di stribution channels. This chapter describes how DOE derived such markups.

The cost to the customer depends on how th e customer purchases the equipment. DOE identified two distribution channels, as shown in Figure 6.1.1, to describe how the equipment passes from the manufacturer to the customer for both new construction and replacement markets. In the replacement distribution channel, the manufacturer sells the CAC product to a distributor/wholesaler, who in turn sells it to a mech anical contractor, who in turn sells it directly to the customer. In new construction distributi on channel, the manufacturer sells the equipment to a wholesaler, who in turn sells it to a mechanical contractor, who in turn sells it to the customer through a general contractor who sells it and its installation to the customer. The distribution chain markup consists of a distributor/wholesaler ma rkup applied by distributors and wholesalers, a dealer/contractor markup applie d by dealers and HVAC contractors and a markup for sales tax. For the new housing market, a mark up is also applied by housing developers and builders. The markups applied in the Pre-NOPR analysis for distributor and dealer markups were determined from aggregate average markups for the businesses in the distribution chain. This means at each stage of distribution, direct costs of sales, i.e., purchased equipment and materials and direct labor costs, were compared with th e total volume of business revenues, and the ratio of total business revenues to direct co sts was used to determine the markup.

New Units: Manufacturer → Distributor → Mechanical Contractor → General Contractor → Customer
Replacement Units: Manufacturer → Distributor → Mechanical Contractor → Customer

Figure 6.1.1 Distribution Channels for CAC Equipment

6-1The analysis detailed here for the Pre-NOPR examined the scaling behavior of markups for wholesalers and contractors, and determined that markups are neither fixed-dollar, nor proportional to all direct costs, but somewhere in-between. Using the available data, we have found measurable differences between incremental markups on direct equipment costs and the

average aggregate markup on direct business costs. Significant differences were found between average and incremental markups for heating, ventilation, air-conditioning and refrigeration (HVACR) wholesalers/distributor s, and for HVAC dealers/cont ractors. Section 6.3 further discusses the differences between average and incremental markups.

The main reason that the selling price of a pr oduct may not be strictly proportional to the purchase price of the equipment is that businesses incur a wide variety of costs. Therefore, when the purchase price of equipment and materials increases, only a fraction of the business expenses increase, while the remainder of the businesses’ expenses stay relatively constant. For example, if the unit price of an air conditioner increases by 30%, it is unlikely that the cost of secretarial support in an administrative office will increase by 30% also. Certain business expenses are relatively uncorrelated with the cost of equipment or cost of goods.

For each of the steps in the distributi on channels presented above, DOE estimated a baseline markup and an incremen tal markup. DOE defined a baseline markup as a multiplier that converts the MSP of equipment w ith baseline efficiency to the customer purchase price for the equipment at the same baseline efficiency leve l. An incremental markup is defined as the multiplier to convert the incremental increase in MSP of higher efficiency equipment to the customer purchase price for the same equipmen t. Both baseline and incremental markups are only dependent on the particular distribution channe l and are independent of the efficiency levels of CAC products.

6.2 MARKUP CALCULATION PROCEDURE

The following equation describes how DOE determined the equipment price if a mechanical contractor sells the equipment to the customer through a general contractor distribution chain:

EQP CUST = MSP x MU WHOLE x MU MECH CONT x MU GEN CONT x (1+ ST) Eq. 6.1

Where:

EQP CUST = equipment price to the customer ($),
MSP= manufacturer selling price ($),
MU WHOLE = wholesaler markup,
MU MECH CONT = residential and li ght commercial mechani cal contractor markup,
MU GEN CONT = general contractor markup,
ST = sales tax ($).

The markup multiplier to the equipment price is lessened for shorter distribution chains by omitting the applicable markup(s).

The general contractor markup is only applie d to new construction because the general contractor not generally involved in the replacem ent market. The later sections of this chapter

6-2describe the determination of the residential and light commercial mechanical contractor markups and market type (i.e., new or replacem ent). For each of the markups presented above, DOE further differentiated between a baseline ma rkup and an incremental markup, as described below. The overall markup describe s the product of all the markups (baseline and incremental) plus sales tax within a distribution channel.

6.2.1 Baseline Markups

DOE defined baseline markups as cost multip liers that convert the MSP of equipment with baseline efficiency to the customer purchase price for the equipment at the same baseline efficiency level.

New equipment is assumed to be sold to a cu stomer by a mechanical contractor through a general contractor:

EQP GEN CONT BASE = MSP BASE x MU WHOLE BASE x MU MECH CONT BASE x MU GEN CONT BASE x (1+ST) Eq. 6.2

Where:

EQP GEN CONT BASE = general contractor price of baseline equipment ($),
MSP BASE = manufacturer selling price of baseline equipment ($),
MU WHOLE BASE = wholesaler markup on baseline equipment,
MU MECH CONT BASE = mechanical contractor markup on baseline equipment,
MU GEN CONT BASE = general contractor markup on baseline equipment,
ST = sales tax rate.

Replacement equipment is assumed to be sold to a customer directly by a mechanical

contractor:

EQP MECH CONT BASE = MSP BASE x MU WHOLE BASE x MU MECH CONT BASE x (1+ST) Eq. 6.3

Where:

EQP MECH CONT BASE = mechanical contractor pri ce of baseline equipment ($),
MSP BASE = manufacturer selling price of baseline equipment ($),
MU WHOLE BASE = incremental wholesaler markup,
MU MECH CONT BASE = mechanical contractor markup on baseline equipment,
MU GEN CONT BASE = general contractor mark up on baseline equipment,
ST = sales tax rate.

The use of the markups results in the mechanical contractor ( EQP MECH CONT BASE ), and general contractor ( EQP GEN CONT BASE ) prices of baseline CAC equipment.

6-36.2.2 Incremental Markups

Incremental markups are defined as the co st multipliers to convert the incremental increase in MSP of higher efficiency equipment to the customer purchase price for the same equipment, as shown in the following equations:

If sold to a customer by a mechanical contractor through a general contractor:

EQP GEN CONT INCR = MSP INCR x MU WHOLE INCR x MU MECH CONT INCR x MU GEN CONT INCR x (1+ST) Eq. 6.4

Where:

EQP GEN CONT INCR = incremental general contractor price ($),
MSP INCR = manufacturer incremental selling price ($),
MU WHOLE INCR = incremental wholesaler markup,
MU MECH CONT INCR = incremental mechanical contractor markup,
MU GEN CONT INCR = incremental general contractor markup,
ST = sales tax rate.

If sold to a customer directly by a mechanical contractor:

EQP MECH CONT INCR = MSP INCR x MU WHOLE INCR x MU MECH CONT INCR x (1+ST) Eq. 6.5

Where:

EQP WHOLE INCR = incremental wholesaler price ($).

In these equations, MSP INCR refers to a change in the MSP (e.g., brought about by an increase in equipment efficiency due to am ended energy conservation standards) and MU WHOLE

INCR , MU MECH CONT INCR , and MU GEN CONT INCR refer to the incremental wholesaler, incremental mechanical contractor, and incremental general c ontractor markups, respectively. The use of the incremental markups results in incremental equipment price to the incremental mechanical contractor ( EQP MECH CONT INCR ), and incremental general contractor ( EQP GEN CONT INCR ) prices experienced by the customer.

6.2.3 Overall Markups

The overall markup is the produc t of all the markups, including both overall baseline and overall incremental markups, for the different steps within a distribution channel plus sales tax, as indicated by the following equations:

EQP CUST BASE = MSP BASE x ( WT MECH CONT BASE x MU WHOLE BASE x MU MECH CONT BASE + WT GEN

CONT BASE x MU WHOLE BASE x MU MECH CONT BASE x MU GEN CONT BASE ) x (1+ ST ) = MSP BASE x MU OVERALL BASE Eq. 6.6

6-4EQP CUST INCR = MSP INCR x ( WT MECH CONT INCR x MU WHOLE INCR x MU MECH CONT INCR + WT GEN

CONT INCR x MU WHOLE INCR x MU MECH CONT INCR x MU GEN CONT INCR ) x (1+ ST ) = MSP INCR x MU OVERALL INCR Eq. 6.7

EQP CUST = EQP CUST BASE + EQP CUST INCR Eq. 6.8

Where:

EQP CUST BASE = baseline customer price ($), EQP CUST INCR = incremental customer price ($), EQP CUST = total customer price ($),
MU OVERALL BASE = overall weighted baseline markup th at is the product of all the weights and baseline markups for each step of the distribution channel,
MU OVERALL INCR = overall weighted incremental mar kup that is the product of all the weights and incremental markups fo r each step of the distribution channel,
WT MECH CONT BASE = weight (percent) of baseline e quipment sales through mechanical
contractors, WT GEN CONT BASE = weight (percent) of baseline equipment sales through general
contractors, WT MECH CONT INCR = weight (percent) of higher efficiency equipment sales through mechanical contractors,
WT GEN CONT INCR = weight (percent) of higher efficiency equipment sales through general contractors.

The use of the overall baseline and overall in cremental markups results in the baseline customer price ( EQP CUST BASE ) and the incremental customer price ( EQP CUST INCR ). For a particular higher efficiency level that increases MSP, the total equipment price ( EQP CUST ) to the customer is the sum of the baseline customer price ( EQP CUST BASE ) and the incremental customer price ( EQP CUST INCR ).

6.3 ASSUMPTIONS USED TO ESTIMATE WHOLESALER AND CONTRACTOR MARKUPS

DOE derived the wholesaler and contractor markups from three key assumptions about CAC costs. DOE based the wholesaler and mechan ical contractor markups on firm balance-sheet data, while it based the general contractor ma rkups on U.S. Census Bureau data for the commercial and instituti onal building construction industry. DOE obtained the firm balance sheets from the Heating, Air-conditioning & Refrigeration Distributors International (HARDI) 2008 Profit Planning Report and from the Air Conditioning Contractor s of America (ACCA). 1,2 HARDI and ACCA are trade associations representing wholesalers and mechanical contractors, respectively. DOE used the financial data fro m the 2002 US Census Bureau for developing general contractor markups in the same form as the balance sheet data for wholesalers and mechanical contractors. 3 These balance sheets break out the components of all costs incurred by

6-5firms that supply and install air conditioning equipment. a The key assumptions used to estimate markups using these financial data are:

• The firm balance sheets accurately represent the various average costs incurred by firms distributing and installing commercial ai r conditioning and heating equipment.

• These costs can be divided into two categorie s: (1) costs that vary in proportion to the MSP of commercial air conditioning and h eating equipment (variable costs); and (2) costs do not vary with the MSP of comme rcial air conditioning and heating equipment (fixed costs).

• Wholesaler and contractor prices vary in proportion to CAC and HP wholesaler and contractor costs included in the balance sheets.

In support of the first assumption, the balan ce sheets itemize firm costs into a number of expense categories, including dire ct costs to purchase or insta ll the equipment, operating labor and occupancy costs, and other operating costs an d profit. Although wholes alers and contractors tend to handle multiple commodity lines (including air conditioners, furnac es, and boilers), the data provide the most accu rate available indication of CAC and HP expenses.

Information obtained from the trade literature and selected heating, ventilating, and air conditioning (HVAC) wholesalers, contractors, and consultants support the second assumption. This information indicated that wholesaler and contractor markups vary according to the quantity of labor and materials used to distribute and inst all appliances, with mark ups on labor tending to be much higher than markups on materials. Th e obtained information described markups as varying much more in relation to sales volume than in relation to other factors, including appliance efficiency. This last fi nding strongly suggested that la bor inputs vary more with sales volume than with appliance cost or efficiency . DOE assumed a division of costs between those costs that do not scale with the MSP (labor a nd occupancy expenses), and those costs that do (operating expenses and profit). This division of costs led to the estimate of wholesaler and contractor markups described below.

In support of the third assumption, the HVAC wholesaler and contractor industry is competitive and customer demand for commercial h eating and air conditioning is inelastic, i.e., the demand is not expected to decrease significantly with an increase in price of equipment. The large number of HVAC firms listed in the 2002 Cens us indicates the competitive nature of the market. For example, there are more than 700 HVAC manufacturers, 4 6,000 wholesalers of heat pumps and air-conditioning equipment, 5 more than 37,000 general contractors, 6 and 87,000 HVAC contractors 7 listed in the 2002 Census. Following standard economic theory, competitive firms facing inelastic demand either set prices in line with costs or quickly go out of business. 8

6.4 ESTIMATION OF WHOLESALER MARKUPS

Wholesalers reported median data in a conf idential survey that HARDI conducted of member firms. 2 In the survey, HARDI itemized revenues and costs into cost categories, including direct equipment expenses (cost of g oods sold), labor expenses, occupancy expenses,

a Wholesalers and mechanical contractors to which these reports refer handle multiple commodity lines, including residential and commercial air-conditioners and warm-air furnaces.

6-6other operating expenses, and profit. DOE presents these data in full in appendix C, Detailed Data for Equipment Price Markups. Table 6.4.1 summarizes them as cost-per-dollar sales revenue in the first data column.

Table 6.4.1 Wholesaler Expenses and Markups

Descriptions Per Dollar Sales Revenue $ Per Dollar Cost of Goods $ Direct Cost of Equipment Sales: Cost of goods sold 0.730 1.000 Labor Expenses: Salaries and benefits 0.156 0.214 Occupancy Expense: Rent, maintenance, and utilities 0.031 0.042 Other Operating Expenses: Depreciation, advertising, and insurance. 0.052 0.071
Profit 0.031 0.042 Baseline Revenue: Baseline revenue earned per dollar cost of goods sold 1.370 Wholesaler Baseline Markup ( MU WHOLE BASE ) 1.370
Incremental Revenue: Increased revenue per dollar increase cost of goods sold 1.114 Incremental Markup ( MU WHOLE INCR ) 1.114 Source: Heating, Air Conditioning & Refrigeration Distributors International. 2008. 2008 Profit Report (2007 Data). 2

In this case, direct equipment expenses (cost of goods sold) represent about $0.73 per dollar sales revenue, so for every $1 wholesalers ta ke in as sales revenue, $0.73 is used to pay the direct equipment costs. Labor expenses represent $0.16 per dollar sales revenue, occupancy expenses represent $0.03, other operating expe nses represent $0.05, and profit accounts for $0.03 per dollar sales revenue.

DOE converted the expenses per dollar sales in to revenue per dollar cost of goods sold, by dividing each figure in the first data colu mn by $0.73 (i.e., cost of goods sold per dollar of sales revenue). The data in co lumn two show that, for every $1.00 the wholesaler spends on equipment costs, the wholesaler earns $1.00 in sales revenue to cover the equipment cost, $0.214 to cover labor costs, $0.042 to cover occupancy expenses, $0.071 for other operating expenses, and $0.042 in profits. This totals to $1.370 in sales revenue earned for every $1.00 spent on equipment costs. Therefore, th e wholesaler baseline markup ( MU WHOLE BASE ) is 1.37 ($1.37 ÷ $1.00).

DOE also used the data in column two to estimate the incremental markups. The incremental markup depends on which of the co sts in Table 6.4.1 are variable and which are fixed. For example, for a $1.00 increase in the MSP, if all of the other costs scale with the MSP (i.e., all costs are variable), the increase in wholesaler price will be $1.370, implying that the incremental markup is 1.370, or the same as the baseline markup. At the other extreme, if none of the other costs is variable, then a $1.00 increase in the MSP will lead to a $1.00 increase in the wholesaler price, for an incremental markup of 1.0. Actually, DOE believes that the labor and occupancy costs will be fixed and that the other operating costs and profit will scale with the MSP (i.e., be variable). In this case, for a $1.00 increase in the MSP, the wholesaler price will increase by $1.114, giving a wholesaler incremental markup ( MU WHOLE INCR ) of 1.114.

6-76.4.1 Estimation of Wholesaler Markup Probability Distribution

DOE characterized the markups developed from the above financial da ta with probability distributions from statistics published by the U.S. Census Bureau for wholesalers (see appendix C). The analysis provided a standard de viation on the markups of wholesaler firms in the U.S. DOE then applied the standard deviati on to the single-point baseline and incremental markups calculated above to create normal probability distributions for these markups.

Based on the analysis of U.S. Census data for wholesalers, DOE calculated a relative standard deviation as 7.7 percent as a percenta ge of the baseline mar kup of 1.362, which resulted in a standard deviation of 5.7 percent as described in appe ndix C. DOE assumed that the variation determined for the ba seline markup applied to the incr emental markup as well. For the baseline markup of 1.370, a standard deviation of 7.7 percent translates into an absolute value of 5.6 percent. For the incremental markup of 1.114, a relative standard deviation of 7.7 percent translates into an absolute value of 6.9 percent.

Figure 6.4.1 and Figure 6.4.2 show the probability distributions that DOE used to characterize the wholesaler ba seline and incremental markups.

Figure 6.4.2 Wholes aler Incremental Markup Probability Distribution Figure 6.4.1 Wholesaler Baseline Markup Probability Distribution

Note that for the incremental markup, the st andard deviation of 6.9 percent results in markup values that are less than 1.0. Since a ma rkup value of less than 1.0 would not allow the wholesaler to recover its costs, DOE trun cated all values less than 1.0 from the normal distribution as shown in Figure 6.4.2.

6.5 ESTIMATION OF MECHANICAL CONTRACTOR MARKUPS

The HVAC contractors, defined here as mech anical contractors, reported median cost data in an ACCA financial analysis of the HVAC industry. 3 These data are shown in Table 6.5.1.

6-8Table 6.5.1 Baseline Markup, All Mechanical Contractors

Description Contractor Expenses or Revenue

Per Dollar Sales Revenue $ Per Dollar Cost of Goods $ Direct Cost of Equipment Sales: Cost of goods sold 0.73 1.00 Gross Margin: Labor, occupancy, operating expenses, and profit 0.27 0.37
Revenue: Baseline revenue earned per dollar cost of goods 1.37 Baseline Markup ( MU MECH CONT BASE ) 1.37 Source: Air Conditioning Contractors of America. 2005. Financial Analysis for the HVACR Contracting Industry. 2

Data reported in this analysis are not as de tailed as that provided by the other sources, containing only cost of goods sold and gross margin. Since the gross margin is the sum of labor, occupancy expenses, operating expenses, and profit, the gross margin allows for the determination of the baseline markup. The first data column in Table 6.5.1 provides the cost of goods sold and gross margin as expenses per dollar sales revenue. The only important difference is that the direct cost of equipment sales in this table includes installation costs as well as the cost of goods sold. As shown in the table, the dir ect cost of sales represents about $0.73 per dollar sales revenue to the contractor and the gro ss margin is $0.27 per do llar sales revenue. The mechanical contractor expenditures per dollar sales revenue in Table 6.5.1 are quite similar to the wholesaler expenditures per dollar sales revenue reported in Table 6.4.1.

DOE converted these expenses per dollar sales into revenue per dollar cost of goods sold by dividing each figure in the first data column by $0.73. For every $1.00 the mechanical contractor spends on equipment co sts, the mechanical contractor earns $1.00 in sales revenue to cover the equipment cost, and $0.37 to cover the ot her costs. This totals $1.37 in sales revenue earned for every $1.00 spent on equipment costs, for a baseline markup ( MU MECH CONT BASE ) of 1.37 for mechanical contract ors, since the contractor earns $1.37 in sales revenue for every $1.00 spent to purchase the equipment.

6.5.1 Markups for Mechanical Contractors in the Replacement and New Construction Markets

The baseline markup derived above for mechanic al contractors is the average value for all contractors including the replacement and ne w construction markets. This section describes how DOE further derived the baseline and incremen tal markups for these latter two markets. As above, the ACCA financia l data provided gross ma rgin data, which allows for the determination of only the baseline markup for the two markets, since the gross margin is the sum of all contractor labor and operating expenses plus pr ofit. Calculation of the incremental markup uses Census Bureau data, because this was not possible with the ACCA data as the variable costs are not provided separately.

Table 6.5.2 summarizes the gross margin and resulting baseline markup data for all mechanical contractors that serve the replacement and new construction markets.

6-9Table 6.5.2 Baseline Markups for the Replacement and New Construction Markets, All
Mechanical Contractors

Description Contractor Expenses or Revenue by Market Type Replacement New Construction
Per Dollar Sales Revenue $ Per Dollar Cost of Goods $ Per Dollar Sales Revenue $ Per Dollar Cost of Goods $ Direct Cost of Equipment Sales: Cost of goods sold 0.70 1.00 0.75 1.00

Gross Margin: Labor, occupancy, operating expenses, and profit 0.30 0.43 0.25 0.33

Baseline Markup ( MU MECH CONT BASE ): Revenue per dollar cost of goods NA 1.43 NA 1.33

Source: Air Conditioning Contractors of America. 2005. Financial Analysis for the HVACR Contracting Industry. 3

Using the baseline markup data from Tabl e 6.5.2 and results of a financial analysis 3 , DOE calculated that the baseline markups for the replacement and new markets are 4.4 percent higher and 2.9 percent lower, respectively, than that for all mechanical contractors serving all markets.

DOE then used the ACCA data to calcu late the baseline markup of 1.32 for the residential and light commerc ial building construction section as shown in Table 6.5.3.

Table 6.5.3 Mechanical Contractor Expenses and Baseline Markup, Residential and Light Commercial

Description Contractor Expenses or Revenue
Per Dollar Sales Revenue $ Per Dollar Cost of Goods $ Direct Cost of Equipment Sales: Cost of goods sold 0.76 1.00 Gross Margin: Labor, occupancy, operating expenses, and profit 0.24 0.32 Baseline Markup ( MU MECH CONT BASE ): Revenue per dollar cost of goods 1.32 Source: Air Conditioning Contractors of America. 2005. Financial Analysis for the HVACR Contracting Industry. 3

The markup deviations derive d above (i.e., 4.4 percent higher and 2.9 percent of lower for the replacement and new construction markets, respectively) were then applied to the baseline markup of 1.32 for the re sidential and light commercial building construction section. This resulted in baseline mar kups of 1.38 and 1.28, respectively, for the replacement and new construction markets served by mechanical cont ractors for the residential and light commercial building construction.

Calculation of the incrementa l markups for each market type required separation of the fixed and variable costs. Since this was not possible using the ACCA data, DOE used more detailed 2002 Census Bureau data for all plumbing, heating, a nd air-conditioning contractors. 7

The Census Bureau data were used to calculate the baseline and increm ental markups as shown in Table 6.5.4.

6-10Table 6.5.4 Mechanical Contractor Expenses and Markups Based on Census Bureau Data

Description Contractor Expenses or Revenue
Per Dollar Sales Revenue $ Per Dollar Cost of Goods $ Direct Cost of Equipment Sales: Cost of goods sold 0.66 1.00 Labor Expenses: Salaries (indirect) and benefits 0.17 0.26 Occupancy Expense: Rent, maintenance, and utilities 0.02 0.03 Other Operating Expenses: Depreciation, advertising, and insurance. 0.03 0.05
Net Profit Before Taxes 0.12 0.18 Baseline Markup ( MU MECH BASE ): Revenue per dollar cost of goods 1.52 Incremental Markup ( MU MECH INCR ): Increased revenue per dollar increase cost of goods sold 1.23 Source: U.S. Census Bureau. 2002. Plumbing, Heating, and Air-Conditioning Contractors: 2002. Report EC02-231-238220, Table 4, Detailed Statistics for Establishments: 2002. 7

Using the data Table 6.5.4, the incremental markup is 19.1 percent lower than the baseline markup. DOE assumed that this devia tion applies equally to the baseline markups calculated for replacement of 1.38 and new constr uction markets of 1.28. This yields incremental markups of 1.12 and 1.04, respectively, for the re placement and new construction markets served by mechanical contractors.

6.5.2 Estimation of Mechanical Contract or Markup Probab ility Distribution

DOE characterized the markups develope d from the ACCA financial data with probability distributions through a statistical analysis of U.S. Census data for plumbing, heating, and air-conditioning contractors. The statistical analysis provi ded a standard deviation on the markups of mechanical contractors in the U.S. DOE then applied the standard deviation to the single-point baseline and incremental markups calculated above to create normal probability distributions for these markups.

Based on the analysis of U.S. Census data for mechanical contractors, DOE calculated a relative standard deviation of 3.7 percent for the baseline markup as described in appendix A. DOE assumed that the variation determined for the baseline markup applied to the incremental markup as well. For the baseline markup of 1.38 and 1.28 for the replacement and new construction markets, respectively, a relative stan dard deviation of 3.7 percent translates into respective absolute values of 0.051 and 0..047. Fo r the incremental markups of 1.12 and 1.04 for the replacement and new construction markets, re spectively, a standard deviation of 3.7 percent translates into respective absolute values of 0.041 and 0.038.

DOE calculated a relative standard deviation of 3.7 percent for m echanical contractor markups but applied the relative markups on a state-by-state basi s. Figure 6.5.1 illustrates the probability distribution that DOE used to characterize the mechanical contractor baseline and incremental markups for the replacement and new markets. The relative values are multiplied times the mean markups for all four categories of mechanical contractor markup: both baseline and incremental markups for both new constr uction and replacements. The probability of purchasing a CAC or heat pump unit is different in the different U.S. states, and the relative markup is different in each state. While the actual probability of a sale in a particular state depends on a number of climate, product-specific, regulatory, and population factors, Figure 6.5.1 shows what the distribution of rela tive markups looks like if population were the

6-11only determinant. The far right-hand bar shows, for example, that based on population, there is a 12.1 percent chance that a given CAC sale woul d be in California (which had an estimated 12.1 percent of the U.S. population in July, 2008). The relative mechanical contractor markup value for California is 1.037, which would be multiplied times the mean markup factor of 1.28 for a new baseline unit, yielding a mechanic al contractor markup of 1.327. If instead the incremental markup on a replacement unit were needed, the 1.037 relative markup value would be multiplied times the mean incremental markup f actor for replacement units of 1.12, yielding a mechanical contractor markup value of 1.161.

Figure 6.5.1 Residential and Light Commercial Mechanical Contractor Relative Markup Probability Distribution

6.6 ESTIMATION OF GENERAL CONTRACTOR MARKUPS

DOE derived markups for general contractor s from U.S. Census Bureau data for the commercial and institutional building construction sector. 4 This sector includes establishments primarily engaged in construction work, includi ng new construction work, additions, alterations, and repairs. The U.S. Census Bureau data for the construction sector include detailed statistics for establishments with payrolls, similar to the data reported by ACCA for wholesalers. The primary difference is that the U.S. Census Bureau reports itemized revenues and expenses for the construction industry as a whole in total dollars ra ther than in typical values for an average or representative business. Because of this, DOE assumed that the total dollar values that the U.S. Census Bureau reported, once converted to a percentage basis, represented revenues and expenses for an average or typical contracting business. Similar to the data for wholesalers, Table 6.6.1 summarizes the expenses for general cont ractors as expenses per dollar sales revenue in the first data column (appendix A contains the full set of data).

6-12Table 6.6.1 General Contractor Expenses and Markups

Description Wholesale Firm Expenses or Revenue
Per Dollar Sales Revenue $ Per Dollar Cost of Goods $ Direct Cost of Equipment Sales: Cost of goods sold 0.78 1.00 Labor Expenses: Salaries (indirect) and benefits 0.08 0.10 Occupancy Expense: Rent, maintenance, and utilities 0.02 0.03 Other Operating Expenses: Depreciation, advertising, and insurance. 0.01 0.01
Net Profit Before Taxes 0.12 0.15 Baseline Markup ( MU GEN CONT BASE ): Revenue per dollar cost of goods 1.29 Incremental Markup ( MU GEN CONT INCR ): Increased revenue per dollar increase cost of goods sold 1.17 Source: U.S. Census Bureau. 2002. Commercial and Institutional Building Construction: 2002. Report EC02-231-236220, Table 4, Detailed Statistics for Establishments: 2002. 7

For example, the direct cost of sales repres ents about $0.78 per dollar sales revenue to the general contractor. Labor expenses represent $0.0 8 per dollar sales revenu e, occupancy expenses represent $0.02 per dollar sales revenue, other operating expenses represent $0.01, and profit makes up $0.12 per dolla r sales revenue.

DOE converted these expenses per dollar sales into revenue per dollar cost of goods sold, by dividing each figure in the first data colu mn by $0.78. The data in column two show that, for every $1.00 the general contractor spends on equi pment costs, the general contractor earns $1.00 in sales revenue to cover the equipment co st, $0.10 to cover labor costs, $0.03 to cover occupancy expenses, $0.01 for other operating ex penses, and $0.15 in profits. This totals to $1.29 in sales revenue earned for every $1.00 sp ent on equipment costs. Thus, the general contractor baseline markup ( MU GEN CONT BASE ) is 1.29.

DOE was also able to use the data in colu mn two in the table above to estimate the incremental markups by being able to separate the fixed and variable costs. At one extreme, if all of the other costs scale with the equipment price (i.e., all costs are variable), the increase in general contractor price will be $1.29, implying th at the incremental markup is 1.29, or the same as the baseline markup. At the other extreme, if none of the other costs are variable, then a $1.00 increase in the equipment price will lead to a $1.0 0 increase in the general contractor price, for an incremental markup of 1.0. DOE believed the labor and occupancy costs to be fixed and the other operating costs and profit to scale with the e quipment price (i.e., be variable). In this case, for a $1.00 increase in the equipment price, the general contractor price will increase by $1.17, giving a general contractor incremental markup ( MU GEN CONT INCR ) of 1.17.

6.6.1 Estimation of General Contractor Markup Probability Distribution

DOE characterized the markups developed a bove with probability di stributions derived from a statistical analysis of U.S. Census data for general contractors engaged in commercial and institutional building construction. The statistical analysis provided a standard deviation on the markups of general contractors in the United States. DOE then applied the standard deviation to the single-point baseline and incremental markups calculated above to create normal probability distributions for these markups.

6-13Based on the analysis of U.S. Census data for general contractors, DOE calculated a standard deviation of 9.0 per cent for the baseline markup as described in appendix A. DOE assumed that the variation dete rmined for the baseline markup a pplied to the incremental markup as well. For the baseline markup of 1.29, a standard deviation of 9.0 percent translates to an absolute value of 0.116. For the incremental mark up of 1.17, a standard deviation of 9.0 percent translates to an absolute value of 0.105.

Figure 6.6.1 and Figure 6.6.2 show the relative probability distributions that DOE used to characterize the residential general contractor and commercial ge neral contractor markups. Both are for new construction, because general contract ors are not part of the distribution channel for replacement CACs. The same relative markups ap ply to both baseline and incremental markups, but they are multiplied times different mean valu es (1.29 for baseline, 1.17 for incremental). The state incremental values are applied in the same way as the mechanical contractor values discussed in section 6.5.2.

Figure 6.6.1 Residential General Contractor Relative Markup Probability Distribution Figure 6.6.2 Commercial General Contractor Relative Markup Probability Distribution

6.7 SALES TAX

The sales tax represents State and local sales taxes that are applied to the customer price of the packaged terminal equipment. The sales tax is a multiplicative factor that increases the customer equipment price. DOE derived sales ta xes representative of both State and local sales taxes from The Sales Tax Clearinghouse, 9 shown in Table 6.7.1.

6-14Table 6.7.1 State Sales Tax Rates (Percent)

State Combined State and Local
Tax Rate State Combined State and
Local Tax Rate State Combined State and
Local Tax Rate Alabama 8.15 Kentucky 6 North Dakota 5.75 Alaska 1.45 Louisiana 8.75 Ohio 6.85 Arizona 7.15 Maine 5 Oklahoma 8.1 Arkansas 8.2 Maryland 6 Oregon

-­ California 9.0 Massachusetts 5 Pennsylvania 6.25 Colorado 6.4 Michigan 6 Rhode Island 7 Connecticut 6 Minnesota 6.85 South Carolina 7.05 Delaware

-­ Mississippi 7 South Dakota 5.5 Dist. of Columbia 5.75 Missouri 7.10 Tennessee 9.4 Florida 6.7 Montana

-­ Texas 8.05 Georgia 6.95 Nebraska 6 Utah 6.7 Hawaii 4.4 Nevada 7.5 Vermont 6.05 Idaho 6.05 New Hampshire

-­ Virginia 5 Illinois 8.4 New Jersey 6.95 Washington 8.75 Indiana 7 New Mexico 6.4 West Virginia 6
Iowa 6.8 New York 8.25 Wisconsin 5.4
Kansas 6.9 North Carolina 6.8 Wyoming 5.40

The State level combined tax rates can be applied to the estimated value of State level CAC equipment shipments to obtain the total purchase cost to the customer located in any state.

The distribution of sales tax rates ranges from a minimum of zero percent to a maximum of 9.4 percent with a population-weighted m ean value of 6.99 percent, or approximately 7.0 percent. DOE applied sales taxes to the customer equipment price irrespective of the distribution channel and the market in which the customer is located.

6.8 OVERALL MARKUPS

DOE multiplied the wholesaler, mechanical a nd general contractor , and national account markups described above by the sales tax to obtain the overall ba seline and incremental markups shown in Table 6.8.1 and Table 6.8.2, respectively.

Table 6.8.1 Average Overall Baseline Markups
Replacement Market New Construction Market
Wholesaler 1.370 1.370
Mechanical Contractor 1.380 1.280
General Contractor

- 1.290
Sales Tax 1.071 1.071
Overall 2.025 2.422

Table 6.8.2 Average Overall Incremental Markups
Replacement Market New Construction Market
Wholesaler 1.114 1.114
Mechanical Contractor 1.120 1.040
General Contractor

- 1.170

6-15Sales Tax 1.071 1.071
Overall 1.336 1.452

6-16REFERENCES

1. Heating, Air Conditioning & Refrigeration Distributors International. 2008. 2008 Profit Report (2007 Data).

2. Air Conditioning Contract ors of America. 2005. Financial Analysis for the HVACR Contracting Industry.

3. U.S. Census Bureau. 2002. Commercial a nd Institutional Building Construction: 2002. Report EC02-231-236220.

4. U.S. Census Bureau. 2002. Air-Conditioning and Warm Air Heating Equipment and Commercial and Industrial Refrigeration Equipment Manufacturing: 2002. Report EC02-311-333415.

5. U.S. Census Bureau. 2005. Produc t Lines: 2002. Report EC02-42SL-LS.

6. U.S. Census Bureau. 2002. Commercial a nd Institutional Building Construction: 2002. Report EC02-231-236220.

7. U.S. Census Bureau. 2002. Plumbing, Hea ting, and Air-Conditioning Contractors: 2002. Report EC02-231-238220.

8. Pindyck, R. and D. Rubinfeld, Microeconomices, Prentice Hall. 2000.

9. The Sales Tax Clearinghouse at https://thestc.com/STRates.stm (Accessed on June 4, 2009)

6-17CHAPTER 7. ENERGY USE CHARACTERIZATION FOR RESIDENTIAL AIR-CONDITIONING AND HEAT PUMP EQUIPMENT

TABLE OF CONTENTS

7.1 Introduction

.................................................................................................................. .... 7-1 7.1.1 General Approach to the Energy Use Analysis – Residential

............................. 7-1 7.1.2 General Approach to the Energy Use Analysis – Commercial

............................ 7-3 7.1.3 Overview of Energy Us e Analysis Inputs

............................................................ 7-4 7.2 ANALYZED RECS HOUSEHOLDS

................................................................................ 7-4 7.3 BASELINE ANNUAL SPACE-COOLING ENERGY USE – RESIDENTIAL

............... 7-5 7.3.1 Methodology for Estimating Stock Annual Space-Cooling Energy Use

............. 7-6 7.3.2 Stock Annual Space-Cooling Energy Use

........................................................... 7-7 7.3.3 Stock Space-Cooling Efficiency (SEER)

............................................................. 7-9 7.3.4 Estimating Baseline Annual Space-Cooling Energy Use

.................................. 7-12 7.4 BASELINE ANNUAL SPACE-HEATING ENERGY USE FOR CHP EQUIPMENTRESIDENTIAL

................................................................................................................. 7- 13 7.4.1 Estimating Stock Annual Space-Heating Energy Use

....................................... 7-14 7.4.2 Stock Space-Heating Efficiency (HSPF)

........................................................... 7-16 7.4.3 Estimating Baseline Annual Space-Heating Energy Use

.................................. 7-18 7.5 BASELINE RESIDENTIAL COOLING AND HEATING RESULTS-ADJUSTED FOR RECS SAMPLE WEIGHTS

.................................................................................... 7-19
7.6 BASELINE COMMERCIAL CAC AND CHP ENERGY USE

...................................... 7-20
7.7 OVERVIEW OF COMMERCIAL ENERGY SIMULATION APPROACH

................. 7-21 7.7.1 Simulation Tool Description

.............................................................................. 7-21 7.7.2 Efficiency Levels Analyzed and Corre sponding Simulation Parameters

.......... 7-22 7.7.3 Small Office Building Characteristics

............................................................... 7-23 7.7.4 Building Operating Characteristics

.................................................................... 7-24 7.7.5 Building Mechanical Systems and Equipment

.................................................. 7-27 7.8 BASELINE COMMERCIAL ENERGY DISTRIBUTION

............................................. 7-27 7.9 COMMERCIAL ENERGY FOR INTERMEDIATE EFFICIENCY LEVELS

............... 7-29 7.10 MARKET BASELINE SPACE-COOLING AND SPACE-HEATING EFFICIENCIES7-29 7.11 ESTABLISHMENT OF GEOGRAPHIC REGIONS FOR STANDARDS ANALYSIS AND CORRESPONDING REGIONAL ENERGY CONSUMPTION BY EFFICIENCY LEVEL

...................................................................................................... 7-32

7-iLIST OF TABLES

Table 7.3.1. The 30-Year Average CDD (1978–2007) and the 2005 CDD for the Nine Census Divisions and the Four Large States

........................................................ 7-7 Table 7.3.2. Weather Adjusted Space-Cooling Ener gy Consumption Statistics at Regional Level (CAC-Stock)

.............................................................................................. 7-8 Table 7.3.3. Weather Adjusted Space-Cooling Ener gy Consumption Statistics at Regional Level (CHP-Stock)

............................................................................................... 7-8 Table 7.3.4. Number of Observati ons for Each Ag e Group

...................................................... 7-10 Table 7.3.5. Average Annual Shipped Space-Cooling Efficiency

............................................. 7-12 Table 7.3.6. Baseline (13 SEER) Space-Coolin g Energy Consumption Statistics at Regional Level (CAC)

....................................................................................... 7-13 Table 7.3.7. Baseline (13 SEER) Space-Coolin g Energy Consumption Statistics at Regional Level (CHP)

........................................................................................ 7-13 Table 7.4.1. 30-Year Average HDD (1978–2007) and the 2005 HDD for the Nine Census Divisions and the Four Large States

.................................................................. 7-15 Table 7.4.2. Statistics of Annual Weather-Adju sted Space-Heating Energy Consumption for RECS-Stock CHP at Regional Level

........................................................... 7-15 Table 7.4.3. Average Annual H eating Pump HSPF

.................................................................. 7-18 Table 7.4.4. Baseline (13 SEER) Space-Heatin g Energy Consumption Statistics at Regional Level(CHP)

......................................................................................... 7-18 Table 7.7.1. CAC and CHP Blower and Characteristics Used in Modeling Commercial Cooling and Heating Energy Use

...................................................................... 7-23 Table 7.10.1. CAC and CHP Efficiency Di stributions Estimated for 2007

.............................. 7-31 Table 7.10.2. CAC and CHP Efficiency Distribu tions Estimated for Market Baseline

............ 7-32 Table 7.11.1. Proposed Climate Regions for Regional Standards

............................................. 7-33 Table 7.11.2. Split-System Air Conditioners: Aver age Annual Energy Use by Efficiency Level for Coil-Only Systems

............................................................................. 7-34 Table 7.11.3. Split-System Air Conditioners: Aver age Annual Energy Use by Efficiency Level—Blower-Coil Systems

............................................................................ 7-34 Table 7.11.4. Split-System Heat Pumps: Aver age Annual Energy Use by Efficiency Level

.................................................................................................................. 7-35 Table 7.11.5. Single-Package Air Conditione rs: Average Annual Energy Use by Efficiency Level

................................................................................................. 7-35 Table 7.11.6. Single-Package Heat Pumps: Av erage Annual Energy Use by Efficiency Level

.................................................................................................................. 7-36

LIST OF FIGURES

Figure 7.1.1. Flow Diagram for the Determina tion of Annual Space-Cooling Energy for Residential CAC and CHPs

................................................................................. 7-2 Figure 7.1.2. Flow Diagram for the Determina tion of Annual Space-Heating Energy for Residential CHPs

................................................................................................. 7-3Figure 7.1.3. Flow Diagram for the Determination of Annual Space-Cooling and SpaceHeating Energy for CAC and CH Ps in Commercial Use

.................................... 7-4

7-iiFigure 7.3.1. National Distribution of Weat her-Adjusted Space-Cooling Energy for RECS Observations

............................................................................................. 7-9 Figure 7.3.2. National Distribution of Weathe r-Adjusted Space-Cooling Energy for CHPRECS Observations

............................................................................................. 7-9 Figure 7.3.3. The Distribution of CACs in the RECS Sample by Age Groups

......................... 7-10 Figure 7.3.4. The Distribution of CHPs in the RECS Sample by Age Groups

......................... 7-11 Figure 7.3.5. Distribution of RECS House holds with CACs by Vintage

.................................. 7-11 Figure 7.4.1. National Distribution of Weathe r-Adjusted Space-Heating Energy for RECS Observations

...................................................................................................... 7-16 Figure 7.4.2. Distribution of Households with Heating-Performance Heat Pumps by Age Groups

................................................................................................................ 7-17 Figure 7.4.3. Distribution of RECS Households with Central Heat Pumps by Vintage

........... 7-17 Figure 7.5.1. Baseline National Cooling Energy Distribution for CAC – Residential

.............. 7-19 Figure 7.5.2. Baseline National Cooling Energy Distribution for CHP – Residential

.............. 7-19 Figure 7.5.3. Baseline National Heating Energy Distribution for CHP – Residential

............... 7-20 Figure 7.7.1. Small Office Building Design View

..................................................................... 7-24 Figure 7.7.2. Small Office Building HVAC Zoning

.................................................................. 7-24 Figure 7.7.3. Small Office Lighting Schedule

........................................................................... 7-25 Figure 7.7.4. Small Office Plug Load Schedule

........................................................................ 7-26 Figure 7.7.5. Small Office Occupancy Schedule

....................................................................... 7-26 Figure 7.7.6. Small Office Thermo stat Set Point Schedule

....................................................... 7-27 Figure 7.8.1. Baseline National Cooling Energy Distribution for CAC-Commercial, Weighted

............................................................................................................ 7-28 Figure 7.8.2. Baseline National Cooling Energy Distribution for CHP-Commercial, Weighted

............................................................................................................ 7-28 Figure 7.8.3. Baseline National Heating Energy Distribution for CHP-Commercial, Weighted

............................................................................................................ 7-29

7-iii7.1 INTRODUCTION

The energy use analysis provides estimate s of the distribution of annual energy consumption for central air c onditioner (CAC) and central heat pump (CHP) equipment at the base case ( i.e. , with no new standards) and at efficien cy standard levels considered in the analysis. This information is used in the subs equent life-cycle cost (LCC) and payback period (PBP) analyses (chapter 8 of the technical s upport document [TSD]), which in turn provides the raw energy use data for the national impacts analys es (chapter 11 of the TSD). Both energy use in the residential sector customers and to the commercial sector customer are considered. In the energy use analysis, the United States (U.S.) Department of Energy (DOE) developed energy consumption estimates for four equipment classes analyzed in the engineering analysis (chapter 5 of the TSD). For one equipment class, split-sy stem air conditioners, tw o installation methods were separately considered: coil-only, where th e indoor furnace fan is not replaced for higher efficiency equipment, and blower-coil, where the indoor blower is replaced, corresponding to the similar breakdown of this equipment cl ass in the engineering analysis.

7.1.1 General Approach to the Energy Use Analysis – Residential

The general approach adopted in the energy use analysis for CAC equipment used in residences was to utilize energy use and house hold characteristics data from the DOE Energy Information Agency (EIA) 2005 Residential Energy Consumpti on Survey (RECS) to provide estimates of cooling and heating energy fo r the sample households using CAC and CHP equipment. This estimate reflects household stoc k equipment efficiency levels. The energy use estimates are then adjusted to reflect long te rm average weather cond itions and then further adjusted to reflect equipment energy consump tion for the same households assuming that they were using new equipment as would be purchased in 2016 under a base case standards scenario.

A sample population of U.S. homes using CA C and CHP equipment was first identified from the RECS households surveyed. This sample provided a dataset of cooling and heating energy use for 2005 for households with CACs and CHPs. This data were then adjusted (weather-normalized) to reflect corresponding ener gy-use figures for typical long-term climate conditions. Historical efficiency data for shipped CAC and CHP equipment was used in conjunction with equipment age information from RECS to estimate the stock equipment efficiency for each household record used in the analysis. The annual energy consumption for equipment in the 2016 base case ( i.e. , no new standards) was then calculated for each equipment class by multiplying the weather-adjusted cooling or heating energy use for each RECS household by the ratio of the efficiency ( e.g. , SEER) of the stock unit in that household to that of an assumed efficiency for that household in th e 2016 base case. This 2016 base case provides an efficiency level likely to be purchased fo r each household assuming a new CAC or CHP purchase in that year. The 2016 efficiency levels used for each househol d were selected at random from a distribution of shippe d efficiencies developed for ea ch product class. This base case is also referred to as the market baseline case, since the efficiency distribution is representative of the current market for CAC and CHP equipment.

Once the base case cooling energy use was established for a selected RECS household record, the corresponding annual cooling energy consumption for higher efficiencies under new standard scenarios was calculated by multiply ing the cooling energy consumption for each

7-1household in the base case by the ratio of the seas onal energy efficiency ratio (SEER) in the base case to that of the SEER in the standards case. In the case of heating energy use for heat pumps the corresponding household annual heat pump heating energy consumption under new standard scenarios was calculated by multiplying the he at pump heating energy consumption for each household in the base case by the ratio of the heating seasonal performance factor (HSPF) in the base case to the HSPF in the standards case. Figure 7.1.1 and Figure 7.1.2 provide a flow diagram on calculation of cooling and heating energy for the residential energy use analysis.

RECS Baseline SEER Market Baseline Stock Household (SEER 13) SEER Standard Level Annual Cooling

Estimated SEER of Stock CAC or CHP Distribution SEER Energy (Weather Normalized)

RECS Age of Household CAC or CHP Baseline Market Baseline Standard Level Annual Cooling Annual Cooling Annual Cooling Energy Use Energy Use Energy Use

AHRI Shipment Average SEER CAC and CHP

Figure 7.1.1. Flow Diagram for the Determin ation of Annual Space-Cooling Energy for Residential CAC and CHPs

7-2RECS Stock Household Annual Heating Energy (Weather Normalized)

RECS Age of Household CHP Baseline SEER (HSPF 7.7)

Baseline Annual Heating Energy Use Market Baseline HSPF Distribution

Market Baseline Annual Heating Energy Use Standard Level HSPF

Standard Level Annual Heating Energy Use Estimated HSPF of Stock
CHP

AHRI Shipment Average HSPF by Vintage
CHP

Figure 7.1.2. Flow Diagram for the Determin ation of Annual Space-Heating Energy for Residential CHPs

7.1.2 General Approach to the Energy Use Analysis – Commercial

DOE also developed estimates for the annual energy use for CAC and CHP sold into the commercial building market. The commercial market is estimated to use approximately seven percent of all CAC and CHP equipment. For the commercial analysis, DOE relied on the use of the EnergyPlus building simulation software to estimate the energy consumption of this equipment at four specific efficiency levels-fro m baseline to the max t ech level-for 237 climates around the United States for a typical commercia l application, a small office building. DOE extracted equipment sizing, supply fan, condenser and heater energy use from these simulations. DOE then used these results to develop es timates of annual energy use for CAC and CHP equipment at other efficiency levels defined in the engineering analysis via interpolation between the efficiency levels simulated. Figure 7.1.3 provi des a flow diagram for the calculation of CAC and CHP cooling and heating energy for the commercial energy use analysis.

7-3Figure 7.1.3. Flow Diagram for the Determination of Annual Space-Cooling and SpaceHeating Energy for CAC and CHPs in Commercial Use

7.1.3 Overview of Energy Use Analysis Inputs

The following are the principal inputs to the residential energy use analysis:

• Household cooling and heating energy from 2005 RECS

• CAC and CHP equipment age information for the RECS households

• Historical state av erage monthly cooling and hea ting degree day data (1978–2007)

• Historical average cooling and heating efficiency data for CAC and CHP from AHRI

• Base case efficiency distributions for 2016 developed for this analysis

• Engineering efficiency levels to be analyzed

• The following are the principal inputs to the commercial energy use analysis:

• Engineering efficiency levels to be analyzed

• Location specific weather file data for use with building simulation tool

• Population-based weighting factors for each weather file

7.2 ANALYZED RECS HOUSEHOLDS

The 2005 RECS includes data for 4,382 housing units, of which 2,317 were reported to have “CAC only” cooling systems. These include 416 housing units reporting their CAC unit also being cooling-performance heat pumps. Th e number of households actually included in the LCC and PBP analyses were 1,854 for the CAC systems and 339 for heat pumps. Out of the 1901 (2317-416) households that could have been potentially considered for analysis of CAC energy consumption, 47 were not included in the analysis for the following reasons:

• the CAC system was reported as not being used (40 households), and

Small Office Building Model EnergyPlus Simulation Tool

CAC or CHP Characteristics for Four Selected Efficiency Levels TMY Weather
Data Bldg. Annual Cooling, Heating, Fan Energy Use Zone Peak Equipment Sizes

Annual Cooling, Heating, Fan Energy Use for Selected Efficiency Levels (Normalized to 3-Ton unit) Market Baseline Annual Cooling , Heating, and Fan Energy Use Market Baseline SEER /HSPF
Distribution Standard Level SEER/HSPF

Standard Level Annual Cooling , Heating, and Fan Energy Use

7-4• the household reported a “heat pump” being the main heating equipment, contradicting a second response that their CAC system is not a heat pump (7 households).

For the seven households with conflicting res ponses, it was considered that the response regarding the main heating equipment being a heat pump should override the secondary response and these records were included in the set for analyzing energy consumption for heat pumps.

For the heat pumps, out of the 423 (416+7) candidate households, DOE removed 84 for the following reasons:

• The system was reportedly not being used (6 households).

• The survey responses reported a non-furnace heating equipment ( i.e. , heating stove, fireplace, built-in wall furnaces etc. being the main heating equipment), thus implying that the heating energy use reported for the household should not be primarily attributed to the heat pump (17 households).

• Some households indicated a warm air furnace as the main heating equipment and no electrical energy use for space heating implying that the heat pump function is not used at all or that the RECS may be reporting the “heat pump” energy consumption or presence in error (36 households), and

• Some households report a warm air furnace as well as heat pump, but questions on usage of any complementary fuel were skipped. Th is led to an ambiguity about whether the heating energy use reported from the conditional demand mode l was reported as representative of a heat pump or an electric furnace. Barring more detail on the analysis of these records by EIA, they were remove d from consideration in DOE’s analysis (25 households).

7.3 BASELINE ANNUAL SPACE-COOLING ENERGY USE – RESIDENTIAL

In order to estimate the energy savings for higher standards, DOE first established estimates of cooling and heating energy consumption for baseline equipment based on energy consumption in the current stock and product effi ciency assumptions appropriate to the stock equipment and the efficiency of baseline products . The energy consumption of CACs and CHPs in the equipment stock is related to the capacity and efficiency of these products, the climate, and individual household use patterns. The efficiency of the equipmen t in the building stock also varies depending on the vintage. The energy cons umption of residential air-conditioners and heat pumps in the current stock and estimates of the efficiency in the current stock are used in conjunction with the efficiencies of baseline e quipment to provide an estimate of energy consumption of baseline equipmen t. The baseline annual space-c ooling energy consumption for residential air conditioners a nd cooling-performance heat pumps was estimated for each RECS observation using equation 7.3.1.

SEER

res

_ stock UEC = UEC × Eq. 7.3.1

res

_ base

_ c res

_ stock

_ c SEER base

Where:

7-5UEC res_base_c = the baseline annual unit energy consumption for space-cooling,
UEC res_stock_c = the annual unit energy consumption space-cooling associated with the stock equipment,
SEER base = the space-cooling efficiency associated with the baseline equipment, and
SEER res_stock_c = the space-cooling efficiency associated with the stock equipment.

Thus, once the annual space-cooling energy consumption associated with the stock equipment, UEC res_stock_c , and the space-cooling efficiency, SEER res_stock_c , are determined; the baseline annual space-cooling energy consump tion is estimated. In the next section, the methodology for obtaining UEC res_stock_c and SEER res_stock are discussed.

7.3.1 Methodology for Estimating Stoc k Annual Space-Cooling Energy Use

The stock annual space cooling energy cons umption was estimated based on data from the 2005 RECS. This survey contains data on household characteristics, end use energy consumption, general location in the United States (limited to location within census division and four large states; New York, Florida, Texas and California), and a pproximate heating and cooling degree days for each sample location for the year of the survey. The latter two statistics are purposefully kept general or sufficiently masked by EIA to preclude identification of the surveyed residences.

The household energy consumption for the indi vidual surveyed households in RECS are obtained by EIA from the energy suppliers via monthly energy bill records. EIA uses a conditional demand analysis (CDA) 1 model to further breakdown the household energy use into end-use energy consumption estimates ( e.g. , cooling, heating, lighting, and hot water energy) which it reports as annual end-use energy in th e survey results. The cooling energy use for the selected households with CAC or CHP products represents th e cooling energy consumption associated with the stock equipment for 2005. Because 2005 may not be representative of typical weather for that location, the cooling energy cons umption associated with the stock equipment in the RECS households are first adjusted (wea ther normalized) using 30-year-average (1978– 2007) cooling degree day (CDD) data (base 65 °F) and Eq. 7.3.2:

CDD 30 _ yr

_ avg UEC

res

_ stock

_ c = UEC

res

_ stock

_ c

_ non

− adj × CDD Eq. 7.3.2

res

_ stock _ 2005

Where:

UEC res_stock_c_non-adj = annual space-cooling energy consumption associated with the stock equipment, extracted dir ectly from RECS household data,
UEC res_stock_c = annual space-cooling consumption associated with the stock equipment, adjusted by using 30-year average CDD data for the RECS location,
CDD res_stock_2005 = CDD in 2005 for the specific Ce nsus Division or state where the housing unit is located, and
CDD 30_yr_avg = 30-year average CDD (1978–2007) for the specific Census Division or state where th e housing unit is located.

7-67.3.2 Stock Annual Space-Cooling Energy Use

DOE first weather-normalized the cooling en ergy use data for the selected RECS households to better reflect long term aver age weather conditions for each location. DOE obtained CDD data for each state on a monthly basis for 1978–2007 from the National Oceanic and Atmospheric Administration (NOAA) Na tional Climatic Data Center (NCDC). 2 DOE aggregated the monthly data for each year to produce annual CDD data for each state. These were then further aggregated geographically to the specific census divisions or four large state geographic regions used by RECS. These states in cluded in each of these geographic regions are shown in Table 7.3.1.

In estimating annual CDD for each census divi sion, the annual CDD for the states in each division are weighted according to the population in the component states for the specific year. Population data from 1978 to 2007 were deve loped based on 1980, 1990, and 2000 U.S. Census Bureau data, 3 with estimates for other years obtained by linear interpolation or extrapolation as necessary. The resulting 30-year average CDD an d the 2005 CDD for the regions are shown in Table 7.3.1.

Table 7.3.1. The 30-Year Average CDD (1978–2007) and the 2005 CDD for the Nine Census Divisions and the Four Large States

Division States 30-Year Average CDD 2005 CDD

1: New England Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont 462 579

2: Middle Atlantic New Jersey, Pennsylvania 737 991
3: East North Central Indiana, Illinois, Michigan, Ohio, Wisconsin 758 983
4: West North Central Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota 989 1,171

5: South Atlantic Delaware, District of Columbia, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia 1,382 1,486

6: East South Central Alabama, Kentucky, Mississippi, Tennessee 1,620 1,747
7: West South Central Arkansas, Louisiana, Oklahoma 2,215 2,402
8: Mountain Arizona, Colorado, Idaho, New Mexico, Montana, Utah, Nevada, Wyoming 1,318 1,498

9: Pacific Alaska, Hawaii, Oregon, Washington 226 226 Four Large States New York 654 943
California 949 837
Texas 2,711 2,908
Florida 3,505 3,436

Based on the 2005 RECS annual space-cooling energy consumption data and the CDD data, the weather-adjusted a nnual space-cooling energy consumption for each household was obtained by using Eq. 7.3.2. Statistics showing the weather-adjusted annual space-cooling energy consumption for the households that have air- conditioners are shown in Table 7.3.2. Statistics showing the weather-adjusted annual space-coolin g energy consumption for the households that have heat pumps are shown in

7-7Table 7.3.3. The frequency distribution of the weather-adjusted annual household energy consumption for space-cooling for CAC and CH P for the RECS observations are shown in Figure 7.3.1 and Figure 7.3.2.

Table 7.3.2. Weather Adjusted Spa ce-Cooling Energy Consumption Statistics at Regional Level (CAC-Stock)

Division or State Number of Observations Min kilowatt hours per

year (kWh/yr) Max kWh/yr Average kWh/yr

New England 50 56 4,186 1,229
Middle Atlantic 127 289 5,420 1,650
East North Central 346 130 9,459 1,477
West North Central 224 207 9,882 2,067
South Atlantic 233 152 8,628 2,952
East South Central 173 331 11,573 3,653
West South Central 79 647 12,359 4,070
Mountain 130 65 26,078 3,167
Pacific 23 89 3,610 1,273
New York 34 333 5,361 1,295
California 160 36 17,335 1,835
Texas 181 44 29,326 5,780
Florida 94 1,508 14,688 6,104
National 1,854 36 29,326 2,851

Table 7.3.3. Weather Adjusted Spa ce-Cooling Energy Consumption Statistics at Regional Level (CHP-Stock)

Division or State Number of Observations Min kWh/yr Max kWh/yr Average kWh/yr New England 1 432 432 432
Middle Atlantic 10 214 2,182 1,460
East North Central 20 455 6,938 2,315
West North Central 12 234 5,634 2,413
South Atlantic 108 445 11,059 3,442
East South Central 54 1,157 11,586 3,968
West South Central 6 1,246 9,573 4,545
Mountain 23 3,220 12,893 7,194
Pacific 13 78 3,221 1,060
New York 1 761 761 761
California 11 312 6,449 2,492
Texas 15 2,166 11,363 6,423
Florida 65 1,805 17,380 6,738
National 339 78 17,380 4,264

7-80% 2% 4% 6% 8% 10% 12% 14% 16% 18%Percentage of Obersavtions

Weather-Adjusted CAC Cooling Energy from RECS (kWh/yr)

Figure 7.3.1. National Distribution of Weath er-Adjusted Space-Coo ling Energy for RECS Observations

0% 2% 4% 6% 8% 10% 12% 14%Percentage of Obersavtions

Weather-Adjusted CHP Cooling Energy from RECS (kWh/yr)

Figure 7.3.2. National Distribution of Weath er-Adjusted Space-Coo ling Energy for CHPRECS Observations

7.3.3 Stock Space-Cooling Efficiency (SEER)

To estimate annual space-cooling energy consumption data at the baseline and higher efficiency levels, DOE relies on the cooling and heating energy calculated for the stock households and the historic space-cooling efficiency levels of the stock equipment, SEER res_stock

. The space-cooling efficiency of stock equipment is related to the vintage of the equipment. In the 2005 RECS database, the age of the equipment is reported in te rms of age groups and not the specific vintage year. The five ag e groups are “less than 2 years old,” “2 to 4 years old,” “5 to

7-99 years old,” “10 to 19 years old,” and “20 years or older.” The da ta also include one additional age category: “as old as the home.” In RECS the y ears of construction of each residence for older homes are also reported in age bands though the sp ecific year of constructi on is indicated for the newer homes. DOE assumed that the age of the CAC system, within a given age group in the general population would be approx imately uniformly distributed throughout the range of the age band. For example, for the CAC systems in the “less than 2 years old” age group, it was assumed that 50 percent of heat pumps were one year old and the other 50 percent were 2 years old. Similar technique was used in ascertaining the probable vintage year of the home and the equipment when the equipment was reported to be the age of the home. The resulting age distribution of the CACs and CHPs in the RECS households identified for analysis are shown in Table 7.3.4 and graphically in Figu re 7.3.3 and Figure 7.3.4, respectively.

Table 7.3.4. Number of Observations for Each Age Group
Equipment Type Less than 2 Years Old 2 to 4 Years Old 5 to 9 Years Old 10 to 19 Years Old 20 Years or Older Total

Central Air 243 321 472 502 316 1854 Conditioners 13.1% 17.3% 25.5% 27.1% 17.0% 100% Cooling-Performance 57 61 104 89 28 339 Heat Pump 16.8% 18.0% 30.7% 26.3% 8.3% 100%

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0%Percent Of households

Less than 2 2 to 4 years 5 to 9 years 10 to 19 20 years or years old old old years old older
Age of CAC Systems

Figure 7.3.3. The Distribution of CACs in the RECS Sample by Age Groups

Once the age group in which the household e quipment falls into was established, DOE estimated the vintage of the equipment for each household in each age group by random assignment using the uniform age distributi on assumption for each age group and the known 2005 survey year. For the 20-year and older ag e group, all equipment were assumed to be between 20 and 29 years old with the actual vintage assigned using a uniform distribution. The

7-10resulting vintage distribution of the residential air conditioners and heat pumps in the overall sample is shown in Figure 7.3.5.

DOE estimated the stock cooling SEER for each household using equipment vintage and average shipped efficiency for each vintage year. The latter was developed from AHRI data 4 and is shown in Table 7.3.5.

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0%

Less than 2 years

old 2 to 4 years old 5 to 9 years old 10 to 19 years old 20 years
or older

Age of Heat Pump SystemsPercent Of households

Figure 7.3.4. The Distribution of CHPs in the RECS Sample by Age Groups

0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0%1,9761,9781,9801,9821,9841,9861,9881,9901,9921,9941,9961,9982,0002,0022,004

Vintage year of CAC Equipm entPercent of Households

Figure 7.3.5. Distribution of RECS Hous eholds with CACs by Vintage

7-11Table 7.3.5. Average Annual Shipped Space-Cooling Efficiency

Year Central A/C (SEER) Heat Pump (SEER)

1976 7.15 6.87
1977 7.18 6.89
1978 7.41 7.24
1979 7.45 7.34
1980 7.51 7.51
1981 7.73 7.70
1982 8.30 7.79
1983 8.44 8.23
1984 8.70 8.45
1985 8.84 8.56

1986 8.87 8.70
1987 8.95 8.93
1988 9.11 9.13
1989 9.23 9.26
1990 9.25 9.41
1991 9.44 9.73
1992 10.43 10.56
1993 10.52 10.82
1994 10.58 10.89
1995 10.64 10.93
1996 10.63 10.95
1997 10.62 10.93
1998 10.23 10.52
1999 10.86 11.24
2000 10.95 11.23
2001 11.07 11.31
2002 11.07 11.32
2003 11.22 11.48
2004 11.32 11.58
2005 11.33 11.69

7.3.4 Estimating Baseline Annual Space-Cooling Energy Use

For each class of equipment, the baseline annual space-cooling energy consumption for each equipment type (air-conditioner or heat pump) was estimated by using Eq. 7.3.2. The key inputs are the weather-adjusted annual space-c ooling energy consumption derived from the 2005 RECS data, the stock space-cooling efficiency estimates for air conditioners and heat pumps from Table 7.3.5, and the baseline cooling efficiency, 13 SEER.

Statistics for the baseline space-cooling energy consumption for RECS households at regional and national level are shown in Table 7.3.6 for air conditioners and Table 7.3.7 for heat

pumps.

7-12Table 7.3.6. Baseline (13 SEER) Space-Cooling Ener gy Consumption Statistics at Regional Level (CAC)

Division or State Number of Observations Min kWh/yr Max kWh/yr Average kWh/yr New England 50 45 3,526 987
Middle Atlantic 127 246 4,550 1,270
East North Central 346 104 7,967 1,148
West North Central 224 145 8,324 1,593
South Atlantic 233 119 7,513 2,314
East South Central 173 247 10,078 2,864
West South Central 79 433 10,115 3,082
Mountain 130 53 21,344 2,536
Pacific 23 78 3074 1,029
New York 34 229 3645 1,016
California 160 24 15,095 1,440
Texas 181 30 25,536 4,520
Florida 94 1,234 12,372 4,860
National 1,854 24 25,536 2,231

Table 7.3.7. Baseline (13 SEER) Space-Cooling Ener gy Consumption Statistics at Regional Level (CHP)

Division or State Number of Observations Min kWh/yr Max kWh/yr Average kWh/yr New England 1 249 249 249
Middle Atlantic 10 118 1,823 1,236
East North Central 20 323 5,566 1,882
West North Central 12 190 4,911 1,962
South Atlantic 108 320 9,417 2,779
East South Central 54 909 9,465 3,203
West South Central 6 973 6,797 3,568
Mountain 23 2,424 8,876 5,616
Pacific 13 68 2,339 842
New York 1 663 663 663
California 11 263 5,492 1,960
Texas 15 1,473 9,191 5,278
Florida 65 1,311 13,677 5,339
National 339 68 13,677 3,412

7.4 BASELINE ANNUAL SPACE-HEATING ENERGY USE FOR CHP EQUIPMENT- RESIDENTIAL

The baseline annual space-heating energy c onsumption for the CHP system is estimated following procedures similar to that for estimating the baseline annual space-cooling energy consumption. The baseline annual space-heating energy consumption for residential heat pumps is estimated by using the following equation:

HSPF

res

_ stock UEC = UEC × Eq. 7.4.1

res

_ base

_ h res

_ stock

_ h HSPF base

7-13Where,

UEC res_base_h = the baseline annual space-heating energy consumption
UEC res_stock_h = the annual space-heating energy c onsumption associated with the stock heat pump
HSPF res_stock_h = the space-heating efficiency associated with the stock equipment
HSPF base = the space-heating efficiency associated with baseline equipment

7.4.1 Estimating Stock Annual Space-Heating Energy Use

The annual space-heating energy consumpti on for the CHP systems in the stock was obtained from the 2005 RECS database for the heat pump sample identified. To account for the variation in weather conditions for the year 2005 from statistical nor mals, the annual spaceheating energy consumption in 2005 was adjust ed by using the following equation:

HDD 30 _ yr

_ avg UEC

res

_ stock

_ h = UEC

res

_ stock

_ h

_ non

− adj ⋅ HDD Eq. 7.4.2

res

_ stock

Where:

UEC res_stock_h = annual space-heating energy consumption associated with the stock equipment after weather-adjustment,
UEC res_stock_h_non-adj = annual space-heating energy c onsumption, obtained directly from RECS database,
HDD 30_yr_avg = 30-year (1978-2007) average heating degree day (HDD, base 65 °F) for the census division or st ate where the household is located, and
HDD res-stock = HDD in 2005 (base 65 °F) for the census division or state where the household is located.

State-wise monthly HDD data from 1978 to 2007 were obtained from National Oceanic and Atmospheric Administra tion (NOAA) database center. 2 DOE aggregated the monthly data for each year to produce annual HDD for each st ate. The state annual HDD data were used to derive annual HDD for the regions identified in RECS (census divisions and separately four large states). In estimating divisional annual HDD, the annual HDD values for states within the regions were weighted by the state population in that year as described in section 7.3.1. The 30­ year average HDD and the 2005 HDD for the nine cen sus divisions and the four large states are shown in Table 7.4.1

7-14Table 7.4.1. 30-Year Average HDD (1978–2007) a nd the 2005 HDD for the Nine Census Divisions and the Four Large States

Division or State 30-Year HDD Average 2005 HDD

New England 6,571 6,453
Middle Atlantic 5,602 5,612
East North Central 6,103 6,323
West North Central 5,989 6,506
South Atlantic 3,665 3,720
East South Central 3,309 3,496
West South Central 2,415 2,723
Mountain 4,666 5,142
Pacific 5,133 5,193
New York 5,912 5,929
California 2,450 2,488
Texas 1,686 1,944
Florida 647 657

By using equation (7.3.2), the weather-a djusted annual space-heating energy consumption was estimated for the equipment in each household. Statistics for the weatheradjusted space-heating energy consumption at both divisional and nationa l level are shown in Table 7.4.2. The frequency distribution of the RE CS sample households in different heating energy consumption bands is shown in Figure 7.4.1.

Table 7.4.2. Statistics of Annual Weather-Ad justed Space-Heating Energy Consumption
for RECS-Stock CHP at Regional Level

Division or State Number of Observations Min kWh/yr Max kWh/yr Mean kWh/yr New England 1 2,399 2,399 2,399
Middle Atlantic 10 581 5,177 2,871
East North Central 20 1,911 10,037 4,237
West North Central 12 926 4,778 2,702
South Atlantic 108 0 6,412 2,692
East South Central 54 0 5,667 2,468
West South Central 6 354 4,434 2,386
Mountain 23 424 1,630 891
Pacific 13 2,171 5,251 3,621
New York 1 3,409 3,409 3,409
California 11 324 3,850 1,391
Texas 15 998 3,788 1,671
Florida 65 200 1,470 625
National 339 0 10,037 2,179

7-150% 5% 10% 15% 20% 25%Percentage of Obersavtions

Weather-Adjusted CHP Heating Energy from RECS (kWh/yr)

Figure 7.4.1. National Distribution of Weathe r-Adjusted Space-Heat ing Energy for RECS Observations

7.4.2 Stock Space-Heating Efficiency (HSPF)

The space-heating efficiency of CHP equi pment has improved over time in response to both technology improvement and minimum efficien cy standards. DOE related the space-heating efficiency of heat pumps in the stock to the e quipment vintage, much as was done for the cooling efficiency. In the 2005 RECS database, the age groups of the equipment and not their specific vintage is given. The five age groups are “less than 2 years old,” “2 to 4 years old,” “5 to 9 years old,” “10 to 19 years old,” and “20 years or olde r.” The data reported also include one additional category: “as old as the home.” The years of construction of the home for older homes are also reported in age bands. It was a ssumed that the age of a heat pump, within a given age group was uniformly distributed over the ra nge of the age group. For exampl e, for the heat pumps in the “less than 2 years old” age group, it was assumed that 50 percent of heat pumps were one year old and the other 50 percent were two years old. Similar technique was used in ascertaining the probable vintage year of the home and the equipm ent when both were reported to have the same age. The distribution of households with h eating-performance heat pumps by age groups is shown in Figure 7.4.2 and the distribution heat pump vintages are shown in Figure 7.4.3.

AHRI does not publish data on the historical average HSPF for CHP equipment. DOE developed historical HSPF es timates from two data sources. For the years from 1973 to 1993, DOE used data reported in the Technica l Support Document for the 2001 Rulemaking. 5 For the period from 1994 to 2005, DOE examined the 1994 ARI directory of Ce rtified Products, and developed a regression equation which relates th e SEER of residential split system heat pump DOE used the 1994 ARI Directory of Certified Equipment Database 6 to generate regressions between SEER and HSPF for CHP equipment on the market in 1994. For split systems, DOE used a regression based on datafor all CHP characterized by the AHRI designations HRCU-ACB and HRCU-A-C. For packaged heat pumps, DOE used a regression for all CHP equipment with an HSP-A designation. Only single phase eq uipment with ratings listed as “Active”, “not

7-16intended for export only”, were included. This resulted in two regressi on equations, one for the split system heat pump equipment class and one fo r single package heat pump equipment class. The historical average HSPF for each equipment class was calc ulated using historical annual average SEER values by equipment class from AHRI 7 and the appropriate regression equation. The annual average HSPF for all CHP equipment was then developed by weighting the annual average HSPF values by class using historical shipment data by equipment class. Table 7.4.3 shows the resulting historical HSPF values by year.

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0%

Less than 2 years

old 2 to 4 years old 5 to 9 years old 10 to 19 years old 20 years
or older

Age of Heat Pump SystemsPercent Of households

Figure 7.4.2. Distribution of Households with Heating-Performance Heat Pumps by Age Groups

0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0%

1 ,

9 7 6

1 ,97

9 1,982

1 , 9 8 5

1 , 9 8 8 1,991 1,994

1 , 9 9 7 2,00 0 2,003

Vintage Year of the Heat Pump SystemsPercent of Households

Figure 7.4.3. Distribution of RECS Households with Central Heat Pumps by Vintage

7-17Table 7.4.3. Average Annual Heating Pump HSPF

Year Average HSPF Year Average HSPF
1973 5.66 1990 6.98
1974 5.66 1991 7.08
1975 5.66 1992 7.19
1976 5.66 1993 7.30
1977 5.74 1994 7.38
1978 5.83 1995 7.39
1979 5.91 1996 7.40
1980 6.00 1997 7.39
1981 6.09 1998 7.29
1982 6.18 1999 7.47

1983 6.28 2000 7.46
1984 6.37 2001 7.49
1985 6.47 2002 7.49
1986 6.56 2003 7.53
1987 6.66 2004 7.56
1988 6.81 2005 7.58
1989 6.87

7.4.3 Estimating Baseline Annual Space-Heating Energy Use

For each class of equipment, the baseline annual space-heating energy consumption for CHP was estimated by using equation 7.4.2. The key inputs are the weather-adjusted annual space-heating energy consumption derived fro m the 2005 RECS data, the stock space-heating efficiency estimates for CHP shown in Tabl e 7.3.5, and the baseline heating efficiency,
7.7 HSPF.

Statistics showing the baseline space-heating energy consumption calculated for RECS households with CHP equipment at regional and national level are shown in Table 7.4.4.

Table 7.4.4. Baseline (13 SEER) Space-Heating Ener gy Consumption Statistics at Regional Level(CHP)

Division Number of Observations Min kWh/yr Max kWh/yr Average kWh/yr New England 50 1,869 1,869 1,869
Middle Atlantic 127 443 5,030 2,778
East North Central 346 1,869 9,855 4,000
West North Central 224 789 4,585 2,546
South Atlantic 233 0 6,105 2,554
East South Central 173 0 5,068 2,323
West South Central 79 340 3,956 2,240
Mountain 130 346 1,329 824
Pacific 23 2,132 4,542 3,407
New York 34 3,356 3,356 3,356
California 160 287 3,745 1,305
Texas 181 982 3,684 1,580
Florida 94 170 1,351 586
National 1,854 0 9,855 2,058

7-187.5 BASELINE RESIDENTIAL COOLING AND HEATING RESULTS-ADJUSTED FOR RECS SAMPLE WEIGHTS

Table 7.3.6 , Table 7.3.7, and Table 7.4.4 direct ly reflect the RECS household sample data. These tabulated results do not take into account the sample weights assigned by RECS for the different households. Figure 7.5.1, Figure 7.5.2 , and Figure 7.5.3 show the distribution of calculated baseline cooling and heating energy for CAC and CHP products used in residences taking into account the RECS household samples weights.

0% 5% 10% 15% 20% 25%Percentage of Households

Baseline CAC Cooling Energy (kWh/yr)

Figure 7.5.1. Baseline National Cooling En ergy Distribution for CAC – Residential

0% 2% 4% 6% 8% 10% 12% 14%Percentage of Households

Baseline CHP Cooling Energy (kWh/yr)

Figure 7.5.2. Baseline National Cooling Energy Distribution for CHP – Residential

7-190% 5% 10% 15% 20% 25%Percentage of Households

Baseline CHP Heating Energy (kWh/yr)

Figure 7.5.3. Baseline National Heating Energy Distribution for CHP – Residential

7.6 BASELINE COMMERCIAL CAC AND CHP ENERGY USE

Seven percent of re sidential-type ( i.e. , single-phase) CAC and CHP applications are assumed to be in commercial buildings. While potentially the variety of buildings to which this equipment could be utilized is wide, DOE believes that the vast majority of the shipments are utilized in small buildings, primarily small retail and commercial buildings. This is primarily because CAC and CHP equipment use single-phase electricity which limits the application to smaller buildings.

Cooling and heating energy use in commercial buildings can be distinctly different from residential buildings even for the same equipment. This is predominantly due to commercial buildings being operated differently, often havi ng defined operating hours when the equipment is used to condition the space, thermostatic setback during other hours, induced ventilation into the building structure to meet occupant needs, and typically continuous fan operation during occupied hours. Space heat gains in commercial bu ildings can be significantly different than in residential buildings due primarily to high internal thermal loads from lighting and electrical equipment during the occupied periods.

In addition multiple cooling and heating units are commonly used. A similar data source to the RECS data discussed earlier is the EIA Commercial Building Energy Consumption Survey (CBECS) 8 which provides estimates of end-use energy consumption in commercial buildings. Because multiple pieces of cooling and heatin g equipment are the norm in most commercial buildings, and the number of units by equipment type is not captured in the survey, it is not possible to readily determine the energy use of individual pieces of CAC and CHP equipment using CBECS. In addition, CBECS does not clearly distinguish equipment types by electrical phase. Hence, identification of buildings that are predominantly served by CAC and CHP equipment is difficult. Given these difficulties, it was determined that CBECS could not be used to estimate the cooling and heating energy data for CAC and CHP equipment used in

7-20commercial buildings. Instead, DOE relied on a building simulation approach to estimate the electrical energy usage of CAC and CHP equipment in commercial buildings.

7.7 OVERVIEW OF COMMERCIAL ENERGY SIMULATION APPROACH

In order to develop energy use statistics that reflect the use of CAC and CHP equipment in commercial buildings, DOE performed an analysis similar to that described in the Framework for Central Air Conditioners. 9 DOE used the EnergyPlus 10 whole-building energy simulation software to estimate the energy consumption of CAC and CHP used to satisfy the cooling, supply fan, and in the case of CHP, the electri cal heating energy required in a representative small office building. Simulations were carried out for 237 locations around the United States. The building model used was an existing single story, 5,500 ft 2 office building model developed by the DOE for energy benchmarking purposes fo r this analysis. This benchmark building model is one of 16 commercial building benchmark models de veloped in support of the DOE Net Zero Energy Commercial Building Initiative. 11,12

Two variations were considered for the simulations: buildings were either entirely served by CAC equipment with gas furnace backup or we re entirely served by CHP equipment. The simulated building utilized five individual CAC (or CHP units). For each equipment type, DOE simulated the equipment at four different efficiency levels starting from the baseline level. For CAC, these levels were: 13 SEER, 14 SEER, 16 S EER, and a max tech level of SEER 22 based on blower-coil ratings. For CHP these levels were: 13 SEER, 14 SEER , 16 SEER, and a max tech level of SEER 19.5 based on blower-coil ratings. Equipment parameters used in the simulation were adjusted to reflect engineering de signs corresponding to each efficiency level. Simulations were carried out using Typical Metrological Weather Files (TMY2) for the 237 U.S. locations 13

.
DOE extracted the annual energy consumption for cooling and fan energy use and heating from each modeled CAC or CHP unit as well as the equipment cooling capacity for each unit from each simulation run and aggregated these to the whole building level. Using this whole building cooling and heating data as well as the equipment capacities, DOE normalized the CAC and CHP energy consumption for each location and efficiency level to that of an average 3-ton CAC or CHP unit. These normalized energy use statistics were then used to represent the commercial energy use for a 3-ton CAC or CHP product for the LCC analysis.

To estimate the energy consumption for intermediate efficiency levels between those simulated, DOE linearly interpolated the energy use estimates for cooling energy, fan energy and heating energy based on the results at the four simulated efficiency levels, the SEER or HSPF rating as the independent variable, and using the nearest lower and upper SEER or HSPF levels simulated.

7.7.1 Simulation Tool Description

DOE chose to use EnergyPlus version 3.0 for th e energy analysis. EnergyPlus is the most recent of several large scale software programs developed for whole-building energy simulation analysis and has been validated by comparing its results with thermal and energy use measurements on actual buildings and with othe r software tools and cal culations. EnergyPlus

7-21predicts the hourly energy use of a building gi ven hourly weather information and a description of the building, the operation of the building, and its heating, ventilation and air-conditioning (HVAC) equipment. Energy use statistics for the building can be readily extracted for different time steps and at detailed sub-component levels if necessary. En ergyPlus is an integrated software tool, where both the building loads and how those loads are served by equipment are solved iteratively and has a separa te, but robust ground heat transfer model, which is particularly useful in the simulation of smaller buildings. DOE is currently using EnergyPlus as the basis for most of its building energy simulation research and the tool and its ongoing development are actively supported within DOE.

7.7.2 Efficiency Levels Analyzed and Corresponding Simulation Parameters

DOE simulated four efficiency levels for CA C equipment and four efficiency levels for CHP equipment, corresponding to particular effi ciency levels identified in the engineering analysis. In order to simulate the equipment within the confines of the simulation software, the SEER and HSPF rating from the engineering analysis must be converted to parameters used by the simulation software. These parameters are th e cooling COP, and for CHP the heating COP, of the condensing unit at rate d conditions, and the fan power . The CAC and CHP condensing unit parameters are in turn calculated from 95 °F EER (EER) and 47 °F COP (COP 47 °F ) ratings for the equipment and the fan power at rated conditions. DOE first estimated these from the SEER and HSPF rating.

The EER rating reflects the cooling performan ce for CAC equipment at a single-point rating condition defined by 95 °F outdoor temperat ure, 80 °F entering air dry bulb temperature and a 67 °F entering air wet bulb temperature. The COP 47 °F rating reflects the heating performance of the heat pump at a single poi nt rating condition defined by 47 °F outdoor temperature, 70 °F entering air dry bulb temper ature and a maximum 60 °F entering air wet bulb temperature. The EER and COP 47 °F ratings for equipment at di fferent SEER levels were estimated using best fit curves for residen tial air conditioning equipment and heat pump equipment established by Wassmer and Brandemuehl. 14 These curve fits are expressed in equation 7.7.1 and 7.7.2.

EER = − 0.0182 × SEER 2 + 1.1088 × SEER Eq. 7.7.1

COP 47 F = − 0.0255 × HSPF 2 + 0.6239 × HSPF Eq. 7.7.2

For 13 SEER equipment, the fan power at rating conditions was established assuming a blower motor efficiency of 0.65, a fan efficiency of 0.58, and a constant total static pressure of 1.105 in H 2 O for the furnace/air handler. The same characteristics for fan power were also assumed to apply to the heat pumps at ratin g condition. The blower motor efficiency was assumed to be 0.65 for the 13 and 14 SEER ratings , consistent with that of a permanent split capacitor (PSC) blower motor. The blower moto r efficiency was assumed to be 0.80 for the 16 SEER and higher SEER ratings consistent w ith that of an electronically commutated motor (ECM) blower motor in this size range. A tran sition to ECM blower motors between the 14 and 16 SEER ratings reflects the use of that technology in the CAC/CHP market from the engineering analysis where ECM motors a ppear to be commonplace at 16 SEER, but not common at 14 SEER. These assumptions result in a blower power under rating conditions of

7-22138 W/ton for 13 and 14 SEER equipment, and a lo wer fan power of 112 W/ton for higher SEER equipment at rated conditions. For comparis on, using the test procedure default 365 W/1,000 CFM default for a coil-only rating would provide the same power levels assumed for 13 and 14 SEER equipment at an ai rflow rate of 377 CFM/ton.

The cooling and heating condens ing unit COP values that are entered in the EnergyPlus software reflect the EER and COP 47 °F ratings but are adjusted for the impact of the blower power. The blower power is directly incorporated into the total system power for these ratings, but because of the effect of fan heat, the incorporating the blower reduces the cooling output and raises the heating output. Equations 7.73 and 7.74 provide cooling and he ating COP ratings for the condensing unit alone after adjus ting for the fan power and fan heat. 

## ( EER / 3.413 + R 

## ) COP CUCool ,95 ° F = Eq. 7.7.3 1

− R

COP

− R ⎛
47 ° F ⎞ COP CUHeat ,47 ° F = ⎜ ⎟ Eq. 7.7.4 ⎝ 1

− R ⎠

Where:

R = ratio of supply fan power to total equipment power at the AHRI rating condition, COP CUCool,95 °F = condensing unit cooling COP, and COP CUHeat,47 °F = condensing unit heating COP.

Table 7.7.1 shows the resulting equipment pe rformance statistics for the commercial building models.

Table 7.7.1. CAC and CHP Blower and Charact eristics Used in Modeling Commercial Cooling and Heating Energy Use Equipment Class SEER HSPF EER 47 °F COP Blower Motor Energy Efficiency Blower Power (w/ton)* Fan Power to Total Power (Rated Conditions) Cool COP 95°F (Condensin g Unit Only) Heating COP 47°F (Condensing Unit Only)
CAC 13 NA 11.339 NA 0.65 138 0.13 3.966 NA
14 NA 11.956 NA 0.65 138 0.135 4.208 NA
16 NA 13.802 NA 0.80 112 0.123 4.511 NA
22 NA 15.585 NA 0.80 112 0.14 5.471 NA
CHP 13 7.7 11.339 3.292 0.65 138 0.13 3.966 3.626
14 8 11.956 3.359 0.65 138 0.135 4.208 3.703
16 8.6 13.802 3.480 0.80 112 0.123 4.511 3.842
22 10.3 15.585 3.721 0.80 112 0.14 5.471 4.118

* Calculated for rating conditions.

7.7.3 Small Office Building Characteristics

The small office building prototype model is a theoretical building modeled with characteristics typical of buildings of this size and use. The building is a 5,500 ft 2 single-story

7-23building. The building is rectangular shaped, 52 ft by 105 ft with an aspect ratio of 1.5. The building has a window-area-fraction of 21 percent w ith a 10 ft floor-to-ceiling height. The small office building is assumed to have slab-on-grade construction for the floor and an attic. A picture of the building structure is shown in Figure 7.7.1. The building is divided into five HVAC zones, four perimeter zones and a core zone as illustrated in Figure 7.7.2, with a single CAC or CHP unit assumed for each HVAC zone. The perimeter z one depth in the center of each zone is 16 ft.

Figure 7.7.1. Small Office Bu ilding Design View

Figure 7.7.2. Small Office Building HVAC Zoning

The building model presumes wood frame construction and punch-out type windows. Where applicable the building components for this model were assumed to “just meet” the minimum prescriptive requirements of the ASHRAE 90.1-2004 standard. Components not regulated by Standard 90.1 are a ssumed to be designed as is considered standard practice for a small office building. Standard practice is deter mined from various sources including a review of the Commercial Buildings Energy Consumption Su rvey (CBECS 2003) and the input of various design and construction industry professiona ls including members of the ASHRAE 90.1 Standing Standard Project Committee. The following sections provide a review of the baseline building and how the baseline building is simulated in EnergyPlus, including characteristics of the building envelope, building internal loads (people, lighting, miscellaneous equipment, and infiltration), HVAC equipment, and service water heating.

7.7.4 Building Operating Characteristics

The building is assumed to follow typical small office occupancy patterns with peak occupancy occurring from 8 AM to 5 PM weekdays with limited occupancy beginning at 6 AM and extending until midnight for janitorial functi ons. The building is assumed to be unoccupied Saturday, Sunday and holidays. Schedules fo r lighting and miscellaneous equipment were matched to occupancy schedules with lower usage during unoccupied times. HVAC system

7-24schedules were matched to the occupancy schedules, and allow for earlier startup times to bring the space to the desired temperature at the beginning of normal occupancy. Figure 7.7.3, Figure 7.7.4, Figure 7.7.5, and Figure 7.7.5 show the EnergyPlus schedules for lighting, plug loads, occupancy, and thermostat set point. Detailed schedules are show n in appendix 7-A for these as well as for HVAC fans, infiltra tion, and service hot water. Thes e schedules represent multipliers to defined daily “peak” conditions. In the case of ventilation, it is assumed that ventilation occurs whenever the fan system is operational. In the ca se of infiltration, a max imum infiltration rate for each hour is calculated hourly using wind speed and multiplied by the value shown in the hourly infiltration schedule. That valu e is 1.0 for hours when the ventilation is off and the building is assumed to be unpressurized. Th e schedule multiplier is assumed to be 0.25 during hours when the fan system is on and the building is pressurized.

The HVAC systems are scheduled to be on from 6 a.m. to 7 p.m. weekdays (13 hours/day) and our schedule off weekends a nd holidays. Building thermostats are set to 70 °F degree heating, 75 °F degree cooling during the occupied period. Thermostats are setback to 60 °F heating, 85 °F cooling during the unoccupied period. Between 6 a.m and 7 a.m weekday mornings the thermostats are set to 65 °F and 80 °F cooling heating set points to provide a onehour thermostat ramp between the setback and oc cupied set points to prevent equipment sizing and temperature balance problems.

For the occupancy, lighting, plug use, ve ntilation, the schedules shown in Appendix 7-B are multipliers to defined peak densities. Ligh ting density was defined using the ASHRAE 90.1­ 2004 maximum LPD requirement of 1.0 w/ft 2 . Plug load density ( e.g. , computers and other miscellaneous loads) was 0.63 w/ft 2 . Occupancy peak density was defined as 31 persons for the building (5.6 persons per thousand square foot ). Ventilation was base d on ASHRAE Standard 62-1999 and set to 0.1 cfm/ft 2 (cubic feet per minute per square ft) of floor area for each conditioned zone. The peak infiltration for th e building was based on hourly wind speed as discussed previously and averages to 0.2016 cfm/ft 2 of total exterior c onditioned zone wall area at a wind velocity of 10 miles per hour.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24PercentofPeakPowerDensity

Weekday

Sat/Sun/Hol

Figure 7.7.3. Small Office Lighting Schedule

7-25Figure 7.7.4. Small Office Plug Load Schedule

Figure 7.7.5. Small Office Occupancy Schedule

7-260 10 20 30 40 50 60 70 80 90 100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24ThermostatSetpoint(°F)

Heat

‐ Weekday

Heat

‐ Sat/Sun/Hol

Cool

‐ Weekday

Cool

‐ Sat/Sun/Hol

Figure 7.7.6. Small Office Thermostat Set Point Schedule

7.7.5 Building Mechanical Systems and Equipment

As discussed, the building used either five CAC units or five CHP units, one for each conditioned zone depending on which equipment class was analyzed. Equipment performance characteristics were developed using perform ance curves based on existing equipment. Performance curves and model input s are documented in appendix 7-A.

Blower energy for the building model used the characteristics for blower motor and fan power efficiency discussed in section 7.7.2. Howeve r, the total fan static pressure was 1.45 in
H 2 0 based on the assumption used in the benchmark prototype, compared to 1.105 in H 2 0 total static pressure used to characterize the equipment performance at rating conditions.

Cooling equipment was sized based on ASHRAE 2.5 percent cooling design day sizing for all climates. A sizing run is done prior to the hourly simulations in EnergyPlus and is used to size all HVAC equipment. The design-day sizes ar e then used in the annual simulation runs. For the heat pumps, equipment sizing is based on coo ling design-day and electric resistance heat is used to make up any remaining heating load.

7.8 BASELINE COMMERCIAL ENERGY DISTRIBUTION

To be of use in the CAC analysis, the ba seline commercial CAC a nd CHP use developed for the 237 TMY locations must have relative weighting factors associated with each TMY location much as the residential analysis uses the representative RECS weights. DOE used population-based weighting fact ors developed for each TMY c limate based on data from the 2000 U.S. Census data to represent the impor tance of each climate in each state. The development and documentation of these weightin g factors is found in Appendix 7-B. Because certain TMY locations represent climates that cover more than one state ( e.g. , for instance where the TMY location is on the border between two st ates), DOE originally developed weighting factors for a total of 543 TMY-State combinations. These weighting factors were then used in the

7-27subsequent LCC analysis in addressing CAC and CHP energy use in commercial buildings. Seventeen Alaskan locations, which make up appr oximately 0.2 percent of the national weight, were however removed from the energy analysis due to issues with electrical price data. Figure 7.8.1, Figure 7.8.2, and Figure 7.8.3 shows a distribution of commercial CAC cooling and CHP cooling and heating energy use in the nation which accounts for the relative weights attached to each of the remaining 526 TMY-State combinations.

0% 10% 20% 30% 40% 50% 60% 70%Percentage of SimulatedCommercial Small Offices

Baseline CAC Cooling Energy (kWh/yr)

Figure 7.8.1. Baseline National Cooling En ergy Distribution for CAC-Commercial, Weighted

0% 10% 20% 30% 40% 50% 60% 70%Percentage of SimulatedCommercial Small Offices

Baseline CHP Cooling Energy (kWh/yr)

Figure 7.8.2. Baseline National Cooling En ergy Distribution for CHP-Commercial, Weighted

7-280% 10% 20% 30% 40% 50% 60%Percentage of SimulatedCommercial Small Offices

Baseline CHP Cooling Energy (kWh/yr)

Figure 7.8.3. Baseline National Heating En ergy Distribution for CHP-Commercial, Weighted

7.9 COMMERCIAL ENERGY FOR INTERMEDIATE EFFICIENCY LEVELS

Calculation of commerc ial annual cooling, and fan energy for intermediate efficiency levels not simulated was by linear interpolation between SEER levels simulated. Calculation of commercial heating energy use for heat pumps for intermediate levels not simulation was by interpolation between HSPF levels simulated.

7.10 MARKET BASELINE SPACE-COOLING AND SPACE-HEATING EFFICIENCIES

The analysis results presented in this chapter up to this point presents the development of the baseline space-cooling and space-heating energy use for CAC and CHP equipment. Baseline in this discussion refers to the energy consump tion if all equipment was brought to the current standard levels of SEER 13 and HSPF 7.7 for packaged and split system CAC and CHP product classes. Not all equipment is sold at the baseline efficiency levels. Much equipment exceeds the baseline level in the current market and is expect ed to continue to do so in the absence of new standards. In order to account for this within the LCC analysis discussed in the next chapter, DOE defined a base case efficiency distribution for 2016, also referred to as the market baseline. The market baseline efficiency distribution was defined to represent the range of efficiencies likely sold into the market in 2016 in the absence of new standards. The market baseline energy consumption is calculated as the energy estimated to be consumed by each individual entity (as characterized by RECS household observation or commercial building TMY-State combination)

DOE estimated this energy use in the same manner as was used in estimating the baseline energy consumption. For RECS household r ecords, DOE first randomly selected a 2016 efficiency level from the market baseline di stribution and then equations 7.3.1 and 7.4.1 were utilized to calculate the cooling and heating c onsumption for the RECS observations in the 2016 base case, by replacing the baseline efficiency (cooling or heating) with the selected efficiency for each observation in the base case. For commercial TMY-State observations, DOE first

7-29randomly selected a 2016 efficiency level from the market baseline distributions and calculated the correspond cooling fan, and heating energy use for that observation in 2016 by linear interpolation between the efficiency levels simulated in the commercial energy analysis.

DOE did not have access to sales data describing the actual distribution of efficiencies in current sales, nor was such information provi ded by industry for this rulemaking. As a consequence, DOE developed estimates of the distribution of SEER levels for four classes of product: split system CAC, single package CAC, split system CHP, and single package CHP. The development of these distributions wa s based on the following key data inputs:

From AHRI data, the average SEER of equi pment sold in each product class in 2006 as well as the relative shipments by product class for the market as a whole.

An industry trade press article which indicat ed approximate sales segmentation by SEER for the CAC/CHP industry in 2007. 15

AHRI Directory of Certified Product Performance 16 which allowed review of specific efficiencies sold into the ma rket for each product class.

According to the trade press article, the di stribution in 2007 had approximately 9 percent of sales at 14 SEER, 3 percent of sales at 15 SEER, 2 percent at 16 SEER, and 2 percent for 17 SEER. The remainder of the product sales was assume d to fall below 14 SEER.

According to AHRI data 7 , product sales in 2007 were as follows: 63.0 percent split CAC, 5.9 percent single-package CAC, 27.6 percent sp lit CHP, and 3.5 percent single-package CHP. Product sales in 2008 thr ough September were as follows: 63.0 percent split CAC, 4.8 percent single-package CAC, 28.8 percent split CHP, and 3.4 percent single-package CHP.

AHRI reported average shipped SEER by product class for 2007: split CAC, 13.72; single-package CAC, 12.83; split CHP 13.86, sing le-package CHP 13.16. DOE did not know if the average 12.83 for single-package CAC repr esented continued sa les of pre-SEER 13 equipment or if it included throug h the wall or other classes with lower efficiency. As this data were provided by AHRI for this rulemaking, it was assumed to be represen tative of single phaseequipment only. AHRI reported average shipped SEER for 2008 as: split CAC, 13.77; singlepackage CAC, 13.17; split CHP 13.97, single-package CHP 13.39.

DOE first created 16 SEER bins corresponding roughly to the SEER efficiency levels developed in the engineering analysis with thos e engineering levels serving as a representative efficiency for each bin. These bins are shown in Table 7.10.1. Then through an iterative process which took into account available efficiency leve ls in each product class, DOE developed an efficiency distribution fo r each product class which was consistent with the above data sources in that it provided average efficiency by split CA C, split CHP, and sing le-package CHP product class as reported by AHRI in 2007 as well as provided an overall distribution by SEER that corresponded with the industry trade press artic le cited above. Bins that included 14 and 15 SEER were assumed to be uniform ly distributed effici encies above and below the characteristic efficiency in the bin. It was obviously not possi ble to develop a shipment-weighted efficiency below 13 SEER as was seen for single package CAC using this distribution. Instead DOE chose

7-30to match the 2008 shipment weighted average value for this product class. The estimated distribution for all classes for 2007 is shown in Table 7.10.1.

Table 7.10.1. CAC and CHP Efficiency Distributions Estimated for 2007

SEER Bins SEER Distribution by Equipment Class Industry- Wide SEER Distribution (Four Classes)
% Bottom of Bin Top of Bin Characteristic Efficiency in Bin Split CAC Single Package CAC
% Split CHP% Single Package CHP
%

13 13.25 13 25.00 76.20 15.00 76.20 27.07
13.25 13.75 13.5 56.00 18.80 57.00 18.80 52.77
13.75 14.25 14 6.00 2.00 8.00 2.00 6.18
14.25 14.75 14.5 2.50 2.00 7.50 2.00 3.83
14.75 15.25 15 3.00 1.00 5.00 1.00 3.36
15.25 15.75 15.5 2.00 0.00 2.00 0.00 1.81
15.75 16.5 16 3.10 0.00 2.00 0.00 2.50
16.5 17.5 17 1.00 0.00 1.50 0.00 1.04
17.5 18.5 18 0.60 0.00 1.50 0.00 0.79
18.5 19.5 19 0.30 0.00 0.50 0.00 0.33
19.5 20.5 20 0.20 0.13
20.5 21.5 21 0.20 0.13
21.5 22.5 22 0.10 0.06
22.5 23.5 23
23.5 24.5 24
24.5 25.5 25 Wt. Average SEER 13.71 13.16 13.85 13.16 13.70
13.66 13.78

DOE was not able to develop a distribu tion using the same methodology for the 2008 data that would be consistent with the industry trade press artic le overall distribution. DOE made slight changes to the relative shipment weights by efficiency bin from 2007 distribution, in order to match the higher average SEERs in 2008 wh ile maintaining the ge neral flavor of the distribution by product class. This overa ll 2008 distribution is shown in Table 7.10.2. DOE assumed that this distribution was representative of the market baseline distribution in 2016 and used it as such for the energy and subsequent LCC analysis.

DOE did not have similar data on space heating efficiencies for CHP equipment. For analysis of the market baseline HSPF efficienci es, DOE used the HSPF values that corresponded to each CHP SEER level as identified in the engineering analysis. Because these engineering levels represented typical market averages base d on the AHRI data, they were deemed sufficient for characterizing average market HSPF by S EER level and corresponding average CHP heating energy use in the market baseline.

7-31Table 7.10.2. CAC and CHP Efficiency Distribut ions Estimated for Market Baseline

SEER Bins SEER Distribution by Equipment Class IndustryWide SEER Distribution (Four Classes)
% Bottom of Bin

SEER Top of Bin

SEER Characteristic Efficiency in Bin

SEER Split CAC

% * SinglePackage

CAC

% Split CHP

% SinglePackage

CHP

%

13 13.25 13 24.00 75.00 13.00 50.00 24.18
13.25 13.75 13.5 55.00 20.00 52.00 32.00 51.66
13.75 14.25 14 4.00 2.00 10.00 11.00 5.87
14.25 14.75 14.5 5.25 2.00 9.00 5.00 6.17
14.75 15.25 15 3.25 1.00 5.50 2.00 3.75
15.25 15.75 15.5 2.00 0.00 3.50 0.00 2.27
15.75 16.5 16 3.50 0.00 3.00 0.00 3.07
16.5 17.5 17 1.50 0.00 2.00 0.00 1.52
17.5 18.5 18 0.70 0.00 1.50 0.00 0.87
18.5 19.5 19 0.30 0.00 0.50 0.00 0.33
19.5 20.5 20 0.20 0.13
20.5 21.5 21 0.20 0.13
21.5 22.5 22 0.10 0.06
22.5 23.5 23
23.5 24.5 24
24.5 25.5 25 Wt. Average SEER 13.77 13.17 13.97 13.39 13.78
13.72 13.91

* A separate, coil-only split air conditioner distribution was created by truncating the split AC distribution shown at SEER bin 8 (16.5-17.5 bin) since the max tech level for this type of equipment was 16.5. The distribution was then normalized back to 100%. This distribution is shown in chapter 8, Life Cycle Cost and Payback Period Analysis.

7.11 ESTABLISHMENT OF GEOGRAPHIC REGIONS FOR STANDARDS ANALYSIS AND CORRESPONDING REGIONAL ENERGY CONSUMPTION BY EFFICIENCY LEVEL

Under EPCA, regional efficiency standards for CAC may be defined for up to two regions consisting of contiguous groups of states. These regional standards are in addition to a base national standard efficiency that represents the minimum efficiency that a manufacturer could produce or that could be imported into the Un ited States. In order to consider establishing regional standards, DOE needed to identify regions for which such standards might be applicable. For cooling equipment performance, the most important regional variations in climate are the annual number of operating hours, and the coincident relative humidity during those hours. For the CAC standard analysis, DOE is considering establishing two regions, hothumid and hot-dry, for the establishment of region al standards in addition to a national standard. In addition, DOE considered using two variants of the SEER rating to establish performance standards: the current SEER definition and a modified definition termed “SEER hot-dry” (SEER HD ). The SEER HD would be calculated using revised temperature bin data and design sizing data as established for the defined hot-dry region.

A national standard and a sta ndard for the proposed hot-humid region may be established using SEER, although potentially at different SE ER efficiencies based on the cooling load and other information characteristic to the nation and to the hot-humid region respectively. The

7-32SEER HD rating would be developed to be more appropriate for hot and dry climates in certain western States where the averag e outdoor air temperature during cooling may be considerably higher than that seen in the remainder of the United States. Whether these regional standards are appropriate will be determined by the LCC and other analyses. For the purpose of DOE’s preliminary analysis, DOE established the two re gions allowed under EPCA as shown in Table 7.11.1. Region 1 refers to the hot-humid region. Region 2 refers to the hot-dry region. For the purpose of characterizing the geographic rema inder of the nation, DOE uses a Region 0 nomenclature. DOE notes that while analysis can be performed for Region 0, DOE does not have authority to set a regional standard for this geographic area. Rather, this area would be covered under the national standard.

Table 7.11.1. Proposed Climate Regi ons for Regional Standards

Hot-Humid (Region 1) Hot-Dry (Region 2) Rest-of-Country (Region 0)
Alabama Arizona Alaska Nebraska
Arkansas California Colorado New Hampshire
Florida Nevada Connecticut New Jersey Georgia New Mexico Delaware New York
Hawaii District of Columbia North Dakota
Louisiana Idaho Ohio Mississippi Illinois Oregon
North Carolina Indiana Pennsylvania
Oklahoma Iowa Rhode Island
South Carolina Kansas South Dakota
Tennessee Kentucky Utah
Texas Maine Vermont Maryland Virginia
Massachusetts Washington Michigan West Virginia
Minnesota Wisconsin
Missouri Wyoming
Montana

For the purposes of the preliminary analysis for the CAC rulemaking, DOE did not develop energy consumption character istics in conformance with the SEER HD rating as this rating was not used in the engineering analysis and no mapping between SEER and SEER HD had been developed. However, DOE did develop the en ergy and subsequent LCC analysis at both the national level and indivi dually for the regions defined in Table 7.11.1. A complete discussion on the development of both the standard regions and the SEER HD parameter are discussed in Appendix 7-C.

For each equipment class, DOE developed energy use statistics for the market baseline and for higher efficiency levels by using a Monte Carlo random selec tion process to select 10,000 observations in each region and 10,000 for the na tion as a whole. Ninety three percent of those observations were residen tial and 7 percent were commercial instances of the use of CAC (or CHP) equipment. Details for the selection process are found in chapter 8, LCC. However

7-33Table 7.11.6 show the resultant baseline, market ba seline, and higher efficiency annual energy statistics developed for each region for each equipment class analyzed.

Table 7.11.2. Split-System Air Conditioners: Av erage Annual Energy Use by Efficiency Level for Coil-Only Systems
Efficiency Level Annual Energy Consumption kWh/yr
National Hot-Humid Hot-Dr y Rest of Countr y # SEER HSPF * Coolin g Heatin g Coolin g Heatin g Coolin g Heatin g Coolin g Heatin g 1 13.0 N/A 2,407 0 3,564 0 2,176 0 1,378 0
Market Baseline Market Baseline N/A 2,291 0 3,393 0 2,071 0 1,310 0

2 13.5 N/A 2,322 0 3,437 0 2,100 0 1,331 0

3 14.0 N/A 2,243 0 3,318 0 2,029 0 1,287 0

4 14.5 N/A 2,168 0 3,205 0 1,960 0 1,244 0

5 15.0 N/A 2,097 0 3,100 0 1,897 0 1,204 0

6 15.5 N/A 2,031 0 3,002 0 1,836 0 1,166 0

7 16.0 N/A 1,968 0 2,909 0 1,780 0 1,130 0

8 16.5 N/A 1,912 0 2,825 0 1,730 0 1,099 0

* N/A means not applicable.

Table 7.11.3. Split-System Air Conditioners: Av erage Annual Energy Use by Efficiency Level—Blower-Coil Systems

Efficiency Level Annual Energy Consumption kWh/yr

National Hot-Humid Hot-Dry Rest of Country

# SEER HSPF* Cooling Heating Cooling Heating Cooling Heating Cooling Heating

1 13.0 N/A 2,433 0 3,584 0 2,172 0 1,365 0
Market Baseline Market Baseline N/A 2,315 0 3,410 0 2,067 0 1,302 0

2 13.5 N/A 2,347 0 3,455 0 2,096 0 1,319 0
3 14.0 N/A 2,267 0 3,336 0 2,025 0 1,275 0

4 14.5 N/A 2,190 0 3,223 0 1,957 0 1,233 0

5 15.0 N/A 2,119 0 3,117 0 1,893 0 1,193 0

6 15.5 N/A 2,052 0 3,018 0 1,833 0 1,155 0

7 16.0 N/A 1,988 0 2,925 0 1,777 0 1,120 0
8 16.5 N/A 1,932 0 2,840 0 1,727 0 1,089 0

9 17.0 N/A 1,878 0 2,760 0 1,679 0 1,060 0

10 18.0 N/A 1,780 0 2,613 0 1,592 0 1,007 0

11 19.0 N/A 1,692 0 2,482 0 1,514 0 960 0

12 20.0 N/A 1,613 0 2,363 0 1,444 0 917 0

13 21.0 N/A 1,541 0 2,256 0 1,380 0 878 0

14 22.0 N/A 1,476 0 2,158 0 1,322 0 842 0

* N/A means not applicable.

7-34Table 7.11.4. Split-System Heat Pumps: Average Annual Energy Use by Efficiency Level

Efficiency Level Annual Energy Consumption kWh/yr

National Hot-Humid Hot-Dry Rest of Country

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating

1 13.0 7.70 3,487 1,749 4,275 1,2 75 4,203 924 1,978 2,968
Market Baseline Market Baseline Market Baseline 3,268 1,687 4,006 1,230 3,937 891 1,857 2,862

2 13.5 7.85 3,363 1,716 4,122 1,2 51 4,053 906 1,909 2,912
3 14.0 8.00 3,248 1,685 3,980 1,2 28 3,913 890 1,846 2,859

4 14.5 8.15 3,138 1,654 3,845 1,2 06 3,780 873 1,784 2,808
5 15.0 8.30 3,035 1,625 3,719 1,1 84 3,656 858 1,726 2,758

6 15.5 8.45 2,939 1,597 3,601 1,1 63 3,539 843 1,671 2,711

7 16.0 8.60 2,848 1,570 3,490 1,1 43 3,430 828 1,620 2,665

8 17.0 9.10 2,688 1,485 3,293 1,0 81 3,235 783 1,531 2,522

9 18.0 9.60 2,545 1,409 3,117 1,0 26 3,062 743 1,452 2,395

10 19.0 10.10 2,417 1,341 2,959 976 2,907 706 1,381 2,279

11 19.5 10.30 2358 1315 2886 957 2835 693 1,348 2,236

Table 7.11.5. Single-Package Air Conditioners: Average Annual Energy Use by Efficiency
Level
Efficiency Level Annual Energy Consumption kWh/yr
National Hot-Humid Hot-Dry Rest of Country
# SEER HSPF * Cooling Heating Cooling Heating Cooling Heating Cooling Heating

1 13.0 N/A 2,376 0 3,602 0 2,170 0 1,363 0

Market Baseline Market Baseline N/A 2,348 0 3,559 0 2,144 0 1,348 0

2 13.5 N/A 2,292 0 3,473 0 2,093 0 1,316 0

3 14.0 N/A 2,214 0 3,353 0 2,022 0 1,273 0

4 14.5 N/A 2,139 0 3,239 0 1,954 0 1,230 0

5 15.0 N/A 2,070 0 3,133 0 1,890 0 1,191 0

6 15.5 N/A 2,004 0 3,033 0 1,831 0 1,153 0

7 16.0 N/A 1,942 0 2,940 0 1,774 0 1,118 0

8 16.6 N/A 1,876 0 2,838 0 1,714 0 1,081 0

* N/A means not applicable.

7-35Table 7.11.6. Single-Package Heat Pumps: Average Annual Energy Use by Efficiency Level

Efficiency Level Annual Energy Consumption kWh/yr

National Hot-Humid Hot-Dry Rest of Country

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating

1 13.0 7.70 3,464 1,720 4,295 1,272 4,211 927 1,96 4 2,953
Market Baseline Market Baseline Market Baseline 3,372 1,698 4,179 1,256 4,098 915 1,91 4 2,916

2 13.5 7.85 3,341 1,688 4,141 1,248 4,060 910 1,89 6 2,898
3 14.0 8.00 3,227 1,657 3,999 1,225 3,920 893 1,833 2,845

4 14.5 8.00 3,117 1,657 3,863 1,225 3,787 893 1,77 2 2,845
5 15.0 8.00 3,015 1,657 3,737 1,225 3,663 893 1,71 4 2,845

6 15.5 8.50 2,920 1,561 3,618 1,154 3,546 841 1,66 0 2,682

7 16.0 9.00 2,829 1,476 3,506 1,091 3,436 795 1,60 9 2,538

8 16.4 9.00 2,763 1,476 3,424 1,091 3,356 795 1,57 2 2,537

7-36REFERENCES

1. Residential Energy Consumption Survey: Qu ality Profile, DOE Pub lication No. DOE/EIA0555(96)/1

2. NOAA, 2009. NNDC Climate Data Online. <www7.ncdc.noaa.gov/CDO/CDODi visionalSelect.jsp> (Assessed February, 2009)

3. Missouri Census Data Center . U.S. Census Data Archive for 1980, 1990, 2000 U.S. Census
Data http://mcdc2.missouri.edu/applications/uexplore.shtml#top and (Accessed February 2009)

4. AHRI 2008, Air Conditioning and Refrigeration Institute Statistical Profile, 2008. Efficiency data averaged by shipment weig hts across air conditioner, and for heat pump product classes.

5. DOE, 2001. Central Air Conditioner Rulema king SNOPR Technical Support Document, Chapter 5. Life Cycle Cost and Payback Analysis.

< http://www1.eere.energy.gov/buildings/applia nce_standards/residential/ac_central_1000

_ r.html > (Accessed April, 2009)

6. ARI, 2004. Directory of Certified Unita ry Equipment Standards 210/240 270. ARI 2003
V. 2.0. Arlington, Va

.

7. AHRI, 2008. Shipment Data and Efficien cy data by CAC and CHP equipment class supplied to DOE for the current CAC rulemaking

8. EIA 2003. Commercial Building Energy Consump tion Survey (CBECS). U.S. Department of Energy Energy Information Administration.

< http://www.eia.doe.gov/emeu/cbecs/cbecs2003 > (Accessed May, 2009).

9. DOE, 2008. Rulemaking Framework for Resi dential Central Air Conditioners and Heat Pumps. Accessed at http://www1.eere.energy.gov/buildings/appliance_standards/residential/pdfs/cac_framewor k.pdf

10. DOE, 2008. EnergyPlus Energy Simulation Soft ware V3.0. U.S. Department of Energy. Washington, D.C. Available at < http://apps1.eere.energy.gov/buildings/energyplus >

11. DOE, 2008. DOE to Pursue Zero-Net Ener gy Commercial Buildings, Available at http://www1.eere.energy.gov/buildin gs/commercial_initiative/about.html

12. DOE, 2009. Commercial Building Benchmark Models. http://www1.eere.energy.gov/buildings/commercial_initiative/benchmark_models.html

13. NREL, 1995. Typical Meteorological Years Derived from the 1961-1990 National Solar Radiation Database . National Renewable Energy Laboratory. Golden, CO.

7-3714. Wassmer M and MJ Brandemuehl. 2006. Effect of Data Availability on Modeling of Residential Air Conditioners and Heat Pumps for Energy Calculations

. ASHRAE
Transactions 111(1), pp. 214-225.

15. ACH&R News, 2007. “Higher SEERs Got Popular”, December 2007. Accessed March 2009 at http://www.achrnews.com/Articles/Web_Exclusive/BNP_GUID_9-5

­ 2006_A_10000000000000222513

16. AHRI, 2009. Directory of Certified Product Performanc e. Available at

< http://www.ahridirectory.org/ah ridirectory/pages/home.aspx >. Accessed March, 2009.

7-38CHAPTER 8. LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS

TABLE OF CONTENTS

8.1 INTRODUCTION

.............................................................................................................. 8-1 8.1.1 General Approach for Life-Cycle Co st and Payback Period Analyses

............... 8-1 8.1.2 Overview of Life-Cycle Cost and Payback Period Analyses Inputs

................... 8-2 8.1.3 Analysis Use of Residential Energy Consumption Survey (RECS) in LCC and
PBP

...................................................................................................................... 8-6 8.1.4 Commercial Building Analysis

............................................................................ 8-7 8.2 LIFE-CYCLE COST ANALYSIS INPUTS

....................................................................... 8-9 8.2.1 Definition

............................................................................................................. 8-9 8.2.2 Total Installed Cost Inputs

................................................................................. 8-10 8.2.3 Operating Cost Inputs

........................................................................................ 8-25 8.3 PAYBACK PERIOD INPUTS

......................................................................................... 8-54 8.3.1 Definition

........................................................................................................... 8- 54 8.3.2 Inputs

.................................................................................................................. 8-54 8.4 SEER AND HSPF RESULTS

.......................................................................................... 8-55 8.4.1 Split-system Air Conditioners

............................................................................ 8-56 8.4.2 Split-System Heat Pumps

.................................................................................. 8-68 8.4.3 Single Package Air Conditioners

....................................................................... 8-74 8.4.4 Single Package Heat Pumps

............................................................................... 8-80 8.5 OFF-MODE AND STANDBY POWER CONSUMPTION

............................................ 8-86 REFERENCES

.................................................................................................................... ...... 8-88

LIST OF TABLES

Table 8.1.1 Summary of Inputs and Key A ssumptions used in the LCC and PBP Analyses

............................................................................................................... 8-4 Table 8.2.1 Representative CAC Products Ev aluated for the Life-Cycle Cost and Payback Analyses

.............................................................................................. 8-11 Table 8.2.2 Baseline Manufacturer Selling Prices per Unit

.................................................. 8-11 Table 8.2.3 SEER Standard-C ompliant Manufacturer Sellin g Prices per Unit

.................... 8-12 Table 8.2.4 Shipping Weights of SEER Standard-complia nt Products

................................ 8-13 Table 8.2.5 MSP Including Transportation of SEER Standard-comp liant Products

............ 8-14 Table 8.2.6 Overall National Average Baselin e Markup Factors by Product Type

............. 8-15 Table 8.2.7 Overall National Incrementa l Markup Factors by Product Type

....................... 8-15 Table 8.2.8 Installation Costs for Ba seline CAC Products (SEER 13)

................................. 8-16 Table 8.2.9 Installation Cost Indices (National Average Value = 100.0)

............................. 8-17 Table 8.2.10 Costs and Markups for Deter mination of Weighted-Average Total Installed Costs for a New 3-Ton Split-system AC Coil-Only Unit (Efficiency Level 5 : SEER 15

............................................................................ 8-17 Table 8.2.11 Manufacturer Selling Price (Inc luding Transportation), Product Price,Installation Cost, and Total Installed Costs for Split-system AC (Coilonly), at Average Prices*

................................................................................... 8-19

8-iTable 8.2.12 Manufacturer Selling Price (Inc luding Transportation), Product Price,Installation Cost, and Total Installed Costs for Split-system AC (BlowerCoil), at Average Prices*

................................................................................... 8-20 Table 8.2.13 Manufacturer Selling Price (Inc luding Transportation), Product Price, Installation Cost, and Total Installed Costs for Split-system HP, at Average Prices*

................................................................................................. 8-22 Table 8.2.14 Manufacturer Selling Price (Inc luding Transportation), Product Price, Installation Cost, and Total Installe d Costs for Single Package AC, at Average Prices*

................................................................................................. 8-23 Table 8.2.15 Manufacturer Selling Price (Inc luding Transportation), Product Price, Installation Cost, and Total Installe d Costs for Single Package HP, at Average Prices *

................................................................................................ 8-24 Table 8.2.16 Regional Averages of the Annua l Average Prices and January and July Marginal Prices

.................................................................................................. 8-28 Table 8.2.17 Effective Marginal Price by Region for the Commercial Building Sample (¢/kWh).

............................................................................................................. 8-29 Table 8.2.18 Central Air Conditioner and Heat Pump Basic Average Repair Costs by Efficiency Level

................................................................................................. 8-33 Table 8.2.19 Central Air Conditioner and H eat Pump Average Repair Costs by Efficiency Level and Region

............................................................................. 8-33 Table 8.2.20 Central Air Conditioner and Heat Pump Basic Average Maintenance Costs by Efficiency Level

............................................................................................ 8-36 Table 8.2.21 Central Air Conditioner and Heat Pump Basic Average Maintenance Costs by Efficiency Level

............................................................................................ 8-37 Table 8.2.22 Central Air Conditioners: Comp arison of RECS and AHS with Modeled Stock

.................................................................................................................. 8-42 Table 8.2.23 Heat Pumps: Comparison of RE CS and AHS Stock to Stock Calculated from a Weibull Survival Function

..................................................................... 8-45 Table 8.2.24 Types of Household Debt and Equity by Percentage Shares

............................. 8-48 Table 8.2.25 Average Nominal Interest Rates for Household Debt

....................................... 8-48 Table 8.2.26 Average Real Effective Inte rest Rates for Household Debt

.............................. 8-49 Table 8.2.27 Average Nominal and Real Inte rest Rates for Household Equity

..................... 8-49 Table 8.2.28 Average Interest on Ho usehold Debt and Equity

.............................................. 8-50 Table 8.2.29 Data Used to Calculate R eal Effective Mortgage Rates

.................................... 8-51 Table 8.2.30 2008 Market Distribution of Effi ciency Levels by Product Class

..................... 8-53 Table 8.4.1 Mean Market Baseline Inst alled Costs, Total Annual Energy Consumption, and Percentage Change for Split-System Air Conditioners (Coil-Only) by Region by Efficiency Level (SEER Value)

.............................. 8-56 Table 8.4.2 Mean Market Baseline Inst alled Costs, Total Annual Energy Consumption, and Percentage Change for Split-System Air Conditioners (Blower-Coil) by Region by Efficiency Level (SEER Value)

........................... 8-56 Table 8.4.3 Mean LCC Savings for Split-System Air Conditioners (Coil-only) by Region by Efficiency Level (SEER Value)

....................................................... 8-58 Table 8.4.4 Mean LCC Savings for Split-Syst em Air Conditioners (Blower-Coil) by Region by Efficiency Level (SEER Value)

....................................................... 8-59

8-iiTable 8.4.5 Mean Payback Period for Split-Sy stem Air Conditioners (Coil-Only) by Region

................................................................................................................ 8-61 Table 8.4.6 Mean Payback Period for Split-sy stem Air Conditioners (Blower-Coil) by Region

................................................................................................................ 8-61 Table 8.4.7 Mean Rebuttable Payback Period for Split-System Air Conditioners (CoilOnly) by Region

................................................................................................. 8-62 Table 8.4.8 Mean Rebuttable Payback Pe riod for Split-system Air Conditioners (Blower-Coil) by Region

................................................................................... 8-62 Table 8.4.9 National LCC and PBP Results for Split-System Air Conditioners (CoilOnly) by Efficiency Level (SEER Value): Nation

............................................ 8-64 Table 8.4.10 LCC and PBP Results for Split-Sy stem Air Conditioners (Blower-Coil) by Efficiency Level (SEER Value): Nation

............................................................ 8-64 Table 8.4.11 LCC and PBP Results for Split-Sy stem Air Conditioners (Coil-Only) by Efficiency Level (SEER Value): Hot-Humid Region

........................................ 8-65 Table 8.4.12 LCC and PBP Results for Split-Sy stem Air Conditioners (Blower-Coil) by Efficiency Level (SEER Value): Hot-Humid Region

........................................ 8-65 Table 8.4.13 LCC and PBP Results for Split-Sy stem Air Conditioners (Coil-Only) by Efficiency Level (SEER Value): Hot-Dry Region

............................................. 8-66 Table 8.4.14 LCC and PBP Results for Split-Sy stem Air Conditioners (Blower-Coil) by Efficiency Level (SEER Value): Hot-Dry Region

............................................. 8-66 Table 8.4.15 LCC and PBP Results for Split-Sy stem Air Conditioners (Coil-Only) by Efficiency Level (SEER Valu e): Rest of Country

............................................. 8-67 Table 8.4.16 LCC and PBP Results for Split-Sy stem Air Conditioners (Blower-Coil) by Efficiency Level (SEER Valu e): Rest of Country

............................................. 8-67 Table 8.4.17 Mean Market Baseline Inst alled Costs, Total Annual Energy Consumption, and Percentage Change for Split-System Heat Pumps by Region by Efficiency Level (SEER Value)

....................................................... 8-68 Table 8.4.18 Mean LCC Savings for Split-System Heat Pumps by Region by Efficiency Level (SEER Value and HSPF Value)

............................................................... 8-69 Table 8.4.19 Mean Payback Period for Split-System Heat Pumps by Region (Years)

.......... 8-71 Table 8.4.20 Mean Rebuttable Payback Period for Split-System Heat Pumps by Region (Years)

................................................................................................................ 8-71 Table 8.4.21 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level (SEER Value): Nation

........................................................................................ 8-72 Table 8.4.22 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level (SEER Value): Hot-Humid Region

................................................................... 8-73 Table 8.4.23 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level (SEER Value): Hot-Dry Region

........................................................................ 8-73 Table 8.4.24 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level (SEER Value): Rest of Country

......................................................................... 8-74 Table 8.4.25 Mean Market Baseline Inst alled Costs, Total Annual Energy Consumption, and Percentage Ch ange for Single Package Air Conditioners by Region by Efficiency Level (SEER Value)

............................. 8-75 Table 8.4.26 Mean LCC Savings for Single Package Air Conditioners by Region by Efficiency Level (SEER Value)

......................................................................... 8-76 Table 8.4.27 Mean Payback Period for Single Package Air Conditioners by Region

............ 8-77

8-iiiTable 8.4.28 Mean Rebuttable Payback Period for Single Package Air Conditioners by Region

................................................................................................................ 8-78 Table 8.4.29 LCC and PBP Results for Single Package Air Conditioners by Efficiency Level (SEER Value): Nation

............................................................................. 8-79 Table 8.4.30 LCC and PBP Results for Single Package Air Conditioners by Efficiency Level (SEER Value): Hot-Humid Region

......................................................... 8-79 Table 8.4.31 LCC and PBP Results for Single Package Air Conditioners by Efficiency Level (SEER Value): Hot-Dry Region

.............................................................. 8-79 Table 8.4.32 LCC and PBP Results for Single Package Air Conditioners by Efficiency Level (SEER Value): Rest of Country

............................................................... 8-80 Table 8.4.33 Mean Market Baseline Inst alled Costs, Total Annual Energy Consumption, and Percentage Change for Single Package Heat Pumps by Region by Efficiency Level (SEER Value)

....................................................... 8-81 Table 8.4.34 Mean LCC Savings for Single Package Heat Pumps by Region by Efficiency Level (SEER Value)

......................................................................... 8-82 Table 8.4.35 Mean Payback Period for Single Package Heat Pumps by Region (Years)

...... 8-84 Table 8.4.36 Mean Rebuttable Payback Period for Single Package Heat Pumps by Region (Years)

................................................................................................... 8-84 Table 8.4.37 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level (SEER Value): Nation

........................................................................................ 8-85 Table 8.4.38 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level (SEER Value): Hot-Humid Region

................................................................... 8-85 Table 8.4.39 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level (SEER Value): Hot-Dry Region

........................................................................ 8-86 Table 8.4.40 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level (SEER Value): Rest of Country

......................................................................... 8-86 Table 8.5.1 Details of Regional LCC a nd Payback Period for Off-Mode Power Consumption Measure: Crank Case Heaters (National Only)

........................... 8-87

8-ivLIST OF FIGURES

Figure 8.1.1 Flow Diagram of Inputs for the Determination of LCC and PBP

....................... 8-4 Figure 8.2.1 Electricity Price Trends for Residential Rates to 2047

...................................... 8-31 Figure 8.2.2 Electricity Price Trends for Commercial Rates to 2047

.................................... 8-31 Figure 8.2.3 Comparison of DOE Modeled Air Conditioner Age Distribution with RECS Reported Stock

........................................................................................ 8-43 Figure 8.2.4 Comparison of DOE Modeled To tal Air Conditioner Stock with Adjusted AHS Stock

......................................................................................................... 8-43 Figure 8.2.5 Central AC Survival Functi on, Characterized by Weibull Parameters α = 20.29, β = 1.89, and θ = 1.0.

.............................................................................. 8-44 Figure 8.2.6 Comparison of DOE Modeled Tota l Heat Pump Stock with Adjusted AHS Stock

.................................................................................................................. 8-46 Figure 8.2.7 Heat Pump Survival Functi on, Characterized by Weibull Parameters α= 17.04, β = 1.64, and θ = 1.0.

.............................................................................. 8-46 Figure 8.4.1 Market Baseline Distributions of LCC for Split-System Air Conditioners (Coil-Only) by Region

....................................................................................... 8-57 Figure 8.4.2 Market Baseline Distributions of LCC for Split-System Air Conditioners (Blower-Coil) by Region

................................................................................... 8-58 Figure 8.4.3 Plots of the Distributions of LCC Savings for Split-System Air Conditioners (Coil-Only) by Region

................................................................. 8-60 Figure 8.4.4 Plots of the Distributions of LCC Savings for Split-system Air Conditioners (Blower-Coil) by Region

.............................................................. 8-60 Figure 8.4.5 Plots of the Distributions of PBP for Split-system Air Conditioners (CoilOnly) by Region

................................................................................................. 8-63 Figure 8.4.6 Plots of the Distributions of PBP for Split-system Air Conditioners (Blower-Coil) by Region

................................................................................... 8-63 Figure 8.4.7 Market Baseline Distributions of LCC for Split-System Heat Pumps by Region

................................................................................................................ 8-69 Figure 8.4.8 Plots of the Distributions of LCC Savings for Split-system Heat Pumps by Region

................................................................................................................ 8-70 Figure 8.4.9 Plots of the Distributions of PBP for Split-System Heat Pumps by Region

...... 8-72 Figure 8.4.10 Market Baseline Distributi ons of LCC for Single Package Air Conditioners by Region

..................................................................................... 8-76 Figure 8.4.11 Plots of the Distributions of LCC Savings for Single Package Air Conditioners by Region

..................................................................................... 8-77 Figure 8.4.12 Plots of the Distributions of PBP for Single Package Air Conditioners by Region

................................................................................................................ 8-78 Figure 8.4.13 Market Baseline Distributions of LCC for Single Package Heat Pumps by Region

................................................................................................................ 8-82 Figure 8.4.14 Plots of the Distributions of LCC Savings for Single Package Heat Pumps by Region

........................................................................................................... 8-83 Figure 8.4.15 Plots of the Distributions of PBP for Single Package Heat Pumps by Region

................................................................................................................ 8-84

8-vCHAPTER 8. LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS

8.1 INTRODUCTION

The effect of amended standards on individua l customers usually includes a reduction in operating cost and an increase in purchase cost. This chapter describes two metrics used in the analysis to determine the economic impact of standards on individual co mmercial customers:

• Life-cycle cost (LCC) is the total customer cost over the life of an appliance or product, including purchase costs and operating costs (whi ch in turn include maintenance, repair, and energy costs). Future operating costs are discounted to the time of purchase, and summed over the lifetime of the appliance or product.

• Payback period (PBP) measures the amount of time it takes customers to recover the assumed higher purchase price of more energy-efficient product through reduced operating costs.

DOE conducted the LCC and PBP analysis us ing a spreadsheet model developed in Microsoft Excel. When combined with Crystal Ball (a commercially available software program), the LCC and PBP model generates a Monte Carlo simulation to perform the analysis by incorporating uncertainty and variability considerations in certain of the key parameters as discussed below.

Inputs to the LCC and PBP analyses of central air conditioning (C AC) and central heat pump (CHP) products are discussed in sections 8.2 and 8.3 respectivel y. Results for each metric are presented in section 8.4. Key variables and ca lculations are presented for each metric. The calculations discussed here were perform ed with a series of Microsoft Excel spreadsheets which are accessible over the Internet ( http://www1.eere.energy.gov/buildings/applianc e_standards/residen tial/central_ac_hp.html ).

Details of, and instructions for, using the spreadsheets are discussed in appendix A. A more complete set of results of the analyses are presented in appendix F.

8.1.1 General Approach for Life-Cycle Co st and Payback Period Analyses

In recognition that each building where air c onditioners or heat pumps are used is unique, variability and uncertainty is analyzed by performing the LCC and PBP calculations detailed here for a representative sample of indivi dual households and commercial buildings. The analysis takes into account product use in comme rcial buildings based on the assumption that seven percent of product applica tions are in commercial buildings . The results are expressed as the number of buildings experiencing economic impacts of different magnitudes. The LCC and PBP model was developed using Microsoft Excel spreadsheets combined with Crystal Ball (a commercially available add-in). The LCC and PBP analyses explicitly model both the uncertainty and the variability in the model’s inputs using Monte Carlo simulation and probability distributions.

The LCC analysis used the estimated energy use for each CAC unit as described in the energy use characterization analysis in Chapter 7 of the TSD. Energy use of CACs is sensitive to climate, so it varies by location within the United States. An important feature of the LCC and

8-1PBP analysis is that it has been conducted at both the regional and national level. Aside from energy use, other important factors influencing the LCC and PBP analyses include energy prices, installation costs, product distri bution markups, and sa les tax. At both the National and the regional level, the LCC spreadsheets explicitly modeled both the uncertainty and the variability in the model’s inputs, using probability distribu tions based on the shipme nt of CAC product to different regions of the country.

As mentioned above, DOE gene rated LCC and PBP results as probability distributions using a simulation based on Monte Carlo analysis methods, in which certain key inputs to the analysis consist of probability distributions rather than single-point values. Therefore, the outcomes of the Monte Carlo analysis can also be expressed as probability distributions. As a result, the Monte Carlo analysis produces a range of LCC and PBP results. A distinct advantage of this type of approach is that DOE can id entify the percentage of customers achieving LCC savings or attaining certain PBP va lues due to an increased efficiency level, in addition to the average LCC savings or average PBP for that efficiency level.

The LCC and PBP results are displayed as distributions of impacts compared to a market baseline. As described in Chapter 7, the market baseline efficiency level is for 2016 is defined as a mix of CAC efficiency levels reflecting the curr ent distribution of effici ency levels purchased by product class. Results are presented at the end of this chapter. A variety of graphic displays can be created to illustrate the implications of the analysis. Examples of graphic displays are (1) a cumulative probability distribution showing the percentage of CAC product in U.S. residential and commercial buildings that w ould experience a net LCC savings, and (2) a cumulative frequency chart depicting variation in PBP for each CAC efficiency level considered.

All analyses were performed under the assumption that the current R-22 refrigerant would have been displaced by an alternative re frigerant in 2010 due to provisions in the Clean Air Act. The analysis methodology and results pr esented in this chapter assume that all CAC and CHP products manufactured after 2010 will use R-410A.

8.1.2 Overview of Life-Cycle Cost and Payback Period Analyses Inputs

The LCC is the total customer cost over the life of the product, including purchase price (including retail markups, sales taxes, and installa tion costs), and operating co st (including repair costs, maintenance costs, and energy cost). Future operating costs are discounted to the time of purchase and summed over the lifetime of the product. The PBP is the increase in purchase cost of higher efficiency product divided by the chan ge in annual operating cost (as a result of lower energy consumption) of the product. It repres ents the number of years that it will take the customer to recover the increased purchase cost through decreased operating costs. In the calculation of PBP, future costs are not discounted.

Inputs to the LCC and PBP analyses are categorized as follows: (1) inputs for establishing the purchase cost, otherwise known as the total installed cost, and (2) inputs for calculating the operating cost (i.e., energy, maintenance, and repair costs).

The primary inputs for establishing the total installed cost are:

8-2• Baseline manufacturer selling price : The baseline manufacturer selling price (MSP) is the price charged by the manufacturer to e ither a wholesaler or customer for product meeting existing minimum efficiency (or baseline) standards. The manufacturer selling price includes a markup that converts the cost of production (i.e., the manufacturer cost) to a manufacturer selling price.

• Standard-level manufacturer selling price increase : The standard-level MSP is the incremental change in MSP associated with producing product at each of the higher standard levels.

• Markups and sales tax : Markups and sales tax are the w holesaler and contractor margins and state and local retail sales taxes associated with converting the MSP to a customer price. The markups and sales tax are desc ribed in detail in Chapter 6, Markups for Product Price Determination.

• Installation cost : Installation cost is the cost to th e customer of installing the product. The installation cost represents all costs re quired to install the CAC product but does not include the marked-up customer product pric e. The installation cost includes labor, overhead, and any miscellaneous mate rials and parts. Thus, the total installed cost equals the customer product price pl us the installation price.

The primary inputs for calculating the operating cost are:

• Product energy consumption : The product energy consumption is the site energy use associated with the use of the CAC units to provide space-conditioning to the building. Chapter 7, Building Energy Use Characteri zation, provides comple te details on CAC energy use simulations and their results.

• Energy Prices : Electricity prices used in the anal ysis are the price per kilowatt-hour in cents or dollars ($/kWh) paid by each customer for electricity. Electricity prices are determined using marginal residential and commercial prices calculated from electrical tariff information on individual service areas, as determined from utility data on 90 utilities, in 2008 dollars 1

.

• Electricity, natural gas, and fuel oil price trends : The EIA’s April 2009 update to the Annual Energy Outlook 2009 ( AEO 2009 ) is used to forecast electricity prices into the future 2

.

• For the results presented in this chapter, DOE used the April 2009 update to the AEO 2009 reference case to forecast future electricity prices.

• Maintenance costs : The labor and material costs associated with maintaining the operation of the product (e.g., cleaning heat ex changer coils and drain pans, changing air filters, etc.).

• Repair costs : The labor and material costs associated with repairing or replacing components that have failed.

• Lifetime : The age at which the CAC product is retired from service.

• Discount rate : The rate at which future costs ar e discounted to establish their present value. Figure 8.1.1 graphically depicts the re lationships between the installed cost and operating cost inputs for the calculation of the LCC and PBP.

8-3Manufacturer Sales Price Standard i 1...n

Manufacturer Sales Price Standard i= 1...n

Installation Costs Installation Costs

Repair Costs

Repair Costs Lifetimes Lifetimes Annual Maintenance Electricity Consumption

Electricity Consumption

Manufacturer Base Price

Total Installed Cost (Std i Base) Manufacturer Base Price

Contractor Markups Wholesaler/
Distributor Markup

Electricity Prices Equipment Prices

Sales Tax

Manufacturer Selling Price (Base)

Installation Costs Manufacturer Selling Price Standard i 1...n

Electricity Consumption Annual Energy Costs

Annual Maintenance

Repair Costs Annual Operating Cost (Std i Base) Payback Period

Discount Rate

Lifetimes Lifetime Operating Cost (Std i – Base) Lifecycle Cost

Annual Maintenance Costs Manufacturer Sales Price Standard i 1...n

Manufacturer Sales Price Standard i= 1...n

Installation Costs Installation Costs

Repair Costs

Repair Costs Lifetimes Lifetimes Annual Maintenance Electricity Consumption

onsumption Manufacturer Base Price

anufacturer Base ice

Annual Maintenance =

–

=

- =

Electricity C Total Installed Cost (Std i –Base) M Pr

Contractor Markups Wholesaler/
Distributor Markup

Electricity Prices Equipment Prices

Sales Tax

Manufacturer Selling Price (Base)

Installation Costs Manufacturer Selling Price Standard i= 1...n

Electricity Consumption Annual Energy Costs

Repair Costs Annual Operating Cost (Std i - Base) Payback Period

Discount Rate

Lifetimes Lifetime Operating Cost (Std i – Base) Lifecycle Cost

Annual Maintenance Costs

Figure 8.1.1 Flow Diagram of Inputs for the Determination of LCC and PBP

Table 8.1.1 provides descriptions for the various inputs to the calculation of the LCC and PBP. As noted earlier, most of the inputs are characterized by probability distributions that capture variability in the input variables.

Table 8.1.1 Summary of Inputs and Key Assumptions used in the LCC and PBP Analyses Inputs Description Affecting Installed Costs

Product Price Derived by multiplying MSP for 3-ton capacity units (from the engineering analysis) by wholesaler markups and contractor markups plus sales tax (from markups analysis). Used the probability distribution for the different markups to describe their variability.

Installation Cost Includes installation labor derived from RS Means CostWorks 2009 and RS Means Residential Cost Data 2009 . Overhead and materials costs and profits are assumed to be included in the contractor’s markup. Thus, the total installed cost equals the c onsumer product price (manufacturer cost multiplied by the various mar kups plus sales tax) plus the installation cost.

Transportation Cost Shipping cost of units based on weight of the unit, average shipment distance of 1100 miles, and an average cost of $0.20 per pound based on that distance and a range of rates from the FreightCenter.com website. Affecting Operating Costs

Annual Energy Use For central air conditioners, the annual energy consumption is the annual site energy use associated with providing space-cooling. For heat pumps, the annual energy consum ption is the annual site energy

8-4use associated with providing bot h space-cooling and space-heating. For households, the annual energy consumption is based on data from the EIA 2005 Residential Energy Consumption Survey (RECS) . For those households surveyed in RE CS with either a central air conditioner or heat pump, the estima ted annual energy consumption corresponds to the household’s air conditioner or heat pump, specifically its capacity and effi ciency. For products used in commercial buildings, the annual ener gy consumption is determined through computer simulations of a representative small commercial building based DOE commercial sm all-office benchmark building developed for use as a baseline benchmark for DOE’s Net Zero Commercial Building Initiative 3

.

Energy Efficiency The seasonal energy efficiency ratio (SEER) is the efficiency descriptor for central air conditioners. For heat pumps, the cooling efficiency is represented with the SEER while the heating efficiency is represented with the heating seas onal performance factor (HSPF). Central air conditioner and heat pump efficiencies in existing households are primarily based on data from the 2005 RECS . For product used in commercial buildings , all buildings were assumed to have product efficiencies equal to existing minimum efficiency standards (SEER 13). To estimate the annual energy consumption associated with a particular standard-level, the ratio of the building’s stock efficiency to the standard-level efficiency is multiplied by the building’s annual energy consumption.

Table 8.1.1 (contd) Inputs Description

Energy Prices For residential customers, calculated for RECS 2005 households from marginal and average electricity price in each utility service area in each region, as determined from utility tariff data for 2008, escalated by the AEO2009 forecasts to estimate the future electricity prices. For commercial customers, the analysis used commercial marginal and average electricity price in each utility service area in each region, as determined for 2004, escalated to 2008 prices using data from Edison Electric Institute and Regulatory Research Associates.

Maintenance Cost The cost associated with mainta ining the operation of the product (e.g., cleaning heat exchanger co ils, checking refrigerant charge levels). Costs were chosen from an array of services from a variety of published sources. Annual maintenance cost increased as a function of
MSP.

Repair Cost Estimated the annualized repair cost for baseline efficiency CAC product, based on costs of major repair (compressor replacement), from a variety of published sources. It is assumed that repair costs would vary in direct proportion with the MSP at higher efficiency levels because it generally costs more to replace components that are more efficient. Affecting Present Value of Annual Operating Cost Savings

Product Lifetime Used the probability distribution of lifetimes, with mean lifetime for each of four product classes assumed to be 19 years for air conditioning units and

8-516.3 years for heat pumps based on literature reviews and consultation with industry experts.

Discount Rate Mean real discount rates ranging from 0 percent to 10.7 percent for various
classes of residential customers based on Federal Reserve Board’s Survey of Consumer Finances . Commercial sector customers are expected to have a mean real discount rate of 7.4 percent based on a sample of 1750 companies on the Damodaran Online website. Probability distributions are assumed for the discount rates of both groups of customers.
Date Standards Become Effective June 30, 2016 (five years after the publication of the final rule)

Analyzed Efficiency Levels

Analyzed Efficiency Levels Baseline efficiency levels will follow the estimated market distribution of efficiency levels in 2016 based on a minimum SEER of 13 for new units and from seven to fifteen higher efficiency levels available in four principal product classes.

All of the inputs depicted in Figure 8.1.1 a nd summarized in Table 8.1.1 are discussed in sections 8.2 and 8.3.

8.1.3 Analysis Use of Residential Energy Co nsumption Survey (RECS) in LCC and
PBP

The LCC and PBP calculations detailed here ar e for a representative sample of individual households and commercial buildings . Ninety-three percent of product applications are assumed to be in residential buildings (households) 4

.
For products used in households, the 2005 Residential Energy Consumption Survey (RECS) 1 serves as the basis for determining the re presentative sample. The 2005 RECS is based on a sample of 4382 households which were surv eyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energyrelated behavior. Information was also coll ected on certain demographic and economic characteristics of household members.

The information collected represents a ll households nationwid e – approximately 111 million. RECS is conducted every three years with da ta collected directly from energy end users. The 2005 RECS is the twelfth survey of re sidential housing units conducted by the U.S Department of Energy’s (DOE) Energy Informat ion Administration (EIA). Previous RECS were conducted annually from 1978 to 1982 and triennially since 1984. The RECS consists of three parts:

• Personal interviews with households for information about energy used, how it is used, energy-using appliances, structural feat ures, energy efficiency measures, and demographic characteristics of the household.

• Telephone interviews with rental agents for hous eholds that have any of their energy use included in their rent. This information au gments information collected from those households that may not be knowledgeable a bout the fuels used for space heating or water heating.

8-6• Mail questionnaires sent to energy suppliers (after obtaining permission from households) to collect the actual billing data on energy consumption and expenditures.

Of the 4,382 households surveyed in the 2005 RECS, 1,854 households representing 25.1% of the housing population have a cent ral air conditioner while 339 households representing 7.7% of housing population have an electric heat pump a . Using the households in RECS that utilize a central air conditioner or heat pump, LCC and PBP analyses are performed on a household-by-household basis to determine whether an increa se in the minimum efficiency standard is economically justified. Each RECS household is identified to be within one of the three geographic regions discussed previously in chapter 7 and has a associated household weight representing the number of similar households in the nation..

Of the inputs necessary for the LCC and PBP an alysis, there are four inputs (as depicted in Figure 8.1.1) which are based on data fro m the 2005 RECS; 1) space-conditioning annual energy consumption (RECS-based), 2) product ef ficiency, 3) average electricity price, and 4) marginal electricity price. All four of these inputs are used in determining the operating cost. With the exception of the product efficiency, each household in RECS with a central air conditioner or heat pump has a unique value for the space-conditioning annual energy consumption, the average electricity price, and the marginal elec tricity price. In other words, the annual energy consumption, average electricity pri ce, and marginal electricity price associated with a particular RECS househol d are not uncertain and are, therefore, not expressed with probability distributions. Although the above thr ee input variables are not uncertain, they are extremely variable. Due to the large number of households considered in the LCC and PBP analysis (over 1850 for central air conditioners an d over 300 for heat pumps), the range of annual energy use, average electricity price, and marginal electricity price is quite large (the actual ranges are presented and discusse d later in this chapter). Thus, although the above three input variables are not uncertain for any particular household, their variability across all households contributes significantly to the range of LCCs and PBPs calculated for any particular standard level.

8.1.4 Commercial Building Analysis

Seven percent of residential- type (i.e., single-phase) centr al air conditioner and heat pump applications are assumed to be in commercial buildings. A small commercial office building was simulated at 237 different loca tions around the country corresponding to the Typical Meteorological Year-2 weather stations) 5 was used to represent commercial applications for CAC and CHP units. The results from these simulations were used for the LCC and PBP analysis of commercial buildings, allowing for a building-by-building approach to be utilized for determining whether an increase in the standard is economically justified (e.g., similar to the approach described above for households from the 2005 RECS). DOE used population weighting factors to represent the importance of e ach climate in each state, and in each of the

a The number of households actually used in the central air conditioner and heat pump LCC and PBP analyses were 1,854 and 339, respectively. A small number of central air-conditioned households were dropped from the analysis for one or more of the following reasons: 1) the central air conditioner was not used, 2) a room air conditioner was present and used, or 3) marginal energy prices could not be determined for the household. With regard to households with heat pumps, they were dropped from the analysis for one or more of the following reasons: 1) the heat pump was not used or 2) marginal energy prices could not be determined for the household.

8-7three regions. These weighting factors, in conjunction with the relative weighting between commercial and residential shipments were used to incorporate the commercial building energy consumption into the overall energy consumption for CAC and CHP equipment at each efficiency level. Seventeen locations in Alaska, representing less than 0.2 percent of the national population, were eventually removed from the LCC an alysis due to lack of data for electrical pricing and uncertainty about comme rcial use in these climates.

As with the analysis of residential buildings , four inputs are necessary (as depicted in Figure 8.1.1) from the commercial building analys is in order to perform the LCC and PBP calculations: 1) space-conditioning annual energy consumption, 2) product efficiency, 3) average electricity price, and 4) marginal electricity price. The space-conditioning energy consumption associated with the commercial building in each of the full set of 237 lo cations simulated were determined through computer modeling perform ed at Pacific Northw est National Laboratory (PNNL) using the Energy Plus simulation tool. The procedure for calculating space-conditioning energy consumption relied on the determination of hourly operating loads for each of the 237 buildings.

DOE performed an analysis in which DOE used the Energy Plus building energy simulation software to simulate the energy consumption of CAC and CHP used to satisfy the cooling, supply fan, and in the case of CHP, th e electrical heating ener gy required in a small office building. DOE used an existing small o ffice building model developed for DOE’s energy benchmarking task for this analysis. The determination of space cooling and space-heating loads assumed that a single type of product, in our case residential-type space-conditioning product, was used to condition the building. DOE simulated the same building as served either by CAC or CHP equipment and for each equipment type, si mulated the equipment using four different efficiency levels. These levels were a 13 S EER, 14 SEER, 16 SEER, and a max tech level for either CAC (SEER 22, based on blower-coil ra tings, or SEER 16.5, based on coil-only ratings) or CHP (SEER 19.5). Equipment pa rameters used in the simulati on were adjusted to reflect engineering designs corresponding to each efficiency level. The simulated building utilized five individual CAC or CHP units. DOE extracted th e annual energy consumption for cooling and fan energy use and CHP heating from each unit as well as the equipment capacity from each unit from each simulation run and aggregated these to the whole building level. Using this whole building data, DOE normalized the CAC and CHP energy consumption for each location and efficiency level to reflect that of an average 3- ton CAC or CHP unit for use in the LCC analysis. To estimate the energy consumption for intermediate efficiency levels between those simulated, DOE linearly interpolated the energy use estimates based on the results for the four simulated efficiencies. A complete descri ption of the commercial energy use calculations is found in Chapter 7.

The baseline commercial CAC and CHP use developed for the 237 TMY locations were associated with relative weighting factors for each TMY location much as the residential analysis uses the representative RECS weights. DOE us ed population-based weight ing factors developed for each TMY climate based on data from the USGS to represent the importance of each TMY2 climate in each state. The development and documentation of these weighting factors is discussed in chapter 7. Because certain TMY locations represent climates that cover more than one state DOE originally developed weigh ting factors for a total of 543 TMY-State combinations. Removal of the se venteen Alaskan locations discussed previously resulted in 526

8-8TMY-State combinations, with a ssociated population weights, whic h then formed the basis of the commercial energy use sample.

The average and marginal electricity prices were developed through a procedure of matching building hourly loads for each of th e 526 represented buildings to actual modeled commercial tariffs (including any time-of-use rates) and then calculating customer bills. The methodology for matching commercial building peak demands to modeled tariffs is explained in appendix 8-B. Energy bills are calculated for a market baseline case and standards cases. Average electricity prices are determined by taking the bill for the market baseline case and dividing it by the amount of energy consumed. Ma rginal electricity pri ces are determined by taking the bill difference between the market baseline and standard cases (in dollars) and dividing it by the usage difference (in kWh) to give a “marginal” rate of $/kWh for that
increment.

Since several tariffs were applied to each building, both the average and marginal rates calculated from each tariff were weighted by the number of customers covered by the tariff to come up with a weighted-average marginal and average rate for each building in each region. The above procedure was used to develop space- cooling and space-heating average and marginal rates. Since detailed building loads and demands were not available for space-heating, average rather than marginal electricity prices were used to determine the energy costs associated with the operation of heat pumps during the space-heating season.

As with the residential buildings from the RECS sample, the annual energy consumption, average electricity price, and marginal electr icity price associated with each of the 526 commercial buildings observations are not uncerta in and are, therefore, not expressed with probability distributions. Although the above thr ee input variables are not uncertain, they are variable. Due to the number of buildings consider ed in the LCC and PBP analysis, the range of annual energy use, average electricity price, and marginal electricity price is large (the actual ranges are presented and discusse d later in this chapter). Thus, although the above three input variables are not uncertain for any particular building, their variability across all buildings contributes significantly to the range of LCCs and PBPs calculated for any particular standardlevel.

8.2 LIFE-CYCLE COST ANALYSIS INPUTS

8.2.1 Definition

Life-cycle cost is the total customer cost over the life of a piece of product, including purchase cost and operating costs (which are comp rised of energy costs, maintenance costs, and repair costs). Future operating costs are disc ounted to the time of purchase and summed over the lifetime of the product. Life-cycle cost is defined by the following equation:

N LCC = IC + 

# ∑ OC
t /(1 + r ) t Eq. 8.2.1

t = 1

Where:

8-9LCC = life-cycle cost ($),
IC = total installed cost ($), ∑ = sum over the lifetime, from year 1 to year N, where N = lifetime of product (years),
OC = operating cost ($),

r = discount rate, and

t = year for which operating cost is being determined.

Although DOE gathered most of its data fo r the LCC analysis in 2009, DOE expresses all the costs in 2008$. By convention, DOE reports its costs in the years’ dollars preceding the year of the analysis. Total installed cost, operating co st, lifetime, and discount rate are discussed in the following sections. In the LCC analysis, th e year of product purchase is assumed to be 2016, the effective date of the amended en ergy conservation standards for CACs.

8.2.2 Total Installed Cost Inputs

The total installed cost to the customer is defined by the following equation:

IC = EQP + INST Eq. 8.2.2

Where: EQP = product price ($) (i.e., customer price for the product only),
INST = installation cost or the customer price to install product ($) (i.e., the cost for labor and materials).

The product price is based on the distribu tion channel through which the customer purchases the product. As discussed in Chap ter 6, Markups for Produc t Price Determination, DOE defined one major distribution channel for new units to describe how the product passes from the manufacturer to the customer: the manufacturer sells the product to a wholesaler/distributor, who sells to a mechanical contractor hired by a general contractor. The general contractor purchases and installs the product on behalf of the customer and adds its markup to the mechanical contr actor’s price. Replacement product s follow the same distribution channel, except that there is no general contract or. Instead, the mechanical contractor takes on the general contractor’s function.

The remainder of this section provides information about the variables DOE used to calculate the total installed cost for CAC products. Inputs to dete rmine total installed cost are shown below:

• Baseline manufacturer selling prices ($) (section 8.2.2.1)

• Standard-level manufacturer sellin g price increases ($) (section 8.2.2.2)

• Transportation costs ($) (section 8.2.2.3)

• Overall markups (section 8.2.2.4)

• Installation costs ($) (section 8.2.2.5)

• Weighted-average total installed costs ($) (section Error! Reference source not found. )

8-108.2.2.1 Baseline Manufacturer Selling Price

The baseline MSP is the price charged by manuf acturers to either a wholesaler or very large customer for product meeting existing minimum efficiency (or baseline) standards. The MSP includes a markup that converts the cost to manufacture (i.e., the manufacturing cost) to a MSP. DOE developed the baseline MSP through an efficiency level analysis supplemented by certain design-option considera tions. Refer to Chapter 5, Engineering Analysis, for details. DOE developed MSP for product classes identified in market and technology assessment analysis, Chapter 3 of the TSD. The LCC and PBP were calculated ba sed on the same set of representative products as given in Table 8.2.1.

Table 8.2.1 Representative CAC Products E valuated for the Life-Cycle Cost and Payback Analyses

Product Class Representative Products Description SS-AC (Coil- Only) SS-AC-3T (Coil- Only) Split-system air conditioners, inside evaporator coil-only (no blower unit purchased) SS-AC (Blower-Coil) SS-AC-3T (Blower-Coil) Split-system air conditioners, including blower unit (evaporator coil and air handler purchased)
SS-HP SS-HP-3T Split-system heat pumps
SP-AC SP-AC-3T Single-package air conditioners
SP-HP SP-HP-3T Single-package heat pumps
SDHV SDHV-3T Small-duct high-velocity (SDHV) systems
SC-AC SC-AC-3T Space-constrained products – air conditioners
SC-HP SC-HP-3T Space-constrained products – heat pumps

DOE determined the market baseline with a minimum requirement of 13 SEER 6 as the baseline efficiency levels for CACs. The minimum efficiency levels specified are detailed in Chapter 5, Engineering Analysis. In the case of split-system air conditioners, DOE analyzed options with and without a complete air handler unit, since it is not clear whether a furnace or other fan unit would be purchase d at the same time as the insi de evaporator coil and outside condensing unit. DOE developed the MSP for the baseline efficiency product as a part of the engineering analysis (see Chapter 5 of the TSD), which are shown in Table 8.2.2.

Table 8.2.2 Baseline Manufacturer Selling Prices per Unit

Representative Product SEER (Baseline Efficiency) Baseline Manufacturer Selling Price* 2008$ SS-AC-3T (Coil-Only) 13.0 885 SS-AC-3T ( Blower-Coil) 13.0 1,063
SS-HP-3T 13.0 1,255
SP-AC-3T 13.0 959
SP-HP-3T 13.0 1,186
SDHV-3T 13.0 1,191
SC-AC-3T 13.0 1,196
SC-HP-3T 13.0 1,201

* Baseline MSP is based upon the CAC products using R-410A refrigerant.

8-11Since air conditioners and heat pumps are commonly sold in situations where heating and cooling equipment are being considered togeth er, there is some uncertainty determination of what assumption should be made concerning any co st and efficiency benefit for a fuel-fired (gas-, oil-, or LPG-fired) furnace. To accountfor this, the manufacturer selling price for splitsystem air conditioner is handled two ways. 1) In coil-only purchases, the air conditioning unit is installed in a situation where a medium-efficiency furnace fan is available to circulate air. This accounts for replacement scenarios in which a furnace fan is already available as well as new systems where the furnace is purchased separately . 2) In blower-coil purchases, it is assumed that there either is no furnace or that its air-handling capacity is not adequate for the air conditioning unit. In this case, the cost include s an air handler with a blower and evaporative coil. Systems using a blower coil can use impr ovements on the indoor air-handler to achieve higher SEER ratings. Systems rated as “co il-only” systems must use improvements on the indoor coil or outdoor condensing unit to achieve higher SEER rating. For simplicity, splitsystem heat pumps were assumed to always be sold with an air handler, due to the need to closely match condensing, evaporative, and air ha ndling capabilities to gain efficiency in a heat pump system. Single package heat pumps and sing le package air conditioners sold as complete packages, including condensing unit, evaporator unit, and blower.

8.2.2.2 Standard-Compliant Manufac turer Selling Price Increases

The standard-compliant MSP increase is the change in MSP associated with producing product at higher efficiency levels. DOE devel oped MSP increases associated with increases in product efficiency levels through a combination of efficiency level and design-option analyses in the engineering analysis (see Chapter 5 of the TSD). MSP increases as a function of product efficiency were developed for each of the re presentative product categories in the engineering analysis as well. Table 8.2.3 summarizes the es timated MSP for CAC and CH P efficiency levels considered in the LCC and PBP analyses.

Table 8.2.3 SEER Standard-Compliant Manufacturer Selling Prices per Unit

Efficiency

Level MSP for Representative Standard-Compliant Products 2008$

SplitsystemAC (CoilOnly) Splitsystem AC(BlowerCoil) Splitsystem HP Single Package AC Single Package
HP
Level 2 930 1,114 1,313 1,045 1,241
Level 3 979 1,165 1,375 1,103 1,312

Level 4 1,033 1,220 1,421 1,188 1,416.

Level 5 1,095 1,259 1,465 1,257 1,507
Level 6 1,171 1,300 1,515 1,344 1,613

Level 7 1,269 1,343 1,578 1,448 1,740

Level 8 1,382 1,387 1,687 1,596. 1,866
Level 9 NA 1,433 1,804 NA NA

Level 10 NA 1,529 1,930 NA NA

Level 11 NA 1,634 1,998 NA NA
Level 12 NA 1,746 NA NA NA

Level 13 NA 1,866 NA NA NA

8-12Level 14 NA 1,996 NA NA NA

8.2.2.3 Transportation Cost

The MSP cost of CAC and CHP products derived above is considered to be a price that includes freight on board charges at the manufact urer’s shipping dock. The additional cost of transporting a CAC or CHP unit to the local dist ribution point depends mainly on its weight. The estimated shipping weight of these units is shown in Table 8.2.4.

Table 8.2.4 Shipping Weights of SEER Standard-complia nt Products

Efficiency

Level Shipping Weight for Representative Standard-Compliant Products LbsSplitsystem AC(CoilOnly) Splitsystem AC

(BlowerCoil) Splitsystem HP Single Package AC Single Package
HP

Level 1 206 288 339 333 379
Level 2 218 303 354 349 395
Level 3 228 316 368 366 411
Level 4 250 329 382 382 427
Level 5 271 344 396 398 443
Level 6 293 357 409 414 460
Level 7 318 370 422 431 476
Level 8 344 382 447 450 489
Level 9 NA 395 468 NA NA
Level 10 NA 422 489 NA NA
Level 11 NA 446 501 NA NA
Level 12 NA 471 NA NA NA
Level 13 NA 496 NA NA NA
Level 14 NA 520 NA NA NA

Table 8.2.5 shows the estimated overall MSPs, including transportation. DOE visited a freight transportation website (FreightCenter.com 7 ) and obtained quotes for a number of shipment options. FreightCenter.com quotes were obtained for palle tized full truckloads assumed to be 26,880 and 15,000 pounds with varying configurations for a shipment from Fort Smith, AR to Richmond, VA (1,117 miles), which was assumed to be a typical shipment distance. Prices ranged for $0.064 per pound to $0.56 per pound for that route, depending on services offered. Excluding high-priced serv ices, DOE determined that a value of $0.20 per pound adequately represented the middle of the ra nge of shipping costs. The value of $0.20 per pound was used for all transportation cost calculations.

8-13Table 8.2.5 MSP Including Transportation of SEER Standard-com pliant Products

Efficiency

Level MSP Including Transportation for Representative Standard-Compliant Products

2008$

Split-systemAC (CoilOnly) Split-system AC(BlowerCoil) Split-system
HP Single Package AC Single Package HP

Level 1 926 1,121 1,323 1,025 1,262
Level 2 974 1,175 1,384 1,115 1,320
Level 3 1,024 1,229 1,448 1,176 1,395
Level 4 1,083 1,286 1,497 1,264 1,502
Level 5 1,149 1,328 1,545 1,336 1,596
Level 6 1,230 1,372 1,596 1,427 1,705
Level 7 1,333 1,417 1,663 1,534 1,835
Level 8 1,451 1,463 1,776 1,686 1,964
Level 9 NA 1,512 1,898 NA NA
Level 10 NA 1,614 2,028 NA NA
Level 11 NA 1,723 2,098 NA NA
Level 12 NA 1,840 NA NA NA
Level 13 NA 1,965 NA NA NA
Level 14 NA 2,100 NA NA NA

8.2.2.4 Overall Markup

For a given distribution channel, the overa ll markup is the value determined by multiplying all the associated markups and the appli cable sales tax together to arrive at a single overall distribution chain markup value. The ove rall markup is multiplied times the baseline or standard-compliant manufacturing selling price (including transportation) to arrive at the price paid by the customer. Because there are baselin e and incremental markups associated with the wholesaler and mechanical cont ractor, the overall markup is also divided into a baseline markup (i.e., a markup used to convert the baseline manuf acturer price into a customer price) and an incremental markup (i.e., a markup used to conver t a standard-compliant MSP increase due to an efficiency increase into an incr emental customer price). Mar kups can differ depending whether the product is being purchased for a new constr uction installation or is being purchased to replace an existing product re placement. DOE developed th e overall baseline markups and incremental markups for both the new construction a nd replacement applications as a part of the markups analysis (chapter 6 of the TSD).

Based on the percentages of the market attr ibuted to each distribution channel in chapter 6, Table 8.2.6 and Table 8.2.7 display the weighted-average overa ll markups and their associated components for the baseline and incr emental markups, respectively. The differences between national average incremental markups for standard size and non-st andard size units are small enough that the last columns in Tabl e 8.2.7 are identical. DOE used the appropriate baseline markup times the baseline and incrementa l MSP (including transportation) to obtain estimates of the retail price of the CAC and CHP equipment. The calculations are demonstrated in section Error! Reference source not found.

.

8-14Table 8.2.6 Overall National Average Baseline Markup Factors by Product Type

Factor New Construction

Application Replacement Application Wholesale Markup 1.370 1.370 Mechanical Contractor Markup 1.280 1.380

General Contractor Markup 1.290 NA*

Sales Tax 1.071 1.071 Total Markup 2.422 2.025
* General contractors do not appear in the replacements distribution channel

Table 8.2.7 Overall National Incremental Markup Factors by Product Type

Factor New Construction

Application Replacement Application Wholesale Markup 1.114 1.114 Mechanical Contractor Markup 1.040 1.120

General Contractor Markup 1.170 NA*

Sales Tax 1.071 1.071 Total Markup 1.452 1.336
* General contractors do not appear in the replacements distribution channel

8.2.2.5 Installation Cost

The installation cost is the price to the customer of labor and materials (other than the actual product) needed to install the CAC produc t. DOE derived installation cost for CAC product from data in the RS Means Residential Cost Data 2009 8 and RS Means CostWorks 2009. 9

RS Means Residential Cost Data provides estimates on the person-hours required to install CAC and CHP produc ts, labor rates, and costs associated with the type of crew required to install the products. Generally speaking, inst allation involves movement into the building, installation or setting of pr oduct (including sleeve), connecting to power supply, filling/flushing/cleaning/touchup, startup and r unning adjustments, training the owner’s representative, and warranty and call-back service. DOE calculated the installation cost by building up the labor costs for installing the components of the system types discussed in the Engineering Analysis, chapter 5, since materials costs, overheads, and profits were assumed to be captured in the contractor markups. Labor ra tes vary significantly from region to region of the country and the RS Means data provide the necessary inform ation to capture this regional variability. RS Means CostWorks provides cost indices that refl ect the labor rates for 295 cities in the United States. Cities in all 50 States and the District of Columbia are identified in the RS
Means data and most states are represented by more than one city. DOE used the city indices to develop population weighted averages for each state and the District of Columbia. DOE

8-15incorporated the state indices into the analysis to capture place-to-place variation in installation

cost.

Table 8.2.8 summarizes the nationally represen tative installation costs based on personhours and labor rates associated with the insta llation of CAC and CHP pr oducts as presented in
RS Means . DOE assumed that these installation costs remain fixed regardless of efficiency level (a “flat” installation cost scenario). DOE’s LCC spreadsheet initially allowed for an alternative scenario - that the installation cost increases with higher efficiency levels - and this alternative was implemented in the LCC spreadsheet by providing for an installation price that varies in proportion to increased manufacturer cost above th e baseline efficiency level. However, DOE discussed installation costs with a small sample of installers and did not find a basis for installation costs increasing with efficiency. DOE therefore assumed that installation costs varied by region but not by efficiency level.

Table 8.2.8 Installation Costs for Baseline CAC Products (SEER 13)
MSP for Representative Standard-Compliant Products 2008$

Split-system AC (Coil- Only) Split-system AC (Blower-Coil) Splitsystem HP Single Package AC Single Package
HP
508 648 561 528 403

Table 8.2.9 summarizes the cost i ndices for installations in each of the 50 states, plus the District of Columbia, used to vary the nationall y representative installation costs in Table 8.2.8.

To arrive at an average index for each state, DOE weighted the city indices in each state by their population within each st ate. Because city-level popula tion estimates were not available for 2008, DOE used estimated city population weights for the year 2007 from the U.S. Census
Bureau 10 to calculate a weighted-average index for each state from the RS Means CostWorks data. Weighted averages and estimates at the regional and national level were computed using 2008 state population weights from the U.S. Census Bureau 11

.

8.2.2.6 Weighted-Average Total Installed Cost

As presented in Eq.8.2, the total installed co st is the sum of the product price and the installation cost. DOE derived the customer produ ct price for any given efficiency level by taking the product of the baseline MSP and the baseline markup index (inc luding the sales tax) and adding to it the product of the increm ental MSP and the incr emental markup index (including the sales tax). MSPs, markups, and the sales tax all can take on a variety of values, depending on location, so the resultin g total installed cost for a par ticular efficiency level will not be a single-point value, but ra ther a distribution of values.

The baseline MSP and the standard-compliant MSP increases are the starting points for determining the total in stalled cost (values are taken dir ectly from Table 8.2.5). DOE used the baseline and incremental markups a nd installation costs to convert the MSPs into total installed costs. Both the percentage retail markups and the percentage installation cost may change with the efficiency level. As an example, the weighted average costs for a 3-ton Split-System AC product category are presented for the baselin e level. Table 8.2.10 summarizes the weighted8-16average costs and markups necessary for determining the weighted-average baseline and standard-compliant total installed costs for a new Split-System AC Coil-Only unit.

Table 8.2.9 Installation Cost Indices (National Average Value = 100.0)

State Index State Index State Index
Alabama 61.8 Kentucky 85.8 North Dakota 62.9
Alaska 112.3 Louisiana 63.1 Ohio 101.2
Arizona 79.6 Maine 74.2 Oklahoma 61.5
Arkansas 60.9 Maryland 96.5 Oregon 111.7
California 133.0 Massachusetts 128.3 Pennsylvania 126.4
Colorado 86.9 Michigan 110.1 Rhode Island 116.9
Connecticut 124.8 Minnesota 122.3 South Carolina 44.5
Delaware 122.6 Mississippi 66.5 South Dakota 51.2
Dist. Of Columbia 102.3 Missouri 105.2 Tennessee 71.4
Florida 67.1 Montana 78.8 Texas 64.7 Georgia 75.2 Nebraska 87.3 Utah 75.8
Hawaii 117.1 Nevada 112.1 Vermont 70.8
Idaho 75.4 New Hampshire 93.0 Virginia 76.3
Illinois 141.3 New Jersey 132.1 Washington 108.6
Indiana 90.2 New Mexico 78.8 West Virginia 93.6
Iowa 79.8 New York 170.7 Wisconsin 102.8
Kansas 71.4 North Carolina 44.6 Wyoming 65.3

Table 8.2.10 Costs and Markups for Determinat ion of Weighted-Average Total Installed Costs for a New 3-Ton Split-system AC Coil- Only Unit (Efficienc y Level 5: SEER 15

Variable SEER Weighted Average Value
National Average HotHumid Hot-Dry Rest of Country
Baseline Manufacturer Selling Price, Including Transportation (SEER 13) $926.15 $926.15 $926.15 $926.15

Standard-compliant Manufacturer selling price Increase (Efficiency Level 5—SEER 15) $223.28 $223.28 $223.28 $223.28

Average Overall Baseline Markup (Regional) 2.423 2.435 2.858 2.444

Average Overall Incremental Markup (Regional) 1.452 1.459 1.712 1.464

Installation Cost $508 $508 $508 $508
Installation Cost Factor – Regional 1.000 0.641 1.223 1.145

To illustrate the derivation of the weighted-average total installed cost shown in Table 8.2.10, DOE presents the calculations for the baseline efficiency (Eq. 8.2.3) and a higher efficiency SS-AC-3T unit at SEER 15 (Level 5) (Eq. 8.2.4). For baseline products, the calculation of the Hot-Humid regional average total installed cost is as follows:

IC BASE SS-AC-3T = EQP B ASE-SS-AC-3T +INST BAS E-SS-AC-3T x INSTNDEX Eq. 8.2.3
= MSP BASE- SS-AC-3T X MU BASE- SS-AC-3T + INST BASE- SS-AC-3T x INSTNDEX = $926.15 x 2.435 + $508 x 0.641

8-17= $ 2,255.18 + $325.62 = $2580.80.

Where:

IC = total installed cost ($), EQP = product price ($),
MSP = manufacturer selling price ($),
MU = overall baseline markup,
INST = installation cost or the custom er price to install product ($),
INSTINDEX = location dependent installation co st index, approximately 1.0 at a national average.

In this specific example, MSP is the national average baseline MSP for the Split-System Coil-Only CAC product class and MU is the overall baseline markup factor. The calculation of the higher efficiency (efficiency level 5-SEER 15) total installed cost includes the use of a MSP adder. In addition, DOE deri ved an incremental markup.

Based on incremental product price changes, the derivation of the efficiency level 5 total installed cost is based on determining the change in product pr ice over the baseline product price. The manufacturer price increment for higher effi ciency product is multiplied by the incremental markup.

DOE calculated the efficiency level 5 total installed cost ( IC SS-AC-3T Level 5 ) as follows:

IC SS-AC-3T Level5 = ( EQP BASE-SS-AC-3T + ∆ EQP SS-AC-3T Level 5 )

+ INST SS-AC-3T Level 5 x INSTINDEX Eq. 8.2.4

= ( MSP BASE-SS-AC-3T X MU BASE-SS-AC-3T ) + ( ∆ MSP SS-AC-3T Level 5

X MU SS-AC-3T Level 5 ) + INST SS-AC-3T Level 5 x ISTINDEX = $926.15 x 2.435 + $223.28 x 1.459 + $508 x 0.641 = $2906.57

Where:

∆ EQP = increase in product price ($),
∆ MFG = increase in manufacturer price ($)

, MU = markup factor (base or incremental, as shown in Table 8.2.6 and Table 8.2.7, respectively)

Table 8.2.11 presents the average product price, installation costs, and total installed costs for the representative product Split-system AC (Coil-only) at the baseline level and each efficiency level examined. Table 8.2.12 through Table 8.2.15 present these data for the other product classes.

8-18Table 8.2.11 Manufacturer Selling Price (Includi ng Transportation), Product Price, Installation Cost, and Total In stalled Costs for Split-system AC (Coil-only), at Average
Prices*

Efficiency Level Manufacturer Selling Price 2008$ Product Price (Including Markups) 2008$ Installation Cost 2008$ Total Installed Cost 2008$ National Average
Level 1 926 2,244 508 2,752
Level 2 974 2,316 508 2,824
Level 3 1,024 2,391 508 2,899
Level 4 1,083 2,479 508 2,987
Level 5 1,149 2,578 508 3,086
Level 6 1,230 2,699 508 3,207
Level 7 1,333 2,853 508 3,361
Level 8 1,451 3,030 508 3,538 Hot-Humid Region
Level 1 926 2,255 325 2,581
Level 2 974 2,325 325 2,651
Level 3 1,024 2,399 325 2,724
Level 4 1,083 2,485 325 2,810
Level 5 1,149 2,581 325 2,907
Level 6 1,230 2,699 325 3,024
Level 7 1,333 2,848 325 3,174
Level 8 1,451 3,021 325 3,347 Hot-Dry Region
Level 1 926 2,647 621 3,268
Level 2 974 2,728 621 3,350
Level 3 1,024 2,815 621 3,436
Level 4 1,083 2,915 621 3,537
Level 5 1,149 3,029 621 3,650
Level 6 1,230 3,167 621 3,788
Level 7 1,333 3,343 621 3,964
Level 8 1,451 3,545 621 4,166 Rest of Country
Level 1 926 2,263 582 2,845
Level 2 974 2,334 582 2,916
Level 3 1,024 2,409 582 2,991
Level 4 1,083 2,497 582 3,078
Level 5 1,149 2,595 582 3,177
Level 6 1,230 2,715 582 3,296
Level 7 1,333 2,867 582 3,449
Level 8 1,451 3,043 582 3,625 * Details may not add to total due to rounding.

8-19Table 8.2.12 Manufacturer Selling Price (Includi ng Transportation), Product Price, Installation Cost, and Total In stalled Costs for Split-system AC (Blower-Coil), at Average
Prices*

Efficiency Level Manufacturer Selling Price 2008$ Product Price (Including Markups) 2008$ Installation Cost 2008$ Total Installed Cost 2008$ National Average

Level 1 1,121 2,954 1,102 4,056

Level 2 1,175 3,028 1,102 4,130

Level 3 1,229 3,102 1,102 4,204

Level 4 1,286 3,181 1,102 4,283

Level 5 1,328 3,239 1,102 4,341

Level 6 1,372 3,299 1,102 4,401

Level 7 1,417 3,362 1,102 4,464

Level 8 1,463 3,426 1,102 4,528

Level 9 1,512 3,492 1,102 4,594

Level 10 1,614 3,633 1,102 4,735

Level 11 1,723 3,783 1,102 4,885

Level 12 1,840 3,944 1,102 5,046

Level 13 1,965 4,117 1,102 5,219

Level 14 2,100 4,303 1,102 5,405 Hot-Humid Region

Level 1 1,121 2,968 706 3,675

Level 2 1,175 3,041 706 3,747

Level 3 1,229 3,113 706 3,819

Level 4 1,286 3,190 706 3,896

Level 5 1,328 3,247 706 3,953

Level 6 1,372 3,305 706 4,011

Level 7 1,417 3,366 706 4,072

Level 8 1,463 3,428 706 4,134

Level 9 1,512 3,493 706 4,199

Level 10 1,614 3,630 706 4,336

Level 11 1,723 3,777 706 4,483

Level 12 1,840 3,934 706 4,640

Level 13 1,965 4,103 706 4,809

Level 14 2,100 4,284 706 4,990

8-20Table 8.2.12 (contd)

Efficiency Level Manufacturer Selling Price 2008$ Product Price (Including Markups) 2008$ Installation Cost 2008$ Total Installed Cost 2008$ Hot-Dry Region

Level 1 1,121 3,483 1,348 4,831

Level 2 1,175 3,568 1,348 4,916

Level 3 1,229 3,653 1,348 5,001

Level 4 1,286 3,743 1,348 5,091

Level 5 1,328 3,810 1,348 5,158

Level 6 1,372 3,879 1,348 5,227

Level 7 1,417 3,950 1,348 5,298

Level 8 1,463 4,023 1,348 5,371

Level 9 1,512 4,099 1,348 5,447

Level 10 1,614 4,260 1,348 5,608

Level 11 1,723 4,432 1,348 5,780

Level 12 1,840 4,616 1,348 5,964

Level 13 1,965 4,814 1,348 6,162

Level 14 2,100 5,027 1,348 6,375 Rest of Country

Level 1 1,121 2,979 1,262 4,241

Level 2 1,175 3,052 1,262 4,314

Level 3 1,229 3,126 1,262 4,388

Level 4 1,286 3,204 1,262 4,466

Level 5 1,328 3,262 1,262 4,524

Level 6 1,372 3,322 1,262 4,584

Level 7 1,417 3,384 1,262 4,646

Level 8 1,463 3,447 1,262 4,709

Level 9 1,512 3,513 1,262 4,775

Level 10 1,614 3,653 1,262 4,915

Level 11 1,723 3,802 1,262 5,064

Level 12 1,840 3,962 1,262 5,224

Level 13 1,965 4,134 1,262 5,396

Level 14 2,100 4,319 1,262 5,581 * Details may not add to total due to rounding.

8-21Table 8.2.13 Manufacturer Selling Price (Includi ng Transportation), Product Price, Installation Cost, and Total Installed Costs for Split-system HP, at Average Prices*

Efficiency Level Manufacturer Selling Price 2008$ Product Price (Including Markups) 2008$ Installation Cost 2008$ Total Installed Cost 2008$

National Average

Level 1 1,323 2,679 561 3,240

Level 2 1,384 2,763 561 3,324

Level 3 1,448 2,852 561 3,412

Level 4 1,497 2,919 561 3,480

Level 5 1,545 2,985 561 3,545

Level 6 1,596 3,056 561 3,616

Level 7 1,663 3,147 561 3,708

Level 8 1,776 3,304 561 3,864

Level 9 1,898 3,471 561 4,031

Level 10 2,028 3,650 561 4,210

Level 11 2,098 3,747 561 4,307 Hot-Humid Region

Level 1 1,323 2,692 359 3,052

Level 2 1,384 2,774 359 3,133

Level 3 1,448 2,861 359 3,220

Level 4 1,497 2,926 359 3,286

Level 5 1,545 2,990 359 3,349

Level 6 1,596 3,060 359 3,419

Level 7 1,663 3,149 359 3,508

Level 8 1,776 3,301 359 3,660

Level 9 1,898 3,464 359 3,823

Level 10 2,028 3,639 359 3,998

Level 11 2,098 3,733 359 4,093 Hot-Dry Region

Level 1 1,323 3,159 686 3,845

Level 2 1,384 3,255 686 3,941

Level 3 1,448 3,357 686 4,042

Level 4 1,497 3,434 686 4,120

Level 5 1,545 3,509 686 4,194

Level 6 1,596 3,590 686 4,276

Level 7 1,663 3,695 686 4,380

Level 8 1,776 3,874 686 4,559

Level 9 1,898 4,065 686 4,751

Level 10 2,028 4,270 686 4,956

Level 11 2,098 4,381 686 5,067

8-22Table 8.2.13 (contd)

Efficiency Level Manufacturer Selling Price 2008$ Product Price (Including Markups) 2008$ Installation Cost 2008$ Total Installed Cost 2008$

Rest of Country

Level 1 1,323 2,702 642 3,343

Level 2 1,384 2,785 642 3,427

Level 3 1,448 2,873 642 3,515

Level 4 1,497 2,940 642 3,582

Level 5 1,545 3,005 642 3,647

Level 6 1,596 3,076 642 3,718

Level 7 1,663 3,167 642 3,808

Level 8 1,776 3,322 642 3,964

Level 9 1,898 3,488 642 4,130

Level 10 2,028 3,666 642 4,308

Level 11 2,098 3,762 642 4,404 * Details may not add to total due to rounding.

Table 8.2.14 Manufacturer Selling Price (Includi ng Transportation), Product Price, Installation Cost, and Total Installed Costs for Single Pa ckage AC, at Average Prices*

Efficiency Level Manufacturer Selling Price 2008$ Product Price (Including Markups) 2008$ Installation Cost 2008$ Total Installed Cost 2008$ National Average

Level 1 1,025 2,077 528 2,604

Level 2 1,115 2,200 528 2,664

Level 3 1,176 2,284 528 2,727

Level 4 1,264 2,405 528 2,811

Level 5 1,336 2,505 528 2,933

Level 6 1,427 2,630 528 3,033

Level 7 1,534 2,778 528 3,158

Level 8 1,686 2,987 528 3,305 Hot-Humid Region

Level 1 1,025 2,087 338 2,425

Level 2 1,115 2,207 338 2,545

Level 3 1,176 2,289 338 2,627

Level 4 1,264 2,407 338 2,745

Level 5 1,336 2,505 338 2,843

Level 6 1,427 2,627 338 2,965

Level 7 1,534 2,771 338 3,109

Level 8 1,686 2,975 338 3,313

8-23Table 8.2.14 (contd)

Efficiency Level Manufacturer Selling Price 2008$ Product Price (Including Markups) 2008$ Installation Cost 2008$ Total Installed Cost 2008$ Hot-Dry Region

Level 1 1,025 2,449 645 3,094

Level 2 1,115 2,590 645 3,235

Level 3 1,176 2,686 645 3,331

Level 4 1,264 2,825 645 3,470

Level 5 1,336 2,939 645 3,584

Level 6 1,427 3,082 645 3,728

Level 7 1,534 3,251 645 3,896

Level 8 1,686 3,490 645 4,136 Rest of Country

Level 1 1,025 2,094 604 2,698

Level 2 1,115 2,133 604 2,820

Level 3 1,176 2,216 604 2,904

Level 4 1,264 2,300 604 3,025

Level 5 1,336 2,421 604 3,124

Level 6 1,427 2,520 604 3,248

Level 7 1,534 2,644 604 3,395

Level 8 1,686 2,791 604 3,602 * Details may not add to total due to rounding.

Table 8.2.15 Manufacturer Selling Price (Includi ng Transportation), Product Price, Installation Cost, and Total In stalled Costs for Single Pack age HP, at Average Prices *

Efficiency Level Manufacturer Selling Price 2008$ Product Price (Including Markups) 2008$ Installation Cost 2008$ Total Installed Cost 2008$ National Average

Level 1 1,262 2,556 403 2,958

Level 2 1,320 2,636 403 3,038

Level 3 1,395 2,739 403 3,141

Level 4 1,502 2,886 403 3,288

Level 5 1,596 3,016 403 3,418

Level 6 1,705 3,166 403 3,569

Level 7 1,835 3,345 403 3,747

Level 8 1,964 3,523 403 3,925 Hot-Humid Region

Level 1 1,262 2,568 258 2,826

Level 2 1,320 2,647 258 2,904

Level 3 1,395 2,747 258 3,005

Level 4 1,502 2,890 258 3,148

8-24Efficiency Level Manufacturer Selling Price 2008$ Product Price (Including Markups) 2008$ Installation Cost 2008$ Total Installed Cost 2008$

Level 5 1,596 3,017 258 3,275

Level 6 1,705 3,164 258 3,422

Level 7 1,835 3,338 258 3,595

Level 8 1,964 3,511 258 3,769 Hot-Dry Region

Level 1 1,262 3,014 492 3,506

Level 2 1,320 3,106 492 3,598

Level 3 1,395 3,223 492 3,715

Level 4 1,502 3,392 492 3,884

Level 5 1,596 3,540 492 4,032

Level 6 1,705 3,712 492 4,205

Level 7 1,835 3,916 492 4,409

Level 8 1,964 4,120 492 4,613 Rest of Country

Level 1 1,262 2,577 461 3,038

Level 2 1,320 2,657 461 3,118

Level 3 1,395 2,759 461 3,220

Level 4 1,502 2,905 461 3,366

Level 5 1,596 3,034 461 3,495

Level 6 1,705 3,184 461 3,645

Level 7 1,835 3,361 461 3,822

Level 8 1,964 3,538 461 3,999

* Details may not add to total due to rounding.

8.2.3 Operating Cost Inputs

The operating cost is determined for house holds using data from the 2005 Residential Energy Consumption Survey (RECS) and industry sources on repair cost and maintenance cost. The operating cost for commercial buildings is based on computer modeling of a representative commercial building in 237 climates. For the LCC analysis of central air conditioners (either split or package systems), the LCC of an increased efficiency level is calculated for those residential and commercial buildings that are determined to have a central air conditioner. For heat pumps (either split or package systems), the LCC of an increased efficiency level is calculated for those buildings that are determined to have a central heat pump. The LCC analysis results in a distribution of LCC savings (i.e., the LCC difference between the baseline product and product with a higher efficiency level) for 10,000 individual observations at each higher efficiency level nationally, and in each region. Th e analysis computes th e mean LCC difference at each efficiency level in each region, as well as the percentage of buildings analyzed that have positive LCC savings associated with the more-efficient product.

8-25DOE defined the operating cost by the following equation:

OC = EC+ RC+ MC Eq. 8.2.5

Where:

OC = operating cost ($),
EC = energy cost associated with operating the product ($),
RC = repair cost associated wi th component failure ($),
MC = annual maintenance cost for ma intaining product operation ($).

The remainder of this section provides inform ation about the variables that DOE used to calculate the operating cost for CAC and CH P products. Product life time, discount rate, and effective date of the amended energy conserva tion standard are required for determining the operating cost and for establishing the operating co st present value. The annual energy costs of the product are computed from energy consumption per unit for the baseline efficiency and standard-compliant cases (efficiency level 1, 2, etc.), combined with the electricity prices. Chapter 7, Building Energy Use Characterization Analysis, provides complete details on the CAC product energy consumption results for three regions and the nation as a whole. The key inputs for the determination of ope rating costs are shown below:

• Baseline and standard-comp liant annual energy consumption (kWh) (Chapter 7)

• Electricity price (cen ts/kWh) (section 8.2.3.1)

• Electricity price trend (section 8.2.3.2)

• Repair cost ($) (section 8.2.3.3 )

• Maintenance cost ($) (section 8.2.3.4)

• Equipment lifetime (years) (section 8.2.3.5)

• Discount rate (percentage) (section8.2.3.6)

• Effective date of amended energy conservation standard (section 8.2.3.7)

8.2.3.1 Electricity Price Analysis

Electricity price information is required to cal culate the dollar benefits to consumers who purchase and operate a more efficient appliance. The electricity cost savings comprise the benefit side of the cost-benefit analysis used to define the life-cycle cost impacts of a proposed standard. In previous rulemakings, DOE has used estimates of marginal electricity prices to calculate these cost savings. The marginal price for a given c onsumer is the cost of the next increment of electricity use on the consumer’s utility bill, and is the correct estimate of the value of savings that a consumer would see in the real world. In some cases, it may be sufficient to use estimates of average electricity prices, which are less accurate but simpler to calculate. However, if there is reason to believe that marginal prices differ significantly from average prices, the approximation is not justified. For a peak-coincident end us e such as air-conditioning, there is a general expectation that the actual cost of operating the appliance is higher than the average price of electricity. These increased costs are often reflected in utility tariff structures, through block

8-26rates, different types of demand charges, or mandatory time-of-use rates. Accurate estimation of marginal prices requires taking rate structures into account explicitly.

In general, several methods a nd data sources can be used to calculate electricity prices. After reviewing the strengths and weaknesses of di fferent approaches and the available data, the Department chose to base the analysis on the utility tariffs comprising the TAP (Tariff Analysis Project) database. 12 The TAP database and calculation tool s were first developed at LBNL for use in the Commercial Unitary Air Conditioning (CUAC) rulemaking. 13 This approach provides an up-to-date and geographically diverse data set that can accurately capture real prices. Other data sources have various weaknesses that could lead to significant errors in the estimated electricity cost savings, and do not provide sufficient information to allow DOE to respond adequately to stakeholder comment s. A more detailed discussion of electricity price data and calculation methods is presented in appendix 8-B, along with a description of the tariff-based approach, the data used, and va lidation tests. Detailed documentation is also available in published reports. 10, 11, 14 Residential electricity cost savings are calculated based on the defaulttariffs collected in the TAP database. Currently, for all utilities the default tariff is not time-ofuse. A large number of utilities offer optional time-of-use (TOU) tariffs, but there are currently very few customers enrolled in these optional rate plans. appendix 8-C provides a quantitative comparison of prices for consumers on TOU vs. default tariffs for utilities that offer both

For the analysis conducted for CAC and HP, electricity prices are required for both residential and commercial cons umers. The LCC is based on a consumer sample derived from RECS and EIA’s Commercial Building Energy Consumption Survey (CBECS), 15 and both an average annual price and a seasonal marginal pri ce are required for each household or building in the sample. Following the methodology in the LCC, the consumer sample is also segregated according to product type (i.e., CAC or HP). The basic methodology is to estimate the customer’s monthly elect ricity use, and use the tariff da ta to calculate the corresponding electricity bill. Empirical marginal prices (EMPs) are calculated by taking the difference between the bill for the baseline electricity use and the bill for a candidate standard level, and dividing by the change in energy use. This approach requires estimation of monthly consumer electricity use for the baseline and the energy savings associated with each candidate standard level. As both the rate structures and the required energy data differ significantly for residential vs. commercial consumers, the details of the approach for these two sectors are discussed separately.

Calculation of Residential Prices

The calculation methodology provides, for each household in the building sample, an average annual price and a monthly marginal price. To compute these prices, the monthly baseline energy consumption must first be estima ted. This is done using the monthly billing data from the RECS 2001 dataset becaus e the detailed monthly billing data from the RECS 2005 was considered to be proprietary a nd could not be used; details of the calculation are presented in appendix 8-C. Given the monthly energy use, tw elve monthly bills per household are calculated using the tariffs. To increase the effective size of the sample, within a region each household is paired with each utility in its region. DOE refers to the pairing of a household with a utility as an account. The utilities ar e weighted by the fraction of cust omers they serve within a region. 11, 12 Taking the weighted sum over accounts provides a single set of prices for each household.

8-27The annual average baseline price is calculat ed as a simple average over the twelve monthly baseline bills. To calculate monthly marginal prices for each account, the monthly energy use is decremented by seven percent and the bill recalculated. The marginal price in each month is defined as the bill savings divided by the energy savings under this test. This will be the valid price under all candidate sta ndard levels. Monthly variability in the marginal price is due primarily to seasonal rates, as season definitions vary by utility. Within the LCC, the annual cost savings are equal to the monthly marginal price times the monthly energy savings, summed across months. A description of how the monthl y energy savings are estimated for each CSL is given in appendix 8-C.

To provide an indication of the prices that result from this analysis, Table 8.2.16 shows the annual average price and marginal prices fo r January and July. The table presents regional averages calculated for the hot -humid, hot-dry and rest-of-country regions defined for this rulemaking. The table also shows the total RECS weight associated with the household sample for each product type. Note that these regional averages are for information only; the LCC uses household-level prices.

Table 8.2.16 Regional Averages of the Annual Average Prices and January and July Marginal Prices

Product and Region RECS Nweight Residential Electricity Prices cents/kWh

Annual Average Price January Marginal Price July Marginal Price

Central Air

Hot-Humid Hot-Dry Rest of Country

Nation 19,045,578
6,164,451
25,769,446
50,979,476 10.04

16.11

10.73

11.12 8.86

19.79

9.11

10.30 9.75

19.97

10.57

11.40 Heat Pump

Hot-Humid Hot-Dry Rest of Country

Nation 5,545,454
837,752
3,608,821
9,992,026 10.01

14.35

9.68

10.26 9.50

16.22

8.52

9.71 10.20

15.80

9.93

10.57

Calculation of Commercial Prices

Electricity tariffs for commercial consumers can be very complex, incorporating block rates, seasonal rates, demand charges, time-of-use rates, etc. To calculate commercial electricitybills requires both the monthly consumption and demand; for utilities with mandatory time-ofuse (TOU) tariffs, consumption and demand data are required for each TOU period. For the CAC and HP analysis, this data is provided from bu ilding simulations. The simulation approach is described in more detail in Chapter 7. Briefly, in this approach a representative set of small commercial building is simulated at several SEER levels across the full set of weather locations defined in the TMY2 data set. b The simulation output for SEER 13 is taken as the baseline. As

b TMY means typical meteorological year; version 3 of this dataset is the most recent.

8-28with the residential data , a set of accounts are created by pairing each building in the simulation set with each utility in its region. For the commercia l analysis the regions are defined as census divisions. Once a building is assigned to a utility, the tariff is assigned automatically based on the annual peak demand and/or energy consumption a nd the tariff rules. For each account and each SEER level, monthly energy and demand values, by TOU period if necessary, are determined from the hourly simulation output. With this data, monthly bills can be calculated using the tariffs.

Given the monthly bills, the bill savings in do llars for each account at each SEER level are determined relative to the baseline bill. The EMP can be calculated by taking the ratio of the bill savings to the energy savings. Note that, as far as the analysis is concerned, the EMP is a derived quantity that is used for information purposes only— the LCC uses the total annual bill savings for each customer directly.

The commercial tariff data we re last updated in 2004. To convert to 2008 dollars, two datasets were used: The report Average Regulated Retail Price of Electricity for the years 2004 through 2007, 16 and the EEI Typical Bill reports for 2007 to 2008. 17 Based on these data, a weighted-average price escalation factor for each region was calculated using consumer counts as the weights. The consumer counts come from the most recent EIA Form 861 data, which is for 2006. 18 EIA data from 2003 through 2006 were used to determine how much the rate of price escalation differs on average between the publicly vs. privately owned utility companies.

To give an indication of the prices obtai ned with this methodology, Table 8.2.17 shows the regional average values of the empirical marginal price at the SEER levels simulated. These regional averages were calculated based on population-weighting of the building simulation sample. The table also shows the scaling fact ors used to convert from 2004 to 2008 nominal dollars. Note that the EMP varies by SEER leve l, and this variation may be non-monotonic. This behavior results from the complex block struct ures for both demand and energy charges that exist in commercial tariffs. 12

Table 8.2.17 Effective Marginal Price by Re gion for the Commercial Building Sample (¢/kWh).

Census Division Marginal Prices cents/kWh
Scaling Factor* Central Air Conditioners

SEER 14 SEER 16 SEER 19 SEER 14 Heat Pumps

SEER 16 SEER 19

1

2

3

4

5

6

7

8

9 32.7 22.1 25.3
25.0 17.4 19.6

22.2 14.3 16.6

7.4 6.6 6.9

14.6 12.3 13.1
10.7 9.5 10.0

17.5 14.8 16.0

10.9 9.8 10.1

12.7 12.2 12.5 28.5

22.6
19.0

8.0

14.6

10.3

16.3

13.2

13.6 19.5

15.4

12.2

6.5

11.7

9.1

13.5

9.8

11.6 21.9

17.4

14.1

6.9

12.6

9.4

14.5

10.6

11.8 1.44

1.15
1.25

1.07

1.36

1.28

1.34

1.18

1.09

* The scaling factors used to convert from 2004 to 2008 dollars .

8-298.2.3.2 Electricity Price Trend

The electricity price trend provides the relative change in electricity prices for future years out to the year 2047. Estimating future electricity prices is difficult, especially considering that there are efforts in many states throughout the country to restructur e the electricity supply industry.

DOE applies a projected trend in national average electricity prices to each customer’s energy prices. Of the following four scenarios, the LCC analysis uses the April 2009 update to the AEO 2009 reference price scenario:

1. Constant energy prices at 2008 va lues (Constant index at 2008 = 1.0)

2. AEO 2009 , High Growth (“High Growth” in Figure 8.2.1).

3. AEO 2009 , Reference Case (“Reference” in Figure 8.2.1)

4. AEO 2009 , Low Growth (“Low Growth” in Figure 8.2.1)

Figure 8.2.1 shows the trends for the three AEO 2009 residential price projections where prices are assumed to change. DOE extrapolated the values in later years ( i.e. , after 2030) from their relative sources because AEO 2009 does not forecast beyond 2030. To arrive at values for these later years, DOE used the price trend from 2020 to 2030 of the forecast to establish prices in the years 2030 to 2047. This method of extrapolation is in line with methods currently used by the EIA to forecast fuel prices for the Federal Energy Management Program.

The default electricity price trend scenario used in the LCC analysis is the trend from the April 2009 update to the AEO 2009 Reference Case, which is the middle line in Figure 8.2.1 Spreadsheets used in calculating the LCC have the capability to analyze the other electricity price trend scenarios, namely, the AEO 2009 High Growth and the AEO 2009 Low Growth price trends and constant energy prices. A similar set of trend scenarios for the commercial sector is shown in Figure 8.2.2.

8-30200 7 200 9 201 1 2013 2015 2017 2019 2021 2023 2025 202 7 202 9 203 1 203 3 203 5 203 7 2039 2041 2043 2045 2047

200

7 200 9 201 1 2013 2015 2017 2019 2021 2023 2025 202 7 202 9 203 1 203 3 203 5 203 7 2039 2041 2043 2045 2047 Residential Prices

0.80 0.85 0.90 0.95 1.00 1.05 1.10 1.15 1.20 1.25 1.30Index 2008=1.00

Low Grow t h

R e f e renc e
H i gh G r o w t h

Years Figure 8.2.1 Electricity Price Tre nds for Residential Rates to 2047

Commercial Prices

0.80 0.85 0.90 0.95 1.00 1.05 1.10 1.15 1.20 1.25Index 2008=1.00

Low Grow t h

R e f e renc e
H i gh G r o w t h

Years Figure 8.2.2 Electricity Price Tre nds for Commercial Rates to 2047

8-318.2.3.3 Repair Cost

The repair cost is the cost to the consumer for replacing or repairing components in the BVM equipment that have failed. The assumed an nualized repair cost for baseline efficiency central air-conditioning and heat pump equipment (i.e., the cost th e consumer pays annually for repairing the equipment) and e quipment with efficiencies of 13 SEER and greater are based on the following expression:

EQP STD RC STD = RC Base • • ( m r ) • ( st

r ) Eq. 8.2.6 EQP BASE

Where:

RC STD = repair cost at a standard efficiency level (e.g., level 2, 3, etc.)
RC BASE = repair cost at the base efficiency level (level 1) EQP STD = equipment price (consumer price for only the equipment) at a standard level, EQP BASE = equipment price (consumer price for only the equipment) at the base efficiency level,

m r = mechanical contractor markup index in region r

st r = state and local tax rate index (factor relative to national average)

Data on average repair costs are scarce in published sources. However, based on information in a few consumer advice websites and discussions with service representatives, it appears that the range of values for parts and labor for major repairs such as replacing a compressor is between $700 and $1500 19 . Furthermore, it appears that compressor replacements are rarely needed before about the eighth year and are often covered by warranty, if needed. In addition, if the equipment is older than 15 years, it is usually economically rational to replace the entire system rather than to incur the cost of a major repair for the limited average equipment life remaining. Because this is a range rather than a specific value associated with a particular technology, DOE applied the range to all classe s and assumed that the range included average national values for wholesale markups, mechan ical contractor mar kups, and sales taxes.

Through 14 SEER, system technology genera lly does not incorporate sophisticated electronic components, whic h are believed to incur higher repa ir costs. Increases in SEER are generally achieved through more efficient single-speed compressors or more efficient and/or larger heat exchanger coils. Systems with effi ciencies beyond 14 SEER st art to incorporate twospeed and variable-speed fans, as well as larger coils and more complex electronics, all of which are expected to be more susceptible to failure and cost more to repair.

Table 8.2.18 shows the basic average repair costs by standard level for split-system and single package central air conditioners and heat pumps. Since equipment pr ices are a function of variables that are represented by distributions ra ther than single point values (e.g., manufacturer, distributor, dealer, and builder mar kups, installation costs, and sales tax), repair costs are actually represented by a distribution of values rather than just the average values shown in Table 8.2.18.

8-32Table 8.2.18 Central Air Conditioner and Heat Pump Basic Average Repair Costs by Efficiency Level

Efficiency

Level Repair Costs for Representative Standard-Compliant Products 2008$Splitsystem AC(CoilOnly) Splitsystem AC

(BlowerCoil) Splitsystem HP Single Package AC Single Package HP Level 1 63.48 63.48 63.48 63.48 63.48
Level 2 65.44 65.50 65.41 67.13 65.42
Level 3 67.51 67.50 67.45 69.63 67.89
Level 4 69.93 69.64 69.00 73.23 71.44
Level 5 72.65 71.23 70.50 76.19 74.56
Level 6 75.96 72.86 72.14 79.90 78.20
Level 7 80.18 74.54 74.24 84.28 82.50
Level 8 85.03 76.28 77.84 90.48 86.79
Level 9 NA 78.08 81.68 NA NA
Level 10 NA 81.90 85.80 NA NA
Level 11 NA 85.97 88.03 NA NA
Level 12 NA 90.34 NA NA NA
Level 13 NA 95.04 NA NA NA
Level 14 NA 100.08 NA NA NA

Because labor rates and sales taxes vary across the country and repair costs also vary for any given efficiency level for each product type, Table 8.2.19 shows the average repair costs by region of the country and product type for the largest product classes.

Table 8.2.19 Central Air Conditioner and Heat Pu mp Average Repair Costs by Efficiency Level and Region

Efficiency

Level Average Repair Costs for Representative StandardCompliant Products 2008$SplitsystemAC (CoilOnly) Splitsystem AC

(BlowerCoil) Splitsystem HP Single Package AC Single Package
HP National Average
Level 1 69 68 68 69 71
Level 2 71 70 70 73 73
Level 3 73 72 72 75 76 Level 4 76 75 74 79 80
Level 5 79 76 76 82 84
Level 6 82 78 77 86 88
Level 7 87 80 80 91 92
Level 8 92 82 83 98 97 Level 9 NA 84 87 NA NA
Level 10 NA 88 92 NA NA
Level 11 NA 92 94 NA NA
Level 12 NA 97 NA NA NA
Level 13 NA 102 NA NA NA
Level 14 NA 107 NA NA NA

8-33Table 8.2.19 (contd)

Efficiency

Level Average Repair Costs for Representative StandardCompliant Products 2008$SplitsystemAC (CoilOnly) Splitsystem AC

(BlowerCoil) Splitsystem HP Single Package AC Single Package
HP Hot-Humid Region
Level 1 68 68 68 68 71
Level 2 70 70 70 72 73
Level 3 72 72 72 74 76 Level 4 75 74 74 78 80
Level 5 78 76 75 81 83
Level 6 81 78 77 85 87
Level 7 86 80 79 90 92
Level 8 91 82 83 97 97 Level 9 NA 83 87 NA NA
Level 10 NA 88 92 NA NA
Level 11 NA 92 94 NA NA
Level 12 NA 97 NA NA NA
Level 13 NA 102 NA NA NA
Level 14 NA 107 NA NA NA Hot-Dry Region
Level 1 71 71 71 71 74
Level 2 73 73 73 75 77 Level 3 76 76 75 78 79
Level 4 78 78 77 82 84
Level 5 81 80 79 85 87
Level 6 85 82 81 89 91
Level 7 90 83 83 94 96
Level 8 95 85 87 101 102
Level 9 NA 87 91 NA NA
Level 10 NA 92 96 NA NA
Level 11 NA 96 98 NA NA
Level 12 NA 101 NA NA NA
Level 13 NA 106 NA NA NA
Level 14 NA 112 NA NA NA
Rest of Country
Level 1 69 69 69 69 72
Level 2 71 71 71 73 74
Level 3 73 73 73 75 77 Level 4 76 75 75 79 81
Level 5 79 77 76 82 84
Level 6 82 79 78 86 88
Level 7 87 81 80 91 93
Level 8 92 82 84 98 98
Level 9 NA 84 88 NA NA
Level 10 NA 89 93 NA NA
Level 11 NA 93 95 NA NA
Level 12 NA 98 NA NA NA
Level 13 NA 103 NA NA NA
Level 14 NA 108 NA NA NA

8-348.2.3.4 Maintenance Cost

The maintenance cost is the routine annua l cost to the consumer of maintaining equipment operation. The maintenance cost excludes the cost associated with the replacement or repair of components that have fa iled (discussed in section 8.2.3.3). It is the cost associated with general maintenance ( e.g ., checking and maintaining refrigerant charge levels, cleaning heat exchanger coils).

Virtually no published data are available on annual maintenance cost per unit. DOE estimated the annualized maintenance costs for CAC products based on fragmentary data available on the internet. The cost of the basic preventative maintenance for an individual CAC unit his specified as range of values from $20 per year (2008$) for minimal maintenance (homeowner replaces the unit’s air filter two times per year) to an advertised full maintenance service at $120 (2008$) per year. 20 The full maintenance service involved the following activities:

For the Indoor Component:

• Inspect refrigerant lines for signs of leakage

• Check and maintain standard air filters

• Check operating temperatures

• Check blower/air handler operati on and lubricate as necessary

• Check blower belt and tension

• Check condensate drain and maintain as necessary

• Check operational controls and thermostat

For the Outdoor Component:

• Inspect refrigerant lines for signs of leakage

• Inspect and clean condenser coil as necessary

• Check condenser fan operation and lubricate as necessary

• Check operation and condition of the compressor contactor

• Check system voltage

• Check operating temperatures

Data were not available to indicate how maintenance costs vary with equipment efficiency, but stakeholder comments on the Framework Document indicated that they likely increase as equipment efficiency increases. DOE decided to use preventative maintenance costs that increase as equipment efficiency increases. The costs were also expected to vary regionally with labor costs. Installation costs vary in the same geographic pattern, so average national costs were multiplied times the installation cost index.

EQP M STD = M Base • STD • ( ic

r ) Eq. 8.2.7 EQP BASE

8-35Where:

M STD = repair cost at a standard efficiency level (e.g., level 2, 3, etc.)
M BASE = repair cost at the base efficiency level (level 1) EQP STD = equipment price (consumer price for only the equipment) at a standard level, EQP BASE = equipment price (consumer price for only the equipment) at the base efficiency level,
ic r = installation cost index in region r (factor relative to national average).

Table 8.2.20 Central Air Conditioner and Heat Pump Basic Average Maintenance Costs by Efficiency Level

Efficiency

Level Maintenance Cost for Representative Standard-Compliant
Products 2008$SplitSystem AC(CoilOnly) SplitSystem AC(BlowerCoil) SplitSystem
HP Single Package AC Single Package
HP Level 1 70.00 70.00 70.00 70.00 70.00
Level 2 72.16 72.22 72.13 74.03 72.13
Level 3 74.44 74.43 74.37 76.78 74.86
Level 4 77.11 76.79 76.09 80.75 78.77
Level 5 80.11 78.54 77.74 84.01 82.22
Level 6 83.76 80.34 79.55 88.10 86.23
Level 7 88.41 82.20 81.86 92.93 90.97
Level 8 93.76 84.11 85.83 99.77 95.71
Level 9 NA 86.10 90.06 NA NA
Level 10 NA 90.31 94.61 NA NA
Level 11 NA 94.80 97.07 NA NA
Level 12 NA 99.62 NA NA NA
Level 13 NA 104.80 NA NA NA
Level 14 NA 110.36 NA NA NA
Level 15 NA NA NA NA NA
Level 16 NA NA NA NA NA

Because labor rates and sales taxes vary ac ross the country and maintenance costs also vary for any given efficiency level for each product type, Table 8.2.21 shows the average repair costs by region of the country and product type for the largest product classes.

8-36Table 8.2.21 Central Air Conditioner and Heat Pump Basic Average Maintenance Costs by Efficiency Level

Efficiency

Level Average Maintenance Costs fo r Representative StandardCompliant Products 2008$SplitsystemAC (CoilOnly) Splitsystem AC

(BlowerCoil) Splitsystem HP Single Package AC Single Package HP National Average

Level 1 75 75 75 75 75
Level 2 77 77 77 79 77 Level 3 80 80 80 82 80
Level 4 83 82 82 86 84
Level 5 86 84 83 90 88
Level 6 90 86 85 94 92
Level 7 95 88 88 100 97
Level 8 100 90 92 107 103
Level 9 NA 92 96 NA NA
Level 10 NA 97 101 NA NA
Level 11 NA 102 104 NA NA
Level 12 NA 107 NA NA NA
Level 13 NA 112 NA NA NA
Level 14 NA 118 NA NA NA
Hot-Humid Region
Level 1 48 48 48 48 48
Level 2 50 50 50 51 50
Level 3 51 51 51 53 52
Level 4 53 53 52 56 54
Level 5 55 54 54 58 57
Level 6 58 55 55 61 59
Level 7 61 57 56 64 63
Level 8 65 58 59 69 66 Level 9 NA 59 62 NA NA
Level 10 NA 62 65 NA NA
Level 11 NA 65 67 NA NA
Level 12 NA 69 NA NA NA
Level 13 NA 72 NA NA NA
Level 14 NA 76 NA NA NA Hot-Dry Region
Level 1 93 93 93 93 93
Level 2 96 96 96 98 96
Level 3 99 99 99 102 99
Level 4 102 102 101 107 105
Level 5 106 104 103 112 109
Level 6 111 107 106 117 115
Level 7 117 109 109 123 121
Level 8 125 112 114 133 127
Level 9 NA 114 120 NA NA
Level 10 NA 120 126 NA NA
Level 11 NA 126 129 NA NA
Level 12 NA 132 NA NA NA
Level 13 NA 139 NA NA NA
Level 14 NA 147 NA NA NA

8-37Table 8.2.21 (contd)

Efficiency

Level Average Maintenance Costs fo r Representative StandardCompliant Products 2008$SplitsystemAC (CoilOnly) Splitsystem AC

(BlowerCoil) Splitsystem HP Single Package AC Single Package
HP
Rest of Country
Level 1 85 85 85 85 85
Level 2 88 88 88 90 88
Level 3 91 91 91 94 91
Level 4 94 94 93 98 96
Level 5 98 96 95 102 100
Level 6 102 98 97 107 105
Level 7 108 100 100 113 111
Level 8 114 103 105 122 117
Level 9 NA 105 110 NA NA
Level 10 NA 110 115 NA NA
Level 11 NA 116 118 NA NA
Level 12 NA 121 NA NA NA
Level 13 NA 128 NA NA NA
Level 14 NA 135 NA NA NA

8.2.3.5 Lifetime

DOE defined lifetime as the age when a CAC unit is retired from service. DOE used national survey data, along with manufacturer shipment data, to cal culate the distribution of air conditioner and heat pump lifetimes. This analysis concluded that the mean lifetime for central air conditioners is 19.01 years and the mean lifetime for heat pumps is 16.24 years.

EIA’s RECS 21 surveys occupied primary housing units and notes the presence of a range of appliances, and places the age of each applia nce into several-year bins. The U.S. Census’s American Housing Survey (AHS) 22 surveys all housing, including vacant and second homes, and allowed DOE to adjust the RECS data to re flect some appliance use outside of primary residences. AHS also has a larger sample size, with correspondingly smaller sampling error. By combining these survey results with the known hi story of appliance shipments (collected from manufacturer trade associations) DOE estimated the fraction of appliances of a given age still in operation. This survival function, which DOE assumed has the form of a cumulative Weibull distribution, provides an estimate of the average and median appliance lifetime.

The Weibull distribution is a probability distribution function commonly used to measure failure rates. 23 Its form is similar to an exponentia l distribution, which would model a fixed failure rate, except that it allows for a failure rate which changes over time in a particular fashion. The cumulative distribution takes the form:

8-38β ⎛ x

− θ ⎞

− ⎜ ⎟ 

### P ( x ) = 

# e ⎝ α ⎠ for x > θ and P(x) = 1 for x ≤ θ

, Eq. 8.2.8

Where:

P(x) = probability that the appliance is still in use at age x ,
x

= appliance age,

α = the scale parameter, which is the decay length in an exponential distribution, β

= the shape parameter, which determines the way in which the failure rate changes in time, and θ

= the delay parameter, which allows for a delay before any failures occur.

When β = 1, the failure rate is constant over time, and this distribution takes the form of a cumulative exponential distribution. For the case of appliances, β is commonly greater than 1, which results from a rising failure rate as the appliance ages. A plot of a Weibull distribution (DOE’s calculated air conditioner survival function) with α = 20.29, β = 1.89, and θ = 1.0 is shown Figure 8.2.5.

The RECS survey is DOE’s primary resource for air conditioner and heat pump ages. For several appliances, including air conditioners, the survey asks respondents to place the appliance’s age into one of these bins:

• Less than 2 years,

• 2 to 4 years,

• 5 to 9 years,

• 10 to19 years, and

• Over 20 years.

The RECS survey has been conducted every th ree or four years for the last several decades. For this analysis, DOE used the surveys conducted in 1990, 1993, 1997, 2001, and 2005. The AHS Survey is conducted every other year, and DOE used the surveys conducted from 1991 to 2007. DOE used the AHS count of hous ing units with air conditioners to scale the RECS data to better ma tch the total installed stock. DOE used the surveys’ household-level micro-data to count households with shared or multiple ai r conditioners or heat pumps. Households which did not know the age of their appliance were allocated among the remaining age bins according to the distribution of re spondents who did report their appliance age.

DOE used RECS appliance age data, AHS tota l installed stock data , and the history of appliance shipments to generate an estimate of the survival function. For example, DOE summed the total shipments from 5 to 9 years prior to the RECS survey, and compared this number with the number of units of those ages still in use, to calculate one approximation of the surviving appliance fraction within that age bin. The AHS total stock acts as an “all ages” bin. By combining the age bins from five RECS surveys and 9 AHS surveys with shipments data, DOE had enough data to build a fit to a Wei bull distribution and find the parameters ( α , β

, θ ) that best approximate the surviving units, using a least-squares method. Because the first two (youngest) RECS bin data tend to have a large scatter relative to the shipments in those years, DOE combined the RECS and shipments data in the fi rst two bins. Generally, appliances do not tend

8-39to fail in large numbers during this period, so combining bins does not appreciably lower the accuracy of the shape of the distribution. DOE weighted each bin’s contribution to the sum of squares by the inverse of the variance in the survey results, which controls for the changes in sample size between RECS bi ns, between RECS and AHS, and within each survey over time. 24 RECS and AHS have complicated error models; DOE used only the error due to finite sample size to determine the variance used to weight ea ch data point’s contribu tion. The error due to sampling is less than one percent for AHS survey data, and typically about five percent for RECS age bins. The equation for the sum of squares DOE minimized is therefore

2 2 

## ( RECS

− Surv 

## ) 

# ( AHS j − Surv j 

# ) ∑ i i + 

# ∑ Eq. 8.2.9

i σ 2 σ 2
i , RECS j j , AHS

Where:

i = the identifier for a bin from a single RECS, j = the identifier for a single AHS survey
RECS i = the number of appliances reported by RECS in bin i

, AHS j = the number of appliances reported by AHS in survey year j

, Surv i = the number of surviving appliances in bin i predicted by the Weibull distribution applied to the num ber of appliances shipped (a function of α , β , and θ ), and

σ

i,RECS = the standard error (square root of the variance) of the RECS data point for bin i.

σ

j,AHS = the standard error (square root of the variance) of the AHS data point for

year j.

DOE adjusted the RECS and AHS survey data in several ways to place it on an even footing with the historical shipment data. In particular, DOE adjusted for the fact that the RECS survey is scaled to July of its reference year and the AHS survey is conducted in the middle portion of the year, while shipment data is provided for each calendar year. Adjustments included:

• DOE modeled the additional retirement of olde r appliances and their replacement by new ones which took place in the latter half of the survey year (after a given respondent had been surveyed), using the survival function. This had the effect of moving households from the older RECS age bins to the youngest age bin.

• For appliances installed directly in new construction, such as central air conditioners, DOE added units to the youngest RECS age bi n and to the AHS total stock to represent half of the new construction for the final year of the survey known to have installed the appliance type in question, us ing data from the U.S. Census.

• DOE assumed that 93 percent of appliances were installed in residences, and 7 percent in commercial or other applications not counted by AHS or RECS.

• Households that shared an air conditioner were counted as owning half of one air conditioner, and households w ho reported owning more than one air conditioner were counted as owning two. (For AHS surveys before 1997, the number of air conditioners

8-40was not reported; DOE assumed a linear increase with time in the fraction of homes with 2 air-conditioning units.)

Assumptions

DOE’s lifetime-calculation technique depends on several assumptions:

• Appliance lifetime can be modeled by a survival function. In particular, a Weibull distribution is an appropr iate survival function.

• The appliance survival function does not change over time.

• The survival function is independent of othe r household factors (such as household size, region, etc.) as well as product class (w ithin air conditioners or heat pumps).

• The age bin for the appliance as reporte d by the RECS respondent is correct.

• The historical shipment data is correct.

• The Weibull delay parameter, θ , is limited to between 1 and 5 years.

Three of these assumptions are of particular importance. The first is the assumption that a Weibull distribution is the correct distribution to use for appliance retirement rates. This distribution is the standard distri bution for use in lifetime analysis, but it is not guaranteed to reflect actual consumer behavior. The second assumption is that c onsumer behavior and mechanical appliance lifetime have not changed over time. This assumption required DOE to treat all data from different RECS surveys on an equal footing. Using only recent surveys (to potentially better reflect recent consumer behavior and appliance lifetime) would result in attempted least-squares fits using a small number of data points, leading to large statistical uncertainty.

DOE limited the delay parameter to between one and five years to reflect the range of common appliance warranties. A delay of less than one would imply that so me appliances fail or are replaced within their initial year of use, when they are commonly covered by parts and labor warranties. A delay of greater than five implies that no appliances are replaced for some length of time after the end of the longest standard warranty. Fits with θ > 5 also commonly show nonsensical behavior with sharp changes in consumer behavior or appliance survival immediately following the “delay” period.

Central Air Conditioners

Table 8.2.22 shows the RECS and AHS data for air conditioners and the corresponding total shipments and best-fit Weibull calculation of stock by age bin. Figure 8.2.3 plots the data from the RECS portion of the third and fourth columns of Table 8.2.22 against each other to show the quality of the fit. Figure 8.2.4 plots the AHS survey total stock against the Weibullbased calculated stock. DOE a llowed the delay parameter, θ , to vary only between one and five years, which corresponds to common warrant y periods (see discussion below); for air conditioners and heat pumps the best fit within this range is 1 year. This Weibull distribution is characterized by the parameters α = 20.29, β = 1.89, and θ = 1.0, and shown in Figure 8.2.5. This distribution has a mean air conditioner lifetim e of 19.01 years and a median lifetime of 17.70 years.

8-41Table 8.2.22 Central Air Conditioners: Comparison of RECS and AHS with Modeled Stock

Age bin RECS 2005 Shipments RECS Stock Modeled Stock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 23,384,298 20,606,096 26,252,849 29,643,170 21,121,201 15,568,739 15,840,393

6,611,168 23,202,596 18,628,161 16,908,120

5,434,630

Age bin RECS 2001 Shipments RECS Stock Modeled Stock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 20,833,446 15,707,082 20,982,218 23,056,758 16,179,828 14,511,234 14,367,204

5,583,734 20,669,235 14,252,361 13,670,285

4,771,136

Age bin RECS 1997 Shipments RECS Stock Modeled Stock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 16,822,938 12,555,897 16,825,109 17,112,973 12,213,941 12,441,915 10,799,049

4,046,096 16,697,701 11,311,053 10,843,901

4,137,030

Age bin RECS 1993 Shipments RECS Stock Modeled stock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 12,781,848 10,579,559 14,275,598 11,535,301 11,450,065 9,198,439 9,410,523 3,727,973 12,671,267 9,572,156 8,960,434 3,257,844

Age bin RECS 1990 Shipments RECS Stock Modeled Stock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 11,836,478 7,930,531 15,067,767

6,644,873 10,544,271 7,343,580 10,136,090

3,025,410 11,745,800 7,200,298 9,435,899 1,897,721

Survey year AMERICAN HOUSING SURVEY Adjusted AHS Stock Modeled Stock
2007
2005
2003
2001
1999
1997
1995
1993
1991 66,850,067 63,023,984 56,640,747 54,080,318 48,189,582 41,173,857 38,446,053 35,072,816 32,893,755 67,116,846 64,173,507 58,293,705 53,363,017 48,428,026 42,989,684 38,517,301 31,793,586 31,733,007

8-42Calculated number of households with AC by bin 25000000

20000000

15000000

10000000

5000000

0 Age bins

ideal

0 5000000 10000000 15000000 20000000 25000000 RECS reported number of households with AC by bin

Figure 8.2.3 Comparison of DOE Modeled Ai r Conditioner Age Dist ribution with RECS Reported Stock

70,000,000

60,000,000

AHS surveys

idealCalculated CAC Stock

50,000,000

40,000,000

30,000,000

20,000,000 20,000,000 30,000,000 40,000,000 50,000,000 60,000,000 70,000,000
Adjusted American Housing Survey CAC Stock

Figure 8.2.4 Comparison of DOE Modeled To tal Air Conditioner St ock with Adjusted
AHS Stock

8-4317.70 19.01

0.0 0.2 0.4 0.6 0.8 1.0 1.2Fraction surviving Survival function
Median lifetime
Mean lifetime

0 1 0 2 0 3 0 4 0 5 0
Age (years)

Figure 8.2.5 Central AC Survival Function, Characterized by Weibull Parameters α = 20.29, β = 1.89, and θ = 1.0.

Heat Pumps

DOE undertook a very similar calculation for heat pumps as it did for central air conditioners. The only difference between the h eat pump and central air conditioner analyses was in the number of AHS survey years included. DOE found that when the heat pump stock analysis was done with AHS-reported stock from all nine AHS surveys between 1991 and 2007 with manufacturer-reported shipme nts history, an assumed uncha nging heat pump lifetime, and an assumed 95 percent to five percent residential/commercial market split, the results were inconsistent. In the interest of timeliness and consistency, DOE chose to use only the most recent four surveys (2001, 2003, 2005, and 2007). Using only the most recent four AHS surveys, DOE was able to develop a consistent survival func tion. Figure 8.2.6 shows the AHS survey results plotted against the modeled stoc k, and shows the contrast betw een earlier and more recent data.

The best-fit Weibull parameters for heat pump lifetime are α = 17.04, β = 1.64, and θ = 1.0. The resulting calculated mean heat pump lifetime is 16.24 years; the median lifetime is 14.63 years. Table 8.2.23 lists the (adjusted) heat pumps reported in each of the RECS age bins and AHS survey year along with the modeled stock based on the best fit Weibull survival function and the manufacturer-pr ovided shipments history. Figure 8.2.7 shows the survival function used in the life-cycle cost and national impact analyses.

8-44Table 8.2.23 Heat Pumps: Comparison of RECS and AHS Stock to Stoc k Calculated from
a Weibull Survival Function

Age Bin RECS 2005 Shipments RECS Dtock Modeled Dtock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 7,656,050 5,437,867 7,609,488 5,421,606 5,903,720 4,186,956 4,167,868 1,172,137 7,531,948 4,545,002 3,947,892

947,223

Age Bin RECS 2001 Shipments RECS Stock Modeled Stock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 5,693,105 4,318,866 6,413,059 3,320,977 4,564,988 3,641,519 3,191,956 1,273,838 5,593,500 3,626,504 3,383,920

622,144

Age Bin RECS 1997 Shipments RECS Stock Modeled Stock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 4,615,287 3,500,621 5,271,716 1,671,785 4,550,375 3,871,200 3,828,288

575,473 4,536,486 2,914,225 2,852,397

319,727

Age Bin RECS 1993 Shipments RECS Stock Modeled Stock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 3,582,387 3,514,244 3,308,542

822,935 3,847,273 3,043,034 2,425,988

523,705 3,515,747 2,938,354 1,803,756

139,039

Age Bin RECS 1990 Shipments RECS Stock Modeled Stock 0 to 4 yrs. 5 to 9 yrs. 10 to 19 yrs. 20 or more yrs. 3,637,163 2,494,052 2,327,546

600,009 2,929,208 3,030,644 1,846,344

168,614 3,565,942 2,112,769 1,356,527

111,330

Survey year AMERICAN HOUSING SURVEY Adjusted AHS Stock Modeled Stock
2007
2005
2003
2001
1999
1997
1995
1993
1991 16,718,490 16,130,513 14,318,151 13,653,239 13,331,680 13,658,054 11,460,574 10,412,946 9,349,377 18,037,674 16,123,461 14,017,726 12,564,764 11,290,213 10,091,692

8,980,076 7,977,051 7,165,773

8-45Modeled stock of heat pumps 20,000,000

15,000,000

10,000,000

5,000,000

0 Recent AHS surveys Older AHS surveys

ideal

0 5,000,000 10,000,000 15,000,000 20,000,000
AHS reported stock of heat pumps

Figure 8.2.6 Comparison of DOE Modeled Tota l Heat Pump Stock with Adjusted AHS
Stock

14.63

16.24

0.0 0.2 0.4 0.6 0.8 1.0 1.2Fraction surviving Survival function
Median lifetime
Mean lifetime

0 5 10 15 20 25 30 35 40 45 50
Age (years)

Figure 8.2.7 Heat Pump Survival Function, Characterized by Weibull Parameters α = 17.04, β = 1.64, and θ = 1.0.

8-468.2.3.6 Discount Rate

The discount rate is the rate at which future expenditures are discounted to establish their present value. DOE derived the discount rates fo r the LCC analysis by estimating the cost of capital for individuals and companies that purchase CAC products.

In the case of individual households, the financing of purchasing products installed in new homes is different than the financing of app liances bought directly by consumers (i.e., as a replacement for a failed unit or as a new purchase for an existing household that does not already own the appliance). Thus, DOE used different di scount rates for these residential purchases.

Residential Discount Rates for Product s Purchased in Existing Households

Households use various methods to finan ce the purchase of major appliances. In principle, one could estimate the interest rates on the actual financing vehicles used to purchase appliances. However, the frequency with which eac h financing vehicle is used to purchase an appliance is unknown.

DOE’s approach involved identifying all possible debt or asset classes that might be used to purchase the considered appliances, including household assets that might be affected indirectly. c DOE excluded debt from primary mortgage s and the equity of assets considered non-liquid (such as retirement accounts), because those financing methods are unlikely to be used by households in existing housing to pur chase appliances. DOE estimated the average percentage shares of the various types of debt and equity in the average U.S. household using data from the Federal Reserve Board’s Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. 25 Table 8.2.24 shows the average percentages of each considered type of debt or equity. DOE derived the mean percentages of each source of financing for the seven years surveyed.

An indirect effect would arise if a household sold assets in order to pay off a loan or credit card debt that might have been used to finance the appliance purchase.

8-47 cTable 8.2.24 Types of Household Debt and Equity by Percentage Shares

Debt or Equity Distribution %

1989 1992 1995 1998 2001 2004 2007 Mean Home equity loan 4.3 4.5 2.7 2.8 2.8 4.4 4.6 3.7

Credit card 1.6 2.1 2.6 2.2 1.7 2.0 2.4 2.1

Other installment loan 2.8 1.7 1.4 1.7 1.1 1.3 1.1 1.6

Other residential loan 4.4 6.9 5.2 4.3 3.1 5.8 7.1 5.3

Other line of credit 1.1 0.6 0.4 0.2 0.3 0.5 0.3 0.5 Checking account 5.8 4.7 4.9 3.9 3.6 4.2 3.4 4.4 Savings or money market account 19.2 18.8 14.0 12.8 14.2 15.1 13.0 15.3 Certificate of deposit 14.5 11.7 9.4 7.0 5.4 5.9 6.5 8.6 Savings bond 2.2 1.7 2.2 1.1 1.2 0.9 0.7 1.4

Bonds 13.8 12.3 10.5 7.0 7.9 8.4 6.7 9.5

Stocks 22.4 24.0 25.9 36.9 37.5 28.0 28.6 29.0

Mutual funds 8.0 11.1 20.9 20.1 21.3 23.4 25.5 18.6

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 2007.

DOE also estimated interest or return rates associated with each type of equity and debt. The source for interest rates for loans, credit ca rds, and lines of credit was the Federal Reserve Board’s SCF for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. Table 8.2.25 shows the average nominal rates in each year and the inflation factors used to calculate real rates. DOE calculated effective interest rates for home equity loans in a similar manner as for mortgage rates, because interest on both such loans is tax deductible. Tabl e 8.2.26 shows the average effective real rates in each year and the mean rate across years. Becau se the interest rates for each type of household debt reflect economic conditions throughout numerous years, they are expected to be representative of rates that may be in effect in 2016.

Table 8.2.25 Average Nominal Interest Rates for Household Debt

Debt Average Nominal Interest Rate %

1989 1992 1995 1998 2001 2004 2007 Mean Home equity loan 11.5 9.6 9.6 9.8 8.7 5.7 6.3 7.9

Credit card*

- - 14.2 14.5 14.2 11.7 7.9 9.0

Other installment loan 9.0 7.8 9.3 7.8 8.7 7.4 12.6 13.4

Other residential loan 8.8 7.6 7.7 7.7 7.5 6.0 10.4 8.6

Other line of credit 14.8 12.7 12.4 11.9 14.7 8.8 6.3 7.4

Inflation rate 4.82 3.01 2.83 1.56 2.85 2.66 2.85
Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 2007.
* No data on interest rates available for credit cards in 1989 or 1992.

8-48Table 8.2.26 Average Real Effective Interest Rates for Household Debt

Debt Average Real Effective Interest Rate %

1989 1992 1995 1998 2001 2004 2007 Mean Home equity loan 3.8 4.3 4.4 5.8 3.8 1.9 2.1 3.0

Credit card*

- - 11.0 12.7 11.1 9.1 3.3 3.9

Other installment loan 4.9 5.8 7.0 6.6 6.1 5.4 9.7 10.7

Other residential loan 4.0 4.7 4.8 6.0 4.6 3.3 5.8 6.0

Other line of credit 9.6 9.4 9.3 10.2 7.3 6.0 3.4 4.4

Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 2007.
* No data on interest rates available for credit cards in 1989 or 1992.

No similar rate data are available from the SCF for classes of assets , so the Department derived that information from national historical data. The interest rates associated with certificates of deposit, 26 savings bonds, 27 and bonds (AAA corporate bonds) 28 were collected from Federal Reserve Board time-series data for 1977–2008. DOE assumed rates on checking accounts to be zero. Rates on savings and money market accounts came from Cost of Savings Index data covering 1984–2008. 29 The rates for stocks are the a nnual returns on the Standard and Poor’s 500 for 1977–2008. 30 Rates for mutual funds are a weighted average of the stock rates (two-thirds weight) and the bond rates (one-t hird weight) in each year for 1977–2008. DOE adjusted the nominal rates to real rates using the annual inflation rate for each year. Average nominal and real interest rates for the classes of household assets are listed in Table 8.2.27. Because the interest and return rates for each type of asset reflect economic conditions throughout numerous years, they are expected to be representative of rates that may be in effect in 2016.

Table 8.2.27 Average Nominal and Real Interest Rates for Household Equity

Type of Equity Average Nominal Rate % Average Real Rate % Checking account

- 0.0 Savings and money market accounts 5.4 2.2 Certificate of deposit 6.6 2.3 Savings bond 7.7 3.3

Bonds 8.5 4.1

Stocks 11.6 7.1

Mutual funds 10.3 5.8

Table 8.2.28 summarizes the mean real effectiv e rates of each type of equity or debt. DOE determined the average percentage of each type of debt and asset using SCF data for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. Each year of SCF data provides the percents of debts and assets for U.S. households. DOE averaged those percentages for the seven years of survey data to arrive at the percenta ges shown in Table 8.2.28. The average rate across all types of household debt and equity, weighted by the pe rcentages of each type, is 4.8 percent.

8-49Table 8.2.28 Average Interest on Household Debt and Equity

Type of Debt or Equity Average Percentage of Household Debt plus Equity* Mean Effective Real Rate % ** Home equity loan 3.7 3.9

Credit card 2.1 10.7

Other installment loan 1.6 6.0

Other residential loan 5.3 4.4

Other line of credit 0.5 8.8 Checking account 4.4 0.0 Savings and money market account 15.3 2.2 Certificate of deposit 8.6 2.3 Savings bond 1.4 3.3

Bonds 9.5 4.1

Stocks 29.0 7.1

Mutual funds 18.6 5.8 Total/weighted-average discount rate 100.0 4.8

* Not including primary mortgage or retirement accounts. ** Adjusted for inflation and, for home equity loans, tax deduction of interest.

DOE developed a normal probability distribution of interest rates for each asset type by using the mean value and standard deviation from the distribution. To account for variation among households, DOE sampled a rate for each household from the distributions for the appropriate asset cl ass. Appendix 8-E presents the probab ility distributions for each class that DOE used in the LCC and PBP analyses.

Residential Discount Ra tes for Products Installed in New Housing

Appliances installed in new homes (“new-housin g appliances”) are purchased as part of the home, which is almost always financed with a mortgage loan. DOE estimated discount rates for new-housing appliances using the effective real (after-inflation) mortgage rate for homebuyers. This rate corresponds to the interest rate after deduction of mortgage interest for income tax purposes and after adjusting fo r inflation (using the Fisher formula). d For example, a six-percent nominal mortgage rate has an effective nominal rate of 4.5 percent for a household at the 25-percent marginal tax rate. When adjusted for inflation of two percent, the effective real rate becomes 2.45 percent.

The data source DOE used for mortgage interest rates is the SCF in 1989, 1992, 1995, 1998, 2001, 2004, and 2007. Using the appropriate SCF data for each year, DOE adjusted the mortgage interest rate for each relevant household in the SCF for mortgage tax deduction and inflation (see Table 8.2.29). In cases where the effective interest rate is equal to or below the inflation rate (resulting in a negative real interest rate), DOE set the real effective interest rate to

zero.

d Fisher formula is given by: Real Interest Rate = [(1 + Nominal Interest Rate) / (1 + Inflation Rate)] – 1.

8-50The average nominal mortgage rate carried by homeowners in these six years was 7.9 percent. Since the mortgage rates carried by households in these ye ars were established over a range of time, DOE believes they are representative of rates that may apply when amended standards take effect. After adjusting for inflation and interest tax deduction, effective real interest rates on mortgages across the six surveys averaged 3.0 percent.

Table 8.2.29 Data Used to Calculat e Real Effective Mortgage Rates

Year Mortgage Interest Rates in Selected Years %

Average Nominal Interest Rate Inflation Rate 58 Marginal Tax Rate Applicable to Mortgage Interest 59 Average Real Effective Interest Rate

1989 9.7 4.82 24.3 2.4

1992 9.1 3.01 23.4 3.8

1995 8.2 2.83 24.1 3.3

1998 7.9 1.56 23.9 4.4

2001 7.6 2.85 22.9 2.9

2004 6.2 2.66 20.6 2.2

2007 6.3 2.85 21.6 2.1 Average 7.9 3.0

To account for variation among households, DOE sampled a rate for each household in the RECS samples from a distribution of mortgage rates. DOE developed the distribution based on the SCF data. Appendix 8-E presents the probability distribution that DOE used in the LCC and PBP analyses.

Commercial Discount Rate

The commercial discount rate for central air conditioners is estimated using cost of capital data for firms that might occupy or rent out office space in small office buildings. DOE estimated the cost of equity using the capital asset pricing model (CAPM). The CAPM assumes that the cost of equity (k
e ) for a particular company is proportional to the systematic risk faced by that company, where high risk is associated with a high cost of equity and low risk is associated with a low cost of equity. The systematic risk facing a firm is determined by several variables: the risk coefficient of the firm ( β ), the expected return on risk free assets (R f ), and the equity risk premium (ERP). The risk coefficient of the firm indicates the risk associated with that firm relative to the price variability in the stock market. The expected return on risk-free assets is defined by the yield on long-term government bonds. The ERP represents the difference between the expected stock market return and the risk-free rate.

Described below, we estimate the cost of equity for each sector with the CAPM model as follows:

k

e = R f + ( β • ERP) Eq. 8.2.10

Where:

k

e = the cost of equity,

8-51R f = the expected return of the risk-free asset (long term treasury bonds), β = the beta of the sector, and E R P is the expected equity risk premium.

From data available on β for individual U.S. commercial companies, estimated market ERP from Damodaran Online 31 and long term treasury bond rates for R f from the Economic Report of the President 32 , we calculate the cost of equity k
e for each firm.

The cost of debt financing ( k d ) is the interest rate paid on money borrowed by a company. The cost of debt is estimated by adding a risk adjustment factor ( R a ) to the risk-free rate.

k = R + R

,

d f a

Where:

k

d = the cost of debt fi nancing for each firm,
R

f = the expected return on risk-free assets, and

R

a = is the risk adjustment factor to risk-free rate for each firm.

The risk adjustment factor depends on the variability of stock returns represented by standard deviations in stock pr ices and was taken from Damodaran Online weighted average cost of capital worksheets for 2001-2008.

Finally, as inflation has already been accounted for in both the cost of debt and the cost of equity, the real weighted average cost of capital WACC r (real discount rate) is calculated as follows:

WACC r = k
e • w e + k d • w d Eq. 8.2.11

Where:

k

e = the cost of equity,

w

e = the percent of equity financing,

k d = the cost of debt, and

w

d = the percent of debt financing.

The discount rate is estimated for each firm for 2009. The two sources of cost of capital data that are used in our calculations are individual company data from Damodaran Online’s Data Page. DOE used Damodaran Online data fro m the SIC categories with Standard Industrial Classification (SIC) 6000-9975, with the exception of Hotels and Gaming (SIC code 7000). Broadly speaking, this includes all of the commercial subsectors that could occupy small offices that might use a residential-sized central air conditioner. The sample includes 1750 companies with usable data. It includes both large and small companies, since it is not clear that small offices would be occupied or owned by an entit y that was also a small business. The weighted average cost of capital for this sample of U.S. companies was 7.56 percent. Nominal rates for individual firms varied from 2.58 percent to 14.10 percent, which were fitted to a normal distribution truncated at 0 to prevent negative rate s. The standard deviation of the statistical

8-52sample was 1.54 percent. Adjusted for the long-term expected inflation rate of 1.8 percent rate from the January, 2009 Economic Report of the Pres ident, the discount rate was 5.66 percent, which is used as the average re al discount rate for central air conditioners purchased for small offices.

8.2.3.7 Effective Date of Standard

The effective date is the future date when a new standard becomes operative. Pursuant to 42 U.S.C. 6295(m), the effective date of any new energy efficiency standard for CAC equipment will be 5 years after the final ru le is published. DOE calculated the LCC for all customers as if they each would purchase a new air conditioner or heat pump in the year the standard takes effect. Consistent with its published regulatory agenda, DOE assumed that the final rule would be issued in 2011 and that, therefore, the new st andards would take effect in 2016 and used these dates in the NOPR analyses. It based the cost of the equipment on this year; however, all dollar values are expressed in 2008$. Annual energy pric es are included for the life of the central air conditioner or heat pump.

8.2.3.8 Base Case Distribution of Efficiency Levels

The market mix of efficiency levels in 2008 is shown in Table 8.2.30 for the four largest product classes, the development of which is discussed in chapter 7. This same distribution is assumed to prevail in 2016 in the absence of an energy conservation standard above 13 SEER. The three smaller product classes (Confined Spac e A/C, Confined Space heat Pump, and SmallDiameter High Velocity A/C units) currently have not been analyzed.

Table 8.2.30 2008 Market Distribution of Efficiency Levels by Product Class

Bin Bottom of Bin Top of Bin Assumed Average SEER in Bin Split-System AC % SplitSystem HP % Single Package AC % Single Package

HP %CoilOnly BlowerCoil
1 13 13.25 13.0 24.37% 24.00 50.00 75.00 50.00

2 13.25 13.75 13.5 55.84% 55.00 32.00 20.00 32.00
3 13.75 14.25 14.0 4.06% 4.00 11.00 2.00 11.00

4 14.25 14.75 14.5 5.33% 5.25 5.00 2.00 5.00
5 14.75 15.25 15.0 3.30% 3.25 2.00 1.00 2.00

6 15.25 15.75 15.5 2.03% 2.00 NA NA NA

7 15.75 16.5 16.0 3.55% 3.50 NA NA NA
8 16.5 17.5 17.0 * 1.52% 1.50 NA NA NA

9 17.5 18.5 18.0 NA 0.70 NA NA NA
10 18.5 19.5 19.0 NA 0.30 NA NA NA

11 19.5 20.5 20.0 NA 0.20 NA NA NA

12 20.5 21.5 21.0 NA 0.20 NA NA NA

13 21.5 22.5 22.0 NA 0.10 NA NA NA

14 22.5 23.5 23.0 NA NA NA NA NA
15 23.5 24.5 24.0 NA NA NA NA NA

16 24.5 25.5 25.0 NA NA NA NA NA
* The selected corresponding efficiency level for this bin is 16.5 for coil-only split system air conditioners

8-538.3 PAYBACK PERIOD INPUTS

8.3.1 Definition

The payback period is the amount of time it ta kes the customer to recover the assumed higher purchase cost of more energy-efficient equipment as a result of lower operating costs. Numerically, the PBP is the ratio of the increase in purchase cost ( i.e ., from a less efficient design to a more efficient design) to the decreas e in annual operating expend itures. This type of calculation is known as a “simple” payback period , because it does not take into account changes in operating cost over time or the time value of money—that is, the calculation is done at an effective discount rate of 0 percent.

The equation for PBP is:

PBP = ∆ IC/ ∆ O C Eq. 8.3.1

Where:

PBC = payback period in years, ∆ IC = difference in the total installed cost between the more efficient standard level equipment (efficiency levels 2,3, etc.) and the baseline efficiency equipment, and ∆ OC = difference in first year annual operating costs.

Payback periods are expressed in years. Payback periods greater than the life of the equipment mean that the increased total installed cost of the more efficient equipment is not recovered fast enough in reduced operating costs.

DOE also calculates a rebuttable payback period, which is the time it takes the consumer to recover the assumed higher purchase cost of more energy-efficient equipment as a result of lower energy costs. Numerically, the rebuttable PBP is the ratio of the increase in purchase cost ( i.e ., from a less efficient design to a more effici ent design) to the decrease in annual energy expenditures; that is, the difference in first year annual energy cost. The calculation excludes repair costs and maintenance costs. This type of calculation also is a “simple” payback period.

8.3.2 Inputs

The data inputs to PBP are the total installed cost of the equipment to the customer for each efficiency level and the annual (first year) operating costs for each efficiency level. The inputs to the total installed cost are the equipm ent price and the installation cost. The inputs to the operating costs are the annual energy cost, th e annual repair cost, a nd the annual maintenance cost (or in the case of rebuttable PBP, only the annual energy cost). The PBP uses the same inputs as the LCC analysis described in section 8.2, except that electri city price trends and discount rates are not required. Since the PBP is a “simple” (undiscounted ) payback, the required electricity cost is only for the year in which a new efficient standard is to take effect—in this case, the year 2016. The el ectricity price used in the PBP cal culation was the price projected for 2016, expressed in 2008$. Discount rates ar e not used in the PBP calculation.

8-548.4 SEER AND HSPF RESULTS

This section presents the LCC and PBP results for residential CACs and CHPs that are used in residential and commercial (small office) applications. As discussed in Section 8.1.1, DOE’s approach for conducting the LCC and PB P analysis relied on de veloping samples of households that use each of the products. DOE also characterized the uncertainty of many of the inputs to the analysis with probability dist ributions. DOE used a Monte Carlo simulation technique to perform the LCC a nd PBP calculations on the households in the sample. For each set of sample households using th e equipment in each product cla ss, DOE calculated the average LCC and LCC savings and the median and average PBP for each of the efficiency levels. These efficiency levels are also referred to as candidate standard levels (CSLs).

DOE calculated LCC savings and PBPs relative to the market baseline equipment that it assigned to the households and commercial consumers. DOE assigned market baseline equipment that is more efficient than some of the CSLs. For that reason, the average LCC impacts are not equal to the difference between the LCC of a specific CSL and the LCC of the market baseline equipment.

LCC and PBP calculations were performed 10,000 times on the sample of households established for each residential product. Each LCC and PBP calculation was performed on a single household that was selected from the sample of the reside ntial observations or alternatively, from one of the commercial build ings commercial building using the CAC or CHP equipment. The first sampling conducted was based on the probability of whether the given observation was a residential or a commercial application. The probability of a residential observation was 93 percent, while that of a co mmercial observation was 7 percent. If the observation was residential, then the selection of a household was based on its weight (i.e., how representative a particular househol d is of other households in th e distribution-either regionally or nationally) in the Energy Information Admi nistration’s 2005 Residential Energy Consumption Survey Public Use Sample, as described in TSD chapter 7. Each LCC and PBP calculation also sampled from the probability distributions that DOE developed to characterize many of the inputs to the analysis. For the commercial a pplications, DOE sample d from commercial small office building simulations using weights repres entative of 526 combinations of TMY weather file and State. . The weights assigned were population weights assigned to each combination as described in chapter 7. The LCC and PBP calcu lations were performed 10,000 times by sampling observations from the total of the Residiential and Commercial samples (reflecting the relative residential and commercial sales weights) and using the probability distributions that DOE developed to characterize many of the inputs.

Based on the Monte Carlo simulations that DOE performed, for each standard-level, DOE calculated the share of households and commer cial consumers receiving a net LCC benefit, with a net LCC cost, and with no impact. DOE considered a household or commercial user to receive no impact at a given if DOE assigned it base case equipment that is the same as or has higher efficiency than the CSL.

8-558.4.1 Split-system Air Conditioners

This section presents summary LCC results for the efficiency improvement levelsspecified in the engineering analysis (Chapter 5) and also presented in Section 8.2.2.2, StandardLevel Manufacturer Price Increases. The results presented here are based on annual operating costs calculated from residential and commercial electricity tariffs, repair costs, and maintenance costs developed for each individua l observation. Section 8.2 presen ts the electrici ty price inputs as well as all other LCC inputs.

To provide perspective on the LCC and PBP results, Table 8.4.1 and Table 8.4.4 present the average values for market baseline installed cost of split-system air conditioners for coil-only and blower-coil options, their average energy cons umption at market baseli ne and the percentage changes in these values at the efficiency improvement levels.

Table 8.4.1 Mean Market Baseline Installed Co sts, Total Annual Energy Consumption, and Percentage Change for Split-System Air Conditioners (Coil-Only) by Region by Efficiency Level (SEER Value)

Efficiency

Level (SEER) Nation Hot-Humid Hot-Dry Rest of Country
Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh
Market Baseline 2,647 2,291 2,400 3,393 3,056 2,071 2,626 1,310

Percentage Change from Market Baseline
13.5 (1.8) 1.4 (1.9) 1.3 (1.8) 1.4 (1.8) 1.6
14 0.9 (2.1) 0.9 (2.2) 0.9 (2.0) 0.9 (1.7)
14.5 4.1 (5.4) 4.3 (5.5) 4.0 (5.3) 4.0 (5.0)
15 7.7 (8.5) 8.1 (8.6) 7.4 (8.4) 7.5 (8.1)
15.5 12.0 (11.4) 12.6 (11.5) 11.7 (11.3) 11.7 (11.0)
16 17.6 (14.1) 18.5 (14.3) 17.0 (14.1) 17.1 (13.7)
16.5 24.0 (16.6) 25.2 (16.8) 23.3 (16.5) 23.3 (16.1) *Values in parentheses denote negative values.

Table 8.4.2 Mean Market Baseline Installed Co sts, Total Annual Energy Consumption, and Percentage Change for Sp lit-System Air Conditioners (B lower-Coil) by Region by Efficiency Level (SEER Value)

Efficiency

Level (SEER) Nation Hot-Humid Hot-Dry Rest of Country
Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh
Market Baseline 4,128 2,315 3,671 3,410 4,782 2,067 4,125 1,302

Percentage Change from Market Baseline
13.5 (0.9) 1.4 (0.9) 1.3 (0.8) 1.4 (0.8) 1.3
14 1.0 (2.1) 1.1 (2.2) 1.0 (2.0) 1.0 (2.0)
14.5 3.0 (5.4) 3.2 (5.5) 2.9 (5.3) 2.9 (5.3)
15 4.5 (8.5) 4.8 (8.6) 4.3 (8.4) 4.3 (8.4)
15.5 6.0 (11.4) 6.4 (11.5) 5.8 (11.3) 5.8 (11.3)
16 7.5 (14.1) 8.1 (14.2) 7.3 (14.1) 7.3 (14.0)
16.5 9.2 (16.6) 9.8 (16.7) 8.8 (16.5) 8.8 (16.3)
17 10.8 (18.9) 11.6 (19.1) 10.5 (18.8) 10.5 (18.5)

8-5618 14.4 (23.1) 15.4 (23.4) 13.9 (23.0) 13.9 (22.6)
19 18.2 (26.9) 19.5 (27.2) 17.5 (26.7) 17.5 (26.3)
20 22.2 (30.3) 23.8 (30.7) 21.5 (30.2) 21.5 (29.6)
21 26.6 (33.4) 28.5 (33.8) 25.7 (33.2) 25.7 (32.6)
22 31.3 (36.3) 33.5 (36.7) 30.2 (36.1) 30.2 (35.3) *Values in parentheses denote negative values.

As stated earlier, DOE used the Monte Carlo method of analysis relying on Crystal Ball (i.e., random sampling from distributions) to c onduct the LCC analysis. The results presented here are based on 10,000 samples per Monte Carlo run. DOE’s fi rst step in developing LCC results was to establish the market baseline LCC for each of the product classes. The market baseline efficiency level for the preliminary analysis is the market-weighted efficiency level in each region. These distributions are shown in Figure 8.4.1 for coil-only split-system AC units and in Figure 8.4.2 for blower-coil AC units.

National Standard Hot-Humid

Hot-Dry Rest of Country
Figure 8.4.1 Market Baseline Distributions of LCC for Split-Sys tem Air Conditioners (Coil-Only) by Region

8-57Nation Hot-Humid

Hot-Dry Rest of Country
Figure 8.4.2 Market Baseline Distributions of LCC for Split-Sys tem Air Conditioners (Blower-Coil) by Region

8.4.1.1 Mean LCC Savings for Split-syste m Air Conditioners by Region

Because the values of most inputs are uncertain in this analysis, DOE represents them as a distribution of values rather than a single point-value. Thus, DOE also represents the LCC results as a distribution of values. Before proceeding with the presentation of the distribution of LCC results, DOE presents average values for LCC savings to show how these savings vary with efficiency for each of the split-system CAC produc t classes and by region. Table 8.4.3 presents results for coil-only improvements. LCC savings are positive at the national level standards up to SEER 13.5, and in the Hot-Humid and Hot- Dry regions up to SEER 15 and SEER 14.5, respectively. No SEER level beyond SEER 13 pr oduces LCC savings for a coil-only standard in the rest of the country. Table 8.4.4 shows that LCC savings are positive at national level blowercoil standards up to SEER 13.5, but in the Hot-Humid and Hot-Dry regions savings are positive up to SEER 19 and SEER 18, respectively. No SEER level beyond SEER 13 produces LCC savings for a blower-coil standard in the rest of the country.

Table 8.4.3 Mean LCC Savings for Split-System Air Co nditioners (Coil-only) by Region by Efficiency Level (SEER Value)
Efficiency LCC by Region 2008$
Level SEER Nation Hot-Humid Hot-Dry Rest of Country
2 13.5 4 11 8 (15)

8-583 14 (1) 36 20 (75)
4 14.5 (29) 39 4 (157)
5 15 (83) 19 (40) (265)
6 15.5 (180) (39) (134) (414)
7 16 (341) (154) (300) (624)
8 16.5 (565) (324) (537) (902) *Values in parentheses denote negative savings

.
Table 8.4.4 Mean LCC Savings fo r Split-System Air Conditi oners (Blower-Coil) by Region by Efficiency Level (SEER Value)
Efficiency Level SEER LCC by Region 2008$
Nation Hot-Humid Hot-Dry Rest of Country
2 13.5 2 11 7 (16)
3 14 0 38 24 (73)
4 14.5 (15) 53 27 (140)
5 15 (5) 90 56 (183)
6 15.5 (5) 118 74 (234)
7 16 (14) 137 81 (291)
8 16.5 (36) 142 73 (361)
9 17 (68) 137 54 (437)
10 18 (159) 100 (19) (611)
11 19 (285) 28 (133) (810)
12 20 (443) (77) (287) (1,036)
13 21 (634) (214) (480) (1,288)
14 22 (859) (384) (713) (1,568) *Values in parentheses denote negative savings.

It is worth reiterating that the results show n in Table 8.4.3 and Table 8.4.4 are mean values and do not show the distributions of savings. Thus, although observations can be made as to how the various inputs impact life-cycle cost and, in turn, how the resulting life-cycle costs change with efficiency, conclusions should only be drawn from the distribution of life-cycle cost results that are presented in Figure 8.4.3 and Fi gure 8.4.4. Section 8.4.1.3 provides information on the percentages of consumers in each region at each efficiency level that would experience LCC savings benefits, LCC cost increases, and no impact from the standard.

8-59-1500 -1000 -500

0 500 1000 1500 2000Life-cycle Cost Savings($)

2 3 Mean

4 5 Median

6 7 8 -1500 -1000 -500

0 500 1000 1500 2000Life-cycle Cost Savings($)

Mean Median `

Efficiency Level National 2 3 4 5 Efficiency Level 6 7 8 Hot-Humid

-2000 -1500 -1000 -500

0 500 1000 1500 2000Life-cycle Cost Savings($)

Mean Median `

-2000 -1500 -1000 -500

0 500 1000 1500 2000Life-cycle Cost Savings($)

Mean Median

2 3 Efficiency Level 4 5 6 7 Hot-Dry 8 2 3 Efficiency Level 4 5 6 Rest-of-Country 7 8

Figure 8.4.3 Plots of the Distributions of L CC Savings for Split-Sys tem Air Conditioners (Coil-Only) by Region

-2500 -2000 -1500 -1000 -500

0 500 1000 1500 2000Life‐cycleCostSavings($)

2 3 4 5 Mean

6 7 8 9 Efficiency Level Median `

10 11 12 13 14 National -2000 -1500 -1000 -500

0 500 1000 1500 2000Life‐cycleCostSavings($)

2 3 4 5 Mean

6 7 8 9 Efficiency Level Median `

10 11 12 13 14
Hot

‐ Humid

-2000 -1500 -1000 -500

0 500 1000 1500 2000Life‐cycleCostSavings($)

Mean Median `

-2000 -1500 -1000 -500

0 500 1000 1500 2000Life‐cycleCostSavings($)

Mean Median

2 3 4 5 6 Efficiency Level 7 8 9 10 11 12 13
Hot

‐ Dry

14 2 3 4 5 6 Efficiency Level 7 8 9 10 11 12 Rest-of-Country 13 14

Figure 8.4.4 Plots of the Distributions of L CC Savings for Split-system Air Conditioners (Blower-Coil) by Region

8-608.4.1.2 Mean PBP Results for Split-syste m Air Conditioners by Region

This section presents PBP results for the efficiency improvement levels specified in the engineering analysis (Chapter 5) and also pr esented in section 8.2.2.2, Standard-Level Manufacturer Price Increases. The results pres ented here are based on annual operating costs calculated from residential and commercial electricity tariffs. Section 8.3 describes the PBP inputs.

Similar to LCC, the analysis provides an estimate of the simple payback period at different ranges of energy prices , sales taxes, and inst allation costs that prevail across the country for each efficiency level and each building (build ing) type. Table 8.4.5 and Table 8.4.6 show the effect on payback period as the level of efficiency changes from the market baseline for CAC products in residential and commerc ial buildings for each region’s energy prices, sales taxes, and installation costs.

Similar to the LCC differences, DOE estimated PBP results as a distribution of values. The means of these distributions are shown in Table 8.4.5 and Ta ble 8.4.6 and the distributions of values for PBP are shown in Figure 8.4.5 and Figure 8.4.6. Mean rebuttable PBP for each region and efficiency level is shown in Table 8. 4.7 and Table 8.4.8. In addition, DOE provides data on the median PBP for each efficiency level in each region in section 8.4.1.3.

Table 8.4.5 Mean Payback Period for Split-System Air Cond itioners (Coil-Only) by Region
Efficiency Level SEER Payback Period by Region years Nation Hot-Humid Hot-Dry Rest of Country
2 13.5 48.6 27.3 47.6 75.9
3 14 53.5 30.2 50.1 80.8
4 14.5 57.0 33.8 53.5 84.1
5 15 61.0 38.2 57.2 87.3
6 15.5 66.0 44.0 61.8 90.8
7 16 71.6 51.6 67.2 94.1
8 16.5 76.8 59.7 72.0 96.5

Table 8.4.6 Mean Payback Period for Split-sys tem Air Conditioners (Blower-Coil) by Region
Efficiency Level SEER Payback Period by Region years Nation Hot-Humid Hot-Dry Rest of Country
2 13.5 48.8 26.3 46.6 75.3
3 14 50.8 27.9 48.0 77.8
4 14.5 52.1 29.0 49.0 79.2
5 15 49.4 26.7 46.3 76.5
6 15.5 49.0 26.3 45.6 76.1
7 16 49.4 26.8 45.8 76.6
8 16.5 51.5 28.6 48.0 78.4
9 17 53.3 30.2 49.7 80.2
10 18 56.9 33.7 53.0 83.5
11 19 60.2 37.3 55.9 86.5
12 20 63.3 41.0 58.6 89.0
13 21 66.3 44.7 61.3 91.2
14 22 69.1 48.4 63.9 93.1

8-61Table 8.4.7 Mean Rebuttable Payback Period for Split-System Air Conditioners (CoilOnly) by Region

Efficiency Level SEER Payback Period by Region

years Nation Hot-Humid Hot-Dry Rest of Country
2 13.5 14.3 8.9 14.5 23.4
3 14 16.5 9.8 15.9 25.6
4 14.5 18.1 10.8 17.3 27.5
5 15 19.9 11.9 19.1 30.2
6 15.5 22.4 13.5 21.4 33.6
7 16 25.7 15.7 24.4 38.0
8 16.5 29.5 18.4 28.0 43.1

Table 8.4.8 Mean Rebuttable Payback Period fo r Split-system Air Co nditioners (BlowerCoil) by Region

Efficiency Level SEER Payback Period by Region

years Nation Hot-Humid Hot-Dry Rest of Country
2 13.5 16.3 10.0 16.2 26.7
3 14 17.6 10.3 16.9 27.6
4 14.5 18.3 10.8 17.5 28.4
5 15 17.3 10.3 16.6 27.1
6 15.5 17.3 10.2 16.5 26.9
7 16 17.6 10.4 16.8 27.4
8 16.5 18.3 10.8 17.5 28.4
9 17 18.9 11.2 18.1 29.3
10 18 20.5 12.2 19.6 31.4
11 19 22.1 13.2 21.2 33.7
12 20 23.7 14.3 22.8 36.0
13 21 25.4 15.5 24.5 38.5
14 22 27.2 16.7 26.2 41.0

8-6240 60 80

40 60 80 120 120

100 100

80

Mean Median National

2 3 4 5 6 7 8
Efficiency Level Mean Median Hot

‐ Humid 2 3 4 5 6 7 8
Efficiency LevelPaybackPeriod(years)PaybackPeriod(years)PaybackPeriod(years)PaybackPeriod(years)

60

40

20 20

0 0

120 120

100 100

Mean Median Hot

‐ Dry

2 3 4 5 6 7 8
Efficiency Level Mean Median `

Rest

‐ of

‐ Country 2 3 4 5 6 7 8
Efficiency Level 80

60

40

20 20

0 0

Figure 8.4.5 Plots of the Distributions of PBP for Split-system Ai r Conditioners (CoilOnly) by Region

0 20 40 60 80 100 120

2 3 4 5 6 7 8 9 10 11 12 13 14
Efficiency LevelPaybackPeriod(years)

Mean Median National 0 20 40 60 80 100 120

2 3 4 5 6 7 8 9 10 11 12 13 14
Efficiency LevelPaybackPeriod(years)

Mean Median Hot

‐ Humid

0 20 40 60 80 100 120

2 3 4 5 6 7 8 9 10 11 12 13 14
Efficiency LevelPaybackPeriod(years)

Mean Median Hot

‐ Dry 0 20 40 60 80 100 120

2 3 4 5 6 7 8 9 10 11 12 13 14
Efficiency LevelPaybackPeriod(years)

Mean Median `

Rest

‐ of

‐ Country
Figure 8.4.6 Plots of the Distributions of PB P for Split-system Air Conditioners (BlowerCoil) by Region

8-638.4.1.3 Detailed Regional Results for Split-system Air Conditioners

This section provides data on the detailed results for split-system CAC life-cycle cost, the components of life-cycle cost, life-cycle cost savi ngs, and payback period. Table 8.4.9 through Table 8.4.16 present these details separately fo r coil-only CAC units and blower-coil CAC units, and for each region by efficiency level

Nation

Table 8.4.9 National LCC and PBP Results for Split-System Air Conditioners (CoilOnly) by Efficiency Level (SEER Value): Nation

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008 $ Average Savings

2008$ Percent of Households with

Median Average Net Cost No Impact Net Benefit
Market Baseline 2,647 418 7,915

- - - - - -

13.5 2,598 418 7,875 4 16 76 8 27.8 48.6
14 2,670 414 7,881 (1) 56 20 24 41.9 53.5
14.5 2,755 410 7,916 (29) 62 16 22 59.4 57.0
15 2,850 408 7,977 (83) 69 10 20 100.0 61.0
15.5 2,965 408 8,084 (180) 75 7 17 100.0 66.0
16 3,112 411 8,255 (341) 81 5 14 100.0 71.6
16.5 3,282 416 8,478 (565) 87 2 11 100.0 76.8 *Values in parentheses denote negative values.

Table 8.4.10 LCC and PBP Results for Split-Sys tem Air Conditioners (Blower-Coil) by Efficiency Level (SEER Value): Nation

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008 $ Average Savings

2008$ Percent of Households with

Median Average Net Cost No Impact Net Benefit
Market Baseline 4,128 418 9,382

- - - - - -

13.5 4,092 420 9,366 2 16 76 8 27.4 48.8
14 4,169 415 9,370 0 55 21 24 33.3 50.8
14.5 4,251 410 9,389 (15) 60 17 23 36.2 52.1
15 4,312 405 9,378 (5) 62 12 26 29.9 49.4
15.5 4,374 400 9,378 (5) 64 9 28 29.0 49.0
16 4,439 396 9,388 (14) 66 7 28 29.6 49.4
16.5 4,506 393 9,411 (36) 70 3 27 34.8 51.5
17 4,575 390 9,444 (68) 71 3 26 39.9 53.3
18 4,721 387 9,537 (159) 74 1 24 56.4 56.9
19 4,878 385 9,664 (285) 77 1 22 84.1 60.2
20 5,045 385 9,823 (443) 80 1 19 100.0 63.3
21 5,226 387 10,015 (634) 83 0 17 100.0 66.3
22 5,419 390 10,239 (859) 84 0 15 100.0 69.1 *Values in parentheses denote negative values.

8-64Hot-Humid Region

Table 8.4.11 LCC and PBP Results for Split-S ystem Air Conditioners (Coil-Only) by Efficiency Level (SEER Va lue): Hot-Humid Region

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 2,400 456 8,157 ­ - - - - -

13.5 2,354 458 8,139 11 12 76 12 9.9 27.3

14 2,423 450 8,107 36 41 20 39 11.6 30.2

14.5 2,503 444 8,103 39 49 16 36 14.3 33.8

15 2,594 439 8,126 19 57 10 33 17.5 38.2

15.5 2,704 436 8,189 (39) 64 7 29 23.1 44.0

16 2,845 435 8,313 (154) 72 5 23 34.5 51.6

16.5 3,006 437 8,484 (324) 80 2 18 63.5 59.7 *Values in parentheses denote negative values.

Table 8.4.12 LCC and PBP Results for Split-Sys tem Air Conditioners (Blower-Coil) by Efficiency Level (SEER Va lue): Hot-Humid Region

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 3,671 457 9,428

- - - - - -

13.5 3,637 459 9,428 11 12 76 12 11.7 26.3

14 3,710 451 9,395 38 41 21 38 12.8 27.9

14.5 3,789 444 9,377 53 46 17 37 11.7 29.0

15 3,847 437 9,336 90 46 12 42 11.5 26.7

15.5 3,906 430 9,306 118 48 9 44 11.7 26.3

16 3,968 424 9,287 137 49 7 44 12.6 26.8

16.5 4,031 419 9,281 142 53 3 44 13.5 28.6

17 4,098 414 9,286 137 55 3 42 15.5 30.2

18 4,237 407 9,324 100 60 1 38 17.9 33.7

19 4,386 401 9,396 28 65 1 35 20.9 37.3

20 4,546 397 9,501 (77) 69 1 31 24.7 41.0

21 4,718 395 9,639 (214) 72 0 27 29.7 44.7

22 4,902 395 9,809 (384) 76 0 24 11.7 48.4 *Values in parentheses denote negati ve values.

8-65Hot-Dry Region

Table 8.4.13 LCC and PBP Results for Split-S ystem Air Conditioners (Coil-Only) by Efficiency Level (SEER Value): Hot-Dry Region

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 3,056 490 9,205 ­ - - - - -

13.5 3,001 491 9,167 8 15 76 9 22.3 47.6

14 3,082 484 9,153 20 52 20 28 28.4 50.1

14.5 3,177 479 9,172 4 58 16 27 42.6 53.5

15 3,283 475 9,224 (40) 64 10 25 64.3 57.2

15.5 3,412 473 9,327 (134) 71 7 22 100.0 61.8

16 3,577 475 9,504 (300) 77 5 18 100.0 67.2

16.5 3,767 479 9,741 (537) 84 2 15 100.0 72.0 *Values in parentheses denote negative values.

Table 8.4.14 LCC and PBP Results for Split-Sys tem Air Conditioners (Blower-Coil) by Efficiency Level (SEER Value): Hot-Dry Region

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 4,782 491 10,967

- - - - - -

13.5 4,742 494 10,964 7 15 76 9 21.5 46.6

14 4,828 486 10,943 24 51 21 28 24.3 48.0

14.5 4,920 479 10,941 27 55 17 28 28.2 49.0

15 4,988 471 10,907 56 57 12 31 24.2 46.3

15.5 5,058 465 10,887 74 59 9 33 23.3 45.6

16 5,130 459 10,879 81 61 7 33 23.8 45.8

16.5 5,205 454 10,887 73 64 3 33 26.9 48.0

17 5,283 450 10,908 54 66 3 31 30.1 49.7

18 5,446 443 10,982 (19) 69 1 29 38.6 53.0

19 5,621 439 11,096 (133) 72 1 27 51.9 55.9

20 5,809 438 11,251 (287) 75 1 25 76.4 58.6

21 6,010 438 11,445 (480) 77 0 23 100.0 61.3

22 6,227 440 11,678 (713) 80 0 20 100.0 63.9 *Values in parentheses denote negative values.

8-66Rest of Country

Table 8.4.15 LCC and PBP Results for Split-S ystem Air Conditioners (Coil-Only) by Efficiency Level (SEER Va lue): Rest of Country

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 2,626 295 6,287 ­ - - - - -

13.5 2,579 294 6,230 (15) 22 76 2 100.0 75.9

14 2,649 295 6,304 (75) 75 20 5 100.0 80.8

14.5 2,730 297 6,403 (157) 80 16 4 100.0 84.1

15 2,822 299 6,524 (265) 87 10 3 100.0 87.3

15.5 2,933 304 6,687 (414) 91 7 2 100.0 90.8

16 3,075 311 6,912 (624) 94 5 1 100.0 94.1

16.5 3,239 320 7,184 (902) 98 2 1 100.0 96.5 *Values in parentheses denote negative values.

Table 8.4.16 LCC and PBP Results for Split-Sys tem Air Conditioners (Blower-Coil) by Efficiency Level (SEER Va lue): Rest of Country

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 4,125 293 7,625

- - - - - -

13.5 4,090 292 7,731 (16) 22 76 2 100.0 75.3

14 4,164 292 7,813 (73) 73 21 6 100.0 77.8

14.5 4,244 293 7,892 (140) 78 17 5 100.0 79.2

15 4,302 292 7,939 (183) 81 12 7 100.0 76.5

15.5 4,362 292 7,990 (234) 84 9 7 100.0 76.1

16 4,425 293 8,048 (291) 86 7 7 100.0 76.6

16.5 4,489 293 8,120 (361) 90 3 7 100.0 78.4

17 4,556 295 8,197 (437) 91 3 6 100.0 80.2

18 4,697 298 8,373 (611) 94 1 4 100.0 83.5

19 4,848 303 8,572 (810) 96 1 3 100.0 86.5

20 5,010 308 8,799 (1,036) 97 1 3 100.0 89.0

21 5,183 315 9,053 (1,288) 98 0 2 100.0 91.2

22 5,370 323 9,333 (1,568) 98 0 1 100.0 93.1 *Values in parentheses denote negative values.

8-678.4.2 Split-System Heat Pumps

This section presents LCC results for the efficiency improvement levels specified in the engineering analysis for split-system CHPs (Chapter 5) and also presented in Section 8.2.2.2, Standard-Level Manufacturer Price Increases. The results presented here are based on annual operating costs calculated from residential and commercial electricity tariffs, repair costs, and maintenance costs developed for e ach individual observation. Secti on 8.2 presents the electricity price inputs as well as all other LCC inputs.

As stated earlier, the Monte Carlo method of analysis relying on Crystal Ball (i.e., random sampling from distributions) was used to conduct the LCC analysis. The following results presented here are base d on 10,000 samples per Monte Carlo run. DOE’s first step in developing LCC results was to establish the mark et baseline LCC for each of the product classes. The market baseline efficiency level for the preliminary analysis is the market-weighted efficiency level in each region. Figure 8.4.7 s hows the market baseline distribution of life-cycle costs for split-system heat pumps for each region.

To provide perspective on the LCC and PBP results, Table 8.4.17 presents the average values for market baseline installed cost of split-system heat pumps, their average energy consumption at market baseline and the percentage changes in these values at the efficiency improvement levels.

Table 8.4.17 Mean Market Baseline Installed Co sts, Total Annual Energy Consumption, and Percentage Change for Spli t-System Heat Pumps by Region by Efficiency Level (SEER Value)

Efficiency Level (SEER) Nation Hot-Humid Hot-Dry Rest of Country
Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh
Market Baseline 3,682 4,954 3,387 5,236 4,239 4,828 3,634 4,719

Percentage Change from Market Baseline
13.5 (2.0) 2.5 (2.1) 2.6 (2.0) 2.7 (2.0) 2.2
14 0.5 (0.4) 0.5 (0.5) 0.5 (0.5) 0.5 (0.3)
14.5 2.4 (3.3) 2.5 (3.5) 2.3 (3.6) 2.4 (2.7)
15 4.3 (5.9) 4.4 (6.3) 4.2 (6.5) 4.2 (5.0)
15.5 6.3 (8.5) 6.6 (9.0) 6.1 (9.2) 6.2 (7.1)
16 8.9 (10.8) 9.3 (11.5) 8.7 (11.8) 8.7 (9.2)
17 13.4 (15.8) 13.9 (16.5) 13.0 (16.8) 13.1 (14.1)
18 18.2 (20.2) 18.8 (20.9) 17.7 (21.2) 17.8 (18.5)
19 23.3 (24.2) 24.2 (24.9) 22.6 (25.2) 22.8 (22.4)
19.5 26.1 (25.9) 27.0 (26.6) 25.3 (26.9) 25.5 (24.0) *Values in parentheses denote negative values.

8-68Nation Hot-Humid

Hot-Dry Rest of Country
Figure 8.4.7 Market Baseline Distributions of LCC for Split-System Heat Pumps by Region

8.4.2.1 Mean LCC Savings for Split-Sys tem Heat Pumps by Region

Because the values of most inputs are uncertain in this analysis, DOE represents them as a distribution of values rather than a single point-value. Thus, DOE also represents the LCC results as a distribution of values. In Table 8. 4.18 DOE presents average values for LCC savings to show how these savings vary with efficiency for the split-system CH P product classes and by region. In contrast to the situation with sp lit-system CAC units, LCC savings for split-system CHPs are positive at the national level standards and in both hot regions up to the max tech level (SEER 19.5). Although SEER 14.5 appears to have positive LCC savings, this is probably a statistical anomaly. It is unlikely that any standard level above SEER13 produces LCC savings in the colder part of the country.

Table 8.4.18 Mean LCC Savings for Split-System Heat Pumps by Region by Efficiency Level (SEER Value and HSPF Value)

Efficiency Level SEER HSPF LCC Savings by Region 2008$

Nation HotHumid Hot-Dry Rest of Country
2 13.5 7.85 8 11 17 0
3 14 8 40 51 81 (10)
4 14.5 8.15 95 113 174 (1)
5 15 8.3 150 176 269 8

8-696 15.5 8.45 194 228 350 3
7 16 8.6 200 245 388 (36)
8 17 9.1 262 312 509 (44)
9 18 9.6 275 333 570 (94)
10 19 10.1 241 311 574 (185)
11 19.5 10.3 196 276 544 (259) *Values in parentheses denote negative values

.
It is worth reiterating that the results show n in Table 8.4.18 are mean values and do not show the distributions of savings. Thus, although observations can be made as to how the various inputs impact life-cycle cost and, in turn, how the resulting life-cycle costs change with efficiency, conclusions should only be drawn from the distribution of life-cycle cost results that are presented in Figure 8.4.8. Section 8.4. 2.3 provides information on the percentages of consumers in each region at each efficiency level that would experience LCC savings benefits, LCC cost increases, and no impact from the standard.

-1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 9 10 11 Efficiency LevelLife-cycle Cost Savings($)

Mean Median `

Hot-Humid -1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 9 10 11 Efficiency LevelLife-cycle Cost Savings($)

Mean Median `

National

-2000 -1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 9 10 11 Efficiency LevelLife-cycle Cost Savings($)

Mean Median `

Hot-Dry -2000 -1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 9 10 11 Efficiency LevelLife-cycle Cost Savings($)

Mean Median

Rest-of-Country Figure 8.4.8 Plots of the Distributions of L CC Savings for Split-system Heat Pumps by Region

8.4.2.2 Mean PBP Results for Split-Sys tem Heat Pumps by Region

This section presents PBP results for the efficiency improvement levels specified in the engineering analysis (Chapter 5) and also pr esented in section 8.2.2.2, Standard-Level Manufacturer Price Increases. The results pres ented here are based on annual operating costs calculated from residential and commercial electricity tariffs. Section 8.3 describes the PBP inputs.

Similar to LCC, the analysis provides an estimate of the simple payback period at different ranges of energy prices , sales taxes, and inst allation costs that prevail across the country

8-70for each efficiency level and each building ( building) type. Table 8.4.19 shows the effect on payback period as the level of efficiency changes from the market baseline for split-system CHP products in residential and commerc ial buildings for each region’s energy prices, sales taxes, and installation costs.

Similar to the LCC differences, DOE depicted PBP results as a distribution of values. The means of these distributions are shown in Table 8.4.19 and th e distributions of values for PBP are shown in Figure 8.4.9. Mean rebuttable PBP for each region and efficiency level is shown in Table 8.4.20. In addition, DOE provides data on the median PBP for each efficiency level in each region in section 8.4.2.3.

Table 8.4.19 Mean Payback Period for Split-S ystem Heat Pumps by Region (Years)

Efficiency Level SEER HSPF Payback Period by Region years

Nation HotHumid Hot-Dry Rest of Country
2 13.5 7.85 22.1 16.1 16.7 28.7
3 14 8 24.2 17.8 18.2 34.5
4 14.5 8.15 20.1 13.5 15.8 29.1
5 15 8.3 18.4 11.8 14.0 27.1
6 15.5 8.45 18.6 11.9 13.8 27.8
7 16 8.6 21.1 13.8 15.4 31.7
8 17 9.1 22.0 15.5 17.4 30.9
9 18 9.6 23.8 17.6 18.9 32.5
10 19 10.1 26.0 19.8 20.6 35.1
11 19.5 10.3 27.5 21.2 21.7 37.2 *Values in parentheses denote negative values.

Table 8.4.20 Mean Rebuttable Payback Period fo r Split-System Heat Pumps by Region (Years)

Efficiency Level SEER HSPF Payback Period by Region years

Nation HotHumid Hot-Dry Rest of Country
2 13.5 7.85 9.5 7.7 8.3 11.3
3 14 8 10.2 8.5 9.0 12.6
4 14.5 8.15 7.9 6.8 6.6 10.2
5 15 8.3 7.5 6.4 6.2 9.6
6 15.5 8.45 7.6 6.5 6.2 9.8
7 16 8.6 8.3 7.2 6.8 10.7
8 17 9.1 8.6 7.6 7.3 10.6
9 18 9.6 9.2 8.2 7.9 11.1
10 19 10.1 9.9 8.8 8.6 11.9
11 19.5 10.3 10.4 9.3 9.1 12.4 *Values in parentheses denote negative values.

8-710 20 40 60 80 100 120

2 3 4 5 6 7 8 9 10 11
Efficiency LevelPayback Period (years)

Mean Median National 0 20 40 60 80 100 120

2 3 4 5 6 7 8 9 10 11
Efficiency LevelPayback Period (years)

Mean Median Hot-Humid

0 20 40 60 80 100 120

2 3 4 5 6 7 8 9 10 11
Efficiency LevelPayback Period (years)

Mean Median Hot-Dry 0 20 40 60 80 100 120

2 3 4 5 6 7 8 9 10 11
Efficiency LevelPayback Period (years)

Mean Median `

Rest-of-Country
Figure 8.4.9 Plots of the Distributions of PBP for Split-System Heat Pumps by Region

8.4.2.3 Detailed Regional Results fo r Split-System Heat Pumps

This section provides data on the detailed results for split-system CHP life-cycle cost, the components of life-cycle cost, life-cycle cost sa vings, and payback period. These details are shown separately by region and efficiency level. Table 8.4.21 through Table 8.4.24 present these details for each region by efficiency level.

Nation

Table 8.4.21 LCC and PBP Results for Split-Sys tem Heat Pumps by Efficiency Level (SEER Value): Nation

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 3,682 705 11,550

- - - - - -

13.5 3,607 716 11,601 8 6 87 7 8.0 22.1

14 3,700 703 11,551 40 32 35 33 9.0 24.2

14.5 3,771 690 11,477 95 33 25 42 7.8 20.1

15 3,840 679 11,409 150 36 16 48 7.6 18.4

15.5 3,915 668 11,361 194 39 11 50 7.9 18.6

16 4,011 659 11,354 200 46 7 47 9.1 21.1

17 4,176 639 11,289 262 48 4 48 9.3 22.0

8-7218 4,352 623 11,275 275 52 2 46 10.1 23.8

19 4,540 610 11,309 241 56 1 43 11.2 26.0

19.5 4,642 605 11,354 196 59 0 41 12.0 27.5 *Values in parentheses denote negative values.

Hot-Humid Region

Table 8.4.22 LCC and PBP Results for Split-Sys tem Heat Pumps by Efficiency Level (SEER Value): Hot-Humid Region

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 3,387 647 10,636

- - - - - -

13.5 3,316 658 10,688 11 5 87 8 6.4 16.1

14 3,404 645 10,627 51 27 35 38 7.4 17.8

14.5 3,472 632 10,544 113 28 25 47 6.5 13.5

15 3,538 620 10,469 176 30 16 54 6.3 11.8

15.5 3,609 609 10,413 228 33 11 57 6.6 11.9

16 3,701 599 10,394 245 39 7 54 7.5 13.8

17 3,858 580 10,325 312 42 4 54 7.8 15.5

18 4,026 563 10,303 333 46 2 52 8.5 17.6

19 4,206 550 10,325 311 51 1 49 9.4 19.8

19.5 4,303 545 10,360 276 54 0 46 10.0 21.2 *Values in parentheses denote negative values

.
Hot-Dry Region

Table 8.4.23 LCC and PBP Results for Split-Sys tem Heat Pumps by Efficiency Level (SEER Value): Hot-Dry Region

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 4,239 842 13,642

- - - - - -

13.5 4,155 857 13,733 17 4 87 9 5.2 16.7

14 4,259 839 13,632 81 23 35 42 6.2 18.2

14.5 4,339 822 13,507 174 24 25 51 5.5 15.8

15 4,416 805 13,393 269 26 16 58 5.4 14.0

15.5 4,500 790 13,303 350 29 11 61 5.6 13.8

16 4,607 777 13,261 388 34 7 59 6.4 15.4

8-7317 4,791 750 13,135 509 37 4 59 6.7 17.4

18 4,988 727 13,071 570 42 2 56 7.4 18.9

19 5,199 709 13,067 574 46 1 53 8.3 20.6

19.5 5,313 702 13,097 544 49 0 51 8.8 21.7 *Values in parentheses denote negative values.

Rest of Country

Table 8.4.24 LCC and PBP Results for Split-Sys tem Heat Pumps by Efficiency Level (SEER Value): Rest of Country

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 3,634 618 10,520

- - - - - -

13.5 3,561 624 10,514 0 8 87 5 12.0 28.7

14 3,651 618 10,530 (10) 44 35 21 15.2 34.5

14.5 3,719 611 10,517 (1) 46 25 29 12.7 29.1

15 3,786 604 10,507 8 50 16 34 12.0 27.1

15.5 3,858 599 10,512 3 55 11 34 12.6 27.8

16 3,951 594 10,554 (36) 63 7 30 15.0 31.7

17 4,110 582 10,562 (44) 63 4 33 13.9 30.9

18 4,279 572 10,613 (94) 66 2 32 14.7 32.5

19 4,461 564 10,704 (185) 71 1 29 16.3 35.1

19.5 4,560 562 10,778 (259) 74 0 26 17.8 37.2 *Values in parentheses denote negative values.

8.4.3 Single Package Air Conditioners

This section presents LCC results for the efficiency improvement levels specified in the engineering analysis for single package CACs (Cha pter 5) and also presented in Section 8.2.2.2, Standard-Level Manufacturer Price Increases. The results presented here are based on annual operating costs calculated from residential and commercial electricity tariffs, repair costs, and maintenance costs developed for e ach individual observation. Secti on 8.2 presents the electricity price inputs as well as all other LCC inputs.

As stated earlier, the Monte Carlo method of analysis relying on Crystal Ball (i.e., random sampling from distributions) was used to conduct the LCC analysis. The following results presented here are base d on 10,000 samples per Monte Carlo run. DOE’s first step in developing LCC results was to establish the mark et baseline LCC for each of the product classes. The market baseline efficiency level for the preliminary analysis is the market-weighted efficiency level. Figure 8.4.10 shows the market baseline distribution of LCC for single package CAC products in each region.

8-74To provide perspective on the LCC and PBP results, Table 8.4.25 presents the average values for market baseline installed cost of single package air conditioners, their average energy consumption at market baseline and the percentage changes in these values at the efficiency improvement levels.

Table 8.4.25 Mean Market Baseline Installed Co sts, Total Annual Energy Consumption, and Percentage Change for Sing le Package Air Conditioners by Region by Efficiency Level (SEER Value)

Efficiency Level (SEER) Nation Hot-Humid Hot-Dry Rest of Country
Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh
Market Baseline 2,807 2,348 2,550 3,559 3,241 2,144 2,784 1,348

Percentage Change from Market Baseline
13.5 3.1 (2.4) 3.3 (2.4) 3.0 (2.4) 3.0 (2.3)
14 6.2 (5.7) 6.5 (5.8) 6.0 (5.7) 6.0 (5.5)
14.5 10.7 (8.9) 11.3 (9.0) 10.4 (8.9) 10.4 (8.7)
15 14.4 (11.9) 15.1 (12.0) 14.0 (11.8) 14.0 (11.7)
15.5 19.1 (14.7) 20.0 (14.8) 18.5 (14.6) 18.5 (14.4)
16 24.5 (17.3) 25.8 (17.4) 23.8 (17.3) 23.9 (17.1)
16.6 32.3 (20.1) 33.9 (20.3) 31.3 (20.0) 31.4 (19.8) *Values in parentheses denote negative values.

Nation Hot-Humid

Hot-Dry Rest of Country

8-75Figure 8.4.10 Market Baseline Distributions of LCC for Single Pack age Air Conditioners by Region

8.4.3.1 Mean LCC Savings for Single Package Air Conditioners by Region

Because the values of most inputs are uncertain in this analysis, DOE represents them as a distribution of values rather than a single point-value. Thus, DOE also represents the LCC results as a distribution of values. In Table 8. 4.26 DOE presents average values for LCC savings to show how these savings vary with efficien cy for each of the single package CAC product classes and by region. The LCC savings for single package CACs are negative at the national level in all regions for a standard at any level beyond SEER 13.

Table 8.4.26 Mean LCC Savings for Single Pack age Air Conditioners by Region by Efficiency Level (SEER Value)
Efficiency Level SEER LCC Savings by Region 2008$
Nation Hot-Humid Hot-Dry Rest of country
2 13.5 (68) (29) (57) (123)
3 14 (95) (17) (64) (214)
4 14.5 (195) (71) (155) (375)
5 15 (266) (101) (212) (504)
6 15.5 (391) (180) (332) (683)
7 16 (564) (303) (507) (907)
8 16.6 (842) (517) (799) (1,243) *Values in parentheses denote negative values.

The results shown in Table 8.4.26 are mean va lues and do not show the distributions of savings. Thus, although observations can be made as to how the various inputs impact life-cycle cost and, in turn, how the resulting life-cycle co sts change with effici ency, conclusions should only be drawn from the distribution of life-cycle cost results that are presented in Figure 8.4.11. Section 8.4.3.3 provides information on the percen tages of consumers in each region at each efficiency level that would experience LCC savings benefits, LCC cost increases, and no impact from the standard.

8-76-1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 Efficiency LevelLife-cycle Cost Savings($)

Mean Median `

Hot-Humid -2000 -1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8
Efficiency LevelLife-cycle Cost Savings($)

Mean Median

National

-2000 -1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 Efficiency LevelLife-cycle Cost Savings($)

Mean Median `

Hot-Dry -2000 -1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 Efficiency LevelLife-cycle Cost Savings($)

Mean Median

Rest-of-Country Figure 8.4.11 Plots of the Distributions of LCC Savings for Single Package Air Conditioners by Region

8.4.3.2 Mean PBP Results for Single Package Air Conditioners by Region

This section presents PBP results for the efficiency improvement levels specified in the engineering analysis (Chapter 5) and also pr esented in section 8.2.2.2, Standard-Level Manufacturer Price Increases. The results pres ented here are based on annual operating costs calculated from residential and commercial electricity tariffs. Section 8.3 describes the PBP inputs.

Similar to LCC, the analysis provides an estimate of the simple payback period at different ranges of energy prices , sales taxes, and inst allation costs that prevail across the country for each efficiency level and each building ( building) type. Table 8.4.27 shows the effect on payback period as the level of efficiency change s from the market baseline for CAC products in residential and commercial buildings for each region’s energy prices, sales taxes, and installation

costs.

Similar to the LCC differences, DOE estimated PBP results as a distribution of values. The means of these distributions are shown in Table 8.4.27 and th e distributions of values for PBP are shown in Figure 8.4.12. Mean rebuttabl e PBP is shown in Table 8.4.28. In addition, DOE provides data on the median PBP for each efficiency level in each region in section 8.4.3.3.

Table 8.4.27 Mean Payback Period for Single Package Air Conditioners by Region
Efficiency Payback Period by Region years Level SEER Nation Hot-Humid Hot-Dry Rest of Country
2 13.5 70.6 49.2 65.0 93.7
3 14 64.3 41.7 59.0 89.6

8-7740 60 80 4 14.5 68.6 46.6 63.1 92.6
5 15 68.9 46.8 63.4 92.7
6 15.5 71.5 50.1 65.9 94.0
7 16 74.6 54.6 68.8 95.5
8 16.6 78.6 61.1 72.6 97.2

Table 8.4.28 Mean Rebuttable Payback Period fo r Single Package Air Conditioners by Region Efficiency Payback Period by Region years
Level SEER Nation Hot-Humid Hot-Dry Rest of Country
2 13.5 26.6 16.2 24.9 39.4
3 14 23.0 13.7 21.4 34.4
4 14.5 25.1 15.1 23.3 37.3
5 15 25.2 15.2 23.3 37.4
6 15.5 26.7 16.2 24.7 39.5
7 16 28.7 17.6 26.4 42.2
8 16.6 31.8 19.9 29.2 46.4

120 120

100 100Payback Period (years)

Mean Median National 2 3 4 5 6 7 8
Efficiency LevelPayback Period (years)

Mean Median Hot-Humid 2 3 4 5 6 7 8
Efficiency Level 80

60

40

20 20

0 0

0 20 40 60 80 100 120

2 3 4 5 6 7 8
Efficiency LevelPayback Period (years)

Mean Median Hot-Dry 0 20 40 60 80 100 120

2 3 4 5 6 7 8
Efficiency LevelPayback Period (years)

Mean Median `

Rest-of-Country
Figure 8.4.12 Plots of the Distributions of PB P for Single Package Air Conditioners by Region

8.4.3.3 Detailed Regional Results for Si ngle Package Air Conditioners

This section provides data on the detailed results for single package CAC life-cycle cost, the components of life-cycle cost, life-cycle cost savings, and payback period. through Table 8.4.32 present these details separately for single package CAC units for each region by efficiency level.

8-78Nation

Table 8.4.29 LCC and PBP Results for Single Package Air Condition ers by Efficiency Level (SEER Value): Nation

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008 $ Average

Operating Cost 2008$ Average LCC 2008$ Average Savings

2008 $ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 2,807 419 8,087

- - - - - -

13.5 2,894 418 8,148 (68) 64 25 11 100.0 70.6

14 2,982 414 8,178 (95) 77 5 18 100.0 64.3

14.5 3,108 412 8,281 (195) 82 3 15 100.0 68.6

15 3,212 410 8,353 (266) 83 1 16 100.0 68.9

15.5 3,342 411 8,478 (391) 86 0 14 100.0 71.5

16 3,496 413 8,651 (564) 88 0 12 100.0 74.6

16.6 3,714 418 8,929 (842) 91 0 9 100.0 78.6 *Values in parentheses denote negative values.

Hot-Humid Region

Table 8.4.30 LCC and PBP Results for Single Package Air Condition ers by Efficiency Level (SEER Value): Hot-Humid Region

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008$ Average Operating Cost 2008$ Average LCC 2008$ Average Savings

2008$ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 2,550 468 8,440

- - - - - -

13.5 2,633 464 8,468 (29) 56 25 19 30.0 49.2

14 2,717 457 8,455 (17) 63 5 32 20.4 41.7

14.5 2,837 452 8,511 (71) 71 3 26 26.5 46.6

15 2,936 447 8,540 (101) 72 1 27 27.1 46.8

15.5 3,061 444 8,620 (180) 76 0 24 32.6 50.1

16 3,207 443 8,743 (303) 80 0 20 42.2 54.6

16.6 3,415 444 8,957 (517) 85 0 15 69.5 61.1 *Values in parentheses denote negative values.

Hot-Dry Region

Table 8.4.31 LCC and PBP Results for Single Package Air Condition ers by Efficiency Level (SEER Value): Hot-Dry Region
Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years

8-79Average Installed Cost 2008$ Average Operating Cost 2008$ Average LCC 2008$ Average Savings

2008$ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 3,241 497 9,507

- - - - - -

13.5 3,339 494 9,562 (57) 60 25 15 100.0 65.0

14 3,437 488 9,568 (64) 71 5 24 85.9 59.0

14.5 3,578 485 9,661 (155) 76 3 21 100.0 63.1

15 3,694 481 9,719 (212) 78 1 21 100.0 63.4

15.5 3,840 479 9,839 (332) 81 0 19 100.0 65.9

16 4,012 480 10,014 (507) 84 0 16 100.0 68.8

16.6 4,256 485 10,305 (799) 87 0 13 100.0 72.6 *Values in parentheses denote negative values.

Rest of Country

Table 8.4.32 LCC and PBP Results for Single Package Air Condition ers by Efficiency Level (SEER Value): Rest of Country

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008$ Average Operating Cost 2008$ Average LCC 2008$ Average Savings

2008$ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 2,784 294 6,424

- - - - - -

13.5 2,868 296 6,535 (123) 74 25 1 100.0 93.7

14 2,952 298 6,631 (214) 93 5 2 100.0 89.6

14.5 3,074 302 6,798 (375) 95 3 2 100.0 92.6

15 3,174 304 6,927 (504) 97 1 2 100.0 92.7

15.5 3,300 309 7,107 (683) 99 0 1 100.0 94.0

16 3,448 316 7,331 (907) 99 0 1 100.0 95.5

16.6 3,658 326 7,667 (1,243) 99 0 1 100.0 97.2 *Values in parentheses denote negative values.

8.4.4 Single Package Heat Pumps

This section presents LCC results for the efficiency improvement levels specified in the engineering analysis for single package CHPs (Cha pter 5) and also presented in Section 8.2.2.2, Standard-Level Manufacturer Price Increases. The results presented here are based on annual operating costs calculated from residential and commercial electricity tariffs, repair costs, and maintenance costs developed for e ach individual observation. Secti on 8.2 presents the electricity price inputs as well as all other LCC inputs.

As stated earlier, the Monte Carlo method of analysis relying on Crystal Ball (i.e., random sampling from distributions) was used to conduct the LCC analysis. The following results presented here are base d on 10,000 samples per Monte Carlo run. DOE’s first step in

8-80developing LCC results was to establish the mark et baseline LCC for each of the product classes. The market baseline efficiency level for the preliminary analysis is the market-weighted efficiency level in each region. Figure 8.4.13 sh ows the market baseline distribution of life-cycle costs for single package heat pumps for each region.

To provide perspective on the LCC and PBP results, Table 8.4.33 presents the average values for market baseline installed cost of single-package heat pumps, their average energy consumption at market baseline and the percentage changes in these values at the efficiency improvement levels.

Table 8.4.33 Mean Market Baseline Installed Co sts, Total Annual Energy Consumption, and Percentage Change for Single Package He at Pumps by Region by Efficiency Level (SEER Value)

Efficiency Level (SEER) Nation Hot-Humid Hot-Dry Rest of Country
Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh Installed Cost 2008$ Total Energy kWh
Market Baseline 3,293 5,070 3,064 5,436 3,785 5,013 3,237 4,830

Percentage Change from Market Baseline
13.5 0.3 (0.8) 0.3 (0.8) 0.3 (0.9) 0.3 (0.7)
14 3.6 (3.7) 3.7 (3.9) 3.5 (4.0) 3.5 (3.1)
14.5 8.3 (5.8) 8.5 (6.4) 8.0 (6.6) 8.1 (4.4)
15 12.4 (7.8) 12.7 (8.7) 12.1 (9.1) 12.2 (5.6)
15.5 17.2 (11.6) 17.6 (12.2) 16.8 (12.5) 16.9 (10.1)
16 22.9 (15.1) 23.5 (15.4) 22.3 (15.6) 22.5 (14.1)
16.4 28.6 (16.4) 29.3 (16.9) 27.8 (17.2) 28.1 (14.9) *Values in parentheses denote negative values.

8-81Nation Hot-Humid

Hot-Dry Rest of Country

Figure 8.4.13 Market Baseline Distributions of LCC for Single Package Heat Pumps by Region

8.4.4.1 Mean LCC Savings for Single Pa ckage Heat Pumps by Region

Because the values of most inputs are uncertain in this analysis, DOE represents them as a distribution of values rather than a single point-value. Thus, DOE also represents the LCC results as a distribution of values. In Table 8. 4.34 DOE presents average values for LCC savings to show how these savings vary with efficiency for the single package CHP product classes and by region.

Table 8.4.34 Mean LCC Savings for Single Package Heat Pumps by Region by Efficiency Level (SEER Value)

Efficiency Level SEER HSPF LCC Savings by Region 2008$

Nation HotHumid Hot-Dry Rest of Country
2 13.5 7.85 27 34 54 (3)
3 14 8 31 54 96 (44)
4 14.5 8 (65) (10) 30 (199)
5 15 8 (146) (62) (21) (340)
6 15.5 8.5 (169) (88) (21) (379)
7 16 9 (253) (168) (91) (480)
8 16.4 9 (455) (336) (291) (720) *Values in parentheses denote negative values.

8-82The results shown in Table 8.4.34 are mean va lues and do not show the distributions of savings. Thus, although observations can be made as to how the various inputs impact life-cycle cost and, in turn, how the resulting life-cycle co sts change with effici ency, conclusions should only be drawn from the distribution of life-cycle cost results that are presented in Figure 8.4.14. Section 8.4.4.3 provides information on the percen tages of consumers in each region at each efficiency level that would experience LCC savings benefits, LCC cost increases, and no impact from the standard.

-1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 Efficiency LevelLife-cycle Cost Savings($)

Mean Median `

Hot-Humid -1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8
Efficiency LevelLife-cycle Cost Savings($)

Mean Median

National

-2000 -1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 Efficiency LevelLife-cycle Cost Savings($)

Mean Median `

Hot-Dry -2000 -1500 -1000 -500

0 500 1000 1500 2000

2 3 4 5 6 7 8 Efficiency LevelLife-cycle Cost Savings($)

Mean Median

Rest-of-Country Figure 8.4.14 Plots of the Distributions of LCC Savings for Single Package Heat Pumps by Region

8.4.4.2 Mean PBP Results for Single Pa ckage Heat Pumps by Region

This section presents PBP results for the efficiency improvement levels specified in the engineering analysis (Chapter 5) and also pr esented in section 8.2.2.2, Standard-Level Manufacturer Price Increases. The results pres ented here are based on annual operating costs calculated from residential and commercial electricity tariffs. Section 8.3 describes the PBP inputs.

Similar to LCC, the analysis provides an estimate of the simple payback period at different ranges of energy prices , sales taxes, and inst allation costs that prevail across the country for each efficiency level and each building ( building) type. Table 8.4.35 shows the effect on payback period as the level of efficiency changes from the market baseline for single package CHP products in residential a nd commercial buildings for each region’s energy prices, sales taxes, and installation costs.

Similar to the LCC differences, DOE depicted PBP results as a distribution of values. The means of these distributions are shown in Table 8.4.35 and th e distributions of values for

8-8340 60 80 PBP are shown in Figure 8.4.15. Mean rebuttabl e PBP for each region and efficiency level is shown in Table 8.4.36. In addition, DOE provides data on the median PBP for each efficiency level in each region in section 8.4.4.3.

Table 8.4.35 Mean Payback Period for Single Package Heat Pumps by Region (Years)

Efficiency Level SEER HSPF Payback Period by Region years

Nation HotHumid Hot-Dry Rest of Country
2 13.5 7.85 21.5 15.5 16.3 30.0
3 14 8 27.6 19.9 19.8 39.0
4 14.5 8 42.2 30.3 27.9 64.1
5 15 8 46.5 33.3 30.2 72.3
6 15.5 8.5 39.8 30.5 29.2 56.1
7 16 9 39.8 32.0 31.0 53.0
8 16.4 9 47.0 38.0 36.0 63.6

Table 8.4.36 Mean Rebuttable Payback Period for Single Package Heat Pumps by Region (Years)

Efficiency Level SEER HSPF Payback Period by Region years

Nation HotHumid Hot-Dry Rest of Country
2 13.5 7.85 8.8 7.3 7.8 11.1
3 14 8 11.1 9.0 9.7 13.6
4 14.5 8 15.0 11.4 11.4 21.1
5 15 8 16.4 12.2 12.1 24.0
6 15.5 8.5 13.1 11.3 10.8 16.6
7 16 9 13.0 11.7 11.1 15.7
8 16.4 9 15.2 13.4 12.8 18.7

120 120

100 100

2 3 4 5 6 7 8
Efficiency Level 2 3 4 5 6 7 8
Efficiency LevelPayback Period (years)Payback Period (years)Payback Period (years)Payback Period (years)

80

60

40

20 20

0 0

Mean Mean Median National Median Hot-Humid

120 120

100 100

2 3 4 5 6 7 8
Efficiency Level `

2 3 4 5 6 7 8
Efficiency Level 80

60

40

20 20

0 0

Mean Mean Median Hot-Dry Median Rest-of-Country
Figure 8.4.15 Plots of the Distributions of PBP for Single Package Heat Pumps by Region

8-84 40 60 808.4.4.3 Detailed Regional Results for Single Package Heat Pumps

This section provides data on the detailed results for single package CHP life-cycle cost, the components of life-cycle cost, life-cycle cost savings, and payback period. These details are shown separately by region and efficiency level. Table 8.4.37 through Table 8.4.40 present these details for each region by efficiency level.

Nation

Table 8.4.37 LCC and PBP Results for Single Pa ckage Heat Pumps by Efficiency Level (SEER Value): Nation

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years Average Installed Cost 2008$ Average Operating Cost 2008$ Average LCC 2008$ Average Savings

2008$ Percent of Households with

Median Average Net Cost No Impact Net Benefit
Market Baseline 3,293 715 10,440

- - - - - -

13.5 3,303 711 10,408 27 22 50 28 7.5 21.5
14 3,411 700 10,401 31 45 18 37 10.5 27.6
14.5 3,566 695 10,503 (65) 67 7 26 20.2 42.2
15 3,702 690 10,586 (146) 74 2 24 24.9 46.5
15.5 3,861 677 10,609 (169) 74 0 26 19.9 39.8
16 4,048 667 10,693 (253) 76 0 24 20.5 39.8
16.4 4,236 669 10,895 (455) 82 0 18 28.1 47.0 *Values in parentheses denote negative values.

Hot-Humid Region

Table 8.4.38 LCC and PBP Results for Single Pa ckage Heat Pumps by Efficiency Level (SEER Value): Hot-Humid Region

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008$ Average Operating Cost 2008$ Average LCC 2008$ Average Savings

2008$ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 3,064 666 9,746

- - - - - -

13.5 3,073 662 9,710 34 18 50 32 6.1 15.5

14 3,176 650 9,687 54 38 18 44 8.2 19.9

14.5 3,324 642 9,756 (10) 60 7 33 13.4 30.3

15 3,454 635 9,809 (62) 67 2 31 15.6 33.3

15.5 3,605 623 9,835 (88) 68 0 32 14.3 30.5

16 3,784 614 9,914 (168) 71 0 29 15.4 32.0

16.4 3,963 613 10,083 (336) 78 0 22 19.4 38.0 *Values in parentheses denote negative values.

8-85Hot-Dry Region

Table 8.4.39 LCC and PBP Results for Single Pa ckage Heat Pumps by Efficiency Level (SEER Value): Hot-Dry Region

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008$ Average Operating Cost 2008$ Average LCC 2008$ Average Savings

2008$ Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 3,785 865 12,451

- - - - - -

13.5 3,796 859 12,400 54 15 50 35 5.2 16.3

14 3,917 842 12,349 96 33 18 49 7.1 19.8

14.5 4,090 832 12,419 30 55 7 38 11.4 27.9

15 4,242 823 12,471 (21) 62 2 36 13.0 30.2

15.5 4,420 806 12,472 (21) 64 0 36 12.6 29.2

16 4,630 793 12,542 (91) 67 0 33 13.8 31.0

16.4 4,840 792 12,741 (291) 75 0 25 17.3 36.0 *Values in parentheses denote negative values.

Rest of Country

Table 8.4.40 LCC and PBP Results for Single Pa ckage Heat Pumps by Efficiency Level (SEER Value): Rest of Country

Efficiency Level Life-Cycle Cost Life-Cycle Cost Savings Payback Period

years
Average Installed Cost 2008$ Average Operating Cost 2008$ Average LCC 2008$ Average Savings Percent of Households with

Median Average Net Cost No Impact Net Benefit

Market Baseline 3,237 626 9,504

- - - - - -

13.5 3,246 624 9,484 (3) 31 50 19 12.2 30.0

14 3,350 619 9,533 (44) 62 18 20 18.5 39.0

14.5 3,499 621 9,700 (199) 86 7 7 87.1 64.1

15 3,631 622 9,844 (340) 94 2 4 100.0 72.3

15.5 3,784 612 9,883 (379) 91 0 9 43.8 56.1

16 3,965 604 9,984 (480) 90 0 10 36.4 53.0

16.4 4,146 611 10,224 (720) 95 0 5 70.0 63.6 *Values in parentheses denote negative values.

8.5 OFF-MODE AND STANDBY POWER CONSUMPTION

Residential air conditioners and heat pumps use a small amount of electricity during their “off mode” (neither cooling nor heating), especially during periods of mild weather in the spring and fall seasons. The principal sources of th is off-mode power consumption are crank case heaters in the outside unit (approximately 60 watts) and transformers in the inside unit. For this

8-86analysis, DOE separately calculated the impact on LCC of thermostatic controls on crank case heaters and replacement of transformers with converter units. This analysis was conducted only at the national level. The impacts are shown in Ta ble 8.5.1. For the analysis in Table 8.5.1, the baseline unit was assumed to have no temperature control, so that the crank case heater is “on” whenever the CAC is in the off mode. The other four levels are as follows:

Level 1 – Temperature controls so that the CCH is only activated below 65°F.

Level 2 – Temperature controls so that the CCH cycles to hold the compressor at a specific temperature.

Level 3 – Modulating CCH to hold the compressor at a specific temperature.

Level 4 – Compressor redesign to go to a modulating compressor, which could potentially eliminate the need for a CCH. The co st is an estimate for the difference in cost between a single-speed compressor and a variable-speed compressor.

Estimated installed cost is shown in the first column of Table 8.5.1. The installed cost is assumed equal the manufacturer’s sales price, plus average na tional retail markup. There is assumed to be no cost for installing the temperature control equipment. There are LCC savings through Level 3, for which the payback period is 3.5 years. The LCC savings turn negative at Level 4, and the payback period exceeds the average life of the equipment.

Table 8.5.1 Details of Regional LCC and Payback Period for Off-Mode Power Consumption Measure: Crank Case Heaters (National Only)

Efficiency Level Life-Cycle Cost 2008$ Savings

Average Installed Cost Average Operating Cost Average LCC Average LCC Savings

2008$ Payback Period

years
Baseline 8 13 118

- NA

1 10 6 62 56 0.3

2 11 4 51 68 0.4

3 38 4 73 45 3.5

4 292 0 292 (173) 22.5

8-87REFERENCES

1. DOE developed residential marginal electricity prices from tariffs collected in 2008 from a representative sample of electric utilities throughout the United States. DOE collected over 150 residential tariffs from a sample of about 90 electric utilities. DOE also developed commercial marginal electricity prices from tariffs for those commercial building applications that use reside ntial CAC and CHP e quipment. DOE used 260 commercial tariffs collected in 2004 and adjusted the values to a 2008 basis using data in Edison Electric Institute, EEI Typical Bills and Average Rates Report http://www.eei.org/products_and_services/de scriptions_and_access/typ_bills_report.htm and in Regulatory Research Associates, Inc., Average Regulated Retail Price of Electricity, 2007 & Comparative Historical Data , 2008. Jersey City, NJ.

2. EIA (Energy Information Administration). 2009. Updated Annual Energy Outlook 2009 Reference Case Servi ce Report, April 2009. EIA, Washington, D.C., DOE/EIA-0383 (2009).

3 . DOE, 2008. DOE to Pursue Zero-Net En ergy Commercial Buildings, Available at http://www1.eere.energy.gov/buildings/commercial_initiative/about.html

4. Letter to Mrs. Rachel Schmeltz, Energy St ar Program Manager, Environmental Protection Agency from Karim Amrane, Vice Presiden t, Regulatory & Research, Air-Conditioning, Heating, and Refrigeration Institute (A HRI), “EPA Proposed Draft Energy Star Specification for Light Commercial HVAC Equipment,” Jan. 30, 2009.

5. NREL, 1995. Typical Meteorological Years Derived from the 1961-1990 National Solar Radiation Database . National Renewable Energy Laboratory. Golden, CO.

6. American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (ASHRAE). 1999. ASHRAE/IES Standard 90.1-1999, “Ene rgy Efficient Design of New Buildings Except Low-Rise Residential Buildings .” Atlanta, Georgia.

7. FreightCenter.com quotes vary conti nuously. Quotes cited were obtained at http://www.freightcenter.com/QuickQuote.aspx on July 10, 2009.

8. R.S. Means Company, Inc. 2009. RS Means Residential Cost Data. 28th Annual Edition. R.S. Means Company, Inc. Kingston , MA., 725 pp.

9. R.S. Means Company, Inc. 2009. RS Means CostWorks 2009. http://www.meanscostworks.com . Accessed March 19, 2009.

10. U.S. Bureau of the Census. American Factfinder. 2007 Population Estimates, Detailed Tables. http://factfinder.census.gov/servlet/DTGeo SearchByListServle t?ds_name=PEP_2007_EST &_lang=en&_ts=257948836197 . (Accessed April 15, 2009.)

8-8811. U.S. Bureau of the Census. American Factfinder. 2008 Population Estimates, Detailed Tables. http://factfinder.census.gov/servlet/DTGeo SearchByListServle t?ds_name=PEP_2008_EST &_lang=en&_ts=257949675405 . (Accessed April 15, 2009.)

12. Coughlin, Katie, Richard White, Chris Bo lduc, Diane Fisher and Greg Rosenquist. The Tariff Analysis Project: A database and analys is platform for electricity tariffs . 2006. Lawrence Berkeley National Laboratory: Berkeley, CA. Report No. LBNL-55680. For data updates see the website < tariffs.lbl.gov >.

13. U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy. Technical Support Document: Energy Efficie ncy Program for Commercial and Industrial Equipment: Commercial Unitary Air Conditioners and Heat Pumps. July, 2004. Washington, D.C. Chapter 8.

< http://www1.eere.energy.gov/buildings/applia nce_standards/commercial/pdfs/cuac_tsd_c hp_8.pdf >

14. Coughlin, K., C. Bolduc, R. Van Busk irk, G. Rosenquist and J. E. McMahon. Tariff-based Analysis of Commercial Building Electricity Prices . 2008. Lawrence Berkeley National Laboratory: Berkeley, CA. Report No. LBNL-55551.

15. U.S. Department of Energy, Energy Info rmation Administration (EIA). 2003 Commercial Building Energy Consumption Survey, Consum ption and Expenditures (CBECS), Public Use Data, 2003. Micro-da ta files on EIA website: ftp://ftp.eia.doe.gov/emeu/cbecs/microdata.html

16. Regulatory Research Associates. Average Regulated Retail Price of Electricity, 2007 & Comparative Historical Data. 2008. Jersey City NJ.

17. Edison Electric Institute, EEI Typical Bills and Average Rates Report (Winter 2007, Summer 2007, Winter 2008 and Summer 2008). Washington, DC.

18. U. S. Department of Energy – Energy Information Administration. Form EIA-861 Annual Electric Power Industry Database.

< http://www.eia.doe.gov/cneaf/e lectricity/page/eia861.html >

19. The sites visited include d: Ask Me Help Desk ( http://www.askmehelpdesk.com/heating

air-conditioning/labor-cost-repl ace-air-compressor-228111.html ), Yahoo! Answers ( http://answers.yahoo.com/question/index?qid=20080809203714AAhtqbk ), All Experts ( http://en.allexperts.com/q /Heating-Air-Conditioning-696/ AC-Compressor-Replacement

Costs.htm ), Home Inspector Locator ( http://www.homeinspectorlocator.c om/resources/Costtorepair.htm ). (All were accessed on April 15, 2009) Also visited were the Harkne ss Repair and Maintenance Cost Guide for Western Pennsylvania http://cost-guide.com/costlst1.html Ingram’s Water and Air Equipment Labor Warranties page http://ingramswaterandair.com/-i-14.html , and Accutex

8-89Home Inspection Service Inc. page on Buying and Air Conditioner http://www.accutekhomeinspection.com/library/cooling.html

.

20. Direct Energy, http://www.directenergy.com/EN/Ontario/RE S/Pages/HC/CoolingRepairAndService.aspx (Accessed April 15, 2009).

21. U.S. Department of Energy–E nergy Information Administration. Residential Energy Consumption Survey, Public Use Data Files. . U.S. Department of Energy: Washington, D.C. < www.eia.doe.gov/emeu/recs/recspubuse05/pubuse05.html >

22. U.S. Census Bureau, Housing and H ousehold Economic Statistics Division. American Housing Survey . Washington, DC.

< http://www.census.gov/hhes/www/housing/ahs/ahs.html >

23. For reference on the Weibull distribution, see Section 1.3.6.6.8 and 8.4.1.3 of the NIST/SEMATECH e-Handbook of Statistical Methods

, http://www.itl.nist.gov/div898/handbook /.

24. See sections 4.1.4.3, 4.4.3.2, and 4.4.5.2 of NIST/SEMATECH e-Handbook of Statistical Methods

, http://www.itl.nist.gov/div898/handbook /

.

25. The Federal Reserve Board. Survey of Consumer Finances . 1989, 1992, 1995, 1998, 2001, and 2004. < www.federalreserve.gov/pubs/oss/oss2/scfindex.html >

26. The Federal Reserve Board. Federal Reserve Statistical Release, Selected Interest Rates, Historical Data, Instrument: CDs (secondary market), Maturity: 6-month, Frequency: Annual, Description: Average rate on 6-month negotiable certificates of deposit (secondary market), quoted on an investment basis . 2009. Washington, D.C.

< www.federalreserve.gov/releases/H15/data.htm >

27. The Federal Reserve Board. Federal Reserve Statistical Release, Selected Interest Rates, Historical Data, Instrument: State and lo cal bonds, Maturity: 20-year, Frequency: Monthly, Description: Bond buyer go 20-bond municipal bond index . 2009. Washington, D.C. < www.federalreserve.gov/releases/H15/data.htm >

28. The Federal Reserve Board. Federal Reserve Statistical Release, Selected Interest Rates, Historical Data, Instrument: Corporat e bonds/Moody’s Seasoned AAA, Frequency: Annual, Description: Moody’s yield on se asoned corporate bonds—all industries, AAA

. 2009. Washington, D.C. < www.federalreserve.gov/releases/H15/data.htm >

29. Mortgage-X, Mortgage Information Service. Cost of Savings Index (COSI), Index History

. 2009. < http://mortgage-x.com/general/indexes/default.asp > (Last accessed, February 25, 2009.)

30. Damodaran Online. The Data Page: Historical Returns on Stocks, Bonds, and Bills— United States . 2009. < http://pages.stern.nyu.edu/~adamodar / >

8-9031. Damodaran Online. http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/wacc.htm (Accessed June 4, 2009).

32. Economic Report of the President, January 2009. http://www.gpoaccess.gov/eop / (Accessed June 4, 2009).

8-91CHAPTER 9. SHIPMENTS ANALYSIS

TABLE OF CONTENTS

9.1 INTRODUCTION

........................................................................................................... 9- 1 9.1.1 Definition of Market Segments for the Shipments Analysis

........................................... 9-1 9.1.2 Fundamental Model Equations

........................................................................................ 9-3 9.2 DATA INPUTS AND SUPPORTING CALCULATIONS

............................................ 9-5 9.2.1 Historical Shipments and the Calcul ation of Replacement Shipments

............................ 9-5 9.2.1.1 Historical Shipments

...................................................................................... 9-5 9.2.1.2 Calculation of Repl acement Shipments

......................................................... 9-7 9.2.2 Shipments to New Construction

...................................................................................... 9-7 9.2.3 Model Calibration and New Owners

............................................................................. 9-10 9.3 DECISION MODEL FOR NEW OWNERS AND REPLACEMENTS

....................... 9-11 9.3.1 Purchase Price Elasticity

............................................................................................... . 9-11 9.3.2 Impact from Increase in Relative Price

.......................................................................... 9-13 9.3.2.1 New Owner Shipment Impact s and Equipment Switching

.......................... 9-14 9.3.2.2 Replacement Shipment Impacts

................................................................... 9-15 9.4 REGIONAL SHIPMENTS MODEL

............................................................................. 9-15 9.4.1 Allocation of Historical Shipments to Regions

............................................................. 9-16 9.4.2 Regional New Construction and Ne w Construction Saturations

................................... 9-19 9.4.2.1 Regional New Construction

......................................................................... 9-19 9.4.2.2 Regional New Construc tion Saturations

...................................................... 9-20 9.5 RESULTS

................................................................................................................... ... 9-22 9.5.1 Split CAC

............................................................................................................... ........ 9-22 9.5.2 Single Package CAC

...................................................................................................... 9-30 9.5.3 Split HP

................................................................................................................ .......... 9-32 9.5.4 Single Package HP

....................................................................................................... .. 9-35

LIST OF TABLES

Table 9.1.1 CAC and HP Product Classes

.............................................................................. 9-2 Table 9.1.2 Stock Categories, Input Data, De cisions, and Resulting Actions used in the Shipments Model

................................................................................................. 9-3 Table 9.2.1 Central Air Conditioner and Heat Pump Historical Shipments*

......................... 9-6 Table 9.2.2 Historical New Ow ner Market Shares of CAC and HP Equipment

.................. 9-11 Table 9.3.1 Change in Relative Price Elasticit y following a Purchase Price Change

.......... 9-13 Table 9.4.1 CAC Reside ntial Regional Stock Saturations

.................................................... 9-16 Table 9.4.2 HP Residential Regi onal Stock Saturations

....................................................... 9-17 Table 9.4.3 CAC Shipment Regi onal Allocation Factors

..................................................... 9-17 Table 9.4.4 HP Shipment Regional Allocation Factors

........................................................ 9-17

9-iTable 9.4.5 Population Projected for 2020 for Areas defined by the Overlap of Census Divisions with Climate Regions

........................................................................ 9-19 Table 9.5.1 Split CAC: Base Case and St andards Case Cumula tive Shipments from 2016-2046 (millions)

......................................................................................... 9-29 Table 9.5.2 Single Package CAC: Base Case and Standard s Case Cumulative Shipments from 2016-2046 (millions)

............................................................... 9-32 Table 9.5.3 Split HP: Base Case and St andards Case Cumula tive Shipments from 2016-2046 (millions)

......................................................................................... 9-34 Table 9.5.4 Single Package HP: Base Case and Standard s Case Cumulative Shipments from 2016-2046 (millions)

............................................................... 9-36

LIST OF FIGURES

Figure 9.2.1 CAC and HP Saturations in Residential New Construction

................................ 9-8 Figure 9.2.2 CAC and HP Saturation in Commercial New C onstruction

................................ 9-9 Figure 9.4.1 Residential CAC and HP Stock Saturations by Region and the Entire U.S.: American Housing Survey (AHS) vs. Shipments Model (Calculated)

.............. 9-18 Figure 9.4.2 CAC National and Re gional Saturations in Reside ntial New Construction

...... 9-20 Figure 9.4.3 HP National and Re gional Saturations in Reside ntial New Construction

......... 9-21 Figure 9.4.4 CAC and HP National and Re gional Saturations in Commercial New Construction

....................................................................................................... 9-22 Figure 9.5.1 Forecasted Shipments (Base Case ) for Split-System CACs, Coil-Only

............ 9-23 Figure 9.5.2 Forecasted Shipments (Base Case ) for Split-System CACs, Blower Coil

........ 9-23 Figure 9.5.3 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) Replacement Shipments Forecasts

........................................................................................... 9-25 Figure 9.5.4 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) New Owner Shipments Forecasts

........................................................................................... 9-26 Figure 9.5.5 Split Coil-Only CAC: Base Case New Constructi on Shipments Forecasts

....... 9-27 Figure 9.5.6 Split Coil-Only CAC: Base Ca se and CSL 13 (22 SEER) Total Shipments
Forecasts

............................................................................................................ 9-28 Figure 9.5.7 Forecasted Shipments (Base Case) for Single Package CACs

.......................... 9-30 Figure 9.5.8 Single Package CAC: Base Ca se and CSL 7 (16.6 SEER) Total Shipments
Forecasts

............................................................................................................ 9-31 Figure 9.5.9 Forecasted Shipments (Bas e Case) for Split System HPs

................................. 9-32 Figure 9.5.10 Split HP: Base Case a nd CSL 10 (19.5 SEER / 10.3 HSPF) Total Shipments Forecasts

........................................................................................... 9-33 Figure 9.5.11 Forecasted Shipments (Base Case) for Single Package HPs

............................. 9-35 Figure 9.5.12 Single Package HP: Base Ca se and CSL 7 (16.4 SEER / 9.0 HSPF Total Shipments Forecasts

........................................................................................... 9-36

9-iiCHAPTER 9. SHIPMENTS ANALYSIS

9.1 INTRODUCTION

Estimates of future product shipments are a n ecessary input to calculations of the national energy savings (NES) and net present value (NPV), as well as to the manufacturer impact analysis (MIA). This chapter describes the data and methods the U.S. Department of Energy (DOE) used to forecast annual product shipments, and presents results for each of the central air conditioner (CAC) and heat pump (H P) product classes being considered in this analysis. The shipments model divides the popula tion of appliance users into sp ecific market segments and estimates the shipment of new equipment to each of these segments under each candidate standard level (CSL). The model starts from a hist orical base year and calculates, for each year of the analysis period, both shipments and retir ements by market segment. This approach produces an estimate of the total equipment stoc k, broken down by age or vintage, in each year of the analysis period. The equipment stock dist ribution is calculated for the base case and for each CSL as well as for each product class. The st ock distribution is used in the national impact analysis (NIA) to estimate the total dollar and energy costs and benefits associated with each CSL.

The shipments model was developed as a Microsoft Excel spreadsheet that is accessible on DOE’s Appliance and Commercia l Equipment Standards website ( http://www1.eere.energy.gov/buildings/applianc e_standards/residen tial/central_ac_hp.html ). Appendix 10-A discusses how to access and utilize the shipments model spreadsheet, which is integrated into the spreadsheet for the NIA. The rest of this chapter explains how the shipments model is constructed a nd provides some summary output. The rest of section 9.1 describes the methodological approach. The analysis incorpor ates a large number of components or market segments, describing different product classes, market sectors and geographic regions; for simplicity, the methodology is explained for a sing le product class for re sidential consumers for the country as a whole. Section 9.2 defines the input data, pre-processi ng and calibration steps that are used in the model. Section 9.3 defines th e decision models used to differentiate between the base case and the CSLs. Section 9.4 presents the modifications to the input data that were used to develop shipments models specific to th e three regions (hot-humid, hot-dry and rest-of

country) used in the analysis. Section 9.5 pres ents summary output from the shipments model,including the shipments forecast for the base cases and different energy conservation standardlevel scenarios. The methodology used to develop price elasticities is de scribed in Appendix 9

- A.

9.1.1 Definition of Market Segments for the Shipments Analysis

The shipments model disaggregates the total stock according to the following characteristics:

9-11. Product class: there are four product classe s as summarized in Table 9.1.1. DOE further disaggregated the split system CAC product cl ass into two unit types: coil-only and blower coil units. Although not considered as separate product classes, DOE structured the shipments model to analyze both split CAC coil-only and split CAC blower coil systems separately.

2. Market sector: residential and commercial bu ilding sectors; approx imately 93 percent of shipments are to the residential sector with the balance going to the commercial sector. 1 This ratio is held constant over the analysis period.

3. Repair status: this is define d as default (i.e., normal repair s and maintenance as accounted for in the lifetime of the equipment) or extended repair (ER). The shipments model allows for the price increase associated with a CSL to influence the consumer decision to repair, rather than replace , broken equipment. The extended repair stock category represents equipment that has been repaired after failure. This component of the stock is accounted for separately because it is furthe r assumed that equipm ent that has undergone one extended repair will last another six years and then be replaced. This category is referred to as extended repair because it mode ls major equipment failures; minor repairs are accounted for in the annual maintenanc e costs and determination of equipment lifetimes.

Table 9.1.1 CAC and HP Product Classes Product Type Product Class Unit Type Coil-Only Central Air Conditioner (CAC) Split System Blower Coil Single Package NA

Heat Pump (HP) Split System NA Single Package NA

Each market sector (i.e., residential and co mmercial) is further disaggregated into three product placement channels (hereafter refe rred to as “channels”) as follows:

1. New construction: a certain fraction of new buildings are assumed to acquire CAC and HP equipment in the year of construction. This fraction is defined as the new construction saturation, which varies by year, by region, and by product type.

2. Existing owners: these are defined as exis ting buildings with CAC and HP equipment installed. This category receives new shipments when existing equipment is replaced.

3. New owners: these are defined as existing bu ildings that acquire CAC and HP equipment for the first time during the analysis period. The fraction of new owners is estimated from trends in overall market saturation. As described later in this chapter, the new owner channel is necessary for calibrating the shipments model to historical shipments.

9-2These three channels are treated differently in the way that the consumer decision is modeled. For new construction the placement of equipment is automatic, in line with observed trends in the data. For new owners, the consumer decision to purchase CAC and HP equipment is affected by the change in purchase price and operating costs; for this category, the number of new purchases will generally decrease for the higher CSLs. In those cases where new owners of CAC and HP equipment have be en modeled to forego a new purchase, DOE assumed that potential new owners would purchase alterna tive space-conditioning systems; room air conditioners in the case of CAC consumers and combination warm-air electric resistance furnaces and CACs in the case of HP consumers. For existing owners, the repair versus replace decision is also affected by the change in ownership cost associated with higher efficiency. In those cases where existing owners have been mo deled as being affected by higher ownership costs, DOE assumed they would perform an ex tended repair which prol ongs the life of the equipment by six years, after which the equipm ent would be replaced. The three channels and related decisions modeled in the sp readsheet are summarized in Table 9.1.2.

Table 9.1.2 Stock Categories, Input Data, Decisions, and Resulting Actions used in the Shipments Model Category Input data Decision Action Equipment Stock =

+ new construction nc_starts (year) buy => add to equip_stock, age=0 nc_saturation(year)

- demolitions housing demolitions(year) remove => subtract from equip_stock Equip_stock(age, year)

+ existing owners Equip_stock(age, year) does not break => stays in equip_stock; increment age survival_function(age) breaks: replace => add to equip_stock, age=0 Repair_probability(year) breaks: repair => convert to ER_equip_stock, a2=0

Extended Repair ER_equip_stock(year,a2) a2 < 6 years => stays in ER_equip_stock; increment a2 a2=6 years, replace => add to equip_stock, age=0

New owners (no CAC or HP) housing_stock(year) buy => add to equip_stock, age=0 Equip_stock(age, year) max_saturation(year) do not buy => stays in no cooling stock purchase_probability(year)

9.1.2 Fundamental Model Equations

The fundamental dependent va riable in the shipments model is the equipment stock which is represented as a function of analysis year (indexed by j) , and equipment vintage or age (the equipment age is noted as a, and is equal to the analysis year minus the vintage). The stock function is adjusted in each year of the anal ysis period by new shipments coming in and broken or demolished equipm ent being taken out.

For existing stock:

9-3Stock 

## ( j,a 

## )

= Stock 

## ( j

− 1 ,a

− 1 

## )

− Re m 

## ( j,a 

## )

p p p

and for new units:

Stock
p 

## ( j,a = 1 

## )

= Ship
p 

## ( j

− 1 

## )

.

Where:

Stock p (j, a) = number of units of product class p and age a in analysis year j,
Rem p (j, a) = number of units of product class p and age a removed in analysis year j, and Ship p (j) = number of units of product class p shipped in year j

.
Shipments are directed to one of the three channels:

Ship 

## ( j 

## )

= Rpl 

## ( j 

## ) + NC 

## ( j 

## ) + NO 

## ( j 

## )

p p p p

Where:

Rpl p (j) = number of units of product p replaced in year j ; it depends on removals,
NC p (j) = number of units installed in new construction of product p in year j , and
NO p (j) = number of units shipped to “new owners” of product p in year j

.
Removals due to equipment breakage contains two terms. In the first, a survival function f

p (a) is used to represent the probability that a unit of age a will survive in a given year; equivalently the probability that this unit will fail is 1- f p (a) . The second term is the extended repair stock that has been in use for six years following the repair date. Total removals in the base case are then:

Re m 

## ( j,a 

## )

= 

# [ 1

− f 

## ( a 

## ) 

# ] × Stock 

## ( j,a 

## ) + ER

_ Stock 

## ( j,a 2 = 6 

## )

p p p p

Where:

a2 = number of years since the equipment was repaired, and ER_Stock p (j, a2) = number of extended-repa ir units of product p replaced in year j.

The new construction and new owner markets depe nd on changes to the building stock, which is included as a component of the shipments model. This is discussed in the next section.

9-49.2 DATA INPUTS AND SUPPORTING CALCULATIONS

Data inputs and supporting calc ulations that are necessary for the shipments model are explained in detail in the following sections.

9.2.1 Historical Shipments and the Calculation of Replacement Shipments

9.2.1.1 Historical Shipments

DOE used historical shipments data (i.e., domestic shipments and imports) to populate its shipments model for CAC and HP equipment. As part of its data submittal to the DOE standards rulemaking, the Air-Conditioning, Heating, and Refrigeration Institute (AHRI) provided historical shipments data ove r the 1990-2007 time-period disaggregated into the four primary product classes. 2 Historical shipments from 1972- 1989 were also provided by AHRI from previous data submittals to the Lawrence Berkeley National Laboratory (LBNL). 3 The data for 1972-1989 included some shipments of 3-phase as well as single -phase CAC and HP, whereas the data for 1990-2007 included onl y single-phase CAC. DOE di saggregated the shipments for single-phase and 3-phase CAC a nd HP equipment in the earlier data and included only single phase units in the analysis.

DOE further broke down split system CAC historical shipments into coil-only and blower coil unit shipments. Because DOE believes that a majority of split CAC shipments are coil-only units, it estimated that coil-only units account for 90 percent of annual split system shipments.

As discussed earlier in section 9.1.1, DOE divi ded all historical sh ipments for all product classes into two market segments, i.e., the residential and commercial building sectors. DOE allocated 93 percent of historical shipments to the residential building sector and the remaining seven percent to the commercial building sector.

Table 9.2.1 summarizes the historical shipme nts data. DOE developed a total stock estimate for each product class and market segment by integrating historical shipments. Over time, units are retired and removed from the stock based on a survival function as discussed in section 9.1.1, triggering the purchase of a new unit. Because of the relationship between retirements and total stock, there is a strong correlation between past and future shipments, independent of cons ervation standards.

9-5Table 9.2.1 Central Air Conditioner and Heat Pump Historical Shipments*

Year Split CAC**
thousands Single Package CAC
thousands Split HP
thousands Single Package HP
thousands
1972 1,489 257 28 52
1973 1,742 318 35 52
1974 1,503 289 49 48
1975 888 159 83 45
1976 1,219 231 177 74 1977 1,364 218 329 89
1978 1,546 253 389 97 1979 1,428 248 376 107
1980 1,233 134 293 61 1981 1,293 122 348 66 1982 1,037 111 267 49
1983 1,558 192 455 82 1984 1,857 189 535 98
1985 1,784 203 619 107 1986 1,876 203 680 106
1987 2,204 237 714 103 1988 2,334 247 649 91
1989 2,516 267 650 91
1990 2,241 334 643 104 1991 2,388 306 615 96
1992 2,254 330 647 101 1993 2,474 346 718 107
1994 3,087 387 825 118
1995 3,221 384 834 120 1996 3,635 418 936 139
1997 3,364 395 917 142 1998 4,010 406 1,019 148
1999 4,317 429 1,044 147
2000 4,280 437 1,073 159
2001 3,931 361 1,180 165
2002 4,381 380 1,229 165
2003 4,281 390 1,350 174
2004 4,561 414 1,584 190
2005 5,461 455 1,810 213
2006 4,038 330 1,807 190
2007 3,582 338 1,570 199
Source: AHRI * For each product class, 93 percent of annual shipments are allocated to the residential building sector and the

remaining seven percent are allocated to the commercial building sector. **Annual split CAC shipments are disaggregated into coil-only and blower coil unit shipments. Coil-only unit

shipments estimated to comprise 90 percent of annual split CAC shipments.

9-69.2.1.2 Calculation of Replacement Shipments

When an equipment unit is broken, it is removed from the stock. The following retirement function r p (a) is used to represent the probability that a unit will be broken at age a

.

Re m p 

## ( j 

## )

= 

# ∑ r a 

## (

a 

## ) × Stock
p 

## ( j,a 

## )

a

Retirement functions and produc t lifetimes are discussed in mo re detail in Chapter 8. The average lifetimes are 18.3 years for split and si ngle package CAC equipment and 15.5 years for split and single package heat pumps.

In each year, equipment are removed with demolished buildings. As represented by the following expression, the shipment s model assumes that the saturation of the equipment in the demolished buildings is the same of that of the overall population.

D 

## ( ) j = H

_ Stock 

## ( j

− 1 

## ) + H

_ Starts 

## ( j 

## )

− H

_ Stock 

## ( j 

## )

Dem 

## ( j 

## )

= D 

## ( j 

## ) × sat 

## ( p , j

− 1 

## )

Where:

H_Stock (j) = number of housing units in analysis year j, H_Starts(j) = number of new housing units in year j

, D(j) = number of demolished buildings, and Dem (j) = number of equipment units demolished in analysis year j. sat(p,j) = saturation of equipment of product class p for all buildings in year j

The shipments model assumes that units that are going away with demolished buildings, Dem(j ), are included in the mix of broken units Rem p (j). Since the demolished units do not need to be replaced, they are deducted from Rem p (j) when calculating the required replacements, as represented by the following expression.

Rpl
p 

## ( j 

## )

= Re m p 

## ( j 

## )

− Dem 

## ( j 

## )

9.2.2 Shipments to New Construction

DOE multiplied new construction market saturations by forecasts of new construction to estimate CAC and HP shipments to the new constr uction channel. On a product class basis, the determination of shipments to new construction is represented by the following expression.

NC
p 

## ( j 

## )

= NC

_ Starts 

## ( j 

## ) × NC _ Sat
p 

## ( j 

## )

Where:

9-7NC_Starts (j) = number of new construction starts in year j, and NC_Sat(j) = new construction saturati on for product class p and year j

.
For the residential market segment, DOE de veloped new constructi on market saturations from Characteristics of New Housing data from the U.S. Census Bureau. 4 CAC and HP historical and projected saturations are depicted in Figure 9.2.1. DOE used historical new construction saturations for all CAC and HP equipment to project saturations into the future. As evidenced in Figure 9.2.1., DOE used a logistic fit to the historical data to estimate future saturations. DOE used product class market shar es based on historical shipments (as shown in Table 9.2.1) to calculate speci fic market saturations fore e ach CAC and HP product class.

Saturation = 0.10Ln(Year-1977) + 0.52
R2 = 0.94

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 10 20 30 40 50 60 70

Year - 1977Residential New Consturciton Saturaitons

CAC + HP

HP

CAC

Figure 9.2.1 CAC and HP Saturations in Residential New Construction

DOE determined new construction starts to the residential market segment, otherwisereferred to as housing starts, by using recorded data through 2007 and projections from the DOEEnergy Information Administration (EIA)’s Annual Energy Outlook 2009 ( AEO2009 ) for the period 2008–2030. 5 New housing includes newly construc ted single- and multi-family units, termed “new housing completions,” and mobile home placements. AEO2009 provides three sets of economic growth scenarios: a Reference case, a High Economic Growth case, and a Low Economic Growth case. The original AEO2009 analysis published by the EIA in March 2009 was modified in April 2009 to incorporate th e effects of the American Recovery and Reinvestment Act. 1 DOE used the high and low growth scenarios from the March 2009 release

9-8of the AEO2009 6 , and the Reference case from the m odified April release. For 2031

− 2046, DOE froze completions at the 2030 level for all three economic scenarios.

For the commercial market segment, DOE developed new construction market saturations from data in EIA’s Commercial Building Energy Consumption Survey (CBECS). 7 Past CBECS surveys for the years 1992, 1995, 1999, and 2003 provided the saturation of residential-type central air conditioners in all ne w commercial buildings by Census Division. To determine nationally representative saturation values, DOE calculated a weighted-average saturation based on historical construction commercial starts by Census Division (in millions of square feet) from AEO2009 . DOE considered residential-type central air conditioners to comprise all split system and single package CAC and HP equipment. DOE used product class market shares based on historical shipments to calculate specific market saturations for each CAC and HP product class. Figure 9.2.2 depi cts the new construction saturations for the commercial market segment. Actual data from CBECS are shown as “black diamonds” in Figure 9.2.2. Saturations prior to 1992 were fixed by DOE to the 1992 value. DOE used linear interpolation to develop the saturations for non-CBECS years between 1992 and 2003. DOE averaged the saturations for the four CBECS years to forecast saturation values after the year 2003.

0% 1% 2% 3% 4% 5% 6%

1990 1995 2000 2005 2010 2015 2020 2025 2030

YearSaturation (percent sq.ft. cooledby CAC and HP)

Sources: DOE-EIA, CBECS; AEO2009
Figure 9.2.2 CAC and HP Saturation in Commercial New Construction

As with the residential market segment, DOE determined new construction starts to the commercial building market segment by using re corded data through 2007 and projections from EIA’s AEO2009 for the period 2008–2030. For 2031

− 2046, DOE froze completions at the 2030

9-9level for all three economic scenarios. DOE used the same data sources that were used for the residential market to estimate new construction starts fo r a Reference case, a High Economic Growth case, and a Low Economic Growth case.

9.2.3 Model Calibration and New Owners

The shipments model begins with an estimat e of the building stock and equipment stock in the base year, and steps forward adding sh ipments each year and removing retirements. In principle, only building and market saturation data are needed to allow the shipments model to estimate shipments to new construction and re placements. The third product channel, new owners, is more difficult to desc ribe based on existing data. Howe ver, the historical shipments data (as described above in sec tion 9.2.1.1) can be used to ca librate the shipments model and improve the representation of the new owner market.

To calibrate estimated shipments with the historical data, as represented by the following expression, DOE treated the new owner market NO p (j) as a residual after shipments for new construction and replaceme nts were subtracted from total shipments.

NO
p 

## ( j 

## )

= Ship
p 

## ( j 

## )

− Rpl
p 

## ( j 

## )

− NC
p 

## ( j 

## )

The three terms on the left are known quantities (calculation of Rpl p (j) and NC p (j) are described above).

The results of the historical calibration ar e shown in Table 9.2.2. The values are historical market shares of total CAC and HP equipment in the new owner channel. The residential market share is th e total CAC and HP shipments to the new owner housing market divided by the number of households without e ither CACs or HPs. The commercial market share is the number of total CAC and HP shipments to the new owner commercial building market divided by the commercial building stoc k not conditioned by CAC and HP equipment. DOE determined the commercial building stock not conditioned by CAC and HP equipment by dividing the total stock in square feet by 500 square feet (i.e., the amount of square feet conditioned by one piece of CA C and HP equipment). DOE used product class market shares based on historical shipments (as shown in Table 9.2.1) to calcu late specific new owner market saturations fore each CA C and HP product class.

9-10Table 9.2.2 Historical New Owner Market Shares of CAC and HP Equipment

Year Residential Commercial
1990 2.05% 0.10%
1991 1.78% 0.09%
1992 1.35% 0.08%
1993 1.59% 0.07%
1994 2.25% 0.07%
1995 2.43% 0.06%
1996 3.22% 0.11%
1997 2.53% 0.10%
1998 3.34% 0.15%
1999 3.82% 0.19%
2000 4.04% 0.16%
2001 3.31% 0.12%
2002 4.10% 0.12%
2003 3.93% 0.09%
2004 4.81% 0.14%
2005 7.75% 0.15%
2006 3.51% 0.07%
2007 1.94% 0.02%

To forecast future shipments to the new owner market, DOE calculated the average market share over the 1990 to 2007 time-period for the residential and commercial markets, 3.21% and 0.10%, respectively, and held the market share fixed from 2008-2046.

9.3 DECISION MODEL FOR NEW OWNERS AND REPLACEMENTS

In the shipments model, two sets of cons umer purchase decisions are modeled. These decisions are influenced by the purchase price and operating cost of equipment, and therefore will be different in the base case vs. different CSLs. These decisions are modeled by estimating the purchase price elasticity for cooling equipment. The purchase price elasticity is defined as the change in the percentage of consumers acquiring CAC and HP equipment divided by a change in the relative price (defined below) for that equipment. This elasticity and information obtained from the life-cycle cost (LCC) and payback period (PBP) analysis on the change in purchase price and operating costs under different CSLs ar e used in the shipments model to estimate the resulting change in equipment shipped.

9.3.1 Purchase Price Elasticity

DOE conducted a literature review and an analysis of appliance price and efficiency data to estimate the combined effects on product ship ments from increases in product purchase price, decreases in product operating costs, and chan ges to household income . Appendix 9-A provides

9-11a detailed explanation of the methodology DOE used to quantify the impacts from these variables.

Existing studies of appliance markets sugge st that the demand for appliances is priceinelastic. Other information in the literature suggests that appliances are a normal good, so that rising incomes increase the demand for applian ces, and that consumers use relatively high implicit discount rates a when comparing appliance prices and appliance operating costs.

DOE used the available data for the pe riod 1980-2002 on large appliance purchases to evaluate broad market trends and conduct simple regression anal yses. These data indicate that there has been a rise in appliance shipments and a decline in appliance purchase price and operating costs over the time period. Household inco me has also risen during this time. Because purchase decisions are sensitive to income, and also to potential savings in the operating cost of the appliance, DOE combined the available economic information into one variable, termed the relative price . This variable was used in a regression analysis to parameterize historical market trends. The relative price is defined with the following expression:

TP PP + PVOC RP = = I

ncome I ncome

Where:

RP = relative price,
TP = total price,
Income = household income,
PP = appliance purchase price, and
PVOC = present value of operating cost, ba sed on an implicit discount rate of 37 percent.

DOE’s regression analysis of the relevant data suggests that the relative price elasticity of demand is approximately -0.34; this implies that a relative price increase of 10 percent results in a 3 to 4 percent decrease in shipments. Note that the relative price elasticity incorporates the impacts from purchase price, operating cost, and household income, so the impact from any single effect can be mitigated by changes from the other two effects. The relative price elasticity of -0.34 is consistent with estimates in the literature, but is based on a small data set. More importantly, the measure is based on an assumpti on that economic variables, including purchase price, operating costs, and household income, ex plain most of the trend in appliances per household in the United States since 1980. Ch anges in appliance quality and consumer preferences may have occurred during this peri od, but DOE did not account for them in this analysis. Despite these uncertainties, DOE believes that its estimate of the relative price elasticity

a A high implicit discount rate with regard to operating costs means that consumers do not put much economic value on the operating cost savings realized from more-efficient appliances. In other words, consumers are much more concerned with higher purchase prices.

9-12of demand provides a reasonable a ssessment of the impact that purchase price, operating cost, and household income have on product shipments.

The forecasts of shipments and national imp acts due to standards are for a 30-year time period, and it is possible that over this time pe riod the numerical value of the relative price elasticity could change; in particular, it can be affected by a new standard that changes consumer expectations about equipment performance. DOE considered the relative price elasticity provided by the preceding analysis to be a s hort-run value. No data exists to allow the determination of long run price elasticities for appliances, so DOE relied on a study pertaining to automobiles. 8 This study shows that the automobile price elasticity of demand changes in the years following a purchase price change, beco ming smaller (more inelastic) until it reaches a terminal value around the tenth year after the pr ice change. Table 9.3.1 shows the relative change in the price elasticity of demand for automobiles over time. DOE developed a time series of relative price elasticities for CAC and CAC-HP based on the relative change in the automobile price elasticity of demand. For years not s hown in Table 9.3.1, DOE performed a linear interpolation to obtain the relative price elasticity.

Table 9.3.1 Change in Relative Pric e Elasticity following a Purchase Price Change Years Following Price Change
1 2 3 5 10 20 Relative Change in Elasticity to 1 st year 1.00 0.78 0.63 0.46 0.35 0.33

Relative Price Elasticity -0.34 -0.26 -0.21 -0.16 -0.12 -0.11

9.3.2 Impact from Increase in Relative Price

Using the relative price elasticity, DOE was able to estimate the impact of the increase in relative price from a particular CSL. The impact, as shown in the equation be low, is expressed as a percentage drop in market share for each year, dMS p j , which is applied in the new owner market channel as well as the decision for replacement versus extended repair. As noted in section 9.1.1, for the new construction market channel, the placement of equipment is automatic, in line with observed trends in the data. In ot her words, DOE assumed that the new construction market channel was unaffected by changes in either the total installed cost or operating costs of the equipment as well as changes in household income.

p ⎡ ⎛ ⎜ RP _ std
p 

## ( j 

## ) ⎞ ⎟ ⎤ dMS j = ⎢ 1

− ⎜ ⎟ ⎥ × e RP 

## ( ) j ⎢ RP _base
p 

## ( ) j ⎥ ⎣ ⎝ ⎠ ⎦

Where:

dMS p j = percentage market share drop for class p, year j

, RP_std p (j)= relative price in the standards case for product class p, year j

, RP p (j)= relative price in the base case for product class p, year j , and

9-13e RP (j) = relative price elasticity in year j

.

9.3.2.1 New Owner Shipment Impacts and Equipment Switching

DOE estimated standards case shipments to the new owner product channel by incorporating the impact of the relative price into the standards case shipments forecast. The relative price and the relative price elasticity are both a function of time.

NO _ std 

## ( j 

## )

= NO 

## ( j 

## ) × 

# ( 1

− dMS p 

# )

p p j

Where:

NO_std p (j)= shipments to new owners in th e standards case for product class p, year j

, and
NO p (j)= shipments to new owners in th e base case for product class p, year j

.
The new owner market is equal to the total building stock minus the building stock with equipment; if each building is assumed to have just one CAC or HP unit then the number of building units with CAC and HP equipment is equal to the CAC and HP equipment stock.

DOE assumed that the new owners impacted by the relative price increase and do not purchase the equipment would switch to purchas e an alternative type of space-conditioning equipment. The number of new ow ners impacted and switching to an alternative equipment type is represented by the following expression.

p NO _ sw p 

## ( j 

## )

= NO
p 

## ( j 

## ) × dMS j

Where:

NO_sw p (j)= new owners for product class p switching to buy other products

, year j.

For new owner purchases of split system and single package CACs, DOE assumed that consumers affected by a relative price increase would switch equipment and purchase a room air conditioner rather than a CAC. Because room air conditioners have lower cooling capacities and lower overall annual energy consumption than CA Cs, DOE did not explicitly account for the increased sales of room air conditioners in its an alysis. Doing so would have credited a standard with energy savings from displaced CAC shipments. To avoid including savings from displaced shipments to new owners, DOE used the shipment s projection estimates for the standards cases to calculate the annual energy consumption in the base case.

For new owner purchases of split system and single package HPs, DOE assumed that consumers affected by a relative price increase would switch equipment and purchase a combination electric resistance furnace and CAC rather than a HP. In its analysis of HP shipments in the NIA (discussed in chapter 10), DOE tracked purchases of electric furnaces and

9-14CACs due to decreases in shipme nts of HPs in order to quantify the energy, operating cost, and total installed cost impacts for consumers who were estimated to forgo a purchase of a new HP. Because DOE explicitly accounted for the energy c onsumption, operating cost , and total installed cost of the displaced shipments of HPs, it maintained use of the base case shipments to determine the annual energy consumption in the base case.

9.3.2.2 Replacement Shipment Impacts

For replacement purchases of split system and single package CACs and HPs, DOE assumed consumers affected by an increase in to tal installed cost would repair their equipment rather than replace it, extending the life of the product by six years. When the extended repaired units fail after six more years, they will be replaced with new ones.

The model calculates for each year after the standard, the relative percentage market drop, dMS p j , due to the equipment price increase as desc ribed in 9.3.1.1. The extended repair is only applicable to broken equipment that are pu rchased before 2016. For broken equipment that are purchased after 2016, extended repair will not be considered since there will be no longer a price impact from standards between new units and the broken units.

The number of broken units that will be furt her repaired instead of being replaced is calculated as follows:

p XR i = 

# ∑ Re m 

## ( j,a 

## ) × dMS i for ( j

− a ) < 2016

a Rpl 

## ( ) j = 

# ∑ Re m( j,a )

− XR i + XR j

− 6 − Dem 

## ( j 

## )

a Where:

dMS p j = percentage market share drop for class p, year j

,
a = age of an equipment j = year, Rem(j,a) = retiring units in year j of age a , XR j = extended repair units, year j

, Rpl(j) = replacement units in year j

, Dem (j) = number of units gone with demolished buildings in analysis year j.

9.4 REGIONAL SHIPMENTS MODEL

As described in Chapter 6, Energy Use De termination, some of the CSLs involve the division of the U.S. into three climate regions : hot-humid, hot-dry, and rest-of-country. For the shipments model, DOE constructed two variants of the national analysis. In the first, the nation as a whole is treated as a single region. In the second, the U.S. is disaggregated into the three climate regions, a separate shipments model is r un for each region, and the results are summed to

9-15provide national-level out put under a regional standard scenar io. In the regional standards case, the mechanics of the shipments model are identical to the one-region case already described. The only changes needed to analyze a specific region ar e definitions of the various data inputs for the region in question. This section describes how these data inputs were disaggregated.

Not every data input can be or needs to be defined at a regional level. DOE assumed the product lifetimes, purchase prices, and relative price elasticities did not vary by region. Product operating costs do vary by region and this in formation is available from the LCC and PBP analysis (see Chapter 8). For the shipments m odel, historical shipments, housing starts and housing stock, commercial buildings starts and stoc k (in square feet), and market saturations for new construction must be developed for each region. The following sections describe the development of regional histori cal shipments, housing and commerc ial building starts and stock, and market saturations.

9.4.1 Allocation of Historical Shipments to Regions

DOE developed regional allocation factors to di vide historical shipments into each of the three climatic regions. The regional allocation factors were determined by trial and error by calibrating to historical residential stock saturations in the American Housing Survey (AHS). 9 Tables 9.4.1 and 9.4.2 provide th e historical regional and nationa l stock saturations for CAC and HP equipment for every other year between 1991

− 2007 as specified in the AHS. The stock saturations are specific to each region or the nati on, i.e., the individual regional stock saturations do not add up to the national stock saturation.

Table 9.4.1 CAC Residential Regional Stock Saturations

Year Hot-Dry Hot-Humid Rest of U.S. Entire U.S.
1991 32.5% 48.6% 23.8% 30.8%
1993 33.5% 50.0% 25.0% 32.0%
1995 36.6% 50.7% 27.3% 33.9%
1997 42.4% 47.3% 29.2% 36.3%
1999 48.0% 54.0% 33.3% 41.4%
2001 51.5% 58.1% 36.6% 45.0%
2003 53.8% 58.1% 38.5% 46.5%
2005 55.9% 61.5% 43.0% 50.2%
2007 63.5% 62.8% 42.8% 51.8%
Source: AHS

9-16Table 9.4.2 HP Residential Regional Stock Saturations

Year Hot-Dry Hot-Humid Rest of U.S. Entire U.S.
1991 6.3% 18.1% 3.7% 7.8%
1993 7.5% 19.7% 3.9% 8.5%
1995 7.1% 21.6% 4.1% 9.1%
1997 9.9% 28.0% 4.4% 12.0%
1999 8.3% 26.8% 4.2% 11.4%
2001 8.0% 26.2% 4.4% 11.3%
2003 7.8% 27.4% 4.4% 11.7%
2005 8.8% 29.0% 5.4% 12.7%
2007 8.1% 28.8% 5.3% 12.8%
Source: AHS

Tables 9.4.3 and 9.4.4 provide the ship ment allocation factors for CAC and HP, respectively. For each of the years presented in the tables below, DOE used the allocation factors to assign the fraction of shipments for each region until the market saturations calculated by the shipments model were nearly equal to th e regional stock saturations reported by AHS.

Table 9.4.3 CAC Shipment Regional Allocation Factors

Year Hot-Dry Hot-Humid Rest U.S.
1983 15.0% 50.0% 35.0%
1987 15.0% 45.0% 40.0%
1990 17.0% 38.0% 45.0%
1993 17.0% 35.0% 48.0%
1997 17.0% 30.0% 53.0%
2001 17.0% 30.0% 53.0%
2003 17.0% 30.0% 53.0%
2005 17.0% 32.0% 51.0%
2007 17.0% 32.0% 51.0%

Table 9.4.4 HP Shipment Regional Allocation Factors

Year Hot-Dry Hot-Humid Rest U.S.
1983 14.0% 75.0% 11.0%
1987 14.0% 72.0% 14.0%
1990 14.0% 70.0% 16.0%
1993 12.0% 70.0% 18.0%
1997 9.0% 70.0% 21.0%
2001 9.0% 60.0% 31.0%
2003 9.0% 50.0% 41.0%
2005 9.0% 50.0% 41.0%
2007 9.0% 50.0% 41.0%

9-17Figure 9.4.1 provides the resulting comparison between the CAC and HP stock saturations by region and the entire U.S. from the AHS and those calculated from the shipments model. As shown in the figure below, the calculated values are relatively close to the values from the AHS. After establishing the appropriate CAC and HP shipment allocation factors, DOE used product class market shares based on histor ical shipments (as shown in Table 9.2.1) to calculate specific allocati ons factors for each CAC and HP product class.

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0% CAC & HP Saturation Hot-Dry CAC & HP Saturation Hot-Humid

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008Saturation CAC calculated HP calculated

CAC AHS HP AHS

CAC & HP Saturation Entire U.S.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008Saturation CAC calculated HP calculated

CAC AHS HP AHS CAC calculated

CAC AHS HP calculated

HP AHSSaturation

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

CAC & HP Saturation Rest of U.S. 100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 CAC calculated HP calculated

CAC AHS HP AHSSaturation

Figure 9.4.1 Residential CAC and HP Stock Saturations by Region and the Entire U.S.: American Housing Survey (AHS) vs. Shipments Model (Calculated)

9-18It is worth noting that, once historical shipments are allocated to each of the three climatic regions, DOE calculated replacement shipments for each region based on when the equipment is forecasted to break. Refer back to section 9.2.1.2 for a description of the method for determining replacement shipments.

9.4.2 Regional New Construction and New Construction Saturations

9.4.2.1 Regional New Construction

AEO2009 provides housing forecasts by Census Di vision. These were converted to the three climate regions by using population data to allocate the housing stock. Each state can be allocated to both a Census Division and a climat e region; hence, a set of overlap regions can defined at the state level. For example, Florida is in the hot-humid climate region and the South Atlantic census division; therefore, the intersec tion of hot-humid with S outh Atlantic contains the state of Florida. (The list of states included in each climate region is defined in Chapter 7, section 7.11). The U.S. Census provides historical population, and popul ation projections, by state at five-year intervals for the years 2005-2030. 10 These data were used to define annual populations for each of the intersection regions over the same period. First, the Census data were interpolated onto one-year intervals by assuming a constant rate of growth within the given fiveyear period. Next, the one-year data were aggreg ated to provide regional populations. Projections out to 2046 were constructed by a ssuming that the rate of growth in each region would remain constant for the years after 2030. The constant in each region was defined as the average of the U.S. Census growth rates for 2025 and 2030. Samp le output from this calculation is represented in Table 9.4.5, which shows the population in each area defined by the overlap of a climate region with a census division. For example, bot h the hot-dry and the rest-of-country regions overlap with the Mountain and P acific census divisions, while the West North Central census division is entirely in the hot-humid region.

Table 9.4.5 Population Projected for 2020 for Areas defined by the Overlap of Census Divisions with Climate Regions Region
Census Division Hot-Dry Hot-Humid Rest-of-Country Total
Northeast

- - 15,309,528 15,309,528

Mid-Atlantic

- - 41,825,909 41,825,909

East North Central

- - 48,208,733 48,208,733

West North Central

- - 21,246,442 21,246,442

South Atlantic

- 49,782,144 18,659,882 68,442,026

East South Central

- 14,554,397 4,424,431 18,978,828

West South Central

- 40,149,965

- 40,149,965

Mountain 13,993,072

- 11,563,977 25,557,049

Pacific 42,206,743

- 13,879,323 56,086,066 Total by Region 56,199,815 104,486,506 175,118,225 335,804,546

9-19Using these numbers for each census division, the fraction of its population that belongs to a given climate region can be determined. This is used to allocate housing stock to climate regions.

In a similar manner, the year-on-year change in population for each Census Division can be disaggregated onto the climate regions that overlap that Cens us Division. The disaggregation of population growth is used to allocate housing starts to climate regions.

The same coefficients are used to allocate commercial building floor space and commercial building starts to the three climate regions.

9.4.2.2 Regional New Constr uction Saturations

DOE developed residential regiona l new construction saturations from Characteristics of New Housing data from the U.S. Census Bureau. 3 The data breaks down CAC and HP saturations for single-family and multi-family ho useholds into the four Census Regions (i.e., northeast, midwest, south, and west). DOE us ed population allocation factors (as discussedpreviously) to properly allocate saturations into the three climate regions (i.e., hot-humid, hotdry, and rest-of-country). Figures 9.4.2 and 9.4. 2 depict the national and regional saturations for CACs and HPs, respectively. The regional saturations depicted in the figures below were determined using the entire U.S. housing stock. In other words, the regional saturations when summed equal the national saturation.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

YearCAC Residential New Construction Saturations Entire U.S. Rest of Country
Hot-Humid Hot-Dry

Figure 9.4.2 CAC National and Regional Saturations in Residential New Construction

9-200% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

YearHP Residential New Construction Saturations Entire U.S. Rest of Country
Hot-Humid Hot-Dry

Figure 9.4.3 HP National and Regional Saturation s in Residential New Construction

For the commercial market segment, DOE developed new construction market saturations from data in EIA’s Commercial Building Energy Consumption Survey (CBECS). 6 As noted above in section 9.2.2, DOE developed new construction saturations through the use of past CBECS surveys and commercial starts from AEO2009. The assembled data breaks down CAC and HP saturations into nine Census Divisions. DOE used population allocation factors (as discussed previously) to properly allocate saturations into the three climate regions (i.e., hothumid, hot-dry, and rest-of-country). Figures 9.4. 4 depicts the national an d regional saturations for CAC and HP equipment. The regional satura tions depicted in the Figure 9.4.4 below were determined using the entire commercial building stock. In other words, the regional saturations when summed equal the national saturation.

9-210% 1% 2% 3% 4% 5% 6%

1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035

YearCAC and HP Commercial New Construction Saturations Entire U.S.

Hot-Humid Rest of Country Hot-Dry

Figure 9.4.4 CAC and HP National and Regional Saturations in Commercial New Construction

9.5 RESULTS

This section presents the shipments forecasts for the base case and for various candidate standard levels (CSL) that DOE considered fo r each of the four CAC and HP product classes.

9.5.1 Split CAC

As noted in section 9.2.1.1, split CAC shipments are divided into coil-only and blower coil units. Figures 9.5.1 and 9.5.2 show the ba se case shipments forecasts for split system CAC coil-only and blower coil units, respectively. Shipments are broken down into each of the three regions and designated by market segment ( i.e. , new construction, replacements, and new owners). Shipments to the commercial building sector are estimated to represent only about seven percent of all prod uct shipments. Therefore, the figu res do not differentiate among units going to the residential and commercial sectors.

9-220 1 2 3 4 5 6

1 9 9 0

1 9 9 4 1998 2 0 0 2 2 0 0 6 2 0 1 0 2014 2 0 1 8 2 0 2 2 2026 2 0 3 0 2 0 3 4 2038 2042 2 0 4 6

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure 9.5.1 Forecasted Shipments (Base Case) for Split-System CACs, Coil-Only

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

1 9 9 0

1 9 9 4 1998 2 0 0 2 2 0 0 6 2 0 1 0 2014 2 0 1 8 2 0 2 2 2026 2 0 3 0 2 0 3 4 2038 2042 2 0 4 6

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure 9.5.2 Forecasted Shipments (Base Case) for Split-System CACs, Blower Coil

9-23To demonstrate the impact of higher effi ciency standards on base case shipments, the following figures focus on coil-only units, as they represent approximately 90 percent of total split CAC shipments. Figures 9.5.3 through 9.5.6 show the split CAC coil-only shipments forecasts for the base case and the standards case corresponding to the highest efficiency CSL (i.e., CSL 13 – 22 SEER) for the replacement, new owner, and new construction marketchannels, respectively. In each figure, shipments are disaggregated by climate region (HH = hothumid; HD = hot-dry; ROC = rest-of-country). Th e solid blue line represents the entire U.S. shipments forecast (i.e., the sum of the three climate regions). b

In Figure 9.5.3, representing replacement shipments, a drop in shipments occurs in the year that standards are effective (i.e., 2016) due to the consumers affected by a relative price increase (i.e., the change in total installed cost and operating costs rela tive to household income caused by the CSL). As discussed in section 9.3. 2.2, affected consumers repair their equipment rather than replace it, extending the life of the product by six years. When the extended repaired units fail after six more years, they are repla ced with new ones. The replacement of extended repairs are shown in Figure 9.5. 1 as additional shipments over the base case, i.e., six years after the effective date of the standard to account fo r CAC purchases delayed by extended repairs. For example, note the increase in shipments in the year 2022 over the base case which is six years after the effective date of the standard. Because the relative price elasticity decreases over time (as summarized in Table 9.3.1), decreases and incr eases in shipments due to extended repairs are not significant after the year 2022.

b Because DOE determined shipments for the entire U.S. independently from the shipments that were determined for each climate region, the regional shipments do not add up precisely to the national value. Because inputs to the NIA, such as product total installed cost, product annual energy consumption, and product repair and maintenance costs, have regional dependencies in addition to being a function of product efficiency, the regional level impacts when summed will differ from the impacts that are determined at the national level. For split CACs, the sum of the regional shipments for any year over the forecast period was less than 0.4 percent of the shipments determined for the nation as a whole. For the three other primary product classes, the percentage differences between the sum of the regional shipments and the shipments determined for the nation as a whole were the following: 0.4 percent for single package CAC, 1.3 percent for split HP, and 1.3 percent for single package HP.

9-240.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044millions HH

HD

ROC HH (CSL13) HD (CSL13) ROC (CSL13)

U.S.

Figure 9.5.3 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) Replacement Shipments Forecasts

9-25InFigure 9.5.4, representing new owner sh ipments, a drop in shipments occurs in the year that standards are effective (i.e., 2016) due to the change in total installed cost and operating costs caused by the CSL. As discussed in secti on 9.3.2.1, consumers affe cted by a relative price increase switch equipment and purchase a room air conditioner rather than a CAC. As shown in Figure 9.5.1, the drop in shipments to this market channel is slight.

0.00 0.50 1.00 1.50 2.00 2.50

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044millions HH

HD

ROC HH (CSL13) HD (CSL13) ROC (CSL13)

U.S.

Figure 9.5.4 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) New Owner Shipments Forecasts

9-26Figure 9.5.5 shows the shipment forecasts fo r the base case. As noted previously in section 9.1.1, the standards case shipments are identical to the base case as shipments to new constructions are assumed to be unaffected by increase in the relative price.

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044millions HH

HD

ROC

U.S.

Figure 9.5.5 Split Coil-Only CAC: Base Case New Construction Shipments Forecasts

9-27Figure 9.5.6 provides the total base case a nd CSL shipments, which are a combination of the shipments depicted from the previous three figures. Most of the decrease in shipments is due to extended repairs.

0.00 1.00 2.00 3.00 4.00 5.00 6.00

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044millions

HH
HD
ROC HH (CSL13) HD (CSL13) ROC (CSL13) U.S. (CSL13) U.S.

Figure 9.5.6 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) Total Shipments Forecasts

Table 9.5.1 summarizes the cumulative ship ments over the 30 year period starting from the assumed effective date of the standard (i.e., 2016) for the base case and each of the thirteen CSLs that DOE considered for split CACs. Cumulative shipments are shown for coil-only units, blower coil units, and total CAC shipments. Sh ipments are also disaggregated by region and sector. Also of note, the efficiency levels for CSLs 8 through 13 for coil-only units are equivalent to CSL 7 (16.5 SEER).

9-28Table 9.5.1Split CAC: Base Case and Standards Case Cumulative Shipments from 2016-2046 (millions)Base CaseCSL 1 (13.5 SEER)CSL 2 (14 SEER)CSL 3 (14.5 SEER)CSL 4 (15 SEER)CSL 5 (15.5 SEER)CSL 6 (16 SEER)RegionSectorCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalHotDryRes25.312.8128.1225.302.8128.1225.302.8128.1125.282.8128.1025.272.8128.0825.252.8128.0625.232.8128.04Com2.680.302.982.680.302.982.680.302.982.670.302.972.670.302.972.670.302.962.660.302.96HotHumidRes41.724.6546.3741.714.6546.3741.704.6546.3541.694.6546.3441.674.6546.3241.644.6546.2941.614.6546.26Com4.580.515.094.580.515.094.570.515.094.570.515.084.560.515.084.560.515.074.550.515.06Rest ofU.S.Res71.917.9979.9071.907.9979.8971.857.9979.8471.797.9979.7871.727.9879.7071.637.9879.6171.527.9879.50Com7.330.818.157.330.818.157.330.818.147.320.818.137.310.818.137.300.818.127.290.818.10EntireU.S.Res139.7115.52155.24139.7015.52155.22139.6315.52155.15139.5515.52155.07139.4515.51154.96139.3215.51154.83139.1715.51154.68Com14.321.5915.9114.311.5915.9114.301.5915.8914.291.5915.8814.271.5915.8614.251.5915.8414.231.5915.82CSL 7 (16.5 SEER)CSL 8 (17 SEER)*CSL 9 (18 SEER)*CSL 10 (19SEER)*CSL 11 (20 SEER)*CSL 12(21 SEER)*CSL 13 (22 SEER)*RegionSectorCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalCoil-OnlyBlowerCoilTotalHotDryRes25.212.8128.0225.212.8128.0225.212.8128.0225.212.8128.0225.212.8028.0225.212.8028.0125.212.8028.01Com2.660.302.952.660.302.952.660.302.952.660.302.952.660.302.952.660.292.952.660.292.95HotHumidRes41.594.6546.2441.594.6546.2441.594.6546.2341.594.6446.2341.594.6446.2341.594.6446.2341.594.6346.22Com4.540.515.054.540.515.054.540.515.054.540.515.054.540.515.054.540.515.054.540.515.05Rest ofU.S.Res71.457.9879.4271.457.9779.4271.457.9679.4171.457.9679.4071.457.9579.3971.457.9479.3871.457.9379.38Com7.280.818.107.280.818.107.280.818.097.280.818.097.280.818.097.280.818.097.280.818.09EntireU.S.Res139.0615.50154.56139.0615.50154.55139.0615.49154.54139.0615.48154.53139.0615.46154.52139.0615.45154.50139.0615.43154.49Com14.211.5915.8014.211.5915.8014.211.5815.7914.211.5815.7914.211.5815.7914.211.5815.7914.211.5715.78*CSL 7 is the maximum efficiency level for Blower Coil units. CSLs 8 -13 for Blower Coil units is equivalent to CSL 7.9-299.5.2 Single Package CAC

Figure 9.5.7 shows the base case shipments forecasts for single package CACs. Shipments are broken down into each of the three regions and designated by market segment ( i.e. , new construction, replacements, and new owners). Shipments to the commercial building sector are estimated to represent only about seve n percent of all product sh ipments. Therefore, the figures do not differentiate among units going to the residential and commercial sectors.

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

1990 1994 199 8 2002 2006 2010 2014 201 8 2022 2026 2030 2034 2 038 2042 2046

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure 9.5.7 Forecasted Shipments (Base Case) for Single Package CACs

9-30Figure 9.5.8 shows total single package CA C shipments forecasts for the base case and the standards case corresponding to the highes t efficiency CSL (i.e., CSL 7 – 16.4 SEER). Because the impact of standards on single packag e CAC shipments is similar to that exhibited for split CAC, figures disaggregating total shipments into the replacement, new owner, and new construction market channels are not provided. In the figure below, shipments are disaggregated by climate region (HH = hot-humid; HD = hot-dry; ROC = rest-of-country). The solid blue line represents the entire U.S. shipments forecast (i.e., the sum of the three climate regions).

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044millions

HH

HD

ROC HH (CSL7) HD (CSL7) ROC (CSL7) U.S. (CSL7)

U.S.

Figure 9.5.8 Single Package CAC: Base Case and CSL 7 (16.6 SEER) Total Shipments Forecasts

Table 9.5.2 summarizes the cumulative ship ments over the 30 year period starting from the assumed effective date of the standard (i.e ., 2016) for the base case and each of the seven CSLs that DOE considered for single package CACs. Shipments are disaggregated by region and sector.

9-31Table 9.5.2 Single Package CAC: Base Case and Standards Case Cumulative Shipments from 2016-2046 (millions)

Region Sector Base Case CSL 1 (13.5 SEER) CSL 2 (14 SEER) CSL 3 (14.5 SEER) CSL 4 (15 SEER) CSL 5 (15.5 SEER) CSL 6 (16 SEER) CSL 7 (16.6 SEER)

Hot-Dry Res 2.77 2.77 2.76 2.76 2.76 2.76 2.76 2.75

Com 0.29 0.29 0.29 0.29 0.29 0.29 0.29 0.28

Hot-Humid Res 4.67 4.66 4.66 4.66 4.66 4.65 4.65 4.65

Com 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50

Rest of U.S. Res 7.85 7.84 7.83 7.82 7.81 7.80 7.79 7.78

Com 0.79 0.79 0.79 0.79 0.78 0.78 0.78 0.78

Entire U.S. Res 15.35 15.34 15.33 15.31 15.30 15.29 15.27 15.26

Com 1.55 1.54 1.54 1.54 1.54 1.54 1.53 1.53

9.5.3 Split HP

Figure 9.5.9 shows the base case shipments forecasts for split system HPs. Shipments are broken down into each of the three regions and designated by market segment ( i.e. , new construction, replacements, and new owners). Shipments to the commercial building sector are estimated to represent only about seven percent of all product shipments. Therefore, the figures do not differentiate among units going to the residential and commercial sectors.

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

1990 1994 199 8 2002 2006 2010 2014 201 8 2022 2026 2030 2034 2 038 2042 2046

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure 9.5.9 Forecasted Shipments (Base Case) for Split System HPs

9-32Figure 9.5.10 shows total split HP shipments forecasts for the base case and the standards case corresponding to the highes t efficiency CSL (i.e., CSL 10 – 19.5 SEER / 10.3 HSPF). Because the impact of standards on split HP shipments is similar to that exhibited for split CAC, figures disaggregating total shipments into the replacement, new owner, and new construction market channels are not provided. In the figure below, shipments are disaggregated by climate region (HH = hot-humid; HD = hot-dry; ROC = rest-o f-country). The solid blue line represents the entire U.S. shipments forecast (i.e., the sum of the three climate regions).

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044millions

HH
HD
ROC HH (CSL10) HD (CSL10) ROC (CSL10) U.S. (CSL10)
U.S.

Figure 9.5.10 Split HP: Base Case and CSL 10 (19.5 SEER / 10.3 HSPF) Total Shipments Forecasts

Table 9.5.3 summarizes the cumulative ship ments over the 30 year period starting from the assumed effective date of the standard (i.e., 2016) for the base case and each of the ten CSLs that DOE considered for split HPs. Shipments are disaggregated by region and sector.

9-33Table 9.5.3Split HP: Base Case and Standards CaseCumulative Shipments from 2016-2046 (millions)RegionSectorBase CaseCSL 1(13.5 SEER7.85 HSPF)CSL 2(14 SEER8.0 HSPF)CSL 3(14.5 SEER8.15 HSPF)CSL 4(15 SEER8.3 HSPF)CSL 5(15.5 SEER8.45 HSPF)CSL 6(16 SEER8.6 HSPF)CSL 7(17 SEER9.1 HSPF)CSL 1(18 SEER9.6 HSPF)CSL 2(19 SEER10.1 HSPF)CSL 3(19.5 SEER10.3 HSPF)Hot-DryRes8.438.438.438.438.438.438.438.438.428.428.41Com1.161.161.161.161.161.161.151.151.151.151.14Hot-HumidRes42.4042.4042.4042.4042.3942.3942.3842.3842.3742.3542.34Com3.973.973.973.973.973.973.973.973.963.953.95Rest of U.S.Res25.2625.2625.2525.2525.2425.2325.2125.2125.1825.1525.12Com3.033.033.033.033.023.023.023.023.013.013.00Entire U.S.Res77.1277.1277.1177.1077.0877.0677.0477.0477.0076.9476.89Com8.208.208.198.198.198.188.178.178.168.148.139-349.5.4 Single Package HP

Figure 9.5.11 shows the base case shipme nts forecasts for single package HPs. Shipments are broken down into each of the three regions and designated by market segment ( i.e. , new construction, replacements, and new owners). Shipments to the commercial building sector are estimated to represent only about seve n percent of all product sh ipments. Therefore, the figures do not differentiate among units going to the residential and commercial sectors.

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50

1990

1 9 9 4 1998 2 002 200 6 2010 2014 2018 2022 2 026 2030 2034 203 8 2042 2046

YearShipments (million) Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace

Rest-of-Country

Hot-Humid

Hot-Dry

Figure 9.5.11 Forecasted Shipments (Base Case) for Single Package HPs

Figure 9.5.12 shows total single package HP shipments forecasts for the base case and the standards case corresponding to the highest ef ficiency CSL (i.e., CSL 7 – 16.4 SEER / 9.0 HSPF). Because the impact of standards on single package HP shipments is similar to that exhibited for split CAC, figures disaggregating total shipments into the replacement, new owner, and new construction market channels are not provided. In the figure below, shipments are disaggregated by climate region (HH = hot-humid ; HD = hot-dry; ROC = rest-of-country). The solid blue line represents the entire U.S. shipments forecast (i.e., the sum of the three climate regions).

9-350.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044millions

HH
HD
ROC HH (CSL7) HD (CSL7) ROC (CSL7) U.S. (CSL7)
U.S.

Figure 9.5.12 Single Package HP: Base Case a nd CSL 7 (16.4 SEER / 9.0 HSPF Total Shipments Forecasts

Table 9.5.4 summarizes the cumulative ship ments over the 30 year period starting from the assumed effective date of the standard (i.e., 2016) for the base case and each of the ten CSLs that DOE considered for single package HPs. Shipments are disaggregated by region and sector.

Table 9.5.4 Single Package HP: Base Case and Standards Case Cumulative Shipments from 2016-2046 (millions)

Region Sector Base Case CSL 1 (13.5 SEER 7.85 HSPF) CSL 2 (14 SEER 8.0 HSPF) CSL 3 (14.5 SEER 8.0 HSPF) CSL 4 (15 SEER 8.0 HSPF) CSL 5 (15.5 SEER 8.5 HSPF) CSL 6 (16 SEER 9.0 HSPF) CSL 7 (16.4 SEER 9.0 HSPF)

Hot-Dry Res 1.10 1.10 1.10 1.10 1.10 1.10 1.09 1.09

Com 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15

Hot-Humid Res 5.55 5.55 5.55 5.54 5.54 5.54 5.54 5.54

Com 0.52 0.52 0.51 0.51 0.51 0.51 0.51 0.51

Rest of U.S. Res 3.22 3.22 3.21 3.21 3.21 3.20 3.20 3.20

Com 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

Entire U.S. Res 10.00 10.00 9.99 9.99 9.98 9.97 9.97 9.96

Com 1.05 1.05 1.05 1.05 1.05 1.05 1.05 1.04

9-36REFERENCES

1 Letter to Mrs. Rachel Schmeltz, Energy Star Program Manager, E nvironmental Protection Agency from Karim Amrane, Vice Presiden t, Regulatory & Research, Air-Conditioning, Heating, and Refrigeration Institute (AHRI), “EPA Proposed Draft Energy Star Specification for Light Commercial HVAC Equipment,” Jan. 30, 2009.

2 Air-Conditioning, Heating and Refrigeration Institute. Historical shipments and shipmentweighted efficiency data submittal. December 2008.

3 Air-Conditioning, Heating and Refrigeration In stitute. Historical shipments data, 1972-1989

–

provided to Lawrence Berkeley National Laboratory.

4 U.S. Census Bureau. Characteristics of New Housing, History Tables, 2008. Washington, DC. < http://www.census.gov/const/C25Ann/c25ann2008.pdf >

5 U.S. Department of Energy-E nergy Information Administration. An Updated Annual Energy Outlook 2009 Reference Case Reflecting Provisions of the American Recovery and Reinvestment Act and Recent Changes in the Economic Outlook , April, 2009. Washington, DC. SR/OIAF/2009-03.

< http://www.eia.doe.gov/oiaf/servicer pt/stimulus/pdf/sroiaf(2009)03.pdf >

6 U.S. Department of Energy–E nergy Information Administration. Annual Energy Outlook 2009 with Projections to 2030 . March 2009. U.S. DOE–EIA: Washington, D.C. DOE/EIA

0383(2009). < http://www.eia.doe.gov/oiaf/aeo/pdf/0383(2009).pdf >

7 U.S. Department of Energy–Ene rgy Information Administration. Commercial Building Energy Consumption Survey. Washington, D.C. Surveys for 1992, 1995, 1999 and 2003.

< http://www.eia.doe.gov/emeu/cbecs />

8 S. Hymans. Consumer Durable Sp ending: Explanation and Prediction, Brookings Papers on Economic Activity , 1971. Vol. 1971, No. 1, pp. 234-239.

9 U.S. Census Bureau, Housing and H ousehold Economic Statistics Division. American Housing Survey . Washington, DC.

< http://www.census.gov/hhes/www/housing/ahs/ahs.html >

10 U.S. Census Bureau, National Popul ation Projections Released 2008. http://www.census.gov/population/www/projections/summarytables.html

9-37CHAPTER 10. NATIONAL AND REGI ONAL IMPACT ANALYSES

TABLE OF CONTENTS

10.1 INTRODUCTION

......................................................................................................... 10- 1 10.1.1 Approach

............................................................................................................ 10 -1 10.1.2 Factors Relevant to the Analysis

........................................................................ 10-2 10.2 BASE AND STANDARDS CASE EFFICIENCY DISTRIBUTIONS AND FORECASTED EFFICIENCY TRENDS

..................................................................... 10-3 10.2.1 Central Air Conditioners

.................................................................................... 10-4 10.2.1.1 Base and Standards Case Efficiencies

............................................. 10-4 10.2.1.2 Forecasted Efficien cy Trends

.......................................................... 10-6 10.2.1.3 Forecasted Efficiency Distributions

............................................... 10-10 10.2.2 Heat Pumps

...................................................................................................... 10-13 10.2.2.1 Base and Standards Case Efficiencies

........................................... 10-13 10.2.2.2 Forecasted Efficien cy Trends

........................................................ 10-16 10.2.2.3 Forecasted Efficiency Distributions

............................................... 10-21 10.3 CALCULATING NATIONAL AND REGIONAL ENERGY SAVINGS

................. 10-23 10.3.1 Definition

......................................................................................................... 10- 24 10.3.2 Inputs to Calculation

........................................................................................ 10-25 10.3.2.1 Annual Energy Consumption per Unit

.......................................... 10-25 10.3.2.2 Shipments including Equipment Switching

................................... 10-37 10.3.2.3 Equipment Stock

............................................................................ 10-41 10.3.2.4 Annual Energy Consumption

......................................................... 10-41 10.3.2.5 Site-to-Source Energy Conversion Factors

.................................... 10-41 10.4 CALCULATING NATIONAL AND REGIONAL NET PRESENT VALUE

........... 10-42 10.4.1 Definition

......................................................................................................... 10- 42 10.4.2 Inputs to Calculation

........................................................................................ 10-44 10.4.2.1 Total Installed Cost per Unit

.......................................................... 10-44 10.4.2.2 Annual Operating Cost per Unit

.................................................... 10-54 10.4.2.3 Shipments including Equipment Switching

................................... 10-62 10.4.2.4 Equipment Stock

............................................................................ 10-64 10.4.2.5 Increases in Total Annua l Installed Cost

....................................... 10-64 10.4.2.6 Savings in Total Annua l Operating Cost

....................................... 10-65 10.4.2.7 Discount Factors

............................................................................ 10-65 10.4.2.8 Present Value of Increased Installed Cost

..................................... 10-65 10.4.2.9 Present Value of Savings

............................................................... 10-66 10.5 RESULTS OF CALCULATIONS

.............................................................................. 10-66 10.5.1 Summary of Inputs

........................................................................................... 10-66 10.5.2 National and Regional Energy Savings

........................................................... 10-67 10.5.2.1 Central Air Conditioners

................................................................ 10-67 10.5.2.2 Heat Pumps

.................................................................................... 10-72 10.5.3 Calculating Annual Co st and Savings

.............................................................. 10-74 10.5.4 Net Present Values

........................................................................................... 10-75

10-i10.5.4.1 Central Air Conditioners

................................................................ 10-76 10.5.4.2 Heat Pumps

.................................................................................... 10-85

LIST OF TABLES

Table 10.2.1 Split System CAC, Coil Only Units : SEER Distributions for the Base and Standards Cases in 2016

.................................................................................... 10-5 Table 10.2.2 Split System CAC, Blower Coil Units: SEER Distributions for the Base and Standards Ca ses in 2016

.............................................................................. 10-5 Table 10.2.3 Single Package Central Air Cond itioners: SEER Distributions for the Base and Standards Ca ses in 2016

.............................................................................. 10-6 Table 10.2.4 CAC SWEF Growth Rates

................................................................................. 10-7 Table 10.2.5 Split System CAC, Coil-Only Units : Base Case Efficiency Distributions and SWEFs

....................................................................................................... 10-11 Table 10.2.6 Split System CAC, Blower Coil Un its: Base Case Efficiency Distributions and SWEFs

....................................................................................................... 10-12 Table 10.2.7 Single Package CAC: Base Case Efficiency Distributions and SWEFs

.......... 10-13 Table 10.2.8 Split System HP: Efficiency Di stributions for the Base and Standards Cases in 2016

................................................................................................... 10-16 Table 10.2.9 Single Package HP: Efficiency Distributions for the Base and Standards Cases in 2016

................................................................................................... 10-16 Table 10.2.10 Heat Pump SW EF Growth Rates

..................................................................... 10-17 Table 10.2.11 Split System HPs: SEER-based Ba se Case Efficiency Distributions and SWEFs

............................................................................................................. 10-22 Table 10.2.12 Single Package HPs: SEER-based Base Case E fficiency Distributions and SWEFs

............................................................................................................. 10-23 Table 10.3.1 Split System CAC, Coil-Only Units, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for Base and Standards Cases in 2016

.................................................................................. 10-26 Table 10.3.2 Split System CAC, Coil-Only Units, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Annual Energy Consumption for Base and St andards Cases in 2016

....................................... 10-27 Table 10.3.3 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighted Average per-Unit Annual Energy Consumption for Base and St andards Cases in 2016

....................................... 10-28 Table 10.3.4 Split System Central Air Cond itioners, Blower Coil Units: Replacement and New Owner Markets, Shipment-Weighted Average per-Unit Annual Energy Consumption for Base a nd Standards Cases in 2016

.......................... 10-29 Table 10.3.5 Single Package Central Air Conditioners: Shipment-Weighted Average per-Unit Annual Energy Consumption for Base and Standards Cases in 2016

.................................................................................................................. 10-30 Table 10.3.6 Split System Heat Pump: Shipment-Weighted Average per-Unit Annual Energy Consumption for Base a nd Standards Cases in 2016

.......................... 10-32

10-iiTable 10.3.7 Single Package Heat Pump: Sh ipment-Weighted Average per-Unit Annual Energy Consumption for Base a nd Standards Cases in 2016

.......................... 10-35 Table 10.3.8 Equipment Switching for New Own er Purchasers of Split System Heat Pumps: Shipment-Weighted Average per-Unit Annual Energy Consumption of Alternative Combination Coil-Only Split System Central Air Conditioner and Electric Furnace System for Base and Standards Cases in 2016

................................................................................................... 10-39 Table 10.3.9 Equipment Switching for New Owner Purchasers of Single Package Heat Pumps: Shipment-Weighted Average per-Unit Annual Energy Consumption of Alternative Combin ation Single Package Central Air Conditioner and Electric Fu rnace System for Base and Standards Cases in 2016

.................................................................................................................. 10-40 Table 10.3.10 Site-to-Source Conversion Factors

.................................................................. 10-42 Table 10.4.1 Split System Central Air Conditioners, Coil-Only Units, New Construction: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

............................................................. 10-45 Table 10.4.2 Split System Central Air Cond itioners, Coil-Only Units, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

...................................... 10-46 Table 10.4.3 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

............................................................. 10-47 Table 10.4.4 Split System Central Air Conditioners, Blower Coil Units, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

...................................... 10-47 Table 10.4.5 Single Package Central Air C onditioners, New Construction: ShipmentWeighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

................................................................................................... 10-49 Table 10.4.6 Single Package Central Air Conditioners, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

................................................................... 10-49 Table 10.4.7 Split System Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Total Installed Cost s for Base and Standards Cases in 2016

.................................................................................................................. 10-51 Table 10.4.8 Split System Heat Pumps, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Total Installed Costs for Base and Standards Cases in 2016

.................................................................................. 10-51 Table 10.4.9 Single Package Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Total Installed Cost s for Base and Standards Cases in 2016

.................................................................................................................. 10-53 Table 10.4.10 Single Package Heat Pumps, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Total Installed Costs for Base and Standards Cases in 2016

.................................................................................. 10-53

10-iiiTable 10.4.11 Split System Central Air C onditioners, Coil-Only Units: ShipmentWeighted Average per-Unit Repair a nd Maintenance Cost for Base and Standards Cases in 2016

.................................................................................. 10-56 Table 10.4.12 Split System Central Air Cond itioners, Blower Coil Units: ShipmentWeighted Average per-Unit Repair a nd Maintenance Cost for Base and Standards Cases in 2016

.................................................................................. 10-57 Table 10.4.13 Single Package Central Air Conditioners: Shipment-Weighted Average per-Unit Repair and Main tenance Cost for Base and Standards Cases in 2016

.................................................................................................................. 10-59 Table 10.4.14 Split System Heat Pumps: Ship ment-Weighted Average per-Unit Repair and Maintenance Costs for Base and Standards Cases in 2016

....................... 10-60 Table 10.4.15 Single Package Heat Pumps: Shipment-Weighted Average per-Unit Repair and Maintenance Costs for Base and Standards Cases in 2016

........... 10-62 Table 10.4.16 Equipment Switching for New Own er Purchasers of Split System Heat Pumps: Shipment-Weighted Average per-Unit Total Installed Costs of Alternative Combination Coil-Only Split System Central Air Conditioner and Electric Furnace System for Base and Standards Cases in 2016

.............. 10-63 Table 10.4.17 Equipment Switching for New Own er Purchasers Single Package Heat Pumps: Shipment-Weighted Average per-Unit Total Installed Costs of Alternative Combination Single Package Central Air Conditioner and Electric Furnace System for Base and Standards Cases in 2016

..................... 10-64 Table 10.5.1 Inputs to Calculations

...................................................................................... 10-6 7 Table 10.5.2 Split System Central Air Cond itioners: Cumulative Na tional and Regional Energy Savings from 2016-2046 for the Residential Sector (quads)

.............. 10-68 Table 10.5.3 Split System Central Air Cond itioners: Cumulative Na tional and Regional Energy Savings from 2016-2046 for the Commercial Sector (quads)

............. 10-69 Table 10.5.4 Split System Central Air Cond itioners: Cumulative Na tional and Regional Energy Savings from 2016-2046 for the Residential and Commercial Sectors (quads)

................................................................................................. 10-69 Table 10.5.5 Single Package Central Ai r Conditioners: Cumulative National and Regional Energy Savings from 2016-2046 (quads)

......................................... 10-71 Table 10.5.6 Split System Heat Pumps: Cu mulative National and Regional Energy Savings from 2016-2046 (quads)

..................................................................... 10-72 Table 10.5.7 Single Package Heat Pumps: Cumulative National and Regional Energy Savings from 2016-2046 (quads)

..................................................................... 10-74 Table 10.5.8 Split System Central Air Conditioners: Discounted Cumulative National and Regional NPV Results from 2016-2046 for the Residential Sector (3% Discount Rate)

................................................................................................. 10-77 Table 10.5.9 Split System Central Air Conditioners: Discounted Cumulative National and Regional NPV Results from 2016-2046 for the Commercial Sector (3% Discount Rate)

.......................................................................................... 10-77 Table 10.5.10 Split System Central Air Conditioners: Discounted Cumulative National and Regional NPV Results from 2016-2046 for the Residential and Commercial Sectors (3% Discount Rate)

........................................................ 10-78

10-ivTable 10.5.11 Split System Central Air Conditioners: Discounted Cumulative National and Regional NPV Results from 2016-2046 for the Residential Sector (7% Discount Rate)

................................................................................................. 10-80 Table 10.5.12 Split System Central Air Conditioners: Discounted Cumulative National and Regional NPV Results from 2016-2046 for the Commercial Sector (7% Discount Rate)

.......................................................................................... 10-80 Table 10.5.13 Split System Central Air Conditioners: Discounted Cumulative National and Regional NPV Results from 2016-2046 for the Residential and Commercial Sectors (7% Discount Rate)

........................................................ 10-81 Table 10.5.14 Single Package Central Ai r Conditioners: Discounted Cumulative National and Regional NPV Results from 2016-2046 (3% Discount Rate)

.... 10-83 Table 10.5.15 Single Package Central Ai r Conditioners: Discounted Cumulative National and Regional NPV Results from 2016-2046 (7% Discount Rate)

.... 10-84 Table 10.5.16 Split System Heat Pumps: Di scounted Cumulative Na tional and Regional NPV Results from 2016-2046 (3% Discount Rate)

......................................... 10-85 Table 10.5.17 Split System Heat Pumps: Di scounted Cumulative Na tional and Regional NPV Results from 2016-2046 (7% Discount Rate)

......................................... 10-87 Table 10.5.18 Single Package Heat Pump s: Discounted Cumulative National and Regional NPV Results from 2016- 2046 (3% Discount Rate)

......................... 10-88 Table 10.5.19 Single Package Heat Pump s: Discounted Cumulative National and Regional NPV Results from 2016- 2046 (7% Discount Rate)

......................... 10-89

LIST OF FIGURES

Figure 10.2.1 CAC Historical SWEFs with Linear Fits

........................................................... 10-7 Figure 10.2.2 Split System CAC, Coil Only Units: SEER-based Hi storical SWEFs and Forecasted Efficiency Trends for the Base Case and Sta ndards Cases

............. 10-8 Figure 10.2.3 Split System CAC, Blower Coil Units: SEER-based Historical SWEFs and Forecasted Efficiency Trends for Ba se Case and Sta ndards Cases

................... 10-9 Figure 10.2.4 Single Package CAC: SEER-b ased Historical SWEFs and Forecasted Efficiency Trends for the Ba se and Standard s Cases

......................................... 10-9 Figure 10.2.5 Split System HP: HSPF and SEER relationship

.............................................. 10-14 Figure 10.2.6 Single Package HP: H SPF and SEER relationship

.......................................... 10-15 Figure 10.2.7 Heat Pump Historical SWEFs based on SEER with Linear Fits

..................... 10-17 Figure 10.2.8 Split System HP: SEER-bas ed Historical SWEFs and Forecasted Efficiency Trends for the Ba se and Standard s Cases

....................................... 10-19 Figure 10.2.9 Split System HP: HSPF-based Historical SWEFs and Forecasted Efficiency Trends for the Ba se and Standard s Cases

....................................... 10-19 Figure 10.2.10 Single Package HP: SEER-b ased Historical SWEFs and Forecasted Efficiency Trends for the Ba se and Standard s Cases

....................................... 10-20 Figure 10.2.11 Single Package HP: HSPF-b ased Historical SWEFs and Forecasted Efficiency Trends for the Ba se and Standard s Cases

....................................... 10-21

10-vFigure 10.3.1 Split System CAC, Coil-Only Units, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period ............. 10-27 Figure 10.3.2 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighted Average per-Unit Annual Energy Consumption for the Base Case a nd Three Standards Cases over the 2016­ 2046 Forecast Period........................................................................................ 10-29 Figure 10.3.3 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period ............. 10-31 Figure 10.3.4 Split System Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Annual Cooling Energy Consumption for the Base Case and Three Standards Cases over th e 2016-2046 Forecast Period .................... 10-33 Figure 10.3.5 Split System Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Annual Heating Energy Consumption for the Base Case and Three Standards Cases over th e 2016-2046 Forecast Period .................... 10-34 Figure 10.3.6 Single Package Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Annual Cooling Energy Consumption for the Base Case and Two Standards Cases over th e 2016-2046 Forecast Period...................... 10-36 Figure 10.3.7 Single Package Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Annual Heating Energy Consumption for the Base Case and Two Standards Cases over th e 2016-2046 Forecast Period...................... 10-37 Figure 10.4.1 Split System Central Ai r Conditioners, Coil-Only Units, New Construction: Shipment-Weighted Average Total Installed Cost for the Base Case and Two Sta ndards Cases over the 2016-2046 Forecast Period .... 10-46 Figure 10.4.2 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighted Average Total Installed Cost for the Base Case and Three Standards Cases over the 2016-2046 Forecast Period .. 10-48 Figure 10.4.3 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average Total Installed Cost for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period ..................................... 10-50 Figure 10.4.4 Split System Heat Pumps, New Construction: Shipment-Weighted Average Total Installed Cost for the Base Case and Three Standards Cases over the 2016-2046 Forecast Period ................................................................ 10-52 Figure 10.4.5 Single Package Heat Pumps, New Construction: Shipment-Weighted Average Total Installed Cost for the Base Case and Tw o Standards Cases over the 2016-2046 Forecast Period ................................................................ 10-54 Figure 10.4.6 Split System Central Ai r Conditioners, Coil-Only Units, New Construction: Shipment-Weighte d Average Annual Repair and Maintenance Costs for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period .............................................................................. 10-56 Figure 10.4.7 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighte d Average Annual Repair and Maintenance Costs for the Base Case and Three Standards Cases over the 2016-2046 Forecast Period .............................................................................. 10-58

10-viFigure 10.4.8 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average Annual Repair and Maintenance Costs for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

............. 10-59 Figure 10.4.9 Split System Heat Pumps, New Construction: Shipment-Weighted Average Annual Repair and Maintena nce Costs for the Base Case and Three Standards Cases over th e 2016-2046 Forecast Period

........................... 10-61 Figure 10.4.10 Single Package Heat Pumps, New Construction: Shipment-Weighted Average Annual Repair and Maintena nce Costs for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

............................. 10-62 Figure 10.5.1 Split System Central Air Conditioners: Cumulative Na tional and Regional Energy Savings from 2016-2046 (quads)

........................................................ 10-70 Figure 10.5.2 Single Package Central Ai r Conditioners: Cumulative National and Regional Energy Savings from 2016-2046 (quads)

......................................... 10-71 Figure 10.5.3 Split System Heat Pumps: Cumulative National a nd Regional Energy Savings from 2016-2046 (quads)

..................................................................... 10-73 Figure 10.5.4 Single Package Heat Pumps: Cumulative National and Regional Energy Savings from 2016-2046 (quads)

..................................................................... 10-74 Figure 10.5.5 Non-Discounted Annual Increa ses in Installed Cost and Savings in Operating Cost for Split System Coil-Only Central Air Conditioners, Candidate Standard Level 2

............................................................................. 10-75 Figure 10.5.6 Split System Central Air Conditioners: Cumulative Na tional and Regional NPV from 2016-2046 (3% discount rate)

........................................................ 10-79 Figure 10.5.7 Split System Central Air Conditioners: Cumulative Na tional and Regional NPV from 2016-2046 (7% discount rate)

........................................................ 10-82 Figure 10.5.8 Single Package Central Ai r Conditioners: Cumulative National and Regional NPV from 2016-2046 (3% discount rate)

........................................ 10-83 Figure 10.5.9 Split System Central Air Conditioners: Cumulative Na tional and Regional NPV from 2016-2046 (7% discount rate)

........................................................ 10-84 Figure 10.5.10 Split System Heat Pumps: Cu mulative National and Regional NPV from 2016-2046 (3% discount rate)

.......................................................................... 10-86 Figure 10.5.11 Split System Heat Pumps: Cu mulative National and Regional NPV from 2016-2046 (7% discount rate)

.......................................................................... 10-87 Figure 10.5.12 Single Package Heat Pump s: Cumulative National and Regional NPV from 2016-2046 (3% discount rate)

................................................................. 10-89 Figure 10.5.13 Single Package Heat Pump s: Cumulative National and Regional NPV from 2016-2046 (7% discount rate)

................................................................. 10-90

10-viiCHAPTER 10. NATIONAL AND REGIONAL IMPACT ANALYSES

10.1 INTRODUCTION

This chapter describes the method that the U.S. Department of Energy (DOE) developed to estimate the energy savings, and net present value of those energy savings, that consumers would receive from potential new energy efficiency standards for residential and commercial consumers of central air cond itioners (CAC) and heat pumps (HP). Chapter 5 describes the efficiency levels, otherwise known as candidate standard levels (CSLs), for the products represented by central air cond itioners and heat pumps. This chapter examines the national energy savings (NES) attributable to each CSL, along with the energy savings specific to three regions based on climate: a hot-humid climate (the Southeast), a hot-dry climate (the Southwest), and the rest of the Nation. The results presented he re for the nation as a whole and for each of the three regions include: (1) potential energy consum ption and savings; (2) the monetary value of energy savings attributable to each CSL; (3) increased total installed costs (purchase price plus installation costs) attributable to each CSL; and (4) the net present value (NPV) of energy savings (the difference between the value of energy savings and increased total installed costs in 2008$).

DOE determined both the energy savings and NPV for each CSL considered for the product comprising central air conditioners and heat pumps. The calcula tions were performed using a Microsoft Excel spreadsheet model, which is accessible on the Internet ( http://www1.eere.energy.gov/buildings/applianc e_standards/residen tial/central_ac_hp.html ). The spreadsheet model, termed the National Impact Analysis (NIA) model, calculates energy savings and NPV for the nation and for each of the three regions (hot-humid, hot-dry, and rest of the Nation). Details regarding and instructions for using the NIA model are provided in appendix 10-A.

10.1.1 Approach

The critical factors that govern energy consumption by CAC and HPs are: (1) the quantities shipped; (2) fina ncial considerations such as consumer response to changes in total installed cost, operating expe nses, and household income; and (3) voluntary programs that promote higher-efficiency product s. Chapter 9 describes in detail the shipments model that DOE used to forecast future purchases of central air conditioners and heat pumps. Chapter 9 includes detailed descriptions of consumers’ sensitivities to total installed cost, operating expense, and income (otherwise known as elasticities), and how DOE captured those elasticities within the NIA model.

Voluntary programs increase the market share of energy efficient equipment. Between 1992 (the effective date of the first federal energy efficiency sta ndards for central air conditioners and heat pumps) and 2005, the ship ment-weighted efficiency of central air conditioners and heat pumps has grown by appr oximately one SEER point. Presumably, the

10-1efficiency increase over this time period has been due at least in part to voluntary programs. Consequently, DOE assumed that market-based initiatives would continue to have the same effect on the efficiency of product shipments as it has in the past. Details on how this effect was captured in the analysis are detailed below in section 10.2.

10.1.2 Factors Relevant to the Analysis

The product and product classe s being considered for new standards are described in detail in chapter 3. Below is a brief description of the product, product classes, and other factors that were considered in evaluating the effects of potential new energy standards.

• Product being considered:

o central air conditioners (CAC s) and heat pumps (HPs)

• Product classes with in this product: a

o split system air conditioners,

o single package air conditioners,

o split system heat pumps, and

o single package heat pumps,

• Markets:

o Central air conditioners: 93 percent used in residential settings; 7 percent used in commercial settings.

 Split systems comprise 90.4 percen t of both the residential and commercial markets.

 Single package systems represent 9.6 pe rcent of both the residential and commercial markets.

o Heat pumps: 93 percent used in residentia l settings; 7 percent used in commercial settings.

 Split systems comprise 87.7 percen t of both the residential and commercial markets.

 Single package systems represent 12.3 percent of both the residential and commercial markets.

• Channels (i.e., product placement):

o Central air conditioners are purchased for:

 new construction,

 replacements, and

 existing households and commercial building owners that do not already own the product (hereafter referred to as “new owners”).

o Heat pumps are purchased for:

 new construction,

 replacements, and

a There are three other product classes including small duct high velocity (SDHV) systems, space-constrained air conditioners, and space-constrained heat pumps which are not being analyzed for this preliminary TSD due to lack of available data and limited product offerings.

10-2 new owners.

• Effects of increased purchase price, opera ting cost savings, and household income:

o Central air conditioners: Evaluated for replacement and new owner purchases.

 For replacement purchases, effected c onsumers repair their product rather than replace it, extending the life of the product by six years.

 For new owner purchases, effected consumers purchase a room air conditioner rather than a central air conditioner.

o Heat pump: Evaluated for repla cement and new owner purchases.

 For replacement purchases, effected c onsumers repair their product rather than replace it, extending the life of the product by six years.

 For new owner purchases, effected consumers purchase a combination electric resistance furnace and central air conditioner rather than a heat

pump.

• Regional standards considered: b

o hot-humid region (consisting of states in the Southeastern U.S. including Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, a nd Texas; Hawaii is also included);

o hot-dry region (consisting of states in the Southwest including Arizona, Nevada, and New Mexico; California is also included);

o the rest of the Nation; that is, the remaining 33 states including Alaska.

• Standard Levels:

o seven levels for split system air conditione rs, coil-only units and 13 levels for split system air conditioners, blower coil units,

o seven levels for single package air conditioners,

o ten levels for split system heat pumps, and

o seven levels for single package heat pumps.

10.2 BASE AND STANDARDS CASE EFFICIENCY DISTRIBUTIONS AND

FORECASTED EFFICIENCY TRENDS

A key component of DOE’s estimates of na tional and regional energy savings and net present value (NPV) is the energy efficiency fo recasted over time for the base case (without new standards) and for each of the standards cases (with potential new standards). The forecasted efficiencies represent the annual shipment-weigh ted energy efficiency (SWEF) of the product classes under consideration from the assumed effec tive date of a new standard to 30 years after that date. Key inputs to the calculation of bot h national and regional energy savings and NPV depend on estimated energy efficiencies. Per-unit annual energy consumption, for example, is a direct function of product effici ency and dictates energy savi ngs. Chapter 6, Energy Use Determination, describes how per-unit energy consumption chan ges as a function of efficiency for each product class. With regard to the NPV, two inputs, the per-unit total installed cost and the per-unit annual operating cost , depend on efficiency. The per-un it total installed cost is a

b Regional standards are being considered in addition to standards for the Nation as a whole.

10-3direct function of efficiency because more effi cient products are assumed to be more expensive than their less efficient counterparts

. Because per-unit annual operatin g cost is a direct function of per-unit annual energy consumption, it too is dependent on product efficiency. Section 8.2.2 of chapter 8, Life-Cycle Cost (LCC) and Paybac k Period (PBP) Analysis, describes how per-unit total installed cost changes as a function of effi ciency for each product class. The above and all other inputs to the calculation of energy savi ngs and NPV are discussed in sections 10.3.2 and 10.4.2. The two sections below (sections 10.2.1 a nd 10.2.2) describe how DOE developed base and standards case efficiency distributions and forecasted efficiency trends.

As noted in section 10.1.2, DOE constructed and conducted its NIA to analyze standards for the Nation as a whole and th ree specific regions (hot-humid, hot-dry, and rest-of-country). Ideally, the base case and standards case efficiency distributions and forecasted efficiency trends would be characterized as a function of region. Unfortunately, DOE only received data at the national level. As a result, DOE assumed that the distributions and trends developed for the entire Nation are also representative for the three re gions (i.e., efficiency distributions and trends do not vary by region).

10.2.1 Central Air Conditioners

10.2.1.1 Base and Standards Case Efficiencies

For both CAC product classes—split system s and single package systems—DOE developed product efficiencies in the base case by assigning equipment to specific efficiency levels for the year 2016. In other words, DOE dete rmined the distribution of product efficiencies currently in the marketplace to develop a SEER-based SWEF for the year 2016. DOE derived its base case efficiency distributions for split system and single package CACs on SWEF data provided by AHRI in combination with the ra nge of product offerings in AHRI’s listing of certified unitary air-conditioner equipment. For more details on the derivation of the split system and single package base case efficiencies, refer to section 8.2.3.8 of chapter 8, LCC and PBP Analysis.

For its determination of sta ndards-case efficiencies, DOE a ssumed a “roll-up” scenario to establish the SWEF for the year that standard s are assumed to become effective (i.e., 2016). DOE assumed that product efficiencies in the ba se case that did not m eet the standard under consideration would “roll up” to meet the new standard level. Also, DOE assumed that all product efficiencies in the base case that were above the standard under consideration would not be affected.

Tables 10.2.1 and 10.2.2 present the SEER-based efficiency distributions and resulting SWEF for the base case and standards cases for split system coil-only and blower coil CACs, respectively, in the year 2016 (the assumed e ffective date of new standards). Table 10.2.3 presents the SEER-based efficiency distributions and resulting SWEF for the base case and standards cases for single package CACs in th e year 2016. Each table clearly shows how each standards case, under a “roll-up” scenari o, affects the effici ency distribution.

10-4Table 10.2.1 Split System CAC, Coil Only Units: SEER Distributions for the Base and Standards Cases in 2016

CSL SEER Market Share

Base Case Standards Case

1 2 3 4 5 6 7

Baseline 13.0 24.6%

- - - - - - - 1 13.5 56.4% 81.0%

- - - - - - 2 14.0 4.1% 4.1% 85.1%

- - - - - 3 14.5 5.4% 5.4% 5.4% 90.5%

- - - - 4 15.0 3.3% 3.3% 3.3% 3.3% 93.8%

- - - 5 15.5 2.1% 2.1% 2.1% 2.1% 2.1% 95.9%

- - 6 16.0 3.6% 3.6% 3.6% 3.6% 3.6% 3.6% 99.5%

- 7 16.5 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 100%

SWEF 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50

Table 10.2.2 Split System CAC, Blower Coil Units: SEER Distributions for the Base and Standards Cases in 2016

CSL SEER Market Share

Base Case Standards Case

1 2 3 4 5 6 7 8 9 10 11 12 13

Baseline 13.0 18.5%

- - - - - - - - - - - - - 1 13.5 42.3% 60.8%

- - - - - - - - - - - - 2 14.0 3.1% 3.1% 63.8%

- - - - - - - - - - - 3 14.5 4.0% 4.0% 4.0% 67.9%

- - - - - - - - - - 4 15.0 2.5% 2.5% 2.5% 2.5% 70.4%

- - - - - - - - - 5 15.5 1.5% 1.5% 1.5% 1.5% 1.5% 71.9%

- - - - - - - - 6 16.0 2.7% 2.7% 2.7% 2.7% 2.7% 2.7% 74.6%

- - - - - - - 7 16.5 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 75.0%

- - - - - - 8 17.0 10.0% 10.0% 10.0% 10.0% 10. 0% 10.0% 10.0% 10.0% 85.0%

- - - - - 9 18.0 7.0% 7.0% 7.0% 7.0% 7.0% 7.0% 7.0% 7.0% 7.0% 92.0% - - - - 10 19.0 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 95.0%

- - - 11 20.0 2.0% 2.0% 2.0% 2.0% 2.0% 2. 0% 2.0% 2.0% 2.0% 2.0% 2.0% 97.0%

- - 12 21.0 2.0% 2.0% 2.0% 2.0% 2.0% 2. 0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 99.0%

- 13 22.0 1.0% 1.0% 1.0% 1.0% 1.0% 1. 0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 100%

SWEF 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00

10-5Table 10.2.3 Single Package Central Air Conditioners: SEER Distributions for the Base and Standards Cases in 2016

CSL SEER Market Share

Base Case Standards Case

1 2 3 4 5 6 7

Baseline 13.0 75%

- - - - - - - 1 13.5 20% 95%

- - - - - - 2 14.0 2% 2% 97%

- - - - - 3 14.5 2% 2% 2% 99%

- - - - 4 15.0 1% 1% 1% 1% 100%

- - - 5 15.5 0% 0% 0% 0% 0% 100% - - 6 16.0 0% 0% 0% 0% 0% 0% 100% - 7 16.6 0% 0% 0% 0% 0% 0% 0% 100%

SWEF 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60

10.2.1.2 Forecasted Efficiency Trends

Historical Efficiency Trends
Using the SWEF for the year 2016 as a starting point, DOE developed base-case forecasted efficiency trends based on assumpti ons regarding future efficiency growth. To estimate SWEFs over the 30 year forecast sp anning 2016–2046, DOE reviewed historical SWEF data provided by the Air-Conditioning, Heating, and Refrigeration Institute (AHRI) spanning the years 1992 to 2008. 1 Between 1992, the year in which the first set of standards for CAC and HPs became effective, and 2006, when an updated se t of standards became effective, the SWEFs for CACs grew by approximately one SEER point. Figure 10.2.1 shows the SWEFs for split system and single package CACs. The figure also presents the linear fit to each product class’ SWEF data series. The linear fits have high coefficients of determination, i.e., linear fits provide a good estimate of the SWEF growth rate. Table 10.2.1 provides a summary of the SWEF growth rates for each product class.

10-6Split A/C SEER = 0.0703 * year - 129.65
R2 = 0.9633

Package A/C SEER = 0.0778 * year - 144.78
R2 = 0.9455

10.0 10.2 10.4 10.6 10.8 11.0 11.2 11.4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

YearShipment-Weighted SEER Split A/C Package A/C Linear (Split A/C) Linear (Package A/C)

Figure 10.2.1 CAC Historical SWEFs with Linear Fits

Table 10.2.4 CAC SWEF Growth Rates

SWEF Growth Rate

Product Class SEER increase per year Split System Air Conditioners 0.0703 Single Package Air Conditioners 0.0778

Base Case Efficiency Trends
Because various market-pull programs such as Energy Star and utility rebate programs were in existence from 1992 to 2005, the SWEF grow th rate evident in th e historical data was likely due in part to these market-pull programs. As a result, DOE applied the SWEF growth rates in Table 10.2.4 to the base case SWEFs in 2016 to forecast annual SWEFs for the CAC product classes from 2016 to 2046. Application of the SWEF growth rates in this manner assumes that future market-pull programs will be as effective at increasing product efficiency as past programs.

Standards Case E fficiency Trends
To develop standards case forecasted SWEFs, DOE developed growth trends for each candidate standard level that maintained the same per-unit average total installed cost difference for the year 2016 between the base case and each standards case over the entire forecast period (2016–2046). DOE’s approach for developing st andards case SWEFs in this manner assumes

10-7that the rate of adoption of more efficient pr oducts under the standards case can occur only at a rate which ensures that the average total installed cost difference between the standards case and base case over the entire forecast period is held co nstant. Because the total installed cost versus efficiency relationship for each product class dem onstrates an increasing cost rate for more efficient products, the SWEF growth rate for each standards case is lower than the SWEF growth rate for the base case.

Depicting Base Case and Stan dards Case Effi ciency Trends
Figures 10.2.2 and 10.2.3 show the SEER-based base case historical SWEFs, the base case forecasted efficiency tre nd, and each standards case forecasted efficiency trend for split system coil-only and blower coil CACs, resp ectively. Figure 10.2.4 shows the SEER-based SWEFs for single package CACs. Looking at ea ch figure closely, it can be seen that the standards case SWEF growth rates are slightly lower than the SWEF growth rate for the base case. Note that for some standards cases, the efficiency trend does not increase past the Max Tech level. The Max Tech levels for split sy stem coil-only and blower coil units are 16.5 SEER and 22 SEER, respectively. The Max Tech leve l for single package units is 16.6 SEER.

10 11 12 13 14 15 16 17

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045

YearSWEF (SEER) Base Case

CSL 1: 13.5 SEER

CSL 2: 14 SEER

CSL 3: 14.5 SEER

CSL 4: 15 SEER

CSL 5: 15.5 SEER

CSL 6: 16 SEER

CSL 7: 16.5 SEER

Figure 10.2.2 Split System CAC, Coil Only Units: SEER-based Historical SWEFs and Forecasted Efficiency Trends for the Base Case and Standards Cases

10-8SWEF (SEER) 22

21

20

19

18

17

16

15

14

13

12

11

10

1990 Base Case CSL 1: 13.5 SEER
CSL 2: 14 SEER CSL 3: 14.5 SEER
CSL 4: 15 SEER CSL 5: 15.5 SEER
CSL 6: 16 SEER CSL 7: 16.5 SEER
CSL 8: 17 SEER CSL 9: 18 SEER
CSl 10: 19 SEER CSL 11: 20 SEER
CSL 12: 21 SEER CSL 13: 22 SEER

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045

Year
Figure 10.2.3 Split System CAC, Blower Coil Units: SEER-based Historical SWEFs and Forecasted Efficiency Trends for Base Case and Standards Cases

17
Base Case
CSL 1: 13.5 SEER 16 CSL 2: 14 SEER
CSL 3: 14.5 SEER 15 CSL 4: 15 SEERSWEF (SEER)

13 14 CSL 5: 15.5 SEER

CSL 6: 16 SEER
CSL 7: 16.6 SEER

12

11

10

1990 1995 2000 2005 2010 2015 2020

Year 2025 2030 2035 2040 2045

Figure 10.2.4 Single Package CAC: SEER-based Historical SWEFs and Forecasted Efficiency Trends for the Base and Standards Cases

10-910.2.1.3 Forecasted Efficiency Distributions

Once DOE developed base case and standa rds case efficiency trends, it derived a distribution of product efficiencies from the forecasted SWEFs for each year of the analysis period (2016–2046) by developing appr opriate market shares for the various standard levels.

As specified in Tables 10.2.1, 10.2.2, and 10.2.3, DOE developed the product efficiency distributions for the year the standard is assu med to become effective (2016) using a “roll-up” scenario. For subsequent years (2017–2046), DOE a ssigned the market shares to the standard levels so that the resulting calculated SWEF remained equal to the forecasted SWEF. This assignment was conducted by pulling market shar es from lower efficiency levels to higher efficiency levels until the calculated SWEF equaled the forecasted value.

Tables 10.2.4 and 10.2.5 provide examples of forecasted efficiency distributions—the specific cases of the forecasted e fficiency distributions for the base case (without standards) for split system coil-only and blower coil central air conditioners, respectively. As an example for single package central air conditioners, Ta ble 10.2.6 provides the forecasted efficiency distributions for the base case. The tables also provide the resulting SWEF for each year during the forecast period. The NIA spre adsheet (detailed in Appendix 10-A) provides the forecasted efficiency distributions for all the standards cases for both split system and single package CACs.

10-10Table 10.2.5 Split System CAC, Coil-Only Units: Base Case Efficiency Distributions and SWEFs

Year Market Shares by SEER Level

SWEF 13 13.5 14 14.5 15 15.5 16 16.5

2016 24.6% 56.4% 4.1% 5.4% 3.3% 2.1% 3.6% 0.5% 13.65

2017 10.6% 70.5% 4.1% 5.4% 3.3% 2.1% 3.6% 0.5% 13.72

2018 0.0% 77.5% 7.6% 5.4% 3.3% 2.1% 3.6% 0.5% 13.79

2019 0.0% 63.5% 21.7% 5.4% 3.3% 2.1% 3.6% 0.5% 13.86

2020 0.0% 49.4% 35.7% 5.4% 3.3% 2.1% 3.6% 0.5% 13.93

2021 0.0% 35.3% 49.8% 5.4% 3.3% 2.1% 3.6% 0.5% 14.00

2022 0.0% 21.3% 63.9% 5.4% 3.3% 2.1% 3.6% 0.5% 14.07

2023 0.0% 7.2% 77.9% 5.4% 3.3% 2.1% 3.6% 0.5% 14.14

2024 0.0% 0.0% 78.3% 12.3% 3.3% 2.1% 3.6% 0.5% 14.21

2025 0.0% 0.0% 64.2% 26.3% 3.3% 2.1% 3.6% 0.5% 14.28

2026 0.0% 0.0% 50.1% 40.4% 3.3% 2.1% 3.6% 0.5% 14.35

2027 0.0% 0.0% 36.1% 54.4% 3.3% 2.1% 3.6% 0.5% 14.42

2028 0.0% 0.0% 22.0% 68.5% 3.3% 2.1% 3.6% 0.5% 14.49

2029 0.0% 0.0% 7.9% 82.6% 3.3% 2.1% 3.6% 0.5% 14.56

2030 0.0% 0.0% 0.0% 84.4% 9.5% 2.1% 3.6% 0.5% 14.63

2031 0.0% 0.0% 0.0% 70.3% 23.5% 2.1% 3.6% 0.5% 14.70

2032 0.0% 0.0% 0.0% 56.3% 37.6% 2.1% 3.6% 0.5% 14.77

2033 0.0% 0.0% 0.0% 42.2% 51.6% 2.1% 3.6% 0.5% 14.84

2034 0.0% 0.0% 0.0% 28.1% 65.7% 2.1% 3.6% 0.5% 14.91

2035 0.0% 0.0% 0.0% 14.1% 79.8% 2.1% 3.6% 0.5% 14.98

2036 0.0% 0.0% 0.0% 0.0% 93.8% 2.1% 3.6% 0.5% 15.05

2037 0.0% 0.0% 0.0% 0.0% 79.8% 16.1% 3.6% 0.5% 15.12

2038 0.0% 0.0% 0.0% 0.0% 65.7% 30.2% 3.6% 0.5% 15.19

2039 0.0% 0.0% 0.0% 0.0% 51.7% 44.2% 3.6% 0.5% 15.26

2040 0.0% 0.0% 0.0% 0.0% 37.6% 58.3% 3.6% 0.5% 15.34

2041 0.0% 0.0% 0.0% 0.0% 23.5% 72.4% 3.6% 0.5% 15.41

2042 0.0% 0.0% 0.0% 0.0% 9.5% 86.4% 3.6% 0.5% 15.48

2043 0.0% 0.0% 0.0% 0.0% 0.0% 91.3% 8.2% 0.5% 15.55

2044 0.0% 0.0% 0.0% 0.0% 0.0% 77.2% 22.2% 0.5% 15.62

2045 0.0% 0.0% 0.0% 0.0% 0.0% 63.2% 36.3% 0.5% 15.69

2046 0.0% 0.0% 0.0% 0.0% 0.0% 49.1% 50.4% 0.5% 15.76

10-11Table 10.2.6 Split System CAC, Blower Coil Units: Base Case Efficiency Distributions and SWEFs

Year Market Shares by SEER Level

SWEF 13 13.5 14 14.5 15 15.5 16 16.5 17 18 19 20 21 22

2016 18.5% 42.3% 3.1% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 14.81

2017 4.4% 56.4% 3.1% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 14.88

2018 0.0% 51.1% 12.7% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 14.95

2019 0.0% 37.0% 26.8% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.02

2020 0.0% 23.0% 40.9% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.09

2021 0.0% 8.9% 54.9% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.16

2022 0.0% 0.0% 58.7% 9.2% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.23

2023 0.0% 0.0% 44.6% 23.3% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.30

2024 0.0% 0.0% 30.6% 37.3% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.37

2025 0.0% 0.0% 16.5% 51.4% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.44

2026 0.0% 0.0% 2.4% 65.4% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.51

2027 0.0% 0.0% 0.0% 56.3% 14.1% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.58

2028 0.0% 0.0% 0.0% 42.2% 28.2% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.65

2029 0.0% 0.0% 0.0% 28.1% 42.2% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.72

2030 0.0% 0.0% 0.0% 14.1% 56.3% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.79

2031 0.0% 0.0% 0.0% 0.0% 70.4% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.86

2032 0.0% 0.0% 0.0% 0.0% 56.3% 15.6% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.93

2033 0.0% 0.0% 0.0% 0.0% 42.3% 29.7% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.00

2034 0.0% 0.0% 0.0% 0.0% 28.2% 43.7% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.07

2035 0.0% 0.0% 0.0% 0.0% 14.1% 57.8% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.14

2036 0.0% 0.0% 0.0% 0.0% 0.1% 71.8% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.21

2037 0.0% 0.0% 0.0% 0.0% 0.0% 57.9% 16.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.28

2038 0.0% 0.0% 0.0% 0.0% 0.0% 43.9% 30.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.35

2039 0.0% 0.0% 0.0% 0.0% 0.0% 29.8% 44.8% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.42

2040 0.0% 0.0% 0.0% 0.0% 0.0% 15.7% 58.9% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.49

2041 0.0% 0.0% 0.0% 0.0% 0.0% 1.7% 72.9% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.56

2042 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 62.2% 12.8% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.63

2043 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 48.2% 26.8% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.70

2044 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 34.1% 40.9% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.77

2045 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 20.0% 55.0% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.84

2046 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 6.0% 69.0% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.92

10-12Table 10.2.7 Single Package CAC: Base Case Efficiency Distributions and SWEFs

Year Market Share by SEER Level

SWEF 13 13.5 14 14.5 15 15.5 16 16.6

2016 75.0% 20.0% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.17

2017 59.4% 35.6% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.25

2018 43.9% 51.1% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.33

2019 28.3% 66.7% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.40

2020 12.8% 82.2% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.48

2021 0.0% 92.2% 4.8% 2.0% 1.0% 0.0% 0.0% 0.0% 13.56

2022 0.0% 76.6% 20.4% 2.0% 1.0% 0.0% 0.0% 0.0% 13.64

2023 0.0% 61.1% 35.9% 2.0% 1.0% 0.0% 0.0% 0.0% 13.71

2024 0.0% 45.5% 51.5% 2.0% 1.0% 0.0% 0.0% 0.0% 13.79

2025 0.0% 30.0% 67.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.87

2026 0.0% 14.4% 82.6% 2.0% 1.0% 0.0% 0.0% 0.0% 13.95

2027 0.0% 0.0% 95.8% 3.2% 1.0% 0.0% 0.0% 0.0% 14.03

2028 0.0% 0.0% 80.3% 18.7% 1.0% 0.0% 0.0% 0.0% 14.10

2029 0.0% 0.0% 64.7% 34.3% 1.0% 0.0% 0.0% 0.0% 14.18

2030 0.0% 0.0% 49.2% 49.8% 1.0% 0.0% 0.0% 0.0% 14.26

2031 0.0% 0.0% 33.6% 65.4% 1.0% 0.0% 0.0% 0.0% 14.34

2032 0.0% 0.0% 18.0% 81.0% 1.0% 0.0% 0.0% 0.0% 14.41

2033 0.0% 0.0% 2.5% 96.5% 1.0% 0.0% 0.0% 0.0% 14.49

2034 0.0% 0.0% 0.0% 85.9% 14.1% 0.0% 0.0% 0.0% 14.57

2035 0.0% 0.0% 0.0% 70.4% 29.6% 0.0% 0.0% 0.0% 14.65

2036 0.0% 0.0% 0.0% 54.8% 45.2% 0.0% 0.0% 0.0% 14.73

2037 0.0% 0.0% 0.0% 39.3% 60.7% 0.0% 0.0% 0.0% 14.80

2038 0.0% 0.0% 0.0% 23.7% 76.3% 0.0% 0.0% 0.0% 14.88

2039 0.0% 0.0% 0.0% 8.1% 91.9% 0.0% 0.0% 0.0% 14.96

2040 0.0% 0.0% 0.0% 0.0% 92.6% 7.4% 0.0% 0.0% 15.04

2041 0.0% 0.0% 0.0% 0.0% 77.0% 23.0% 0.0% 0.0% 15.11

2042 0.0% 0.0% 0.0% 0.0% 61.5% 38.5% 0.0% 0.0% 15.19

2043 0.0% 0.0% 0.0% 0.0% 45.9% 54.1% 0.0% 0.0% 15.27

2044 0.0% 0.0% 0.0% 0.0% 30.3% 69.7% 0.0% 0.0% 15.35

2045 0.0% 0.0% 0.0% 0.0% 14.8% 85.2% 0.0% 0.0% 15.43

2046 0.0% 0.0% 0.0% 0.0% 0.0% 99.2% 0.8% 0.0% 15.50

10.2.2 Heat Pumps

10.2.2.1 Base and Standards Case Efficiencies

For both HP product classes—split systems and single package systems—DOE developed product efficiencies in the base case by assigning equipment to specific efficiency

10-13levels for the year 2016. In other words, DOE de termined the distribution of product efficiencies currently in the marketplace to develop a SEER-based SWEF for the year 2016. DOE derived its base-case efficiency distributions for split system and single package HPs on SWEF data provided by AHRI in combination with the ra nge of product offerings in AHRI’s listing of certified unitary HP equipment. For more details on the derivation of the split system and single package base case efficiencies, refer to section 8.2.3.8 of chapter 8, LCC and PBP Analysis.

AHRI’s SWEF data for HPs was based so lely on SEER—not HSPF. To determine HSPF-based SWEFs for the base case, DOE used the SEER and HSPF pairings presented in section 5.9.1 of chapter 5, Engineering Analysis, to define the relationship between SEER and HSPF for both split system and single package HPs. The SEER and HSPF pairings for split system HPs are graphically presented in Figure 10.2.5. As is evident from this figure, the relationship can be represented accurately with a second-order polynomial expression.

10.5

10.0

9.5

9.0

8.5

8.0

7.5

12 13 14 15 16 17 18 19 20
SEER

Figure 10.2.5 Split System HP: HSPF and SEER relationship

The SEER and HSPF pairings for single packag e HPs are graphically presented in Figure 10.2.6. For single package units, the HSPF is dependent on the following ranges of SEER:

SEER < 14, HSPF = 0.30 * SEER + 3.80;

14 ≤ SEER < 15, HSPF = 8.0;

10-14HSPF HSPF = 0.025 * SEER 2 - 0.408 * SEER + 8.78915 ≤ SEER < 16, HSPF = 1.0 * SEER + 7.00; and

SEER ≥ 16, HSPF = 9.00.HSPF 9.5

9.0

8.5

HSPF = 0.30 * SEER + 3.80
SEER < 14 HSPF = 8.00
14 < SEER < 15 HSPF = 1.00 * SEER - 7.00
15 < SEER < 16 HSPF = 9.00
SEER > 16

8.0

7.5

12 16 17

Figure 10.2.6 Single Package HP: HSPF and SEER relationship

For its determination of sta ndards-case efficiencies, DOE a ssumed a “roll-up” scenario to establish both a SEER-based and HSPF-based SWEF for the year that standards are assumed to become effective (i.e., 2016). Using the sa me method as was developed for CACs, DOE assumed that product efficiencies in the base case that did not m eet the standard under consideration would “roll up” to meet the new standard level. Also, DOE assumed that all product efficiencies in the base case that were above the standard under consideration would not be affected.

Tables 10.2.8 and 10.2.9 present the efficiency distributions and resulting SEER-based and HSPF-based SWEFs for the base case and standards cases for split system and single package HPs, respectively. Each table clearly shows how each standards case, under a “roll-up” scenario, affects the e fficiency distribution. 13 14 15
SEER

10-15Table 10.2.8 Split System HP: Efficiency Distributions for the Base and Standards Cases in 2016

CSL SEER HSPF Market Share

Base Case Standards Case

1 2 3 4 5 6 7 8 9 10

Baseline 13.0 7.7 13%

- - - - - - - - - - 1 13.5 7.9 52% 65%

- - - - - - - - - 2 14.0 8.0 10% 10% 75%

- - - - - - - - 3 14.5 8.2 9.0% 9.0% 9.0% 84%

- - - - - - - 4 15.0 8.3 5.5% 5.5% 5.5% 5.5% 89.5%

- - - - - - 5 15.5 8.5 3.5% 3.5% 3.5% 3.5% 3.5% 93%

- - - - - 6 16.0 8.6 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 96%

- - - - 7 17.0 9.1 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 98%

- - - 8 18.0 9.6 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 99.5%

- - 9 19.0 10.1 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 100%

- 10 19.5 10.3 0.0% 0.0% 0.0% 0.0% 0. 0% 0.0% 0.0% 0.0% 0.0% 0.0% 100%
SWEF (SEER) 13.97 14.03 14.36 14.73 15.15 15.60 16.07 17.03 18.01 19.00 19.50
SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8. 49 8.63 9.11 9.60 10.10 10.30

Table 10.2.9 Single Package HP: Efficiency Distributions for the Base and Standards Cases in 2016

CSL SEER HSPF Market Share

Base Case Standards Case

1 2 3 4 5 6 7

Baseline 13.0 7.7 50%

- - - - - - - 1 13.5 7.9 32% 82%

- - - - - - 2 14.0 8.0 11% 11% 93%

- - - - - 3 14.5 8.0 5% 5% 5% 98%

- - - - 4 15.0 8.0 2% 2% 2% 2% 100% - - - 5 15.5 8.5 0% 0% 0% 0% 0% 100% - - 6 16.0 9.0 0% 0% 0% 0% 0% 0% 100% - 7 16.4 9.0 0% 0% 0% 0% 0% 0% 0% 100%
SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40
SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00

10.2.2.2 Forecasted Efficiency Trends

Historical Efficiency Trends
Using the SWEF for the year 2016 as a starting point, DOE developed a SEER-based base case forecasted efficiency trend based on a ssumptions regarding future efficiency growth. To estimate SEER-based SWEFs over the 30 ye ar forecast spanning 2016–2046 (2016 being the

10-16assumed effective date of a new standard), DOE reviewed historical SWEF data provided by the Air-Conditioning, Heating, and Refrigeration Ins titute (AHRI) spanning the years 1992 to 2008. 1 Between 1992, the year in which the first set of standards for CAC and HPs became effective, and 2006, when an updated set of standards becam e effective, the SEER-based SWEFs for HPs grew by approximately one SEER point. Figu re 10.2.7 shows the SEER-based SWEFs for split system and single package HPs. The figure also presents the linear fit to each product class’ SWEF data series. The linear fits have high coefficients of determination, i.e., linear fits provide a good estimate of the SWEF growth rate. Table 10.2.10 provides a summary of the SEERbased SWEF growth rates fo r each product class.

Split HP SEER = 0.0739 * year - 136.55
R2 = 0.9594

Package HP SEER = 0.0736 * year - 136.03
R2 = 0.8886

10.2 10.4 10.6 10.8 11.0 11.2 11.4 11.6 11.8

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

YearShipment-Weighted SEER Split HP Package HP Linear (Split HP) Linear (Package HP)

Figure 10.2.7 Heat Pump Historical SWEFs base d on SEER with Linear Fits

Table 10.2.10 Heat Pump SWEF Growth Rates

SWEF Growth Rate

Product Class SEER increase per year Split System Heat Pumps 0.0739 Single Package Heat Pumps 0.0736

Base Case Efficiency Trends
Because various market-pull programs such as Energy Star and utility rebate programs were in existence from 1992 to 2005, the SEER-based SWEF growth rate evident in the historical data was likely due in part to these market-pull programs. As a result, DOE applied the SEER-based SWEF growth rates in Table 10.2.6 to the SWEFs in 2016 to forecast annual

10-17SEER-based SWEFs for the HP product classes from 2016 to 2046. Application of the SWEF growth rates in this manner assumes that future market-pull programs will be as effective at increasing product efficiency as past programs.

Standards Case E fficiency Trends
To develop standards case forecasted S EER-based SWEFs, DOE developed growth trends for each candidate standard level that maintained the same per-unit average total installed cost difference for the year 2016 between the ba se case and each standards case over the entire forecast period (2016–2046). DOE’s approach fo r developing standards case SWEFs assumes that the rate of adoption of more efficient pr oducts under the standards case can occur only at a rate which ensures that the average total installed cost difference between the standards case and base case over the entire forecast period is held co nstant. Because the total installed cost versus efficiency relationship for each product class dem onstrates an increasing cost rate for more efficient products, the SEER-based SWEF growth rate for each standards case is lower than the SEER-based SWEF growth rate for the base case.

Depicting Base Case and Stan dards Case Effi ciency Trends
Figures 10.2.8 and 10.2.9 show the base case hi storical SWEFs, the base case forecasted efficiency trend, and each standards case forecast ed efficiency trend for split system HP SEER and HSPF, respectively. The HSPF-based SWEF s were derived from the SEER-based SWEFs using the SEER and HSPF relationship for sp lit systems presented in section 10.2.2.1. Looking at Figure 10.2.8 closely, it can be seen that th e standards case SEER-based SWEF growth rates are slightly lower than the SWEF growth rate fo r the base case. Note that for some standards cases, the efficiency trend does not increase past the Max Tech level. The Max Tech level for split systems is 19.5 SEER and 10.3 HSPF.

10-18SWEF (SEER) 20

19

18

17

16

15

14

13

12

11

10

1990 Base Case

CSL 1: 13.5 SEER

CSL 2: 14 SEER

CSL 3: 14.5 SEER

CSL 4: 15 SEER

CSL 5: 15.5 SEER

CSL 6: 16 SEER

CSL 7: 17 SEER

CSL 8: 18 SEER

CSl 9: 19 SEER

CSL 10: 19.5 SEER

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045

Year Figure 10.2.8 Split System HP: SEER-based Historical SWEFs and Forecasted Efficiency Trends for the Base and Standards Cases

10.5 Base Case

CSL 1: 13.5 SEER 10.0 CSL 2: 14 SEER

CSL 3: 14.5 SEER 9.5SWEF (HSPF)
9.0

8.5

8.0

7.5

7.0

1990 CSL 4: 15 SEER

CSL 5: 15.5 SEER

CSL 6: 16 SEER

CSL 7: 17 SEER

CSL 8: 18 SEER

CSl 9: 19 SEER

CSL 10: 19.5 SEER

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045

Year Figure 10.2.9 Split System HP: HSPF-based Historical SWEFs and Forecasted Efficiency Trends for the Base and Standards Cases

10-19Figures 10.2.10 and 10.2.11 show the base case historical SWEFs, the base case forecasted efficiency trend, and each standards case forecasted efficiency trend for single package HP SEER and HSPF, respectively. The HSPF-based SWEFs were derived from the SEER-based SWEFs using the SEER and HSPF re lationship for single package units presented in section 10.2.2.1. Looking at Figure 10.2.10 closely, it can be seen that the standards case SEER-based SWEF growth rates are slightly lower than the SWEF growth rate for the base case. Note that for some standards cases, the efficiency trend does not increase past the Max Tech level. The Max Tech level for single package units is 16.4 SEER and 0.9 HSPF.

10 11 12 13 14 15 16 17

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045

YearSWEF (SEER) Base Case

CSL 1: 13.5 SEER

CSL 2: 14 SEER

CSL 3: 14.5 SEER

CSL 4: 15 SEER

CSL 5: 15.5 SEER

CSL 6: 16 SEER

CSL 7: 16.4 SEER

Figure 10.2.10 Single Package HP: SEER-based Historical SWEFs and Forecasted Efficiency Trends for the Base and Standards Cases

10-206.5 7.0 7.5 8.0 8.5 9.0

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045

YearSWEF (HSPF) Base Case
CSL 1: 13.5 SEER
CSL 2: 14 SEER
CSL 3: 14.5 SEER
CSL 4: 15 SEER
CSL 5: 15.5 SEER
CSL 6: 16 SEER
CSL 7: 16.4 SEER

Figure 10.2.11 Single Package HP: HSPF-based Historical SWEFs and Forecasted Efficiency Trends for the Base and Standards Cases

10.2.2.3 Forecasted Efficiency Distributions

Once DOE developed base case and standa rds case efficiency trends, it derived a distribution of product efficiencies from the forecasted SWEFs for each year of the analysis period (2016–2046) by developing appr opriate market shares for the various standard levels.

As specified in Tables 10.2.8 and 10.2.9, DOE developed the product efficiency distributions for the year the standard is assu med to become effective (2016) using a “roll-up” scenario. For subsequent years (2017–2046), DOE a ssigned the market shares to the standard levels so that the resulting calculated SWEF remained equal to the forecasted SWEF. This assignment was conducted by pulling market shar es from lower efficiency levels to higher efficiency levels until the calculated SWEF equaled the forecasted value.

Tables 10.2.11 and 10.2.12 provide examples of forecasted efficiency distributions—the specific cases of the forecasted SEER-based efficiency distributions for the base case (without standards) for split system and single package HPs, respectively. The tables also provide the resulting SEER-based SWEF for each year during the forecast period. The NIA spreadsheet (detailed in Appendix 10-A) provides the forecasted efficiency distributions for all the standards cases for both split system and single package HPs.

10-21Table 10.2.11 Split System HPs: SEER-based Base Case Efficiency Distributions and SWEFs

Year Market Shares by SEER Level

SWEF 13 13.5 14 14.5 15 15.5 16 17 18 19 19.5

2016 13.0% 52.0% 10.0% 9.0% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 13.97

2017 0.0% 63.2% 11.8% 9.0% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.04

2018 0.0% 48.4% 26.6% 9.0% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.12

2019 0.0% 33.7% 41.3% 9.0% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.19

2020 0.0% 18.9% 56.1% 9.0% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.26

2021 0.0% 4.1% 70.9% 9.0% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.34

2022 0.0% 0.0% 64.3% 19.7% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.41

2023 0.0% 0.0% 49.5% 34.5% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.48

2024 0.0% 0.0% 34.7% 49.3% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.56

2025 0.0% 0.0% 20.0% 64.0% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.63

2026 0.0% 0.0% 5.2% 78.8% 5.5% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.71

2027 0.0% 0.0% 0.0% 74.4% 15.1% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.78

2028 0.0% 0.0% 0.0% 59.6% 29.9% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.85

2029 0.0% 0.0% 0.0% 44.8% 44.7% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.93

2030 0.0% 0.0% 0.0% 30.0% 59.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 15.00

2031 0.0% 0.0% 0.0% 15.3% 74.2% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 15.08

2032 0.0% 0.0% 0.0% 0.5% 89.0% 3. 5% 3.0% 2.0% 1.5% 0.5% 0.0% 15.15

2033 0.0% 0.0% 0.0% 0.0% 75.2% 17. 8% 3.0% 2.0% 1.5% 0.5% 0.0% 15.22

2034 0.0% 0.0% 0.0% 0.0% 60.4% 32. 6% 3.0% 2.0% 1.5% 0.5% 0.0% 15.30

2035 0.0% 0.0% 0.0% 0.0% 45.6% 47. 4% 3.0% 2.0% 1.5% 0.5% 0.0% 15.37

2036 0.0% 0.0% 0.0% 0.0% 30.9% 62. 1% 3.0% 2.0% 1.5% 0.5% 0.0% 15.45

2037 0.0% 0.0% 0.0% 0.0% 16.1% 76. 9% 3.0% 2.0% 1.5% 0.5% 0.0% 15.52

2038 0.0% 0.0% 0.0% 0.0% 1.3% 91.7% 3.0% 2.0% 1.5% 0.5% 0.0% 15.59

2039 0.0% 0.0% 0.0% 0.0% 0.0% 79.5% 16.5% 2.0% 1.5% 0.5% 0.0% 15.67

2040 0.0% 0.0% 0.0% 0.0% 0.0% 64.7% 31.3% 2.0% 1.5% 0.5% 0.0% 15.74

2041 0.0% 0.0% 0.0% 0.0% 0.0% 49.9% 46.1% 2.0% 1.5% 0.5% 0.0% 15.82

2042 0.0% 0.0% 0.0% 0.0% 0.0% 35.2% 60.8% 2.0% 1.5% 0.5% 0.0% 15.89

2043 0.0% 0.0% 0.0% 0.0% 0.0% 20.4% 75.6% 2.0% 1.5% 0.5% 0.0% 15.96

2044 0.0% 0.0% 0.0% 0.0% 0.0% 5.6% 90.4% 2.0% 1.5% 0.5% 0.0% 16.04

2045 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 91.4% 6.6% 1.5% 0.5% 0.0% 16.11

2046 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 84.0% 14.0% 1.5% 0.5% 0.0% 16.18

10-22Table 10.2.12 Single Package HPs: SEER-based Base Case Efficiency Distributions and SWEFs

Year Market Share by SEER Level

SWEF 13 13.5 14 14.5 15 15.5 16 16.4

2016 50.0% 32.0% 11.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.39

2017 35.3% 46.7% 11.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.46

2018 20.6% 61.4% 11.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.53

2019 5.9% 76.1% 11.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.61

2020 0.0% 73.2% 19.8% 5.0% 2.0% 0.0% 0.0% 0.0% 13.68

2021 0.0% 58.4% 34.6% 5.0% 2.0% 0.0% 0.0% 0.0% 13.75

2022 0.0% 43.7% 49.3% 5.0% 2.0% 0.0% 0.0% 0.0% 13.83

2023 0.0% 29.0% 64.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.90

2024 0.0% 14.3% 78.7% 5.0% 2.0% 0.0% 0.0% 0.0% 13.97

2025 0.0% 0.0% 92.6% 5.4% 2.0% 0.0% 0.0% 0.0% 14.05

2026 0.0% 0.0% 77.9% 20.1% 2.0% 0.0% 0.0% 0.0% 14.12

2027 0.0% 0.0% 63.2% 34.8% 2.0% 0.0% 0.0% 0.0% 14.19

2028 0.0% 0.0% 48.5% 49.5% 2.0% 0.0% 0.0% 0.0% 14.27

2029 0.0% 0.0% 33.7% 64.3% 2.0% 0.0% 0.0% 0.0% 14.34

2030 0.0% 0.0% 19.0% 79.0% 2.0% 0.0% 0.0% 0.0% 14.41

2031 0.0% 0.0% 4.3% 93.7% 2.0% 0.0% 0.0% 0.0% 14.49

2032 0.0% 0.0% 0.0% 87.6% 12.4% 0.0% 0.0% 0.0% 14.56

2033 0.0% 0.0% 0.0% 72.9% 27.1% 0.0% 0.0% 0.0% 14.64

2034 0.0% 0.0% 0.0% 58.2% 41.8% 0.0% 0.0% 0.0% 14.71

2035 0.0% 0.0% 0.0% 43.5% 56.5% 0.0% 0.0% 0.0% 14.78

2036 0.0% 0.0% 0.0% 28.8% 71.2% 0.0% 0.0% 0.0% 14.86

2037 0.0% 0.0% 0.0% 14.1% 85.9% 0.0% 0.0% 0.0% 14.93

2038 0.0% 0.0% 0.0% 0.0% 99.3% 0.7% 0.0% 0.0% 15.00

2039 0.0% 0.0% 0.0% 0.0% 84.6% 15.4% 0.0% 0.0% 15.08

2040 0.0% 0.0% 0.0% 0.0% 69.9% 30.1% 0.0% 0.0% 15.15

2041 0.0% 0.0% 0.0% 0.0% 55.2% 44.8% 0.0% 0.0% 15.22

2042 0.0% 0.0% 0.0% 0.0% 40.5% 59.5% 0.0% 0.0% 15.30

2043 0.0% 0.0% 0.0% 0.0% 25.8% 74.2% 0.0% 0.0% 15.37

2044 0.0% 0.0% 0.0% 0.0% 11.1% 88.9% 0.0% 0.0% 15.44

2045 0.0% 0.0% 0.0% 0.0% 0.0% 96.4% 3.6% 0.0% 15.52

2046 0.0% 0.0% 0.0% 0.0% 0.0% 81.7% 18.3% 0.0% 15.59

10.3 CALCULATING NATIONAL AND REGIONAL ENERGY SAVINGS

This section describes DOE’s calculation of national energy savings (NES) and regional energy savings (RES) for central air conditi oners and heat pumps under various CSLs or standards cases. Similar methods are used to calcul ate energy savings for the Nation and for each

10-23of the three climate regions that are evaluated separately (hot-humid, hot-dry, and rest of the Nation).

10.3.1 Definition

As the following equation illu strates, DOE calculates annual NES and RES as the difference between two projections: a base case (without new standards) and a standards case (with new standards). Positive values of NES or RES indicate energy savings (i.e., annual energy consumption ( AEC ) in the standards case is less than AEC in the base case). The calculation of annual nation energy savings ( NES y ) and annual regional energy savings ( RES y ) are represented by the following expressions.

_ NES
y = AEC natl

− base AEC natl

− std

_ REG
y = AEC
reg

− base AEC
reg

− std

Cumulative energy savings are the sum over the forecast period, which extends from a standard’s assumed effective date (2016), to 30 years after the effective date (2046), of the annual NES and annual RES for each region. This calculation is repr esented by the following equations for :

NES = 

# ∑ NES

cum y

RES

cum = 

# ∑ RES
y

DOE calculated AEC by multiplying the number or stock of a given product (by vintage) by its unit energy consumption (also by vintag e). The calculation of the national and each regional AEC is represented by the following equation:

AEC = 

# ∑ STOCK V × UEC V

DOE defined the variables in th e above expressions as follows:

AEC = annual energy consumption each year for the Nation or region in quadrillion British thermal units (Btus)—or quads—summed over vintages of the product stock, STOCK V ; NES y = national annual energy savings (quads);
RES y = regional annual energy savings (quads);
NES cum = national cumulative energy savings (quads);
RES cum = regional cumulative energy savings (quads);
STOCK V

= stock of product (millions of units) of vintage V that survive in the year for which DOE calculated annual energy consump tion (vintages range from approximately

10-24two to approximately 50 years, dependi ng on the retirement function of the product);
UEC V = annual energy consumption per produc t in kilowatt-hours (kWh); electricity consumption is converted from site energy to source energy (quads) by applying a time-dependent conversion factor; natl = designates the quantity corresponds to the Nation;

reg = designates the quantity corresponds to a region; base = designates the quantity corresponds to the base case; std = designates the quantity corresponds to the standards case;

y = year in the forecast (2016–2046); and

cum = cumulative over the forecast period (2016–2046); and
V

= year in which the product was purchased as a new unit.

The stock of equipment depends on annual shipments and the lifetime of the given product. As described in chapter 9, DOE projected shipments for the base case and standards

cases.

10.3.2 Inputs to Calculation

The inputs for calculating national and regional energy savings are:

• Average annual energy consumption per unit ( UEC ),

• shipments,

• equipment stock ( STOCK V

),

• annual energy consumption for the Nation or a give region ( AEC ), and

• site-to-source conversion factor ( src_conv ).

10.3.2.1 Annual Energy Consumption per Unit

For each product class, DOE presented th e per-unit annual energy consumption as a function of product efficiency in chapter 6, En ergy Use Determination. Because the per-unit annual energy consumption is directly depe ndent on efficiency, DOE used the shipmentsweighted energy efficiency (SWEF) of the ba se and standards cases presented in section 10.2, along with the annual energy use data presented in chapters 6 and 8, to estimate the shipmentweighted average annual per-unit energy cons umption (UEC) under the base and standards cases. The following sections describe DOE’s calculation of the shipment-weighted average annual UEC for both product classes of CAC and HPs.

Split System CACs DOE based its calculation of the annual UEC of split system CACs on data presented in chapter 6. Based on the relationship between CA C efficiency (SEER) and annual UEC, Table 10.3.1 presents the base case and standards case shipment-weighted annual UECs in the year 2016 (the assumed effective date of new standards) for new cons truction coil-only installations for the Nation and the three specific regions ( hot-humid, hot-dry, and rest-of-country). Table

10-2510.3.2 presents the same UEC data but for coil-only units installed as either replacements or for new owners. In both tables, UECs are presented for both reside ntial and commercial installations. In each table, the SWEF corre sponding to the shipment-weighted annual UEC is also provided.

To illustrate how shipment-weighted annua l UECs change over the forecast period, Figure 10.3.1 demonstrates how the UECs for ne w construction coil-only installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. Because SWEFs in the base case and each standards case were forecast ed to increase over the forecast period, the corresponding UEC decreases over time. As not ed earlier in section 10.2.1.2, DOE’s approach for forecasting standards case SWEFs assumes that the rate of adoption of more efficient products under the standards case can occur only at a rate which ensures that the shipmentweighted average total installed cost difference between the standards case and base case over the entire forecast period be held constant. Beca use the total installed cost versus efficiency relationship for split system coil-only CACs demonstrates an increasing cost rate for more efficient products, the SWEF growth rate for each standards case is lower than the SWEF growth rate for the base case. This is evident in Figu re 10.3.1 as the gap in the shipment-weighted UECs between CSL 2 and the base case decreases over time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighte d SWEF and the corresponding shipment-weighted UEC have achieved their maximum and minimum values, respectively, in the first year that the standard is assumed to become effective (2016).

Table 10.3.1 Split System CAC, Coil-Only Units, New Construction: Shipment-Weighted Average per-Unit Annual Energy Consumption for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7
SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50

Annual Energy Use (kWh/yr) Sector Region

Resid. Nation 2351 2328 2260 2193 2126 2061 2000 1939

Hot-Humid 3458 3425 3324 3226 3128 3033 2942 2853

Hot-Dry 1998 1979 1921 1864 1807 1752 1700 1648
Rest-of-Country 1252 1240 1203 1167 1132 1098 1065 1032

Comm. Nation 2338 2331 2307 2260 2210 2157 2104 2091

Hot-Humid 2637 2627 2596 2545 2490 2432 2374 2357
Hot-Dry 2403 2395 2370 2321 2269 2215 2160 2147
Rest-of-Country 2053 2048 2032 1989 1943 1896 1848 1840

10-26Table 10.3.2 Split System CAC, Coil-Only Units, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Annual Energy Consumption for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50

Annual Energy Use (kWh/yr) Sector Region

Resid. Nation 2287 2265 2199 2133 2069 2006 1945 1887

Hot-Humid 3472 3439 3338 3239 3140 3045 2953 2864

Hot-Dry 2076 2056 1996 1936 1878 1821 1766 1713
Rest-of-Country 1268 1256 1219 1182 1146 1112 1078 1046

Comm. Nation 2345 2338 2314 2267 2216 2164 2110 2098

Hot-Humid 2607 2598 2567 2516 2461 2405 2347 2331
Hot-Dry 2375 2368 2344 2295 2244 2191 2136 2123
Rest-of-Country 2050 2045 2029 1986 1941 1894 1846 1837

1800 1850 1900 1950 2000 2050 2100 2150 2200 2250 2300 2350

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Cooling Energy Use (kWh/yr) Base Case
CSL 2 (14 SEER)
CSL 7 (16.5 SER)

Figure 10.3.1 Split System CAC, Coil-Only Units, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

10-27Table 10.3.3 presents the base case and stan dards case shipment-weighted annual UECs in the year 2016 (the assumed effective date of new standards) for new construction blower coil installations for the Nation and the three speci fic regions (hot-humid, hot-dry, and rest-ofcountry). Table 10.3.4 presents the same UEC data but for blower coil units installed as either replacements or for new owners. In both tables , UECs are presented for both residential and commercial installations. In each table, the SWEF corresponding to the shipment-weighted annual UEC is also provided.

To illustrate how shipment-weighted annua l UECs change over the forecast period, Figure 10.3.2 demonstrates how the UECs for new construction blower coil installations for the base case and three standards cases (CSL 2, CSL 9, and CSL 13) change over time. For the same reasons given above for coil-only units, the gap in the shipment-weighted UECs between the CSLs and the base case decrease over time. This is not evident in CSL 13, the Max Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted UEC have achieved their maximum and minimum values, respectively, in the first year that the standard is assumed to become effective (2016).

Table 10.3.3 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighted Average per-Unit Annual Energy Consumption for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 8 9 10 11 12 13
SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16. 95 17.32 18.17 19.09 20.04 21.01 22.00

Annual Energy Use (kWh/yr) Sector Region

Resid. Nation 2229 2212 2160 2109 2059 2010 1963 1917 1874 1784 1697 1616 1541 1471

Hot-Humid 3310 3285 3207 3132 3057 2984 2914 2846 2782 2649 2519 2399 2288 2185

Hot-Dry 1906 1891 1847 1803 1760 1718 1678 1639 1602 1525 1451 1382 1318 1258
Rest-of-Cntry 1150 1142 1115 1088 1062 1037 1013 989 967 921 876 834 795 759

Comm. Nation 2287 2282 2264 2228 2190 2150 2110 2100 2091 2069 2045 2020 1995 1970

Hot-Humid 2532 2525 2502 2464 2423 2380 2336 2324 2312 2284 2253 2222 2190 2157
Hot-Dry 2306 2300 2282 2245 2207 2167 2126 2116 2106 2084 2059 2034 2008 1982
Rest-of-Cntry 1987 1984 1971 1940 1906 1870 1834 1828 1821 1806 1790 1774 1757 1740

10-28Table 10.3.4 Split System Central Air Conditioners, Blower Coil Units: Replacement and New Owner Markets, Shipment-Weighted Average per-Unit Annual Energy Consumption for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 8 9 10 11 12 13
SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16. 95 17.32 18.17 19.09 20.04 21.01 22.00

Annual Energy Use (kWh/yr) Sector Region

Resid. Nation 2167 2150 2100 2050 2001 1954 1908 1863 1821 1734 1649 1571 1498 1431

Hot-Humid 3257 3232 3156 3082 3008 2937 2868 2801 2738 2606 2479 2361 2252 2150

Hot-Dry 1933 1918 1873 1829 1785 1742 1702 1662 1624 1546 1471 1401 1336 1276
Rest-of-Cntry 1180 1171 1143 1116 1090 1064 1039 1015 992 944 898 855 816 779

Comm. Nation 2274 2269 2251 2215 2177 2138 2098 2088 2079 2057 2033 2009 1984 1959

Hot-Humid 2546 2539 2516 2477 2436 2393 2349 2337 2325 2296 2265 2234 2201 2168
Hot-Dry 2311 2305 2287 2250 2212 2172 2131 2121 2111 2088 2064 2038 2012 1986
Rest-of-Cntry 1989 1985 1973 1941 1907 1872 1836 1829 1823 1808 1792 1775 1758 1741

1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Cooling Energy Use (kWh/yr) Base Case
CSL 2 (14 SEER)
CSL 9 (18 SEER)
CSL 13 (22 SEER)

Figure 10.3.2 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighted Average per-Unit Annual Energy Consumption for the Base Case and Three Standards Cases over the 2016

- 2046 Forecast Period

10-29Central Air Conditioners —Single Package System

DOE based its calculation of the annual UEC of single p ackage CACs on data presented in chapter 6. Based on the relationship between CAC efficiency (SEER) and annual UEC, Table 10.3.5 presents the base case and standards case shipment-weighted annual UECs in the year 2016 (the assumed effective date of new standards). Unlike split systems, the UECs for single package systems do not vary based on the insta llation (i.e., new construc tion, replacement, or new owner). In the table below, UECs are presented for both residential and commercial installations. Also, the SWEF corresponding to the shipment-weighted annual UEC is also provided.

To illustrate how shipment-weighted annua l UECs change over the forecast period, Figure 10.3.3 demonstrates how the UECs for the base case and two standards cases (CSL 2 and CSL 7) change over time. For the same reasons given above for coil-only and blower coil split system central air conditioners, the gap in the shipment-weighted UECs between the CSL 2 and the base case decrease over time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and the corres ponding shipment-weighted UEC have achieved their maximum and minimum values, respectively, in the first year that the standard is assumed to become effective (2016).

Table 10.3.5 Single Package Central Air Conditioners: Shipment-Weighted Average perUnit Annual Energy Consumption for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7
SWEF (SEER) 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60

Annual Energy
Use (kWh/yr) Sector Region

Resid. Nation 2346 2280 2202 2129 2058 1992 1930 1860

Hot-Humid 3627 3525 3405 3291 3182 3080 2983 2876
Hot-Dry 2123 2063 1993 1926 1863 1803 1746 1683
Rest-of-Country 1292 1256 1213 1173 1134 1097 1063 1025

Comm. Nation 2376 2354 2327 2273 2218 2162 2106 2091

Hot-Humid 2662 2634 2598 2540 2480 2419 2359 2339
Hot-Dry 2422 2399 2370 2315 2259 2202 2145 2129
Rest-of-Country 2071 2057 2038 1989 1940 1890 1840 1830

10-301800 1900 2000 2100 2200 2300 2400

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Cooling Energy Use (kWh/yr) Base Case
CSL 2 (14 SEER)
CSL 7 (16.6 SER)

Figure 10.3.3 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

Heat Pumps—Split System

DOE based its calculation of the annual UEC of split system HPs on data presented in chapter 6. Based on the relationship between HP efficiency and annual UEC, Table 10.3.6 presents the base case and standards case sh ipment-weighted annual space-cooling and spaceheating UECs in the year 2016 (the assumed eff ective date of new standards). The UECs for split system heat pumps do not vary based on the installation (i.e., new construction, replacement, or new owner). In the table belo w, UECs are presented for both residential and commercial installations. Also, the SEER-based and HSPF-based SWEFs corresponding to the shipment-weighted annual space-cooling and sp ace-heating UECs, respectively, are also provided.

To illustrate how shipment-weighted annua l UECs change over the forecast period, Figures 10.3.4 and 10.3.5 demonstrate how the space-cooling and space-heating UECs, respectively, for the base case and three standards cases (CSL 2, CSL 7, and CSL 10) change over time. For the same reasons given above fo r split system and single package central air conditioners, the gap in the shipment-weighted UECs between the CSLs and the base case decrease over time. This is not evident in CSL 10, the Max Tech standards case, as the

10-31shipment-weighted SWEFs and the corresponding sh ipment-weighted UECs have achieved their maximum and minimum values, respectively, in the first year that the standard is assumed to become effective (2016).

Table 10.3.6 Split System Heat Pump: Shipment-Weighted Average per-Unit Annual Energy Consumption for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 8 9 10
SWEF (SEER) 13.77 13.89 14.28 14.70 15.14 15.59 16.06 17.03 18.02 19.01 19.50

SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8. 49 8.63 9.11 9.60 10.10 10.30

Cooling Annual Energy
Use (kWh/yr) Sector Region

Resid. Nation 3337 3320 3240 3154 3065 2975 2888 2725 2576 2441 2379

Hot-Humid 4109 4087 3989 3884 3773 3664 3556 3355 3172 3006 2929

Hot-Dry 4054 4033 3936 3832 3724 3615 3509 3310 3130 2966 2890

Rest-of-Country 1840 1831 1787 1740 1690 1641 1593 1503 1421 1346 1312

Comm. Nation 2366 2364 2354 2315 2271 2224 2175 2149 2123 2096 2082

Hot-Humid 2643 2640 2627 2585 2538 2488 2436 2402 2368 2333 2316

Hot-Dry 2398 2396 2386 2346 2301 2253 2204 2177 2149 2121 2107

Rest-of-Country 2070 2069 2062 2026 1986 1943 1898 1881 1863 1844 1835

Heating Annual Energy
Use (kWh/yr) Resid. Nation 1779 1775 1753 1728 1702 1674 1647 1560 1480 1407 1380

Hot-Humid 1306 1303 1287 1269 1249 1229 1209 1145 1087 1033 1013

Hot-Dry 949 946 935 922 907 893 878 832 789 750 736

Rest-of-Country 2998 2991 2953 2912 2867 2822 2776 2629 2494 2371 2325

Comm. Nation 463 463 462 463 464 465 466 464 462 459 458

Hot-Humid 215 215 215 215 215 215 216 215 213 212 212

Hot-Dry 121 121 121 121 121 121 121 121 121 120 120

Rest-of-Country 1065 1064 1062 1064 1066 1068 1070 1066 1061 1056 1053

10-322300 2500 2700 2900 3100 3300 3500

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Cooling Energy Use (kWh/yr) Base Case
CSL 2 (14 SEER)
CSL 7 (17 SEER)
CSL 10 (19.5 SEER)

Figure 10.3.4 Split System Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Annual Cooling Energy Consumption for the Base Case and Three Standards Cases over the 2016-2046 Forecast Period

10-331300 1350 1400 1450 1500 1550 1600 1650 1700 1750 1800

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Heating Energy Use (kWh/yr) Base Case CSL 2 (14 SEER) CSL 7 (17 SEER) CSL 10 (19.5 SEER)

Figure 10.3.5 Split System Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Annual Heating Energy Consumption for the Base Case and Three Standards Cases over the 2016-2046 Forecast Period

Heat Pumps—Single Package System DOE based its calculation of the annual UEC of split system heat pumps (HPs) on data presented in chapter 6. Based on the relationship between HP efficiency and annual UEC, Table 10.3.7 presents the base case and standards ca se shipment-weighted annual space-cooling and space-heating UECs in the year 2016 (the assumed effective date of new standards). The UECs for split system heat pumps do not vary base d on the installation (i .e., new construction, replacement, or new owner). In the table belo w, UECs are presented for both residential and commercial installations. Also, the SEER-based and HSPF-based SWEFs corresponding to the shipment-weighted annual space-cooling and sp ace-heating UECs, respectively, are also provided.

To illustrate how shipment-weighted annua l UECs change over the forecast period, Figures 10.3.6 and 10.3.7 demonstrate how the space-cooling and space-heating UECs, respectively, for the base case and two standards cases (CSL 2 and CSL 7) change over time. For the same reasons given above for split system heat pumps, the gap in the shipment-weighted UECs between the CSL 2 and the base case decrease over time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-wei ghted SWEFs and the corresponding shipment10-34weighted UECs have achieved their maximum and minimum values, respectively, in the first year that the standard is assumed to become effective (2016).

Table 10.3.7 Single Package Heat Pump: Shipment-Weighted Average per-Unit Annual Energy Consumption for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40
SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00

Cooling Annual Energy
Use (kWh/yr) Sector Region

Resid. Nation 3446 3380 3280 3175 3071 2972 2879 2809

Hot-Humid 4294 4212 4087 3956 3826 3703 3587 3500

Hot-Dry 4223 4143 4020 3891 3764 3642 3529 3443
Rest-of-Country 1899 1863 1808 1750 1692 1638 1587 1548

Comm. Nation 2392 2384 2372 2323 2272 2219 2167 2157

Hot-Humid 2666 2656 2640 2588 2533 2478 2422 2408
Hot-Dry 2429 2421 2408 2358 2306 2253 2200 2188
Rest-of-Country 2102 2097 2088 2044 1997 1949 1900 1893

Heating Annual Energy
Use (kWh/yr) Resid. Nation 1790 1773 1745 1745 1745 1643 1551 1551

Hot-Humid 1334 1321 1301 1301 1301 1224 1156 1156
Hot-Dry 975 965 950 950 950 894 845 845
Rest-of-Country 3056 3027 2980 2980 2980 2805 2649 2649

Comm. Nation 477 476 475 476 477 478 479 478

Hot-Humid 221 221 220 220 221 221 221 221
Hot-Dry 125 125 124 125 125 125 125 125
Rest-of-Country 1054 1052 1050 1052 1054 1057 1059 1057

10-352800 2900 3000 3100 3200 3300 3400 3500

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Cooling Energy Use (kWh/yr) Base Case
CSL 2 (14 SEER)
CSL 7 (16.4 SER)

Figure 10.3.6 Single Package Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Annual Cooling Energy Consumption for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

10-361500 1550 1600 1650 1700 1750 1800

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Heating Energy Use (kWh/yr) Base Case
CSL 2 (14 SEER)
CSL 7 (16.4 SER)

Figure 10.3.7 Single Package Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Annual Heating Energy Consumption for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

10.3.2.2 Shipments including Equipment Switching

DOE forecasted shipments for the base case and all standards cases for the Nation as a whole and for the three climate regions that we re evaluated separately (the hot-humid region, hot-dry, and rest of the Nation). An extens ive description of the methodology for conducting and generating the shipments foreca sts for all four of the product cl asses is presented in Chapter 9, Shipments Analysis.

In projecting standards case shipments, DOE analyzed the combined effects of increased total installed costs (purchase price plus insta llation costs), operating cost savings, and household income on consumer replacement and new owner purchase decisions. DOE determined that increased total installed cost is the most significant effect and impacts consumer replacement and new owner purchase decisions. As described in section 9.3 of chapter 9, DOE treated the impact of total installed cost increases on standards ca se shipments differently for the new construction, replacement, and new owner markets.

For new construction purchases of split system and single package CACs and HPs, DOE assumed consumers were unaffected by an increase in total installed cost. In other words, DOE

10-37assumed new construction ship ments under any standards case equaled new construction shipments under the base case.

For replacement purchases of split system and single package CACs and HPs, DOE assumed consumers affected by an increase in to tal installed cost would repair their equipment rather than replace it, extending th e life of the product by six years.

For new owner purchases of split system and single package CACs, DOE assumed consumers affected by an increase in total installed cost would switch equipment and purchase a room air conditioner rather than a CAC. Because room air conditioners have lower cooling capacities and lower overall annua l energy consumption than CACs, DOE did not explicitly account for the increased sales of room air conditi oners in its analysis. Doing so would have credited a standard with energy savings from displaced CAC shipments. To avoid including savings from displaced shipments to new owne rs, DOE used the shipments projection estimates for the standards cases to calculate the a nnual energy consumption in the base case.

For new owner purchases of split system and single package HPs, DOE assumed that consumers affected by an increase in total installed cost would switch equipment and purchase a combination electric resistance furnace and CAC rather than a HP. In its analysis of HP shipments in the NIA, DOE tracked purchases of electric furnaces and CACs due to decreases in shipments of HPs in order to quantify the energy impacts for consumers who were estimated to forgo purchasing a new HP. Because DOE explicitl y accounted for the energy consumption of the displaced shipments of HPs, it maintained use of the base case shipments to determine the annual energy consumption in the base case.

For the analysis of new owner purchases of split system HPs, DOE assumed that those

consumers switching equipment would purchase a combination coil-only split system CAC and electric resistance furnace. For a given split system HP standard level, DOE assumed that the efficiency of the alternative split system CAC would be equal to the SEER of the foregone HP. As a result, DOE assumed the space-cooling UEC of the alternative split system CAC was no different than the space-cooling UEC of the forgone split system HP. The exception pertains to HP standard levels of 17 SEER and greater. The alternative coil-only split system CAC has a maximum efficiency of 16.5 SEER while the split system HP has a higher maximum efficiency level of 19.5 SEER. Therefore, for split system HP standard levels of 17 SEER and higher, the efficiency of the alternative coil-only split system CAC was held at 16.5 SEER. Correspondingly, at these maximum efficiency le vels, the space-cooling UEC of the alternative split system CAC was greater than the UEC of the forgone split system HP which it was replacing. On the space-heating side, DOE assumed the UEC of the replacement electric resistance furnace had a coeffici ent of performance (COP) of 1.0 (equivalent to a 3.41 HSPF). Therefore, the electric furnace space-heating UEC was assumed to equal the space-heating UEC of the forgone HP at the base case level multiplied by the ratio of the HP efficiency at the base case level and the electric furnace efficiency. Table 10.3.8 presents the space-cooling and spaceheating UECs of the alternative coil-only split system CAC and electric furnace combination in the year 2016. UECs are provided for each of the candidate standard levels considered for split system HPs. As with the space-cooling UECs for heat pumps, the space-cooling UECs of the

10-38alternative split system CACs also decrease over the forecast period of 2016

─ 2046 because of the adoption of more efficient equipment over tim e (refer to Figure 10.3.4 for split system HPs). Because electric resi stance furnaces only have a single effi ciency (COP = 1.0), the space-heating UECs of electric furnaces remain constant over the forecast period.

Table 10.3.8 Equipment Switching for New Owner Purchasers of Split System Heat Pumps: Shipment-Weighted Average per-Unit Annual Energy Consumption of Alternative Combination Coil-Only Split System Central Air Conditioner and Electric Furnace System for Base and Standards Cases in 2016

Base Case Split Heat Pump Candidate Standard Level

1 2 3 4 5 6 7 8 9 10

Cooling Annual Energy Use (kWh/yr) Sector Region

Resid. Nation 3407 3374 3275 3178 3081 2988 2898 2728 2728 2728 2728

Hot-Humid 4195 4155 4033 3913 3794 3679 3568 3359 3359 3359 3359

Hot-Dry 4140 4100 3979 3861 3744 3630 3521 3315 3315 3315 3315

Rest-of-Country 1879 1861 1806 1753 1699 1648 1598 1505 1505 1505 1505

Comm. Nation 2385 2381 2368 2324 2276 2227 2177 2150 2150 2150 2150

Hot-Humid 2664 2659 2642 2595 2544 2492 2438 2403 2403 2403 2403

Hot-Dry 2417 2413 2400 2355 2306 2256 2205 2177 2177 2177 2177

Rest-of-Country 2086 2083 2075 2034 1990 1945 1899 1881 1881 1881 1881

Heating Annual Energy
Use (kWh/yr) Resid. Nation 4173 4173 4171 4169 4168 4168 4167 4166 4166 4166 4166

Hot-Humid 3063 3063 3062 3061 3060 3060 3059 3058 3058 3058 3058

Hot-Dry 2225 2225 2224 2224 2223 2223 2222 2222 2222 2222 2222

Rest-of-Country 7032 7032 7029 7026 7025 7023 7022 7021 7020 7020 7020

Comm. Nation 1086 1089 1100 1117 1137 1157 1178 1238 1299 1360 1384

Hot-Humid 505 506 511 519 527 536 546 573 601 629 639

Hot-Dry 283 284 287 292 297 302 307 323 339 355 362

Rest-of-Country 2496 2502 2528 2568 2612 2659 2708 2846 2985 3125 3179

For the analysis of new owner purchases of single package HPs, DOE assumed that those

consumers switching equipment would purchase a combination single package CAC and electric furnace. For a given single package HP standard level, DOE assumed that the efficiency of the alternative single package CAC woul d be equal to the SEER of the foregone HP. As a result, the space-cooling UEC of the alternative single package CAC was assumed to be no different than the space-cooling UEC of the forgone single package HP. The one exception pertains to the maximum efficiency HP standard level of 16.4 SEER. The altern ative single package CAC has a maximum efficiency of 16.6 SEER. Therefore, fo r the single package HP standard levels of 16.4 SEER, the efficiency of the alternative single package CAC was set at 16.6 SEER. Correspondingly, at the maximum efficiency leve l, the space-cooling UEC of the alternative

10-39single package CAC was slightly less than the UEC of the forgone single package HP which it was replacing. On the space-heating side, DOE assumed the UEC of the replacement electric furnace had a coefficient of pe rformance (COP) of 1.0 (equivalent to a 3.41 HSPF). Therefore, the electric furnace space-heating UEC was assumed to equal the space-heating UEC of the forgone HP at the base case level multiplied by the ratio of the HP efficiency at the base case level and the electric furnace efficiency. Table 10.3.9 presents the space-cooling and spaceheating UECs of the alternative single pack age CAC and electric furnace combination. UECs are provided for each of the candidate standard levels considered for single package HPs. As with the space-cooling UECs for heat pumps, the space-cooling UECs of the alternative single package CACs will also decrease over the forecast period of 2016

─ 2046 because of the adoption of more efficient equipment over time (refer to Figure 10.3.6 for single package HPs). Because electric resistance furnaces only have a single efficiency (COP = 1.0), the space-heating UECs of electric furnaces remain cons tant over the forecast period.

Table 10.3.9 Equipment Switching for New Owner Purchasers of Single Package Heat Pumps: Shipment-Weighted Average per-Unit Annual Energy Consumption of Alternative Combination Single Package Central Air Conditioner and Electric Furnace System for Base and Standards Cases in 2016

Base Case Single Package Candidate Standard Level

1 2 3 4 5 6 7

Cooling Annual Energy
Use (kWh/yr) Sector Region

Resid. Nation 3500 3402 3286 3176 3071 2972 2879 2809

Hot-Humid 4361 4239 4094 3957 3826 3703 3587 3500

Hot-Dry 4290 4169 4027 3892 3764 3642 3529 3443
Rest-of-Country 1929 1875 1811 1750 1692 1638 1587 1548

Comm. Nation 2400 2389 2374 2323 2272 2219 2167 2157

Hot-Humid 2676 2662 2643 2589 2533 2478 2422 2408
Hot-Dry 2438 2426 2410 2359 2306 2253 2200 2188
Rest-of-Country 2109 2101 2091 2044 1997 1949 1900 1893

Heating Annual Energy
Use (kWh/yr) Resid. Nation 4071 4092 4092 4092 4092 4092 4092 4092

Hot-Humid 3054 3050 3050 3050 3050 3050 3050 3050
Hot-Dry 2238 2228 2228 2228 2228 2228 2228 2228
Rest-of-Country 6970 6988 6987 6987 6987 6987 6987 6987

Comm. Nation 1089 1100 1115 1117 1119 1192 1264 1262

Hot-Humid 505 510 516 517 518 551 584 583
Hot-Dry 285 288 292 292 293 312 331 330
Rest-of-Country 2406 2429 2462 2467 2472 2633 2794 2788

10-4010.3.2.3 Equipment Stock

The stock of equipment in any given year depends on annual ship ments and the lifetime of a given product class. The NIA model keeps track of the number of units shipped each year. The lifetime of a unit (18.3 years for CACs and 15.5 years for heat pumps) determines how many units shipped in previous years survive in the given year. DOE assumes that products have an increasing probability of retiring as they age. The probability of survival as a function of years since purchase is termed the survival functi on. Refer to chapter 8, section 8.2.3.5 for further details on the survival functions that DOE used in its analysis.

10.3.2.4 Annual Energy Consumption

For each product class, DOE calculated na tional annual energy consumption (AEC) and AECs for each of the three climate regions being evaluated separately (the hot-humid, hot-dry, and rest of the Nation). Annual energy consum ption is the product of the AEC per unit [also termed the unit energy consumption (UEC)] and the number of units of each vintage. This method accounts for differences in UEC from year to year. The equation for determining annual energy consumption, presented in section 10.3.1, is repeated here.

AEC = 

# ∑ STOCK V × UEC V

10.3.2.5 Site-to-Source Energy Conversion Factors

In determining annual energy consumpti on for the Nation and for each of the three regions being evaluated separately, DOE initiall y calculated the annual energy consumption at the site ( i.e. , the energy in kWh consumed at the house hold or establishment). It then derived primary (source) energy from site energy cons umption by applying a conversion factor to account for losses associated with the generati on, transmission, and distri bution of electricity. The site-to-source conversion factor is a multiplicative factor used for converting site energy consumption into primary or source energy consumption, expressed in quads. DOE used annual site-to-source conversion factors based on the ve rsion of the National Energy Modeling System (NEMS) that corresponds to Energy Information Administration (EIA’s) Annual Energy Outlook 2009 ( AEO 2009 ). 2 The factors used are marginal values , which represent the response of the electrical system to an incremen tal decrease in consumption. The conversion factors change over time, in response to projected changes in generation sources (the types of power plants projected to provide electricity to the country). DOE assu med that conversion factors remain constant at 2030 values throughout the rest of forecast period. Table 10.3.10 shows the site-to-source conversion factors from 2005 to the end of the forecast period (2046).

10-41Table 10.3.10 Site-to-Source Conversion Factors

Year Electricity Btu/kWh Year Electricity Btu/kWh

2005 11,500 2011 9,737

2006 11,500 2012 9,649

2007 11,200 2013 9,649

2008 10,000 2014 8,649

2009 9,737 2015 7,324

2010 9,737 2016-2070 7,024

10.4 CALCULATING NATIONAL AND REGIONAL NET PRESENT VALUE

This section describes DOE’s calculation of the national and regional net present value (NPV) of costs and savings for the four product classes of central air conditioners and heat pumps under various candidate standards levels. Calculations were perf ormed for the national NPV and NPVs for each of the three climate regions that are evaluated separately (hot-humid, hot-dry, and the rest of the Nation).

10.4.1 Definition

The NPV is the value in the present of a time-series of costs and savings. The NPV for the Nation as a whole and the three regions evalua ted separately is descri bed by the equation:

_ NPV = PVS PVC

Where:

PVS = present value of savings in operating cost (including costs for energy, repair, and maintenance); and
PVC = present value of increase in total insta lled cost (including costs for equipment and installation).

DOE determined the PVS and PVC according to the following expressions.

PVS = 

# ∑ OCS y × DF y

PVC = 

# ∑ TIC y × DF y

DOE calculated the total annual savings in ope rating cost for the Nation as a whole and the three regions evaluated separately by multiplying the number or stock of a given product (by vintage) by its per-unit operating cost savings (also by vintage). DOE cal culated the total annual

10-42increase in installed cost for the Nation as a whole and the three regions by multiplying the number or stock of a given product (by vintage) by its per-unit total installed cost increase (also by vintage). Total annual savings in operating cost and increases in installed cost are calculated using the following equations.

OCS y = 

# ∑ STOCK V × UOCS V

TIC y = 

# ∑ STOCK V × UTIC V

DOE defined the variables in th e above expressions as follows.

OCS = total annual savings in operating cost each year summed over vintages of the product stock, STOCK V ; TIC = total annual increase in installed cost each year summed over vintages of the product stock, STOCK V ; DF = discount factor in each year;
STOCK V

= stock of product (millions of units) of vintage V that survive in the year for which DOE calculated annual energy consump tion (vintages range from approximately two to approximately 50 years, dependi ng on the retirement function of the product); UOCS V = annual per-unit savi ngs in operating cost;
UTIC V = annual total per-unit in crease in installed cost;
V

= year in which the product was purchased as a new unit; and

y = year in the forecast (2016–2046).

DOE determined the PVC for each year from the effective date of the standard until 2046. DOE determined the PVS for each year from the effective date of the standard until the year when units purchased in 2046 retire. DOE calculated costs and savings as the difference between a standards case and case without new standards (base case).

DOE calculated a discount factor from the di scount rate (7.0%) and the number of years between the “present” (2009, the year to which the sum is being discounted) and the year in which the costs and savings occur. The NPV is the sum over time of the discounted net savings.

10-4310.4.2 Inputs to Calculation

Listed below are the inputs to DOE’s calculation of the NPV of costs and savings for the Nation as a whole and the three areas evaluated separately.

• Total installed cost per unit,

• annual per-unit saving s in operation cost,

• shipments,

• equipment stock ( STOCK V

),

• total annual increases in installed cost ( TIC ),

• total annual operating cost ( OCS ),

• discount factor ( DF ),

• present value of costs ( PVC ), and

• present value of savings ( PVS ).

The total annual increase in installed cost is equal to the annual change in the total perunit installed cost (difference between base case and standards case) multiplied by the shipments forecasted for each candidate standards level. As with calculating energy savings, DOE did not use base-case shipments to calcula te total annual installed costs for all of the product classes. DOE assumed that consumers who forgo the purchase of a central air conditioner because of standards instead would purchase a room air conditioner, which will cost far less to purchase and operate. DOE used the projected shipments and stock for each candidate standard level to calculate costs. In the case of heat pumps, DOE assumed that any decrease in shipments caused by standards would result in the purchase of an electric furnace plus CAC. Thus the analysis tracked sales of electric furnaces and CACs that result from decreases in sales of heat pumps.

The annual operating cost includes energy , repair, and maintenance costs. The total annual savings in operating cost are equal to the change in the annual operating costs (difference between base case and standards case) per unit multiplied by the shipments forecasted for each candidate standards level. As with calculating total annual installed costs, DOE did not necessarily use base-case shipments to calculate savings in operating cost.

10.4.2.1 Total Installed Cost per Unit

DOE described the total per-unit installed cost for each product class as a function of product efficiency in section 8.2.2 of Chapter 8, Life-Cycle Cost and Payback Period Analysis. Because the total per-unit annual installed cost depends directly on efficiency, DOE used the shipments-weight efficiencies (SWEFs) for the base and standards cases presented in section 10.2, combined with the total installed cost pres ented in chapter 8, to estimate the shipmentsweighted total per-unit average annual installed cost under the ba se and standards cases. The following sections describe the shipments-weighted total per-unit average annual installed cost for all four product classes of centr al air conditioners and heat pumps.

10-44Central Air Conditioners—Split System DOE based its total per-unit installed cost for split system CACs on data presented in sections 8.2.2 of chapter 8. The total installe d cost includes both the purchase price and installation cost. DOE based average equipment prices on average manufacturer costs multiplied by average overall markup values. Based on th e relationship between CAC efficiency (SEER) and total installed cost presen ted in chapter 8, Tables 10.4.1 a nd 10.4.2 present the total per-unit installed cost for split system coil-only CACs based on the shipments-weighted energy factors (SWEFs) that correspond to the base case a nd each candidate standard level. Table 10.4.1 presents the base case and standards case shipment-weighted total per-unit installed costs in the year 2016 (the assumed effective date of ne w standards) for new construction coil-only installations for the Nation and the three speci fic regions (hot-humid, hot-dry, and rest-ofcountry). Table 10.4.2 presents the same total per- unit installed cost data but for coil-only units installed as either replacements or for new owners. In both tabl es, per-unit total installed costs are the same for both residential and commercial installations. In each table, the SWEF corresponding to the shipment-weighted annual pe r-unit total installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit total in stalled costs change over the forecast period, Figure 10.4.1 demonstrates how the total installed costs for new construction coil-only installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. Because SWEFs in the base case and each standards case were forecasted by DOE to increase over the forecast period, the corresponding total installed cost increases over time. As noted in earlier in section 10.2.1.2, DOE’s appr oach for forecasting standards case SWEFs assumes that the rate of adoption of more e fficient products under the standards case can occur only at a rate which ensures that the shipment-weighted average total installed cost difference between the standards case and base case over the entire forecast period is held constant. This is evident in Figure 10.4.1 as the gap in the shipme nt-weighted total insta lled cost between CSL 2 and the base case remains constant over time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted total installed cost have achieved their maximum values in the first year that the standard is assumed to become effective (2016).

Table 10.4.1 Split System Central Air Conditioners, Coil-Only Units, New Construction: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7
SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50

Total Installed Cost Region

Nation $2,943 $2,961 $3,024 $3,101 $3,192 $3,308 $3,459 $3,639

Hot-Humid $2,685 $2,702 $2,761 $2,835 $2,922 $3,032 $3,176 $3,348

Hot-Dry $3,395 $3,415 $3,485 $3,571 $3,674 $3,803 $3,972 $4,173
Rest-of-Country $2,905 $2,922 $2,982 $3,056 $3,145 $3,256 $3,402 $3,576

10-45Table 10.4.2 Split System Central Air Conditioners, Coil-Only Units, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50

Total Installed Cost Region

Nation $2,718 $2,813 $2,895 $3,015 $3,116 $3,244 $3,395 $3,609

Hot-Humid $2,464 $2,554 $2,631 $2,746 $2,843 $2,965 $3,109 $3,313

Hot-Dry $3,138 $3,244 $3,335 $3,470 $3,583 $3,726 $3,895 $4,134
Rest-of-Country $2,699 $2,790 $2,869 $2,985 $3,082 $3,206 $3,352 $3,558

$2,900 $3,000 $3,100 $3,200 $3,300 $3,400 $3,500 $3,600 $3,700

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageTotal Installed Cost ($/unit)

Base Case
CSL 2 (14 SEER)
CSL 7 (16.5 SER)

Figure 10.4.1 Split System Central Air Conditioners, Coil-Only Units, New Construction: Shipment-Weighted Average Total Insta lled Cost for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

Table 10.4.3 presents the base case and stan dards case shipment-weighted per-unit total installed costs in the year 2016 (the assumed effective date of new standards) for new construction blower coil installa tions for the Nation and the thr ee specific regions (hot-humid,

10-46hot-dry, and rest-of-country). Table 10.4.4 presents the same per-unit total in stalled cost data but for blower coil units installed as either replacem ents or for new owners. In both tables, per-unit total installed costs are the same for both residential and commercial installations. In each table, the SWEF corresponding to the shipment-weighted per-unit total installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit total in stalled costs change over the forecast period, Figure 10.4.2 demonstrates how the total installed costs for new construction blower coil installations for the base case and th ree standards cases (CSL 2, CSL 9, and CSL 13)change over time. For the same reasons given above for coil-only units, the gap in the shipmentweighted per-unit total installed costs between the CSLs and the base case are maintained over time. This is not evident in CSL 13, the Max T ech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted pe r-unit total installed cost have achieved their maximum values in the first year that the st andard is assumed to become effective (2016).

Table 10.4.3 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 8 9 10 11 12 13
SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00

Total Installed Cost Region

Nation $3,738 $3,753 $3,803 $3,859 $3,903 $3,950 $4,000 $4,053 $4,108 $4,241 $4,395 $4,565 $4,752 $4,956

Hot-Humid $3,413 $3,427 $3,475 $3,528 $3,570 $3,615 $3,663 $3,713 $3,766 $3,892 $4,039 $4,201 $4,379 $4,574
Hot-Dry $4,315 $4,332 $4,388 $4,451 $4,500 $4,553 $4,609 $4,668 $4,730 $4,879 $5,051 $5,241 $5,450 $5,679
Rest-of-Country $3,695 $3,709 $3,758 $3,811 $3,854 $3,899 $3,947 $3,998 $4,052 $4,179 $4,327 $4,491 $4,671 $4,868

Table 10.4.4 Split System Central Air Conditioners, Blower Coil Units, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 8 9 10 11 12 13
SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00

Total Installed Cost Region

Nation $4,422 $4,436 $4,482 $4,533 $4,574 $4,617 $4,663 $4,711 $4,763 $4,885 $5,026 $5,182 $5,354 $5,542

Hot-Humid $3,921 $3,935 $3,979 $4,028 $4,066 $4,107 $4,151 $4,198 $4,246 $4,363 $4,497 $4,647 $4,810 $4,990
Hot-Dry $5,119 $5,135 $5,186 $5,244 $5,289 $5,338 $5,389 $5,443 $5,500 $5,637 $5,795 $5,970 $6,162 $6,373
Rest-of-Country $4,423 $4,436 $4,480 $4,530 $4,569 $4,611 $4,655 $4,702 $4,751 $4,869 $5,005 $5,157 $5,322 $5,504

10-47$3,700 $3,800 $3,900 $4,000 $4,100 $4,200 $4,300 $4,400 $4,500 $4,600 $4,700 $4,800 $4,900 $5,000

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageTotal Installed Cost ($/unit) Base Case
CSL 2 (14 SEER)
CSL 9 (18 SEER)
CSL 13 (22 SEER)

Figure 10.4.2 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighted Average Total Installed Cost for the Base Case and Three Standards Cases over the 2016-2046 Forecast Period

Central Air Conditio ners—Single Package DOE based its total per-unit installed cost for single package central air conditioners (CACs) on data presented in sections 8.2.2 of chap ter 8. The total installed cost includes both the purchase price and installation cost. DOE based average equipment prices on average manufacturer costs multiplied by average overall markup values. Using th e relationship between CAC efficiency (SEER) and total installed cost presented in chapter 8, Table 10.4.5 presents the base case and standards case shipment-weighted total per-unit installed costs in the year 2016 (the assumed effective date of new standards) for new construc tion installations for the Nation and the three specific regions ( hot-humid, hot-dry, and rest-of-country). Table 10.4.6 presents the same total per-unit installed cost data but for units installed as either replacements or for new owners. In both tables, per-un it total installed costs are the same for both residential and commercial installations. In each table, the SWEF corresponding to the shipment-weighted annual per-unit tota l installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit total in stalled costs change over the forecast period, Figure 10.4.3 demonstrates how the total installed costs for new construction installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. For

10-48the same reasons given above for split system CA Cs, the gap in the shipment-weighted per-unit total installed costs between CSL 2 and the base case are maintained over time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted per-unit total in stalled cost have achieved their maximum values in the first year that the standard is assumed to become effective (2016).

Table 10.4.5 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 SWEF (SEER) 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60

Total Installed Cost Region

Nation $3,141 $3,244 $3,333 $3,463 $3,573 $3,712 $3,877 $4,109

Hot-Humid $2,877 $2,975 $3,059 $3,184 $3,289 $3,421 $3,578 $3,799

Hot-Dry $3,629 $3,744 $3,843 $3,989 $4,112 $4,268 $4,452 $4,712
Rest-of-Country $3,103 $3,201 $3,287 $3,413 $3,519 $3,653 $3,811 $4,035

Table 10.4.6 Single Package Central Air Conditioners, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Total Installed Cost for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7
SWEF (SEER) 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60

Total Installed Cost Region

Nation $2,718 $2,813 $2,895 $3,015 $3,116 $3,244 $3,395 $3,609

Hot-Humid $2,464 $2,554 $2,631 $2,746 $2,843 $2,965 $3,109 $3,313

Hot-Dry $3,138 $3,244 $3,335 $3,470 $3,583 $3,726 $3,895 $4,134
Rest-of-Country $2,699 $2,790 $2,869 $2,985 $3,082 $3,206 $3,352 $3,558

10-493100 3200 3300 3400 3500 3600 3700 3800 3900 4000 4100 4200

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageTotal Installed Cost ($/unit)

Base Case
CSL 2 (14 SEER)
CSL 7 (16.6 SER)

Figure 10.4.3 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average Total Installed Cost for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

Heat Pumps—Split System DOE based its total per-unit installed cost for split system heat pumps (HPs) on data presented in sections 8.2.2 of chapter 8. The tota l installed cost includes both the purchase price and installation cost. DOE base d average equipment prices on average manufacturer costs multiplied by average overall markup values. Using the relationship between HP efficiency (SEER/HSPF) and total installed co st presented in chapter 8, Table 10.4.7 presents the base case and standards case shipment-weighted total per-un it installed costs in th e year 2016 (the assumed effective date of new standards) for new construction installati ons for the Nation and the three specific regions (hot-humid, hot-dry, and rest-o f-country). Table 10.4.8 presents the same total per-unit installed cost data but fo r units installed as either repla cements or for new owners. In both tables, per-unit total installed costs are the same for both residential and commercial installations. In each table, the SWEF corre sponding to the shipment-weighted annual per-unit total installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit total in stalled costs change over the forecast period, Figure 10.4.4 demonstrates how the total installed costs for new construction installations for the base case and three standards cases (CSL 2, CSL 7, and CSL 10) change

10-50over time. For the same reasons given above fo r split system CACs, the gap in the shipmentweighted per-unit total installed costs between the CSLs and the base case are maintained over time. This is not evident in CSL 10, the Max T ech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted pe r-unit total installed cost have achieved their maximum values in the first year that the st andard is assumed to become effective (2016).

Table 10.4.7 Split System Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Total Installed Costs for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 8 9 10
SWEF (SEER) 13.77 13.89 14.28 14.70 15.14 15. 59 16.06 17.03 18.02 19.01 20.00
SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8. 49 8.63 9.11 9.60 10.10 10.30

Total Installed Cost Region

Nation $4,051 $4,063 $4,127 $4,184 $4,245 $4,316 $4,410 $4,577 $4,759 $4,957 $5,065

Hot-Humid $3,746 $3,758 $3,819 $3,873 $3,93 1 $3,998 $4,088 $4,247 $4,421 $4,610 $4,713

Hot-Dry $4,657 $4,671 $4,742 $4,806 $4,874 $4,953 $5,059 $5,245 $5,449 $5,670 $5,791
Rest-of-Country $3,986 $3,998 $4,059 $4,114 $4, 172 $4,241 $4,332 $4,492 $4,668 $4,859 $4,963

Table 10.4.8 Split System Heat Pumps, Replacement and New Owner Markets: ShipmentWeighted Average per-Unit Total Installed Costs for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 8 9 10
SWEF (SEER) 13.77 13.89 14.28 14.70 15.14 15. 59 16.06 17.03 18.02 19.01 20.00
SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8. 49 8.63 9.11 9.60 10.10 10.30

Total Installed Cost Region

Nation $3,492 $3,503 $3,562 $3,614 $3,670 $3,735 $3,822 $3,976 $4,143 $4,326 $4,425

Hot-Humid $3,203 $3,213 $3,270 $3,319 $3,37 2 $3,435 $3,517 $3,664 $3,824 $3,997 $4,092

Hot-Dry $4,024 $4,036 $4,102 $4,160 $4,223 $4,296 $4,393 $4,565 $4,752 $4,957 $5,067
Rest-of-Country $3,452 $3,463 $3,520 $3,570 $3, 624 $3,687 $3,771 $3,919 $4,080 $4,256 $4,352

10-514000 4100 4200 4300 4400 4500 4600 4700 4800 4900 5000 5100

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageTotal Installed Cost ($/unit)

Base Case
CSL 2 (14 SEER)
CSL 7 (17 SEER)
CSL 10 (19.5 SEER)

Figure 10.4.4 Split System Heat Pumps, New Construction: Shipment-Weighted Average Total Installed Cost for the Base Case and Three Standards Cases over the 2016-2046 Forecast Period

Heat Pumps—Single Package DOE based its total per-unit installed cost fo r single package heat pumps (HPs) on data presented in sections 8.2.2 of chapter 8. The tota l installed cost includes both the purchase price and installation cost. DOE base d average equipment prices on average manufacturer costs multiplied by average overall markup values. Using the relationship between HP efficiency (SEER/HSPF) and total installed co st presented in chapter 8, Table 10.4.9 presents the base case and standards case shipment-weighted total per-un it installed costs in th e year 2016 (the assumed effective date of new standards) for new construction installati ons for the Nation and the three specific regions (hot-humid, hot-dry, and rest-o f-country). Table 10.4.10 presents the same total per-unit installed cost data but fo r units installed as either repla cements or for new owners. In both tables, per-unit total installed costs are the same for both residential and commercial installations. In each table, the SWEF corre sponding to the shipment-weighted annual per-unit total installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit total in stalled costs change over the forecast period, Figure 10.4.5 demonstrates how the total installed costs for new construction installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. For

10-52the same reasons given above for split system CA Cs, the gap in the shipment-weighted per-unit total installed costs between CSL 2 and the base case are maintained over time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted per-unit total in stalled cost have achieved their maximum values in the first year that the standard is assumed to become effective (2016).

Table 10.4.9 Single Package Heat Pumps, New Construction: Shipment-Weighted Average per-Unit Total Installed Cost s for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7
SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40
SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00

Total Installed Cost Region

Nation $3,646 $3,691 $3,784 $3,936 $4,078 $4,245 $4,444 $4,642

Hot-Humid $3,408 $3,450 $3,539 $3,684 $3,819 $3,979 $4,168 $4,357

Hot-Dry $4,185 $4,235 $4,339 $4,510 $4,668 $4,855 $5,076 $5,298
Rest-of-Country $3,575 $3,618 $3,708 $3,855 $3,991 $4,152 $4,343 $4,534

Table 10.4.10 Single Package Heat Pumps, Replacement and New Owner Markets: Shipment-Weighted Average per-Unit Total Installed Costs for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7
SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40
SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00

Total Installed Cost Region

Nation $3,120 $3,161 $3,247 $3,387 $3,517 $3,671 $3,853 $4,036

Hot-Humid $2,895 $2,935 $3,017 $3,150 $3,274 $3,421 $3,595 $3,769
Hot-Dry $3,589 $3,635 $3,731 $3,888 $4,033 $4,206 $4,410 $4,614
Rest-of-Country $3,071 $3,110 $3,193 $3,328 $3,454 $3,602 $3,778 $3,954

10-533600 3700 3800 3900 4000 4100 4200 4300 4400 4500 4600 4700

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageTotal Installed Cost ($/unit)

Base Case
CSL 2 (14 SEER)
CSL 7 (16.4 SER)

Figure 10.4.5 Single Package Heat Pumps, New Construction: Shipment-Weighted Average Total Installed Cost for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

10.4.2.2 Annual Operating Cost per Unit

The per-unit annual operating cost includes costs for energy, repair, and maintenance. DOE calculated the annual savings in cost per unit for the nation as a whole and for the three regions that were evaluated separately.

Annual Energy Costs DOE determined the per-unit a nnual savings in energy costs by multiplying the per-unit annual savings in energy consumption developed for each produc t class by the appropriate energy price.

For both classes of both CACs and HPs, estimates of the per-unit annual energy consumption for the base case and each sta ndards case were presented in section 10.3.2.1. As described previously, DOE forecasted the per-unit annual energy consumption for the base case and each standards case for all product classes by applying a growth trend in efficiency.

10-54Energy prices are described in section 8.2.3.1 of chapter 8. DOE forecasted energy prices based on EIA’s AEO2009 . Trends in energy prices are desc ribed in section 8.2.3.2 of chapter 8.

Annual Repair and Maintenance Costs DOE described the total per-unit repair and maintenance costs for each product class as a function of product efficiency in sections 8.2.3.3 and 8.2.3.4 of Chapter 8, Life-Cycle Cost and Payback Period Analysis. Because the per-unit re pair and maintenance co sts depend directly on efficiency, DOE used the shipments-weight effi ciencies (SWEFs) for the base and standards cases presented in section 10.2, combined with th e repair and maintenanc e costs presented in chapter 8, to estimate the shipments-weighted per-unit average repair and maintenance costs under the base and standards cases.

Based on the relationship between CAC effici ency (SEER) and repair and maintenance costs presented in chapter 8, Table 10.4.11 presents the base case and standards case shipmentweighted per-unit repair and ma intenance costs for coil-only inst allations in the year 2016 (the assumed effective date of new standards) for the Nation and the three specific regions (hothumid, hot-dry, and rest-of-country). The per-unit repair and maintenance costs are the same for both residential and commercial installations as well as new c onstruction and replacement/new owner installations. In each table, the SWEF corresponding to the shipment-weighted annual per-unit total installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit repair and maintenance costs change over the forecast period, Figure 10.4.6 demonstrates how the costs for coil-only installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. Because SWEFs in the base case and each standards case were fo recasted by DOE to increase over the forecast period, the corresponding repair a nd maintenance costs increase ove r time. As noted in earlier in section 10.2.1.2, DOE’s approach for forecasting sta ndards case SWEFs assumes that the rate of adoption of more efficient products under the st andards case can occur only at a rate which ensures that the shipment-weighted average total installed cost difference between the standards case and base case over the entire forecast period is held constant. Because the change in repair and maintenance costs (as a function of efficiency) mirrors the change in total installed costs, the repair and maintenance cost diffe rence between the standards case and base case over the entire forecast period also remains constant. This is ev ident in Figure 10.4.6 as the gap in the shipmentweighted repair and maintenan ce costs between CSL 2 and the base case remains constant over time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted repair and maintenanc e costs have achieved their maximum values in the first year that the standard is assumed to become effective (2016).

10-55Table 10.4.11 Split System Central Air Conditioners, Coil-Only Units: Shipment-Weighted Average per-Unit Repair and Maintenance Cost for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50

Repair and Maint. Cost Region

Nation $152 $153 $157 $162 $168 $176 $186 $198

Hot-Humid $122 $123 $127 $131 $136 $142 $150 $160

Hot-Dry $173 $174 $179 $185 $192 $200 $212 $225
Rest-of-Country $159 $160 $165 $170 $176 $184 $195 $207

$150 $155 $160 $165 $170 $175 $180 $185 $190 $195 $200

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Repair and Maintenance Costs ($/unit)

Base Case
CSL 2 (14 SEER)
CSL 7 (16.5 SER)

Figure 10.4.6 Split System Central Air Conditioners, Coil-Only Units, New Construction: Shipment-Weighted Average Annual Repair and Maintenance Costs for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

Table 10.4.12 presents the base case and standards case shipment-weighted per-unit repair and maintenance costs for split system CAC blower coil inst allations in the year 2016 (the assumed effective date of new standards) for the Nation and the three specific regions (hothumid, hot-dry, and rest-of-country). The per-unit repair and maintenance costs are the same for

10-56both residential and commercial installations as well as new c onstruction and replacement/new owner installations. In each table, the SWEF corresponding to the shipment-weighted annual per-unit total installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit total in stalled costs change over the forecast period, Figure 10.4.7 demonstrates how th e repair and maintenance costs for blower coil installations for the base case and three standards cases (CSL 2, CSL 9, and CSL 13) change over time. For the same reasons given above for coil-only units, the gap in the shipmentweighted per-unit repair and maintenance costs between the CSLs and the base case are maintained over time. This is not evident in CSL 13, the Max Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted per-unit repair and maintenance costs have achieved their maximum values in the first year that the standard is assumed to become effective (2016).

Table 10.4.12 Split System Central Air Conditioners, Blower Coil Units: ShipmentWeighted Average per-Unit Repair and Maintenance Cost for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 8 9 10 11 12 13
SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00

Repair and Maint. Cost Region

Nation $160 $161 $164 $167 $169 $172 $175 $177 $180 $188 $196 $205 $216 $227

Hot-Humid $129 $130 $132 $134 $136 $138 $141 $143 $145 $151 $158 $166 $174 $183

Hot-Dry $182 $183 $186 $190 $192 $195 $198 $202 $205 $213 $223 $233 $245 $258
Rest-of-Country $168 $169 $172 $175 $177 $180 $183 $186 $189 $197 $205 $215 $226 $237

10-57$160 $170 $180 $190 $200 $210 $220 $230

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Repair and Maintenance Costs ($/unit) Base Case
CSL 2 (14 SEER)
CSL 9 (18 SEER)
CSL 13 (22 SEER)

Figure 10.4.7 Split System Central Air Conditioners, Blower Coil Units, New Construction: Shipment-Weighted Average Annual Repair and Maintenance Costs for the Base Case and Three Standards Cases over the 2016-2046 Forecast Period

Table 10.4.13 presents the base case and standards case shipment-weighted per-unit repair and maintenance costs for single package CAC installations in the year 2016 (the assumed effective date of new standards) for the Nation and the three specific regions (hot-humid, hotdry, and rest-of-country). The per-unit repair and maintenance costs are the same for both residential and commercial installations as we ll as new construction and replacement/new owner installations. In each table, the SWEF corre sponding to the shipment-weighted annual per-unit total installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit total in stalled costs change over the forecast period, Figure 10.4.8 demonstrates how th e repair and maintenance costs for blower coil installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. For the same reasons given above for split system CACs, the gap in the shipment-weighted per-unit repair and maintenance costs between the CSLs and the base case are maintained over time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted per-unit repa ir and maintenance cost s have achieved their maximum values in the first year that the st andard is assumed to become effective (2016).

10-58Table 10.4.13 Single Package Central Air Conditioners: Shipment-Weighted Average perUnit Repair and Maintenance Cost for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 SWEF (SEER) 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60

Repair and Maint. Cost Region

Nation $147 $154 $159 $167 $173 $182 $191 $205

Hot-Humid $119 $124 $128 $134 $140 $146 $154 $165

Hot-Dry $168 $175 $181 $190 $197 $206 $218 $233
Rest-of-Country $154 $161 $166 $175 $181 $190 $200 $215

140 150 160 170 180 190 200 210

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Repair and Maintenance Costs ($/unit)

Base Case
CSL 2 (14 SEER)
CSL 7 (16.6 SER)

Figure 10.4.8 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average Annual Repair and Maintenance Costs for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

Table 10.4.14 presents the base case and standards case shipment-weighted per-unit repair and maintenance costs fo r split system HP installations in the year 2016 (the assumed effective date of new standards) for the Nation and the three specific regions (hot-humid, hotdry, and rest-of-country). The per-unit repair and maintenance costs are the same for both residential and commercial installations as we ll as new construction and replacement/new owner

10-59installations. In each table, the SWEF corre sponding to the shipment-weighted annual per-unit total installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit total in stalled costs change over the forecast period, Figure 10.4.9 demonstrates how th e repair and maintenance costs for blower coil installations for the base case and three standards cases (CSL 2, CSL 7, and CSL 10) change over time. For the same reasons given above fo r split system CACs, the gap in the shipmentweighted per-unit repair and maintenance costs between the CSLs and the base case are maintained over time. This is not evident in CSL 10, the Max Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted per-unit repair and maintenance costs have achieved their maximum values in the first year that the standard is assumed to become effective (2016).

Table 10.4.14 Split System Heat Pumps: Shipment-Wei ghted Average per- Unit Repair and Maintenance Costs for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7 8 9 10
SWEF (SEER) 13.77 13.89 14.28 14.70 15.14 15. 59 16.06 17.03 18.02 19.01 20.00
SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8. 49 8.63 9.11 9.60 10.10 10.30

Repair and Maint. Cost Region

Nation $153 $153 $156 $159 $162 $165 $169 $177 $185 $194 $199

Hot-Humid $123 $124 $126 $128 $130 $133 $136 $142 $149 $157 $160

Hot-Dry $174 $174 $178 $181 $184 $187 $192 $201 $210 $221 $226
Rest-of-Country $160 $161 $164 $166 $169 $173 $177 $185 $194 $203 $209

10-60150 155 160 165 170 175 180 185 190 195 200

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Repair and Maintenance Costs ($/unit)

Base Case
CSL 2 (14 SEER)
CSL 7 (17 SEER)
CSL 10 (19.5 SEER)

Figure 10.4.9 Split System Heat Pumps, New Construction: Shipment-Weighted Average Annual Repair and Maintenance Co sts for the Base Case and Three Standards Cases over the 2016-2046 Forecast Period

Table 10.4.15 presents the base case and standards case shipment-weighted per-unit repair and maintenance costs for single package HP installations in the year 2016 (the assumed effective date of new standards) for the Nation and the three specific regions (hot-humid, hotdry, and rest-of-country). The per-unit repair and maintenance costs are the same for both residential and commercial installations as we ll as new construction and replacement/new owner installations. In each table, the SWEF corre sponding to the shipment-weighted annual per-unit total installed cost is also provided.

To illustrate how shipment-w eighted annual per-unit total in stalled costs change over the forecast period, Figure 10.4.10 demonstrates how the repair and maintenance costs for blower coil installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. For the same reasons given above for split system CACs, the gap in the shipment-weighted perunit repair and maintenance costs between the CSLs and the base case are maintained over time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted per-unit repa ir and maintenance cost s have achieved their maximum values in the first year that the st andard is assumed to become effective (2016).

10-61Table 10.4.15 Single Package Heat Pumps: Shipment- Weighted Average per-Unit Repair and Maintenance Costs for Base and Standards Cases in 2016

Base Case Candidate Standard Level

1 2 3 4 5 6 7
SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40
SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00

Repair and Maint. Cost Region

Nation $151 $153 $158 $165 $172 $181 $190 $200

Hot-Humid $122 $124 $128 $134 $139 $146 $154 $162

Hot-Dry $172 $174 $179 $188 $196 $205 $216 $227
Rest-of-Country $158 $161 $165 $173 $180 $189 $199 $209

150 155 160 165 170 175 180 185 190 195 200

2015 2020 2025 2030 2035 2040 2045

YearShipment-Weighted AverageAnnual Repair and Maintenance Costs ($/unit)

Base Case
CSL 2 (14 SEER)
CSL 7 (16.4 SER)

Figure 10.4.10 Single Package Heat Pumps, New Construction: Shipment-Weighted Average Annual Repair and Maintenance Costs for the Base Case and Two Standards Cases over the 2016-2046 Forecast Period

10.4.2.3 Shipments including Equipment Switching

DOE forecasted shipments for the base case and all standards cases for the Nation as a

10-62whole and for the three climate regions that we re evaluated separately (the hot-humid region, hot-dry, and rest of the Nation). An extens ive description of the methodology for conducting and generating the shipments foreca sts for all four of the product cl ass is presented in Chapter 9, Shipments Analysis.

In projecting standards case shipments, DOE analyzed the combined effects of increased total installed costs (purchase price plus insta llation costs), operating cost savings, and household income on consumer replacement and new owner purchase decisions. DOE determined that increased total installed cost is the most significant effect and impacts consumer replacement and new owner purchase decisions. As described in section 9.4 of chapter 9, DOE treated the impact of total installed cost increases on standards ca se shipments differently for the new construction, replacement, and new owner markets.

As described earlier in section 10.3.2.2, for ne w construction purchases of split system and single package CACs and HPs, DOE assumed consumers were unaffected by an increase in total installed cost. In other words, DO E assumed new construc tion shipments under any standards case equaled new construction shipme nts under the base case. For replacement purchases of split system and single package CACs and HPs, DOE assumed consumers affected by an increase in total installed cost would repair their equipment rather than replace it, extending the life of the product by six years. For new owner purchases of split system and single package CACs, DOE assumed consumers affect ed by an increase in total installed cost would switch equipment and purchase a room air conditioner rather than a CAC. For new owner purchases of split system and single package HPs, DOE assumed that consumers affected by an increase in total installed cost would switch equipment and purchase a combination electric resistance furnace and CAC rather than a HP.

Table 10.4.16 presents the per-unit total insta lled costs of the alternative coil-only split system CAC and electric furnace combination to replace split system HPs. Per-unit costs are the same for residential and commercial installations.

Table 10.4.16 Equipment Switching for New Owner Purchasers of Split System Heat Pumps: Shipment-Weighted Average per-Unit Total Installed Costs of Alternative Combination Coil-Only Split System Central Air Conditioner and Electric Furnace System for Base and Standards Cases in 2016

Region Base Case Split Heat Pump Candidate Standard Level

1 2 3 4 5 6 7 8 9 10

Nation $3,188 $3,205 $3,262 $3,333 $3,417 $3,524 $3,663 $3,828 $3,828 $3,828 $3,828

Hot-Humid $2,946 $2,961 $3,016 $3,084 $3,16 4 $3,265 $3,398 $3,556 $3,556 $3,556 $3,556

Hot-Dry $3,583 $3,602 $3,666 $3,745 $3,839 $3,958 $4,114 $4,299 $4,299 $4,299 $4,299

Rest-of-Country $3,173 $3,189 $3,244 $3,313 $3, 394 $3,497 $3,630 $3,790 $3,790 $3,790 $3,790

10-63Table 10.4.17 presents the per-unit total installe d costs of the alternative single package CAC and electric furnace combination to replace single package HPs. Per-unit costs are the same for residential and commercial installations.

Table 10.4.17 Equipment Switching for New Owner Purchasers Single Package Heat Pumps: Shipment-Weighted Average per-Unit Total Installed Costs of Alternative Combination Single Package Central Air Conditioner and Electric Furnace System for Base and Standards Cases in 2016

Region Base Case Single Package Candidate Standard Level

1 2 3 4 5 6 7

Nation $3,359 $3,454 $3,535 $3,656 $3,757 $3,885 $4,036 $4,249

Hot-Humid $3,104 $3,194 $3,272 $3,387 $3,483 $3,605 $3,749 $3,953

Hot-Dry $3,779 $3,885 $3,976 $4,111 $4,224 $4,367 $4,536 $4,775
Rest-of-Country $3,340 $3,431 $3,510 $3,626 $3,723 $3,847 $3,992 $4,199

10.4.2.4 Equipment Stock

The stock of equipment in any given year depends on annual ship ments and the lifetime of a given product class. The NIA model keeps track of the number of units shipped each year. The lifetime of a unit determines how many units shipped in previous years survive in the given year. DOE assumes that products have an increasing probability of retiring as they age. The probability of survival as a function of years since purchase is termed the survival function. Refer to the specific section for each product cl ass in Chapter 9, Shipments Analysis, for further details on the survival functions that DOE used in its analysis.

10.4.2.5 Increases in Total Annual Installed Cost

The increase in total annual installed cost for a product under any given standards case is the product of the increase in total installed cost per unit attributable to the standard and the number of units of each vintage. This method acc ounts for differences in total installed cost from year to year. The equation for determining the total annual installed cost increase for a given candidate standards level, presented in section 10.4.1 is repeated here.

TIC = 

# ∑ STOCK V × UTIC V

As noted earlier, when considering heat pumps DOE accounted for the total installed cost for those consumers who decided to switch from a heat pump to an electric furnace plus CAC because standards increased the cost of new units. Therefore, the total annual increase in installed cost accounts for the tota l installed cost of CACs purchas ed in lieu of new heat pumps.

10-6410.4.2.6 Savings in Total Annual Operating Cost

The savings in total annual ope rating cost for any given candi date standards level is the product of the annual per-unit sa vings in operating cost attribut able to the standard and the number of units of each vintage. This method acc ounts for the year-to-year differences in annual operating cost savings. The equa tion for determining the total annual savings in operating cost for a given candidate standards level, which was presented in section 10.4.1, is repeated here.

OCS = 

# ∑ STOCK V × UOCS V

As noted earlier, when considering heat pumps DOE accounted for the energy use of those consumers who decided to switch from a heat pump to an electric furnace and CAC in response to standards. Therefore, the total a nnual savings in operating cost accounts for the energy costs of the CACs purchased in lieu of heat pumps.

10.4.2.7 Discount Factors

DOE multiplied monetary values in future years by a discount factor to determine the present value. The discount factor (DF) is described by the equation:

1 DF =

_ ( y yp ) ( 1+ r )

Where:

r = discount rate,

y = year of the monetary value, and

y P = year in which the present value is being determined.

Although DOE used consumer discount rate s to determine the life-cycle cost of refrigeration products (chapter 8), it used nationa l discount rates to calc ulate national NPV. DOE estimated NPV using both a 3-percent and a 7-percen t real discount rate, in accordance with the Office of Management and Budget’s guidance to Federal agencies on the development of regulatory analysis, particularly section E therein: Identifying and Measuring Benefits and
Costs

. 3 DOE defined the present year as 2009.

10.4.2.8 Present Value of Increased Installed Cost

The present value of increased installed cost is the difference between installation cost in each standards case and the base case discount ed to the present and summed throughout the period over which DOE is considering the installation of units (from the effective date of standards, 2016, to 2046).

10-65The increase in total installed cost refers to both the purchase price and installation cost associated with the more expensive units purchased in the standards case compared to the base case. DOE calculated annual increases in installed cost as the difference in total installed cost for new equipment purchased each year, multiplied by the shipments in the standards case.

10.4.2.9 Present Value of Savings

The present value of annual savings in operating cost is the difference between the base case and each standards case discounted to the present and summed throughout the period from the effective date, 2016, to the time when the last unit installed in 2046 is retired from service.

Savings represent decreases in operating co st (including electricity, repair, and maintenance) associated with the more energy efficient equipment purchased in each standards case compared to the base case. Total annual sa vings in operating cost are the savings per unit multiplied by the number of units of each vintage that survive in a particular year. For units purchased in 2046, energy consumption continues until the unit is retired from service.

10.5 RESULTS OF CALCULATIONS

The National Impacts Analysis (NIA) model estimates the national energy savings (NES), the regional energy savi ngs (RES), and the net present value (NPV) attributable to each candidate standards level. DOE generated the NES, RES, and NPV results using a Microsoft Excel spreadsheet, which is accessible on the Internet at: ( http://www1.eere.energy.gov/buildings/applianc e_standards/residen tial/central_ac_hp.html ). Details and instructions for using the sp readsheet are provided in appendix 10-A.

10.5.1 Summary of Inputs

Table 10.5.1 summarizes the inputs to the NIA model. The inputs were discussed in sections 10.3.2 (inputs for NES and RES) and 10. 4.2 (inputs for the national and regional NPV). A brief description of the data source or each input also is provided in Table 10.5.1.

10-66Table 10.5.1 Inputs to Calculations Input Data Description Shipments Annual shipments from shipments model (chapter 9).
Effective date of standard 2016.

Forecasted efficiencies for base

case SWEF* determined in the year 2016 for each product class. Growth trend applied to SWEF throughout forecast period, 2016–2046 (section 10.2).
Efficiencies for standards case Growth trends applied to determine SWEF for each standards case and each product class for 2016–2046 (section 10.2). Annual energy consumption per unit Annual weighted-average values are a function of SWEF (section 10.3.2.1).

Total installed cost per unit Annual weighted-average values are a function of SWEF (section 10.4.2.1). Energy cost per unit Annual weighted-average values are a function of annual energy consumption per unit and energy prices. (See section 8.2.3.1 of chapter 8 for energy prices.) Repair and maintenance costs per unit Annual weighted-average values are a function of SWEF (section 10.4.2.3).

Increase in energy prices EIA AEO 2009 forecasts (to 2030) and extrapolation to 2046. (See section 8.2.3.2 of chapter 8.) Energy site-to-source conversion Conversion factor, which changes yearly, is generated by DOE/EIA’s NEMS † program as a time-series factor that includes electric generation, transmission, and distribution losses.

Discount rate Seven percent real. Present year Future expenses are discounted to 2009.

* SWEF = shipments-weighted energy factor (efficiency).
† NEMS = National Energy Modeling System. Chapter 13 , Utility Impact Analysis, and the Environmental

Assessment Report [Give reference]provide more detail on NEMS.

10.5.2 National and Regional Energy Savings

The following sections provide the nationa l energy savings (NES) and regional energy savings (RES) that DOE calculated for each of the candidate standard levels (CSLs) analyzed for all four product classes of central air conditioners and heat pumps. Results, which are cumulative to 2046, are shown as primary energy savings. DOE based the inputs to the NIA model on weighted-average values, producing results that are discrete point values, rather than a distribution of values such as is generated by the life-cycle cost and payback period analyses.

10.5.2.1 Central Air Conditioners

This section provides NES and RES results fo r the efficiency levels considered for the two product classes of centra l air conditioners (split system and single package).

Central Air Conditioners—Split System Tables 10.5.2 through 10.5.4 show the energy savings for the CSLs analyzed for split system CACs for the Nation as a whole and for each of the three climate regions evaluated separately (the hot-humid, hot-dry, and rest of the Nation). Table 10.5.2 shows the results for the residential sector only, Table 10.5.3 shows the resu lts for the commercial sector only, and Table 10.5.4 shows the results for both sectors. Each table shows the breakdown of energy savings for

10-67coil-only units and blower coil units. Figure 10.5. 1 depicts the total national and regional energy savings for each CSL.

Table 10.5.2 Split System Central Air Conditioners: Cumulative National and Regional Energy Savings from 2016-2046 for th e Residential Sector (quads)

CSL SEER Nation* Hot-Humid Hot-Dry Rest of Country

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

1 13.5 0.19 0.17 0.02 0.08 0.08 0.01 0.03 0.03 0.00 0.05 0.05 0.00

2 14.0 0.77 0.71 0.07 0.35 0.32 0.03 0.12 0.11 0.01 0.22 0.20 0.02

3 14.5 1.36 1.24 0.12 0.62 0.56 0.05 0.22 0.20 0.02 0.38 0.35 0.03

4 15.0 1.94 1.77 0.17 0.88 0.80 0.08 0.31 0.28 0.03 0.55 0.50 0.05

5 15.5 2.51 2.29 0.22 1.14 1.04 0.10 0.40 0.37 0.03 0.71 0.65 0.06

6 16.0 3.03 2.77 0.26 1.37 1.26 0.12 0.49 0.44 0.04 0.86 0.78 0.07

7 16.5 3.30 2.99 0.31 1.50 1.36 0.14 0.53 0.48 0.05 0.93 0.85 0.09

8 17.0 3.35 0.36 1.52 0.16 0.54 0.06 0.94 0.10

9 18.0 3.45 0.45 1.56 0.20 0.55 0.07 0.97 0.13

10 19.0 3.54 0.55 1.60 0.25 0.57 0.09 1.00 0.15

11 20.0 3.63 0.63 1.64 0.29 0.58 0.10 1.02 0.18

12 21.0 3.70 0.71 1.68 0.32 0.59 0.11 1.04 0.20

13 22.0 3.74 0.75 1.70 0.34 0.60 0.12 1.05 0.21

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. ** Total NES for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

10-68Table 10.5.3 Split System Central Air Conditioners: Cumulative Nation al and Regional Energy Savings from 2016-2046 for the Commercial Sector (quads)

CSL SEER Nation* Hot-Humid Hot-Dry Rest of Country

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

1 13.5 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

2 14.0 0.05 0.05 0.00 0.02 0.02 0.00 0.01 0.01 0.00 0.02 0.02 0.00

3 14.5 0.09 0.09 0.01 0.03 0.03 0.00 0.02 0.02 0.00 0.04 0.04 0.00

4 15.0 0.14 0.13 0.01 0.05 0.04 0.00 0.03 0.02 0.00 0.06 0.06 0.00

5 15.5 0.18 0.16 0.01 0.06 0.06 0.00 0.03 0.03 0.00 0.08 0.07 0.01

6 16.0 0.20 0.18 0.01 0.07 0.06 0.01 0.04 0.03 0.00 0.09 0.08 0.01

7 16.5 0.20 0.19 0.02 0.07 0.07 0.01 0.04 0.04 0.00 0.09 0.08 0.01

8 17.0 0.21 0.02 0.07 0.01 0.04 0.00 0.09 0.01

9 18.0 0.21 0.02 0.07 0.01 0.04 0.00 0.09 0.01

10 19.0 0.21 0.02 0.07 0.01 0.04 0.00 0.09 0.01

11 20.0 0.21 0.02 0.08 0.01 0.04 0.00 0.09 0.01

12 21.0 0.22 0.03 0.08 0.01 0.04 0.01 0.10 0.01

13 22.0 0.22 0.03 0.08 0.01 0.04 0.01 0.10 0.01

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. ** Total NES for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

Table 10.5.4 Split System Central Air Conditioners: Cumulative Nation al and Regional Energy Savings from 2016-2046 for the Re sidential and Commercial Sectors (quads)

CSL SEER Nation* Hot-Humid Hot-Dry Rest of Country

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

1 13.5 0.20 0.18 0.02 0.09 0.08 0.01 0.03 0.03 0.00 0.06 0.05 0.00

2 14.0 0.82 0.75 0.07 0.37 0.34 0.03 0.13 0.12 0.01 0.24 0.22 0.02

3 14.5 1.46 1.33 0.12 0.65 0.59 0.06 0.24 0.22 0.02 0.43 0.39 0.04

4 15.0 2.08 1.90 0.18 0.93 0.85 0.08 0.34 0.31 0.03 0.61 0.56 0.05

5 15.5 2.69 2.46 0.23 1.20 1.10 0.10 0.44 0.40 0.04 0.79 0.72 0.07

6 16.0 3.23 2.95 0.28 1.44 1.32 0.12 0.52 0.48 0.04 0.95 0.87 0.08

7 16.5 3.51 3.18 0.33 1.57 1.43 0.15 0.57 0.52 0.05 1.02 0.93 0.09

8 17.0 3.56 0.37 1.59 0.17 0.57 0.06 1.04 0.11

9 18.0 3.65 0.47 1.64 0.21 0.59 0.08 1.06 0.13

10 19.0 3.75 0.57 1.68 0.25 0.61 0.09 1.09 0.16

11 20.0 3.84 0.66 1.72 0.30 0.62 0.11 1.12 0.19

12 21.0 3.92 0.74 1.76 0.33 0.63 0.12 1.14 0.21

13 22.0 3.96 0.78 1.78 0.35 0.64 0.12 1.15 0.22

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. ** Total NES for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

10-690.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

1 2 3 4 5 6 7 8 9 10 11 12 13

Candidate Standard LevelNational or Regional Energy Savings (quads) Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.1 Split System Central Air Conditioners: Cumulative Nation al and Regional Energy Savings from 2016-2046 (quads)

Central Air Conditio ners—Single Package Table 10.5.5 shows the energy savings for the CSLs analyzed for single package CACs for the Nation as a whole and for each of the three climate regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation) . Total energy savings in Table 10.5.5 are also broken down by sector (i.e., resi dential and comme rcial). Figure 10.5.2 depi cts the total national and regional energy savings for each CSL.

10-70Table 10.5.5 Single Package Central Air Conditioners : Cumulative Nation al and Regional Energy Savings from 2016-2046 (quads)

CSL SEER Nation* Hot-Humid Hot-Dry Rest of Country

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm.

1 13.5 0.08 0.08 0.00 0.04 0.04 0.00 0.01 0.01 0.00 0.02 0.02 0.00

2 14.0 0.15 0.14 0.01 0.07 0.07 0.00 0.02 0.02 0.00 0.04 0.04 0.00

3 14.5 0.24 0.22 0.02 0.11 0.11 0.01 0.04 0.04 0.00 0.07 0.06 0.01

4 15.0 0.30 0.28 0.02 0.14 0.13 0.01 0.05 0.05 0.00 0.09 0.08 0.01

5 15.5 0.36 0.34 0.02 0.17 0.16 0.01 0.06 0.05 0.00 0.11 0.10 0.01

6 16.0 0.41 0.39 0.02 0.19 0.18 0.01 0.07 0.06 0.00 0.12 0.11 0.01

7 16.6 0.43 0.41 0.03 0.20 0.19 0.01 0.07 0.07 0.00 0.13 0.12 0.01

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES.

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45

1 2 3 4 5 6 7

Candidate Standard LevelNational or Regional Energy Savings (quads) Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.2 Single Package Central Air Conditi oners: Cumulative National and Regional Energy Savings from 2016-2046 (quads)

10-7110.5.2.2 Heat Pumps

This section provides NES and RES results fo r the efficiency levels considered for the two product classes of heat pumps (split system and single package).

Heat Pumps—Split System Table 10.5.6 shows the energy savings for the CSLs analyzed for split system HPs for the Nation as a whole and for each of the three climate regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). Tota l energy savings in Table 10.5.6 are also broken down by sector (i.e., residentia l and commercial). Figure 10.5.3 depicts the total national and regional energy savings for each CSL.

Table 10.5.6 Split System Heat Pumps: Cumulati ve National and Regional Energy Savings from 2016-2046 (quads)

CSL SEER HSPF Nation* Hot-Humid Hot-Dry Rest of Country

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm.

1 13.5 7.85 0.11 0.10 0.00 0.07 0.06 0.00 0.01 0.01 0.00 0.03 0.03 0.00

2 14.0 8.00 0.56 0.54 0.02 0.34 0.33 0.01 0.07 0.06 0.00 0.15 0.14 0.01

3 14.5 8.15 1.03 1.00 0.03 0.63 0.61 0.02 0.12 0.11 0.00 0.28 0.27 0.01

4 15.0 8.30 1.53 1.48 0.05 0.93 0.90 0.03 0.18 0.17 0.01 0.42 0.40 0.02

5 15.5 8.45 2.09 2.03 0.06 1.26 1.23 0.03 0.24 0.23 0.01 0.58 0.56 0.02

6 16.0 8.60 2.78 2.71 0.07 1.66 1.62 0.04 0.31 0.30 0.01 0.79 0.77 0.02

7 17.0 9.10 3.93 3.84 0.09 2.94 2.28 0.05 0.44 0.42 0.01 1.15 1.12 0.03

8 18.0 9.60 4.98 4.88 0.10 3.36 2.88 0.06 0.55 0.54 0.01 1.47 1.44 0.03

9 19.0 10.10 5.68 5.57 0.11 3.41 3.29 0.06 0.63 0.61 0.02 1.68 1.65 0.03

10 19.5 10.30 5.78 5.67 0.11 2.94 3.35 0.06 0.64 0.62 0.02 1.71 1.68 0.03

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES.

10-720.0 1.0 2.0 3.0 4.0 5.0 6.0

1 2 3 4 5 6 7 8 9 10

Candidate Standard LevelNational or Regional Energy Savings (quads) Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.3 Split System Heat Pumps: Cumulati ve National and Regional Energy Savings from 2016-2046 (quads)

Heat Pumps—Single Package Table 10.5.7 shows the energy savings for the CSLs analyzed for single package HPs for the Nation as a whole and for each of the three climate regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation) . Total energy savings in Table 10.5.7 are also broken down by sector (i.e., resi dential and comme rcial). Figure 10.5.4 depi cts the total national and regional energy savings for each CSL.

10-73Table 10.5.7 Single Package Heat Pumps: Cumula tive National and Regional Energy Savings from 2016-2046 (quads)

CSL SEER HSPF Nation* Hot-Humid Hot-Dry Rest of Country

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm.

1 13.5 7.85 0.04 0.04 0.00 0.02 0.02 0.00 0.00 0.00 0.00 0.01 0.01 0.00

2 14.0 8.00 0.10 0.10 0.00 0.06 0.06 0.00 0.01 0.01 0.00 0.03 0.02 0.00

3 14.5 8.00 0.19 0.19 0.01 0.12 0.12 0.00 0.02 0.02 0.00 0.05 0.05 0.00

4 15.0 8.00 0.28 0.27 0.01 0.17 0.17 0.00 0.03 0.03 0.00 0.08 0.08 0.00

5 15.5 8.50 0.36 0.35 0.01 0.22 0.21 0.01 0.04 0.04 0.00 0.11 0.11 0.00

6 16.0 9.00 0.41 0.40 0.01 0.25 0.24 0.01 0.05 0.04 0.00 0.12 0.12 0.00

7 16.4 9.00 0.43 0.41 0.01 0.26 0.25 0.01 0.05 0.05 0.00 0.12 0.12 0.00

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES.

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45

1 2 3 4 5 6 7

Candidate Standard LevelNational or Regional Energy Savings (quads) Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.4 Single Package Heat Pumps: Cumula tive National and Regional Energy Savings from 2016-2046 (quads)

10.5.3 Calculating Annual Cost and Savings

To illustrate the basic inputs to the calculati ons of net present value (NPV) of costs and savings attributable to proposed standards for central air conditioners and heat pumps, Figure 10.5.5 shows the non-discounted annual increases in installed cost and annual savings in

10-74operating cost at the national level for CSL 2 for split system coil-only CACs. The figure also shows net savings, which is the difference between the savings and costs for each year. The annual total installed cost is the increase in the total installed cost for products purchased each year for 2016–2046. The annual savings in operating cost applies to products that are operating in each year. The NPV is the difference betwee n the cumulative annual discounted savings and the cumulative annual discounted cost. DOE coul d create figures like the one below for every standards case for all four product classes of CACs and heat pumps.

-0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2

2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064 2068 2072 2076 2080

YearBillion of 2008 Dollars Total Installed Cost Increase Operating Cost Savings Net Savings

Figure 10.5.5 Non-Discounted Annual Increases in Installed Cost and Savings in Operating Cost for Split System Coil-Only Central Air Conditioners, Candidate Standard Level 2

10.5.4 Net Present Values

The following sections provide results of ca lculating the net present value (NPV) for each candidate standard level considered for the four product classes of cent ral air conditioners and heat pumps (split systems and packaged systems). Results were calculated for the nation as a whole and for each of the three climate regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). Results, whic h are cumulative, are shown as the discounted dollar value of the savings. DOE based the inputs to the NIA model on weighted-average values, yielding results that are discrete point values, rather than a distribution of values such as produced by the life-cycle cost and payback period analyses.

The present value of increased total installed cost is the total annual increase (the difference between the standards case and base case) discounted to the present and summed

10-75throughout the period for which DOE evaluates the ef fect of standards (from the effective date of standards, 2016, to 2046).

Savings derive from decreases in operating costs related to the energy consumption associated with the higher energy efficiency of equipment purchased in the standards case compared to the base case. Total savings in operating costs are the savings per unit multiplied by the number of units of each vintage (i.e., the year of manufacture) that survive in a particular year. Equipment consumes energy and must be maintained throughout its lifetime. For units purchased through 2046, the operating cost includes energy consumed until the last unit is retired from service.

10.5.4.1 Central Air Conditioners

The following sections provide the results of calculating net pres ent value (NPV) based on a discount rate of seven percent for the candida te standard levels DOE analyzed for the two product classes of central air conditioners, sp lit system and single package. Results are cumulative to 2046.

Central Air Conditioners—Split System Tables 10.5.8 through 10.5.10 show the NPVs at a three percent real discount rate for the CSLs analyzed for split system CACs for the Nation as a whole and for each of the three climate regions evaluated separately (the hot-humid, hot-dry, and rest of the Nation). Table 10.5.8 shows the results for the residential sector only, Tabl e 10.5.9shows the results for the commercial sector only, and Table 10.5.10 shows the results for both s ectors. Each table shows the breakdown of the NPV for coil-only units and blower coil units . Figure 10.5.6 depicts the total national and regional NPVs for each CSL.

10-76Table 10.5.8 Split System Central Air Conditioners: Discounted Cumulati ve National and Regional NPV Results from 2016-2046 for the Residential Sector (3% Discount Rate)

CSL SEER Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

1 13.5 -0.65 -0.65 0.00 0.10 0.08 0.02 -0.01 -0.02 0.01 -0.86 -0.81 -0.05

2 14.0 -3.65 -3.63 -0.01 0.19 0.09 0.10 -0.23 -0.27 0.04 -4.07 -3.87 -0.20

3 14.5 -8.33 -8.29 -0.04 -0.18 -0.34 0.16 -0.79 -0.86 0.07 -8.16 -7.80 -0.36

4 15.0 -15.13 -15.04 -0.09 -1.11 -1.33 0. 22 -1.79 -1.88 0.09 -13.32 -12.78 -0.54

5 15.5 -24.15 -23.95 -0.20 -2.67 -2.94 0. 27 -3.24 -3.35 0.10 -19.55 -18.82 -0.74

6 16.0 -34.13 -33.78 -0.35 -4.61 -4.91 0. 30 -4.94 -5.04 0.10 -26.06 -25.10 -0.96

7 16.5 -39.83 -39.27 -0.57 -5.78 -6.09 0. 31 -5.91 -6.00 0.09 -29.70 -28.49 -1.21

8 17.0 -40.10 -0.84 -5.78 0.31 -5.93 0.06 -29.97 -1.48

9 18.0 -40.86 -1.59 -5.84 0.25 -6.02 -0.03 -30.64 -2.15

10 19.0 -41.91 -2.64 -5.98 0.11 -6.18 -0.18 -31.45 -2.96

11 20.0 -43.25 -3.98 -6.21 -0.12 -6.39 -0.39 -32.40 -3.91

12 21.0 -44.77 -5.50 -6.50 -0.41 -6.65 -0.65 -33.41 -4.92

13 22.0 -45.56 -6.30 -6.67 -0.57 -6.79 -0.79 -33.91 -5.42

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. ** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

Table 10.5.9 Split System Central Air Conditioners: Discounted Cumulati ve National and Regional NPV Results from 2016-2046 for the Commercial Sector (3% Discount Rate)

CSL SEER Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

1 13.5 -0.11 -0.11 0.00 -0.02 -0.02 0.00 -0.03 -0.03 0.00 -0.06 -0.06 0.00

2 14.0 -0.49 -0.47 -0.02 -0.09 -0.09 0.00 -0.14 -0.14 -0.01 -0.28 -0.27 -0.01

3 14.5 -0.99 -0.96 -0.03 -0.19 -0.19 0.00 -0.28 -0.27 -0.01 -0.55 -0.53 -0.02

4 15.0 -1.73 -1.68 -0.06 -0.37 -0.36 -0. 01 -0.47 -0.45 -0.02 -0.95 -0.92 -0.03

5 15.5 -2.73 -2.64 -0.09 -0.62 -0.60 -0. 01 -0.70 -0.67 -0.03 -1.49 -1.43 -0.05

6 16.0 -3.89 -3.76 -0.14 -0.92 -0.90 -0. 02 -0.96 -0.92 -0.04 -2.10 -2.02 -0.08

7 16.5 -4.60 -4.40 -0.20 -1.11 -1.07 -0. 04 -1.10 -1.05 -0.05 -2.48 -2.37 -0.11

8 17.0 -4.66 -0.26 -1.13 -0.06 -1.12 -0.07 -2.51 -0.15

9 18.0 -4.81 -0.40 -1.17 -0.09 -1.15 -0.10 -2.59 -0.23

10 19.0 -4.98 -0.57 -1.21 -0.14 -1.19 -0.14 -2.69 -0.32

11 20.0 -5.17 -0.76 -1.26 -0.18 -1.23 -0.18 -2.79 -0.42

12 21.0 -5.36 -0.96 -1.31 -0.24 -1.27 -0.22 -2.90 -0.53

13 22.0 -5.46 -1.05 -1.33 -0.26 -1.29 -0.24 -2.95 -0.58

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. ** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

10-77Table 10.5.10 Split System Central Air Conditioners: Discounted Cumulati ve National and Regional NPV Results from 2016-2046 for the Residential and Commercial Sectors (3% Discount Rate)

CSL SEER Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

1 13.5 -0.76 -0.76 0.00 0.08 0.06 0.02 -0.04 -0.05 0.01 -0.93 -0.88 -0.05

2 14.0 -4.14 -4.11 -0.03 0.10 0.00 0.10 -0.37 -0.41 0.03 -4.35 -4.14 -0.21

3 14.5 -9.32 -9.25 -0.07 -0.37 -0.53 0.16 -1.07 -1.13 0.06 -8.71 -8.33 -0.38

4 15.0 -16.86 -16.71 -0.15 -1.48 -1.69 0. 22 -2.25 -2.33 0.07 -14.27 -13.70 -0.57

5 15.5 -26.88 -26.59 -0.29 -3.28 -3.54 0. 26 -3.95 -4.02 0.07 -21.04 -20.25 -0.79

6 16.0 -38.02 -37.53 -0.49 -5.54 -5.81 0. 27 -5.89 -5.95 0.06 -28.16 -27.13 -1.04

7 16.5 -44.43 -43.67 -0.76 -6.89 -7.17 0. 27 -7.01 -7.05 0.04 -32.18 -30.86 -1.32

8 17.0 -44.77 -1.09 -6.91 0.25 -7.05 0.00 -32.48 -1.63

9 18.0 -45.67 -1.99 -7.01 0.16 -7.17 -0.12 -33.23 -2.37

10 19.0 -46.89 -3.22 -7.19 -0.03 -7.36 -0.31 -34.14 -3.28

11 20.0 -48.41 -4.74 -7.47 -0.30 -7.62 -0.57 -35.19 -4.33

12 21.0 -50.13 -6.46 -7.81 -0.64 -7.92 -0.87 -36.30 -5.44

13 22.0 -51.02 -7.35 -8.00 -0.83 -8.08 -1.03 -36.86 -6.00

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. ** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

10-78-50 -45 -40 -35 -30 -25 -20 -15 -10

-5 0 5

1 2 3 4 5 6 7 8 9 10 11 12 13

Candidate Standard LevelNational and Regional NPV (billion 2008$)

Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.6 Split System Central Air Conditioners: Cumulative Nation al and Regional NPV from 2016-2046 (3% discount rate)

Tables 10.5.11 through 10.5.13 show the NPVs at a seven percent real discount rate for the CSLs analyzed for split system CACs for th e Nation as a whole and for each of the three climate regions evaluated separately (the hot-humid, hot-dry, and rest of the Nation). Table 10.5.11 shows the results for the residential sector only, Table 10.5.12 shows the results for the commercial sector only, and Table 10.5.13 shows the results for both sectors. Each table shows the breakdown of the NPV for coil-only units a nd blower coil units. Figure 10.5.7 depicts the total national and regional NPVs for each CSL.

10-79Table 10.5.11 Split System Central Air Conditioners: Discounted Cumulati ve National and Regional NPV Results from 2016-2046 for the Residential Sector (7% Discount Rate)

CSL SEER Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

1 13.5 -0.37 -0.36 -0.01 0.00 -0.01 0.00 -0.03 -0.03 0.00 -0.39 -0.36 -0.02

2 14.0 -1.95 -1.88 -0.07 -0.11 -0.13 0.02 -0.20 -0.20 0.00 -1.81 -1.71 -0.10

3 14.5 -4.26 -4.13 -0.12 -0.42 -0.45 0.03 -0.51 -0.52 0.00 -3.61 -3.42 -0.18

4 15.0 -7.46 -7.28 -0.18 -0.98 -1.01 0.04 -1.02 -1.02 0.00 -5.85 -5.58 -0.27

5 15.5 -11.81 -11.55 -0.26 -1.85 -1.89 0. 04 -1.75 -1.75 0.00 -8.67 -8.30 -0.36

6 16.0 -17.06 -16.69 -0.37 -3.00 -3.03 0. 04 -2.67 -2.66 -0.01 -11.88 -11.42 -0.46

7 16.5 -20.51 -20.02 -0.50 -3.78 -3.81 0. 02 -3.29 -3.26 -0.03 -13.96 -13.38 -0.58

8 17.0 -20.67 -0.65 -3.80 0.01 -3.31 -0.05 -14.08 -0.70

9 18.0 -21.07 -1.05 -3.86 -0.06 -3.37 -0.10 -14.38 -1.01

10 19.0 -21.60 -1.58 -3.96 -0.15 -3.45 -0.19 -14.75 -1.37

11 20.0 -22.25 -2.23 -4.09 -0.28 -3.56 -0.30 -15.17 -1.79

12 21.0 -22.99 -2.97 -4.25 -0.45 -3.69 -0.43 -15.63 -2.25

13 22.0 -23.45 -3.44 -4.36 -0.55 -3.78 -0.51 -15.91 -2.53

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. ** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

Table 10.5.12 Split System Central Air Conditioners: Discounted Cumulati ve National and Regional NPV Results from 2016-2046 for the Commercial Sector (7% Discount Rate)

CSL SEER Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

1 13.5 -0.06 -0.05 0.00 -0.01 -0.01 0.00 -0.01 -0.01 0.00 -0.03 -0.03 0.00

2 14.0 -0.25 -0.24 -0.01 -0.06 -0.05 0.00 -0.06 -0.06 0.00 -0.14 -0.13 -0.01

3 14.5 -0.49 -0.47 -0.02 -0.11 -0.11 0.00 -0.13 -0.12 -0.01 -0.26 -0.25 -0.01

4 15.0 -0.81 -0.78 -0.03 -0.19 -0.19 -0. 01 -0.20 -0.19 -0.01 -0.44 -0.42 -0.02

5 15.5 -1.25 -1.21 -0.05 -0.31 -0.30 -0. 01 -0.30 -0.29 -0.01 -0.67 -0.64 -0.03

6 16.0 -1.81 -1.75 -0.07 -0.46 -0.45 -0. 01 -0.43 -0.41 -0.02 -0.96 -0.93 -0.04

7 16.5 -2.21 -2.12 -0.09 -0.57 -0.55 -0. 02 -0.51 -0.49 -0.02 -1.17 -1.12 -0.05

8 17.0 -2.24 -0.12 -0.58 -0.03 -0.51 -0.03 -1.19 -0.06

9 18.0 -2.30 -0.18 -0.59 -0.05 -0.53 -0.04 -1.22 -0.10

10 19.0 -2.38 -0.26 -0.61 -0.06 -0.54 -0.06 -1.26 -0.14

11 20.0 -2.46 -0.34 -0.64 -0.09 -0.56 -0.08 -1.30 -0.18

12 21.0 -2.55 -0.43 -0.66 -0.11 -0.58 -0.09 -1.35 -0.23

13 22.0 -2.60 -0.48 -0.67 -0.12 -0.59 -0.11 -1.38 -0.26

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. ** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

10-80Table 10.5.13 Split System Central Air Conditioners: Discounted Cumulati ve National and Regional NPV Results from 2016-2046 for the Residential and Commercial Sectors (7% Discount Rate)

CSL SEER Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil Total** CoilOnly Blower Coil

1 13.5 -0.43 -0.41 -0.02 -0.01 -0.02 0.00 -0.04 -0.04 0.00 -0.42 -0.39 -0.03

2 14.0 -2.20 -2.12 -0.08 -0.17 -0.18 0.01 -0.26 -0.26 0.00 -1.95 -1.84 -0.11

3 14.5 -4.74 -4.60 -0.14 -0.53 -0.56 0.02 -0.64 -0.64 0.00 -3.87 -3.67 -0.20

4 15.0 -8.27 -8.06 -0.21 -1.17 -1.20 0.03 -1.22 -1.21 -0.01 -6.29 -6.00 -0.29

5 15.5 -13.06 -12.75 -0.31 -2.16 -2.19 0. 03 -2.05 -2.04 -0.01 -9.33 -8.95 -0.39

6 16.0 -18.87 -18.44 -0.43 -3.46 -3.48 0. 02 -3.10 -3.07 -0.03 -12.85 -12.35 -0.50

7 16.5 -22.73 -22.14 -0.59 -4.35 -4.36 0. 00 -3.80 -3.75 -0.05 -15.13 -14.50 -0.63

8 17.0 -22.91 -0.77 -4.38 -0.02 -3.82 -0.07 -15.27 -0.77

9 18.0 -23.37 -1.24 -4.46 -0.10 -3.89 -0.15 -15.60 -1.11

10 19.0 -23.98 -1.84 -4.57 -0.22 -4.00 -0.25 -16.01 -1.51

11 20.0 -24.71 -2.57 -4.73 -0.37 -4.12 -0.38 -16.47 -1.98

12 21.0 -25.53 -3.40 -4.91 -0.56 -4.27 -0.52 -16.98 -2.48

13 22.0 -26.05 -3.91 -5.03 -0.68 -4.37 -0.62 -17.29 -2.79

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. ** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER.

10-81-30 -25 -20 -15 -10

-5 0

1 2 3 4 5 6 7 8 9 10 11 12 13

Candidate Standard LevelNational and Regional NPV (billion 2008$)

Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.7 Split System Central Air Conditioners: Cumulative Nation al and Regional NPV from 2016-2046 (7% discount rate)

Central Air Conditio ners—Single Package Table 10.5.14 shows the NPVs at a three percent real discount rate for the CSLs analyzed for single package CACs for the Nation as a whole and for each of the three climate regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 10.5.14 are also broken down by sector (i.e., resi dential and commercial) . Figure 10.5.8 depicts the total national and regional NPVs for each CSL.

10-82Table 10.5.14 Single Package Central Air Conditioners : Discounted Cumu lative National and Regional NPV Results fr om 2016-2046 (3% Discount Rate)

CSL SEER Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm.

1 13.5 -0.62 -0.55 -0.07 -0.03 -0.02 -0. 02 -0.07 -0.06 -0.02 -0.54 -0.50 -0.04

2 14.0 -1.26 -1.12 -0.13 -0.10 -0.07 -0. 03 -0.16 -0.13 -0.03 -1.05 -0.98 -0.07

3 14.5 -2.32 -2.09 -0.23 -0.25 -0.20 -0. 05 -0.32 -0.27 -0.06 -1.82 -1.69 -0.13

4 15.0 -3.31 -2.98 -0.33 -0.42 -0.35 -0. 08 -0.49 -0.41 -0.08 -2.49 -2.31 -0.18

5 15.5 -4.53 -4.08 -0.45 -0.66 -0.56 -0. 11 -0.70 -0.59 -0.11 -3.27 -3.03 -0.24

6 16.0 -5.67 -5.11 -0.56 -0.91 -0.77 -0. 14 -0.90 -0.77 -0.13 -3.97 -3.67 -0.30

7 16.6 -6.37 -5.74 -0.63 -1.07 -0.91 -0. 16 -1.02 -0.88 -0.15 -4.39 -4.05 -0.34

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV.

-7 -6 -5 -4 -3 -2 -1 0

1 2 3 4 5 6 7

Candidate Standard LevelNational and Regional NPV (billion 2008$)

Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.8 Single Package Central Air Conditi oners: Cumulative National and Regional NPV from 2016-2046 (3% discount rate)

Table 10.5.15 shows the NPVs at a seven percent real discount rate for the CSLs analyzed for single package CACs for the Nation as a whole and for each of the three climate regions that were evaluated separately (the hot-h umid, hot-dry, and rest of the Nation). NPVs in Table 10.5.14 are also broken down by sector (i.e ., residential and co mmercial). Figure 10.5.9 depicts the total national and regional NPVs for each CSL.

10-83Table 10.5.15 Single Package Central Air Conditioners : Discounted Cumu lative National and Regional NPV Results fr om 2016-2046 (7% Discount Rate)

CSL SEER Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm.

1 13.5 -0.33 -0.29 -0.04 -0.04 -0.03 -0. 01 -0.05 -0.04 -0.01 -0.25 -0.23 -0.02

2 14.0 -0.65 -0.58 -0.07 -0.09 -0.08 -0. 02 -0.09 -0.08 -0.02 -0.47 -0.44 -0.04

3 14.5 -1.15 -1.04 -0.11 -0.19 -0.16 -0. 03 -0.18 -0.15 -0.03 -0.82 -0.76 -0.06

4 15.0 -1.62 -1.46 -0.15 -0.28 -0.24 -0. 04 -0.26 -0.22 -0.04 -1.11 -1.03 -0.08

5 15.5 -2.21 -2.01 -0.21 -0.41 -0.36 -0. 05 -0.36 -0.31 -0.05 -1.47 -1.36 -0.11

6 16.0 -2.83 -2.57 -0.27 -0.56 -0.49 -0. 07 -0.47 -0.41 -0.06 -1.83 -1.69 -0.14

7 16.6 -3.27 -2.96 -0.31 -0.66 -0.58 -0. 08 -0.55 -0.48 -0.07 -2.08 -1.92 -0.16

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV.

-3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0

1 2 3 4 5 6 7

Candidate Standard LevelNational and Regional NPV (billion 2008$)

Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.9 Split System Central Air Conditioners: Cumulative National and Regional NPV from 2016-2046 (7% discount rate)

10-8410.5.4.2 Heat Pumps

The following sections provide the results of calculating net pres ent value (NPV) based on a discount rate of seven percent for the candida te standard levels DOE analyzed for the two product classes of heat pumps, split system and single package. Results are cumulative to 2046.

Heat Pumps—Split System Table 10.5.16 shows the NPVs at a three percent real discount rate for the CSLs analyzed for split system HPs for the Nation as a whole and for each of the three climate regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 10.5.16 are also broken down by sector (i.e., residential a nd commercial). Figure 10.5.10 depicts the total national and regional NPVs for each CSL.

Table 10.5.16 Split System Heat Pumps: Discounted Cumulative Nation al and Regional NPV Results from 2016-2046 (3% Discount Rate)

CSL SEER HSPF Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm.

1 13.5 7.85 0.34 0.37 -0.03 0.30 0.31 -0.01 0.09 0.09 -0.01 0.01 0.02 -0.01

2 14.0 8.00 1.73 1.88 -0.15 1.55 1.60 -0.04 0.44 0.47 -0.03 0.05 0.12 -0.06

3 14.5 8.15 3.12 3.40 -0.28 2.82 2.90 -0.08 0.81 0.86 -0.06 0.09 0.21 -0.12

4 15.0 8.30 4.31 4.78 -0.47 4.01 4.16 -0.14 1.15 1.24 -0.09 0.06 0.26 -0.20

5 15.5 8.45 5.28 6.04 -0.76 5.14 5.39 -0.25 1.47 1.61 -0.14 -0.05 0.26 -0.31

6 16.0 8.60 6.27 7.45 -1.19 6.35 6.77 -0.42 1.81 2.03 -0.22 -0.19 0.29 -0.48

7 17.0 9.10 7.12 9.14 -2.03 7.94 8.69 -0.75 2.27 2.62 -0.35 -0.63 0.18 -0.81

8 18.0 9.60 6.07 9.00 -2.93 8.49 9.60 -1.11 2.46 2.96 -0.50 -1.64 -0.48 -1.16

9 19.0 10.10 4.17 7.74 -3.57 8.21 9.58 -1.37 2.44 3.04 -0.60 -2.71 -1.30 -1.40

10 19.5 10.30 3.70 7.37 -3.67 8.07 9.48 -1.41 2.41 3.02 -0.61 -2.94 -1.50 -1.44

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV.

10-85-3 -2 -1 0 1 2 3 4 5 6 7 8 9

1 2 3 4 5 6 7 8 9 10

Candidate Standard LevelNational and Regional NPV (billion 2008$) Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.10 Split System Heat Pumps: Cumulative National and Regional NPV from 2016-2046 (3% discount rate)

Table 10.5.17 shows the NPVs at a seven percent real discount rate for the CSLs analyzed for split system HPs for the Nation as a whole and for each of the three climate regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 10.5.17 are also broken down by sector (i.e., resi dential and commercial) . Figure 10.5.11 depicts the total national and regional NPVs for each CSL.

10-86Table 10.5.17 Split System Heat Pumps: Discounted Cumulative Nation al and Regional NPV Results from 2016-2046 (7% Discount Rate)

CSL SEER HSPF Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm.

1 13.5 7.85 0.06 0.08 -0.02 0.08 0.08 -0.01 0.02 0.03 0.00 -0.02 -0.01 -0.01

2 14.0 8.00 0.32 0.40 -0.08 0.39 0.42 -0.03 0.13 0.14 -0.02 -0.08 -0.05 -0.03

3 14.5 8.15 0.57 0.72 -0.15 0.72 0.77 -0.05 0.23 0.26 -0.03 -0.16 -0.10 -0.06

4 15.0 8.30 0.68 0.92 -0.24 0.97 1.06 -0.08 0.32 0.36 -0.04 -0.27 -0.18 -0.09

5 15.5 8.45 0.61 0.98 -0.36 1.15 1.28 -0.13 0.38 0.45 -0.06 -0.45 -0.30 -0.14

6 16.0 8.60 0.44 0.99 -0.55 1.30 1.51 -0.21 0.44 0.54 -0.10 -0.67 -0.45 -0.22

7 17.0 9.10 -0.08 0.85 -0.92 1.41 1.78 -0.37 0.51 0.66 -0.15 -1.08 -0.72 -0.36

8 18.0 9.60 -1.35 -0.02 -1.33 1.12 1.66 -0.53 0.47 0.69 -0.22 -1.73 -1.21 -0.51

9 19.0 10.10 -2.92 -1.26 -1.66 0.59 1.26 -0.68 0.37 0.63 -0.27 -2.42 -1.78 -0.64

10 19.5 10.30 -3.32 -1.60 -1.72 0.43 1.13 -0.70 0.33 0.61 -0.28 -2.59 -1.93 -0.66

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV.

-4 -3 -2 -1 0 1 2

1 2 3 4 5 6 7 8 9 10

Candidate Standard LevelNational and Regional NPV (billion 2008$) Nation

Hot-Humid
Hot-Dry Rest-of-Country

Figure 10.5.11 Split System Heat Pumps: Cumulative National and Regional NPV from 2016-2046 (7% discount rate)

10-87Heat Humps—Single Package Table 10.5.18 shows the NPVs at a three percent real discount rate for the CSLs analyzed for single package HPs for the Nation as a whole and for each of the three climate regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 10.5.18 are also broken down by sector (i.e., resi dential and commercial) . Figure 10.5.12 depicts the total national and regional NPVs for each CSL.

Table 10.5.18 Single Package Heat Pump s: Discounted Cumulative National and Regional NPV Results from 2016-2046 (3% Discount Rate)

CSL SEER HSPF Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm.

1 13.5 7.85 -0.05 -0.02 -0.03 0.03 0.04 -0.01 0.01 0.01 0.00 -0.05 -0.04 -0.01

2 14.0 8.00 -0.22 -0.14 -0.08 0.03 0.06 -0.03 0.01 0.03 -0.01 -0.16 -0.13 -0.03

3 14.5 8.00 -0.58 -0.42 -0.16 -0.04 0.03 -0.06 0.00 0.03 -0.03 -0.35 -0.29 -0.06

4 15.0 8.00 -0.94 -0.70 -0.24 -0.13 -0.03 -0.10 -0.02 0.02 -0.04 -0.51 -0.42 -0.09

5 15.5 8.50 -1.35 -1.02 -0.33 -0.27 -0.14 -0.13 -0.05 0.00 -0.05 -0.67 -0.55 -0.12

6 16.0 9.00 -1.86 -1.46 -0.40 -0.47 -0.31 -0.16 -0.10 -0.03 -0.07 -0.87 -0.72 -0.15

7 16.4 9.00 -2.16 -1.73 -0.43 -0.60 -0.42 -0.18 -0.13 -0.06 -0.07 -0.99 -0.83 -0.16

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV.

10-88National and Regional NPV (billion 2008$) 0.5

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

1 2 3 4 5 6 7 Nation

Hot-Humid
Hot-Dry Rest-of-Country

Candidate Standard Level

Figure 10.5.12 Single Package Heat Pumps: Cumulati ve National and Regional NPV from 2016-2046 (3% discount rate)

Table 10.5.19 shows the NPVs at a three percent real discount rate for the CSLs analyzed for single package HPs for the Nation as a whole and for each of the three climate regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 10.5.19 are also broken down by sector (i.e., resi dential and commercial) . Figure 10.5.13 depicts the total national and regional NPVs for each CSL.

Table 10.5.19 Single Package Heat Pump s: Discounted Cumulative National and Regional NPV Results from 2016-2046 (7% Discount Rate)

CSL SEER HSPF Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry ( bill. 2008$) Rest of Cntry (2008$)

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm.

1 13.5 7.85 -0.05 -0.03 -0.01 -0.01 0.00 -0.01 0.00 0.00 0.00 -0.03 -0.02 0.00

2 14.0 8.00 -0.18 -0.14 -0.04 -0.04 -0.03 -0.02 -0.01 0.00 -0.01 -0.09 -0.08 -0.01

3 14.5 8.00 -0.42 -0.35 -0.08 -0.12 -0.09 -0.03 -0.02 -0.01 -0.01 -0.20 -0.17 -0.03

4 15.0 8.00 -0.63 -0.52 -0.11 -0.20 -0.15 -0.05 -0.04 -0.02 -0.02 -0.29 -0.25 -0.04

5 15.5 8.50 -0.87 -0.72 -0.15 -0.30 -0.23 -0.06 -0.06 -0.04 -0.02 -0.37 -0.31 -0.06

6 16.0 9.00 -1.18 -0.99 -0.19 -0.43 -0.35 -0.08 -0.09 -0.06 -0.03 -0.48 -0.41 -0.07

7 16.4 9.00 -1.38 -1.16 -0.21 -0.52 -0.43 -0.09 -0.11 -0.08 -0.03 -0.56 -0.48 -0.08

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV.

10-89National and Regional NPV (billion 2008$) 0.0

-0.5

-1.0

-1.5 Nation

Hot-Humid
Hot-Dry Rest-of-Country

1 2 3 4 5 6 7

Candidate Standard Level

Figure 10.5.13 Single Package Heat Pumps: Cumulati ve National and Regional NPV from 2016-2046 (7% discount rate)

10-90REFERENCES

1 Air-Conditioning, Heating and Refrigerator Institute. Historical shipments and shipmentweighted efficiency data submittal. December 2008.

2 U.S. Department of Energy –Energy Information Administration. Annual Energy Outlook 2009 with Projections to 2030 . March 2009. U.S. DOE–EIA: Washington, D.C. DOE/EIA0383(2009). < http://www.eia.doe.gov/oiaf/aeo/pdf/0383(2009).pdf >

3 Office of Management and Budget. OMB Circular A-4, Regulatory Analysis . 2003. OMB: Washington, D.C. September 17, 2003.

< www.whitehouse.gov/omb/assets/omb/circulars/a004/a-4.pdf >

10-91CHAPTER 11. LIFE-CYCLE COST SUBGROUP ANALYSIS

TABLE OF CONTENTS

11.1 INTRODUCTION

............................................................................................................ 11-1 11.2 GENERAL APPROACH

.................................................................................................. 11-1

11-iCHAPTER 11. LIFE-CYCLE COST SUBGROUP ANALYSIS

11.1 INTRODUCTION

The life-cycle cost (LCC) subgroup analysis evaluates impacts on any identifiable groups or customers who may be disproportionately affect ed by any national energy efficiency standard level. The U.S. Department of Energy (DOE) will conduct this analysis as one of the analyses for the notice of proposed rulemaking. DOE will accomplish this, in part, by analyzing the LCC and payback periods (PBPs) for thos e customers that fall into any identifiable groups. DOE plans to evaluate variations in regional energy prices and va riations in energy use that might affect the net present value of a standard to customer subpopul ations. To the extent possible, DOE will obtain estimates of each input parameter’s variability and will consider this variability in its calculation of customer impacts. DOE plans to perform sensit ivity analyses to consider how differences in energy use will affect subgroups of customers.

DOE will determine the impact on customer subgroups using the LCC spreadsheet model, which allows for different data inputs. The standard life-cycle cost and payback period analysis (described in the preliminary Technical Support Document (TSD) chapter 8) focuses on residential and light commercial consumers that us e residential central air conditioners and heat pumps (CACs). DOE can use the LCC spreadshee t model to analyze the LCC for any subgroup by sampling only that subgroup. Model inputs used by the Department to determine LCC and PBPs are described in detail in the life-cycle cost and payback period analysis (see TSD chapter 8).

In the case of CACs, some possible consumer subgroups include low income consumers, households headed by older pe rsons, and small businesses.

11.2 GENERAL APPROACH

For CACs, DOE estimates LCC savings and PBPs for consumers in the residential and light commercial sectors at the regional level.

DOE will use the LCC spreadsheet model to evaluate impacts on consumer subgroups, especially low-income and small-business consumers. DOE can analyze the LCC for any subgroup by applying the LCC spreadsheet model to only that subgroup within individual regions. DOE is particularly sensitive to increases in the consumer price of the considered products, wishing to avoid a negative economic impact on any identified consumer subgroup with limited capacity to absorb price increases. The impacts on subgroups will be compared to impacts on the overall population.

In the LCC subgroup analysis, DOE will exa mine a variety of consumer sub-populations. This analysis will determine whether any par ticular group of consumers would be adversely affected.

11-1CHAPTER 12 : PRELIMINARY MANUFACTURER IMPACT ANALYSIS

TABLE OF CONTENTS

12.1 INTRODUCTION

......................................................................................................... 12-1 12.2 METHODOLOGY

........................................................................................................ 12-1 12.2.1 Phase 1: Industry Profile

.................................................................................... 12-2 12.2.2 Phase 2: Industry Cash-Flow Analysis and Interview Guide

............................ 12-2 12.2.3 Phase 3: Subgroup Analysis

............................................................................... 12-2 12.3 PRELIMINARY MANUFACTURER IMPACT ANALYSIS RESULTS

................... 12-4 12.3.1 Industry Overview

............................................................................................. 12-5 12.3.2 Interview Topics and Preliminary Findings

....................................................... 12-7 12.3.3 Overall Key Issues

........................................................................................... 12-10

LIST OF TABLES

Table 12.3.1 Central Air Conditioner and Heat Pu mp Industry Employment and Earnings

.... 12-5 Table 12.3.2 Central Air Conditioner and Heat Pump Industry Material and Payroll Costs

.... 12-5 Table 12.3.3 Central Air Conditioner and Heat Pu mp Industry End-of-Year Inventory

.......... 12-6 Table 12.3.4 Full Production Capaci ty Utilization Rates

.......................................................... 12-6 Table 12.3.5 Central Air Conditioner and Heat Pump Industry Year 2007 Data as a Percentage of
Revenue

....................................................................................................................... ..... 12-7 Table 12.3.6 Other 2007 Financials

........................................................................................... 12 -7CHAPTER 12: PRELIMINARY MANUFACTURER IMPACT ANALYSIS

12.1 INTRODUCTION

The purpose of the manufacturer impact analysis (MIA) is to identify and quantify the likely impacts of amended energy conservation standards on manufacturers. In the Notice of Proposed Rulemaking (NOPR) stage of analys is, the U.S. Department of Energy (DOE) considers a wide range of quan titative and qualitative industry impacts that might occur due to an amended energy conservation standard. For exampl e, a particular standa rd level could require changes in manufacturing practices. DOE identifies and analyzes these impacts during the NOPR stage. To the extent that it is appropriate for this rulemaking, DOE applies this methodology to evaluate amended energy conservation standard s for central air conditioners and heat pumps.

DOE announced changes to the MIA format through a report issued to Congress on January 31, 2006 (as required by section 141 of the Energy Policy Act of 2005 (EPACT 2005), entitled “Energy Conservation Standards Activities.” 1 Previously, DOE did not report any MIA results until the notice of proposed rulemaking st age (NOPR). However, under this new format, DOE collects, evaluates, and reports preliminary information and data in the preliminary analysis. Such preliminary information includes efficiency and market data, key issues, production mixes, conversion costs, foreign compe tition, market shares, industry consolidation, and cumulative regulatory information. DOE so licited this information during the preliminary manufacturer interviews and reports the results in this chapter. Appendix 12A includes a copy of the interview guide that DOE distributed to manufacturers.

12.2 METHODOLOGY

DOE conducts the MIA in three phases. In Ph ase 1, DOE creates an industry profile to characterize the industry and conducts a prelimin ary MIA to identify important issues that require consideration. Se ction 12.3 of this chapter presents initial findings of the Phase 1 analysis. In Phase 2, DOE prepares an industry cash flow model and an interview questionnaire to guide subsequent discussions with manufactur ers. In Phase 3, DOE interviews manufacturers and assesses the impacts of amended energy conservation standards both quantitatively and qualitatively. DOE assesses industry and subgro up cash flow impacts and industry net present value (INPV) using the Government Regulatory Impact Model (GRIM). DOE then assesses impacts on competition, manufacturing capacity, em ployment, and regulatory burden based on manufacturer interviews and discussions. DOE wi ll conduct Phase 2 and 3 for the NOPR stage of the rulemaking.

1 This report is available on the DOE website at www.eere.energy.gov/buildings/appliance_standards/2006_schedule_setting.html

.

12-112.2.1 Phase 1: Industry Profile

In Phase 1 of the MIA, DOE collects pertinent qualitative and quantitative financial and market information. This includes wages, em ployment, industry cost data, and capacity utilization rates for manufacturers of central air conditioners and heat pumps. Sources of information include reports published by indus try groups, trade journals, the U.S. Census Bureau, and Securities Exchange Commission (S EC) 10-K filings. In addition, DOE relies on information from its market and technology asse ssment, engineering analysis, life-cycle cost analysis, and consumer price analysis to characterize the central air conditioner and heat pump manufacturing industry.

12.2.2 Phase 2: Industry Cash-Flow Analysis and Interview Guide

In Phase 2, DOE performs a preliminary industry cash-flow analysis and prepares written guidelines for interviewing manufacturers.

12.2.2.1 Industry Cash-Flow Analysis

DOE uses the GRIM to analyze the financia l impacts of amended energy conservation standards. Amended energy conservation standard s may require additional investment, increase production costs, and affect revenue through high er prices and possibly lower shipments. The GRIM uses several factors to determine a series of annual cash flows for the year that amended energy conservation standards become effectiv e and for several years after implementation. These factors include annual expected revenues, costs of sales, selling and general administration costs, taxes, and capital expenditures. Inputs to the GRIM include financial information, manufacturing costs, shipment forecasts, and pr ice forecasts developed in other analyses. The financial information is developed from publicly available data and confidentially submitted manufacturer information. DOE compares the resu lts of the GRIM against baseline projections in which no amended energy conservation standa rds are in place. The financial impact of amended energy conservation standards is the di fference between the two sets of discounted annual cash flows.

12.2.2.2 Interview Guide

DOE conducts interviews with manufacturers to gather in formation on the effects of amended energy conservation standards on revenu es and finances, direct employment, capital assets, and industry competitiven ess. Before the interviews, which occur in Phase 3, DOE distributes an interview guide to help identif y the impacts of amended energy conservation standards on individual manufactur ers or subgroups of manufacturers. Interview guide topics include: production costs; ship ment projections and market share; product mix; conversion costs; markups and profitab ility; assessment of the impact on competition, manufacturing capacity, and other topics that are relevant to assessing the impacts of amended energy conservation standards on the central air conditioner and heat pump industry.

12.2.3 Phase 3: Subgroup Analysis

Phase 3 activities take place afte r publication of the preliminary analysis notice of public meeting. These activities include manufacturer in terviews; revision of the industry cash-flow

12-2analysis; a manufacturer subgroup analysis; an assessment of the impacts on industry competition, manufacturing capacity, direct employment and the cumulative regulatory burden; and other qualitative impacts.

12.2.3.1 Manufacturer Interviews

DOE conducts detailed interviews with manufacturers to gain insight into the potential impacts of amended energy conservation standard s on sales, direct empl oyment, capital assets, and industry competitiveness. Interviews are scheduled well in advance to provide every opportunity for key individuals to be availabl e for comment. Although a written response to the questionnaire is acceptable, DOE prefers interactiv e interviews, which help clarify responses and provide the opportunity to identify additional issu es not specifically addressed in the interview questionnaire. A non-disclosure agreement allows confidential or sensitiv e information to be considered in DOE’s decision-making process. However, confidential information will not be made available in the public record. At most, sensitive or confidential information may be aggregated and presented in i ndustry-wide representations.

DOE supplements the information gathered in Phase 1 and the cash flow analysis performed in Phase 2 with information gathered during manufacturer interviews. The interview process is critical to the MIA because it provides an opportunity for interested parties to privately express their views on important issues.

12.2.3.2 Revised Industry Cash-Flow Analysis

During the interviews, DOE requests inform ation about profitabilit y impacts, necessary plant changes, and other manufacturing impacts. Following the interview process, DOE revises its industry cash flow model based on the feedback it receives.

12.2.3.3 Manufacturer Subgroup Analysis

Using average cost assumptions to devel op an industry cash flow estimate will not adequately assess differential impacts among ma nufacturer subgroups. Smaller manufacturers, niche players, and manufacturers exhibiting a cost structure that differs largely from the industry average could be more negatively affected. Id eally, DOE would consider the impact on every firm individually; however, it typically uses the results of the industry characterization to group manufacturers with similar characteristics. During the interviews, DOE discusses the potential subgroups that have been identified for th e analysis. DOE asks manufacturers and other interested parties to suggest what subgroups or characteristics are most appropriate for the analysis.

12.2.3.4 Competitive Impact Assessment

Section 342 (6)(B)(i)(V) of the Energy Policy Act of 1992 (EPCA) directs DOE to consider any lessening of competition likely to result from imposition of standards. EPCA further directs the U.S. Attorney General to determine the impacts, if any, of any decrease in competition. DOE attempts to gath er and report firm-specific fi nancial informa tion and impacts. The competitive impact assessment will be based on manufacturer cost data and information collected from interviews. The interviews will focus on assessing asymmetrical cost increases to

12-3some manufacturers, the potential increase in business risks from an increased proportion of fixed costs, and potential barriers to market entry ( e.g ., proprietary technologies). The competitive analysis will also focus on assessing any differential impacts to smaller manufacturers.

12.2.3.5 Manufacturing Capacity Impact

One of the significant outcomes of amended energy conservation standards can be the obsolescence of existing manufacturing assets, in cluding tooling and other investments. The manufacturer interview guide will have a seri es of questions to help identify impacts on manufacturing capacity, specifically capacity utilization and plant location decisions in North America with and without amended energy conser vation standards; the ability of manufacturers to upgrade or remodel existing facilities to accommodate the new requirements; the nature and value of stranded assets, if any; and estimates for any one-time restructuring or other charges, where applicable.

12.2.3.6 Employment Impact

The impact of amended energy conservation standards on employment is an important consideration in the rulemaking process. To as sess how domestic employ ment patterns might be affected, the interview will explore current employ ment trends in the central air conditioner and heat pump industry and solicit manufacturer views on changes in employment patterns that may result from increased standard levels. The employment impacts section of the interview guide will focus on current employment levels at production facilities; expected future employment levels with and without an amended energy c onservation standard; differences in workforce skills; and employee retraining.

12.2.3.7 Cumulative Regu latory Burden

DOE seeks to mitigate the overlapping effects on manufacturers due to energy conservation standards and other regulatory actions. If possible, DOE will consider the impact on manufacturers of multiple, pr oduct-specific regulatory actions.

12.3 PRELIMINARY MANUFACTURER IMPACT ANALYSIS RESULTS
For the preliminary analysis, DOE conducted a preliminary evaluation of the impact of potential amended energy conser vation standards on the central air conditioning and heat pump industry. A primary focus was to identify the cumulative burden that the industry faces from the overlapping effect of new or recent DOE energy conservation standards a nd/or other regulatory action affecting the same equipment or industry.

The primary source of information for this an alysis was interviews with manufacturers of central air conditioning and heat pump produc ts, conducted during the spring of 2009. To maintain confidentiality, DOE only reports aggreg ated information here. DOE does not disclose company-specific information, nor does it identif y the individual manufact urers that disclosed information.

12-412.3.1 Industry Overview

The following section summarizes publicly available industry data.

12.3.1.1 Industry Cost Structure

DOE developed the central air conditioner and heat pump industry cost structure from the U.S. Census Bureau, Annual Survey of Manufacturers, Statistics for Industry Groups and Industries from 2002-2007. Residential Central Air Conditioner and Heat Pump manufacturing is classified under the North American Industry Classifica tion System (NAICS) code 333415 ( AC, Refrigeration, and Forced Air Heating ).

Table 12.3.1 presents the central air conditione r and heat pump employment levels and earnings from 2002 to 2007. The statistics illustrate approximately an 8-percent decrease in the number of production workers and in the ov erall number of employees from 2002 to 2007.

Table 12.3.1 Employment and Earnings for th e Central Air Conditioner and Heat Pump Industry

Year Production Workers All Employees Annual Payroll (thousand $)

2002 80,400 108,252 3,815,129
2003 77,471 104,646 3,775,799

2004 73,559 99,669 3,707,969
2005 76,011 102,354 3,942,808
2006 74,909 98,097 4,019,813

2007 73,993 100,284 3,975,785
Source: U.S. Census Bureau. Annual Survey of Manufacturers, 2002-2007

Table 12.3.2 presents the costs of materials and industry payroll as a percentage of shipment value from 2002 to 2007. The cost of mate rials as a percentage of shipment value has steadily increased from 2002 to 2007. The cost of payroll for production workers and the cost of total payroll have declined by 17.3 pe rcent and 16.1 percent, respectively.

Table 12.3.2 Material and Payroll Costs for th e Central Air Conditioner and Heat Pump Industry

Year Cost of Materials (percent of shipment value) Cost of Payroll for Production Workers (percent of shipment value) Cost of Total Payroll (percent of shipment value)

2002 49.36 9.83 15.85

2003 50.59 9.53 15.39
2004 51.81 8.99 14.57
2005 53.78 8.52 13.78
2006 53.17 8.87 13.80
2007 55.52 8.12 13.29
Source: U.S. Census Bureau. Annual Survey of Manufacturers, 2002-2007

12-512.3.1.2 Inventory Levels

Table 12.3.3 shows the end-of-year inventory for the central air conditioner and heat pump industry obtained from the U.S. Census Bureau, Annual Survey of Manufacturers, Statistics for Industry Groups and Industries from 2002 to 2007. The end-of-year inventory is defined as the The industry’s end-of-year i nventory from 2002 to 2007 experienced an overall increase when expressed both in dollars a nd as a percentage of shipment value.

Table 12.3.3 End-of-Year Inventory for the Central Air Conditioner and Heat Pump Industry

Year End-of-Year Inventory (thousand $) End-of-Year Inventory (percent of shipment value)

2002 2,302,012 9.57
2003 2,376,827 9.69
2004 2,473,932 9.72
2005 2,687,441 9.39

2006 2,887,139 9.91
2007 3,011,358 10.07
Source: U.S. Census Bureau. Annual Survey of Manufacturers, 2002-2007

DOE obtained full production capacity utilization rates from the U.S. Census Bureau, “Current Industrial Reports,” Survey of Plant Capacity from 2002 to 2006. Table 12.3.4 presents production capacity utilization rates for NAICS code 333415. Full production capacity is defined as the maximum level of produc tion an establishment could attain under normal operating conditions. In the Survey of Plant Capacity report, the full production utili zation rate is a ratio of the actual level of operations to the full production level.

Table 12.3.4 Full Production Capacity Utilizatio n Rates for the Central Air Conditioner and Heat Pump Industry

Year AC and Warm Air Heating and Comm ercial/Industrial Refrigeration Equipment Manufacturing (%)

2002 60

2003 62
2004 60
2005 66
2006 63
Source: U.S. Census Bureau. 2007 Current Industrial Reports: Table 1a - Full Production Capacity Utilization Rates by Industry: Fourth Quarters 2002 through 2006. November 2007

12.3.1.3 Other Industry Data

Table 12.3.5 shows various 2007 statistics for th e central air conditioner and heat pump industry, as taken from Standard and Poor Annual Reports and ma nufacturer 10-K reports.

12-6Table 12.3.5 2007 Financial Data as a Percentage of Revenue for the Central Air Conditioner and Heat Pump Industry

Measure Amount as a Percentage of Revenue Property, Plant, & Equipment, Net 20.0% Depreciation 1.7%

R&D 2.5% Capex 2.2% Selling, General & Admin. Expense 13.2% Working Capital 6.6%

Current Assets 34.0%

EBIT 6.8%
Source: Standard & Poor Annual Reports, 10Ks

Table 12.3.6 presents the 2007 central air c onditioner and heat pump industry data detailing the industry tax rate, real weighted av erage cost of capital, and manufacturer markup. The manufacturer markup is a factor that rais es the manufacturer production cost (MPC) to the manufacturer selling price (MSP). It accounts for non-production costs such as SG&A, R&D, as well as profit.

Table 12.3.6 Other 2007 Financials

Tax Rate as a % of Earnings before Tax 26.4%

Real WACC 10.3% Markup 1.32

12.3.2 Interview Topics and Preliminary Findings

The following section summarizes information gathered during interviews held during the first and second quarters of 2009 for the preliminary MIA.

12.3.2.1 Market Shares and Industry Consolidation

Amended energy conservation standards can alter the competitive dynamics of the marketplace, prompting companies to enter the market, exit the market, or merge with other companies. During preliminary MIA interviews, manufacturers were asked to share their perspectives on industry consolidation both in the absence of amended energy conservation standards and assuming amended st andards at various efficiency levels. The need to assess anticompetitive effects of proposed amended energy conservation standards comes from the need to protect consumer interests. The interview que stions focused on gathering information that assessed:

 disproportionate cost increases to some manufacturers;

 increased proportion of fixed costs potentially increasing business risks; and

 potential barriers to market entry (e.g., proprietary technologies).

During the interviews, DOE solicited information to determine whether amended energy conservation standards could re sult in disproportionate economic or performance penalties for particular consumer or user subgroups. Manufacturers were also asked if amended energy

12-7conservation standards could re sult in products that would be more or less desirable to consumers due to changes in product func tionality, utility, or other features.

Market Shares: DOE inquired about current market shares of manufacturers in the central air conditioning and heat pump industry. DOE also asked how manufacturers expect their market share to change after an amended ener gy conservation standard. One manufacturer said that, under a new standard, some of their competit ors may elect to only participate in a certain product segment, which would lower their overall market share. According to this manufacturer, some companies may choose to exit some regions or product categories due to a lower return on investment under the amended standards when co mpared to a potentially smaller market that could result from higher prices after amended standards. Another manufacturer said that standards favor larger companies, and the market share of smaller firms would not increase. Other manufacturers said that they expect no significant change in market share due to the adoption of the new standard, and that they see this market as a relatively level playing field.

Industry Consolidation: DOE inquired about the potential for industry consolidation in the manufacturer interviews. One manufacturer said that industry consolidation is likely even in the absence of amended standards because the in dustry is currently too small to support seven major manufacturers. Most manufacturers indicated that amended energy conservation standards could accelerate this trend. Some manufacturers said that, depending on the complexities of products required after the adoption of the amende d energy conservation standard, there could be some consolidation. Manufacturers stated that a continued decline in shipments and a relatively high level of financing to comply with the amended standard would harm the industry. Large capital required to comply with the standard c ould harm manufacturers in part because this financing cannot be accounted for until the act ual standard level is public. Finally, one manufacturer indicated that if industry shipments are reduced due to higher prices of standardscompliant products, the industry would require less overall capacity. A lower diminished capacity could come through plant consolidation or company consolidation, but which one is unclear. They also claim that the greatest threat of consolidation comes from Asian firms, which would be potentially interested in buying an American manufacturer for increased access to distribution channels.

12.3.2.2 Production and Product Mix

DOE requested manufacturers’ feedback on wh at they perceived to be the possible impact of energy conservation standards on profita bility. For instance, the capital and product conversion outlays needed to upgrade or redesign products before they ha ve reached the end of their useful life may create significant convers ion costs, resulting in reduced cash flow and stranded investments. Higher en ergy conservation standards could also result in higher per-unit cost that could cause consumers to shift to less expensive products.

Product Mix: Manufacturers indicated that amen ded energy conservation standards would affect the product mix of central air conditioners and heat pumps. According to manufacturers, a reasonable energy conservation standard for central ai r conditioners and heat pumps would still allow for cost-effective, premium-efficiency products to be developed. One manufacturer said that a high energy conservatio n standard could result in a change in their product mix such that they may only offer products at the energy conservation standard. For that

12-8manufacturer, a high energy conservation standard might result in the loss of the opportunity to create up-sells, because consumers may not choos e a slightly more efficient unit. This manufacturer said that a high energy conservation standard increases the chances of market entrants, as producing a full range of products ta kes significant capital expenditures and entrants could focus only on the baseline level. The manufacturer also said that a more limited range of product offerings would create a commoditized ma rket, which would hurt their profitability.

Product Utility: Certain manufacturers expressed concern that amended energy conservation standards might require changes in product functionality, utility , and other features that would make products less desirable to consumers. Some manufacturers were concerned about the product size increases that would be associated with higher energy conservation standards. Due to the complexity and potential large size of central air conditioners and heat pumps at higher efficiency levels, manufacturers are concerned that installations will be far more difficult and could force many consumers to pay substantially higher installed costs if their replacement unit does not fit into their existing space.

12.3.2.3 Cumulative Regu latory Burden

While any one regulation may not impose a significant burden on manufacturers, the combined effects of several impending regulatio ns may have serious consequences for some manufacturers, groups of manufacturers, or an enti re industry. Assessing the impact of a single regulation may overlook this cumulative regulatory burden. For the cumulative regulatory burden analysis, DOE describes other significant product-specific regulations that could affect central air conditioner and heat pump manuf acturers or their parent companies.

Based on its own research and discussions with manufacturers, DOE identified several regulations relevant to central air conditioners and heat pumps, including:

 Phase-out of hydrochlorofluor ocarbon (HCFC) refrigerants

 DOE’s gas furnace rulemaking

 Other DOE regulations

Refrigerant: Due to the phase-out of HCFCs, th e central air conditioning and heat pump industry must transition to non-ozone-depleting refrigerants. As a result, the industry is transitioning to hydrofluorocarbon-based (HFC-bas ed) refrigerants in central air conditioners and heat pumps. Several manufacturers noted that the transition from HCFC R-22 to HFC R-410A has resulted in the complete redesign of all central air conditioners and heat pumps. Some manufacturers stated that some business was lost due to the refrigerant switch. In addition to the switch from R-22 to R-410A, a manufacturer expr essed concern about existing legislative proposals that would eliminate the use of HFCs. It said that this would require additional significant redesigns. See s ection 12.3.3.1 for additional details.

Other Appliance Standards: Several central air conditioning and furnace manufacturers also produce other appliances th at have existing or upcoming DOE energy conservation standards rulemakings. Some of these other appliances include residential furnaces, furnace fans, and direct heatin g equipment. Manufacturers stated that if these standards

12-9rulemakings for other appliances result in modi fications to their product designs or product offerings, then they could result in additional cumulative regulatory burdens.

Other Regulatory Concerns: Potential changes to the DOE test procedure are a major concern for manufacturers. Additionally, severa l manufacturers said that commercial standards affect their overall regulatory burden because of the switch to HFC R-410A refrigerant for those commercial products, potentially increasing its price. Another manufacturer expects the total impact of those other regulations to be higher product costs for customers, reduced profitability for manufacturers, and further reduced domestic manufacturing employment.

12.3.3 Overall Key Issues

Perhaps the most important aspect of the pr eliminary MIA is the opportunity it creates for DOE to identify key manufacturer issues early in the development of amended energy conservation standards. During preliminary interviews, manufacturers identified several major issues that are detailed in the following sections.

12.3.3.1 Refrigerant Switch

The EPA has mandated a phase- out of HCFC refrigerants (i.e., R-22) for use in new equipment in January 2010. DOE is basing its engineering analysis on HFC-based refrigerants that comply with the EPA phase-out of HCFCs. During interviews, manufacturers discussed the possible impact of these new refrigerants on their existing central air conditioners and heat pump designs. The switch from HCFC R-22 refriger ant to HFC R-410A refrigerant was a major concern. Manufacturers said that HFC refrigerant s would be significantly more expensive after the refrigerant switch because there would be no other viable alternatives. In addition, manufacturers pointed out that with higher SEER re quirements, more refrigerant is needed due to larger coil sizes. Because of the need for more HFC refrigerants at higher SEER ratings and the lack of alternatives, manufacturers stated th at amended energy cons ervation standards could cause a dramatic increase in the price of R-410A refrigerant. Manufacturers also noted that any alternative refrigerants to R-410A are unknown, whic h raises potential issues with uncertainty in the design of future systems, the research and development required, and the questionable availability of the necessary refrigerants.

12.3.3.2 Regional Standards

Several manufacturers expresse d concerns about the potential adoption of regional standards. Manufacturers indicated that distribution channels a nd shipping would become more complicated and costly with regional standards. Ma nufacturers stated said that regional standards could potentially lower sales and increase requirements for testing, rating, labeling, etc. Some manufacturers stated that regional standards may ca use dealers to stop buying certain products in certain regions.

Most manufacturers indicated that they would prefer a single national standard, because regional standards could become very complicat ed. One manufacturer said that if a regional standard were set, then only two regions should be used because the distribution complexity greatly increases for each additional region. Th is manufacturer was concerned about the five

12-10regions that have been previously suggested. Manu facturers also stated that if regional standards are set, the regions should be identical to the regions used for furnaces, contiguous, and use the same rating method for each region.

During the interviews, DOE asked manufacturers whether regional standards would cause them to exit certain markets. Manufacturers said that the decision to offer products in a region depends on the stringency of the standards, market size, and profitability of offering those specific products in the region. Manufacturers said that it is highly unlikely that all manufacturers would participate in all regions, even if prices stabilized at a higher level. Also, manufacturers stated that they may elect not to offer products in certain regions if regional standards resulted in a significant change from th e baseline product. Manufacturers stated that if regional standards are effective in an area with low market share relative to the return on investment required to meet the amended standards, manufacturers would be more likely to exit that region.

Several manufacturers stated that their working capital, overhead costs, and research and development costs would have to be higher under regional standards. They said that there is also the potential for distribution consolidation. Some manufacturers stated that regional standards could cause transportation costs to increase, as they pay shipping as part of their factory distribution expenses. Finally, manufacturers we re concerned that enforcement of regional standards could be difficult, a nd asserted that building codes would have to be the enforcement vehicle.

12.3.3.3 Product Repairs versus Product Replacement

Several manufacturers noted that an amended energy conservation standard could cause a trend to repair central air conditi oners and heat pumps rather than replace them. Higher prices of new products after the effective date of the amended standard may make the repair option relatively more attractive to consumers. Additionally, some manufacturers stated that lower income households would be more likely to repair failed units or substitute room air conditioners for central air conditioners or heat pumps. These manufacturers poi nted to the results of the switch from the 10 SEER to the 13 SEER standard, which increased repairs relative to replacements and decreased shipments.

12.3.3.4 Shipments

Shipment projections can be a significant f actor in determining the impacts of amended energy conservation standards. The interviews provide an opportunity for manufacturers to share information that can help DOE quantify the magnitude of any changes in shipments resulting from amended energy conservation standards. In response to DOE inquiries about the potential change in shipments under a more stringent ener gy conservation standar d, several manufacturers believed shipments would d ecrease at higher standard levels . These manufacturers said that one example of a decline in shipments was shown by the switch to the 13 SEER standard in their industry from the previous standard. Manufacturers stated that 2009 shipments were down more than 50 percent from 2005.

12-11Some manufacturers said that based on the effects seen from the previous standard, the sales of room air conditioners would increase as a substitute. One manufacturer pointed out that higher efficiency products require more material, and higher material dema nd raises raw material cost. This would in turn increase the cost of the consumer products. Following this logic, the manufacturer said that this increase in the central air conditioner and heat pump prices would dampen demand.

12.3.3.5 Impact on Manufacturer Outlook

DOE interviewed manufacturers about any poten tial change in outlook that could arise from the new standard. One manufacturer said that there is a significant risk with higher minimum efficiency standards coupled with potential regional standards. They also said that the higher the standards are and the more complex the distribution is, the less affordable the units will become. Another manufacturer said that their outlook would not change with higher standard levels; that the necessary technology is av ailable; and that having time to adjust to the standard is their only main outlook concern.

12-12CHAPTER 13. UTILIT Y IMPACT ANALYSIS

TABLE OF CONTENTS

13.1 INTRODUCTION

......................................................................................................... 13- 1 13.2 METHODOLOGY

........................................................................................................ 13-2 13.3 RESULTS

.................................................................................................................. .... 13-2

13-iCHAPTER 13. UTILITY IMPACT ANALYSIS

13.1 INTRODUCTION

The U.S. Department of Energy (DOE) w ill analyze specific effects of its proposed standard levels on the electric utility industry as part of the notice of proposed rulemaking analyses, using a variant of the DOE/Energy Information Administration (EIA)’s National Energy Modeling System (NEMS). The NEMS is a large, multi-sectoral, partial equilibrium model of the U.S. energy sector. EIA uses NEMS to produce the Annual Energy Outlook (AEO)

. 1 NEMS produces a widely recognized baseline energy forecast for the United States, and this energy forecast is available in the public domain. DOE will use a variant known as NEMS

BT to provide key inputs to the analysis. a

The utility impact analysis will consist of a comparison between model results for the base case and for policy cases in which proposed standards are in place. The use of NEMS-BT for the utility analysis offers several advantages. As the official DOE energy forecasting model, NEMS relies on a set of assumptions that are tr ansparent and have received wide exposure and commentary. NEMS-BT allows an estimate of the interactions between the various energy supply and demand sectors and the economy as a whole. The utility impact analysis will report the changes in installed capacity and generation, by fuel type, that result for each trial standard level, as well as changes in electricity and natural gas sales to the residential and commercial

sectors.

DOE plans to conduct the utility impact analysis as a policy deviation from the 2010 version of the AEO ( AEO2010 ), 1 applying the same basic set of assumptions. For example, the operating characteristics (e.g., ener gy conversion efficiency, emissions rates) of future electricity generating plants are as specified in the AEO2010 reference case. DOE also will explore deviations from some of the reference case assumptions, to represent alternative futures. Two alternative scenarios use the high and low ec onomic growth cases. (The reference case corresponds to medium growth.) The high ec onomic growth case assumes higher projected growth rates for population, labor force, and la bor productivity, resulting in lower predicted inflation and interest rates relative to the reference case and higher overall aggregate economic growth. The opposite is true for the low growth case.

a For more information on NEMS, please refer to the U.S. Department of Energy, Energy Information Administration documentation. A useful summary is National Energy Modeling System: An Overview 2000

, DOE/EIA-0581(2000), March 2000. EIA approves use of the name NEMS to describe only an official version of the model without any modification to code or data. Because this analysis entails some minor code modifications and the model is run under various policy scenarios that are variations on EIA assumptions, DOE refers to the model by the name NEMS-BT (BT is DOE’s Building Technologies Program, under whose aegis this work has been performed). NEMS-BT was previously called NEMS-BRS.

13-113.2 METHODOLOGY

The electric utility impact analysis will consist of NEMS-BT forecasts for generation, installed capacity, sales, and pri ces. NEMS provides reference cas e load shapes for several end uses. The model uses predicted growth in dema nd for each end use to build up a projection of the total electric system load growth for each region, which it uses in turn to predict the necessary additions to capacity. NEMS-BT accounts for the implementation of efficiency standards by decrementing the appropriate reference case load shape. DOE will determine the size of the decrement using data for the per-unit energy savings developed in the life-cycle cost and payback period analysis (Chapter 8) and the forecast of shipments developed for the national impact analysis (Chapter 9).

The predicted reduction in capacity additions is sensitive to the peak load impacts of the standard. DOE will investigate the need to adjust the hourly load profiles that include this end use in NEMS-BT.

Since the AEO2010 version of NEMS forecasts only to the year 2035, DOE must extrapolate results to 2045. DOE conducts an extr apolation to 2045 to be consistent with the analysis period being used by DOE in the national impact analysis (NIA). It will not be feasible to extend the forecast period of NEMS-BT for the purposes of this analysis, nor does EIA have an approved method for extrapolation of ma ny outputs beyond 2035. While it might seem reasonable in general to make simple linear extr apolations of results, in practice this is not advisable because outputs could be contradictory. For example, changes in the fuel mix implied by extrapolations of those outputs could be inconsistent with the extrapolation of marginal emissions factors. An analysis of various trends sufficiently detailed to guarantee consistency is beyond the scope of this work and, in any case, would involve a great deal of uncertainty. Therefore, for all extrapolations beyond 2035 DOE intends to use simple replications of year 2035 results; in this way results are guaran teed to be consistent. As with the AEO reference case in general, the implicit assumption is that the regulatory environment does not deviate from the current known situation during the extrapolation pe riod. Only changes that have been announced with date-certain introduction are included in NEMS-BT.

For petroleum products, EIA uses the average gr owth rate for the world oil price over the years 2010 to 2025, in combination with the refinery and distribution markups from the year 2025, to determine the regional price forecasts. Similarly, EIA derives natural gas prices from an average growth rate figure in combination w ith regional price margins from the year 2025.

13.3 RESULTS

Results of the analysis will include changes in residential and commercial electricity sales, installed capacity and generation by fuel type for each trial standard level, in five-year increments extrapolated to the year 2045

13-21 REFERENCES

U.S. Department of Energy-E nergy Information Administration. Annual Energy Outlook 2010 with Projections to 2035 , March, 2010. Washington, DC. DOE/EIA-0383(2010).

13-3CHAPTER 14. EMPLOYME NT IMPACT ANALYSIS

TABLE OF CONTENTS

14.1 INTRODUCTION

............................................................................................................ 14-1 14.2 ASSUMPTIONS

.............................................................................................................. . 14-1 14.3 METHODOLOGY

........................................................................................................... 14 -1 REFERENCES

.................................................................................................................... ...... 14-3

14-iCHAPTER 14. EMPLOYME NT IMPACT ANALYSIS

14.1 INTRODUCTION

The Department of Energy (DOE) intends the employment impact analysis to estimate national job creation or job elimination resulting from possible new standards, due to reallocation of the associated expenditures for purchasing and operating equipment. DOE will conduct this analysis as one of the analyses for the no tice of proposed rulemaking (NOPR). DOE will estimate national impacts on major sectors of the U.S. economy, using publicly available data and incorporating different energy price scenarios that it will carry out as part of the analysis for the NOPR. DOE will make all methods a nd documentation available for review.

The imposition of standards can impact employment both directly and indirectly. Direct employment impacts are changes in the number of employees at the plants that produce the covered equipment, along with the affiliated distribution and service companies, resulting from the imposition of standards. DOE will evaluate direct employment impacts in its manufacturer impact analysis, as described in chapter 12. Indirect employment impacts may result from expenditures shifting between goods (the substitu tion effect) and changes in income and overall expenditure levels (the income effect) that occur due to the imposition of standards..

14.2 ASSUMPTIONS

DOE expects new equipment standards to decr ease energy consumption, and therefore to reduce expenditures for energy. The savings in energy expenditures may be spent on new investment and other items. Th e standards may increase the purchase price of equipment, including the retail price plus sales tax, and increase installation costs.

Using an input-output model of the U.S. economy, this analysis seeks to estimate the year-to-year effect of these expenditure impacts on net economic output and employment. A simple model might involve reduced expenditure s for energy and reallocation of that money toward other sectors in the economy. DOE intends the employment impact analysis to quantify the indirect employment impacts of these expenditure changes. It will evaluate direct employment impacts in the manufacturer impact analysis step of the process.

14.3 METHODOLOGY

DOE developed Impact of Sector Energy Technologies (ImSET), a model of the U.S. economy that focuses on sectors most releva nt to industrial, comme rcial, and residential building energy use. 1 ImSET is a special-purpose version of the U.S. Benchmark National I-O model designed to estimate the national employment and income effects of energy-saving technologies deployed by the DOE Office of Energy Efficiency and Renewable Energy. Compared with previous versions of the model used in earlier energy conservation rulemakings, the current version allows for more complete and automated analysis of the essential features of energy efficiency investments in buildings, industry, transportation, and the electric power

sectors.

14-1 14 CAC_PreNOPR_TSD_EMPLOYMENT IMPACT ANALYSIS_2010-03-23.docThe ImSET model includes structural coefficients to characterize economic flows among the multiple sectors. ImSET’s national economic I-O structure is based on the 2002 Benchmark U.S. table, 2 which is specially aggregated to 187 sect ors. The time step of the model is annual and the time scale of the model is 100 years (2001-2099).

The ImSET model allows a great deal of flexibility for analyzing types of energy efficiency effects. For example, certain economic effects of energy efficiency improvements require an assessment of inter-indus try purchases, which is handled in the model. Some energy efficiency investments will not only reduce the costs of energy in the economy but also the costs of labor and other goods and se rvices, which is accommodated through a recalculation of the I-O structure in the model. Output from ImSET can be used to estimate changes in employment, industry output, and wage income in the ove rall U.S. economy resulting from changes in expenditures in the various sectors of the economy.

The following is an example of how the employment impact analysis might track impacts from a standard for CACs. Depending on the design options considered, one possible outcome is that the standards for these CACs would redu ce energy expenditures and increase equipment prices in the residential and commercial sector s. These expenditure changes may reduce energy sector employment and either reduce or increase employment in selected commercial sectors. At the same time, the standard may increase investment in the residential and commercial sector and employment in other sectors. DOE designed the employment impact analysis to estimate the annual net national employme nt impact of these types of expenditure flows.

14-2 14 CAC_PreNOPR_TSD_EMPLOYMENT IMPACT ANALYSIS_2010-03-23.docREFERENCES

1. Scott M.J., O.V. Livingston, J.M. Roop, R.W. Schultz, and P.J. Balducci. 2009. Impact of Sector Energy Technologies Mode l Description and User’s Guide . Pacific Northwest National Laboratory, Richland, WA. PNNL-18412,

2. Stewart, RL, JB Stone, and ML Streitwiese r. 2007. U.S. Benchmark Input-Output Accounts, 2002. Survey of Current Business October 2007. Accessed March 11, 2009 at http://www.bea.gov/industry/index.htm#benchmark_io

.

14-3 14 CAC_PreNOPR_TSD_EMPLOYMENT IMPACT ANALYSIS_2010-03-23.docCHAPTER 15. ENVIRONMENTAL ASSESSMENT FOR PROPOSED ENERGY CONSERVATION STANDARDS FOR CENTRAL AIR CONDITIONERS AND HEAT PUMPS

TABLE OF CONTENTS

15.1 INTRODUCTION

......................................................................................................... 15- 1 15.2 METHODOLOGY

........................................................................................................ 15-2 15.2.1 Air Emissions

.......................................................................................................... ....... 15-2 15.2.2 Monetization of Emission Reductions Benefits

............................................................. 15-5 15.3 RESULTS

.................................................................................................................. .... 15-7

15-iCHAPTER 15. ENVIRONMENTAL ASSESSMENT FOR PROPOSED ENERGY CONSERVATION STANDARDS FOR CENTRAL AIR CONDITONERS AND HEAT PUIMPS

15.1 INTRODUCTION

The U.S. Department of Energy (DOE) will conduct an environmental assessment as part of the notice of proposed rulemaking. DOE will assess the impacts of proposed energy conservation standards for central air conditioners and heat pumps on certain environmental indicators using a variant of the Energy Information Administration (EIA)’s National Energy

1 Modeling System (NEMS). a EIA uses NEMS to produce the Annual Energy Outlook (AEO)

. DOE will use a variant known as NEMS-BT to provide key inputs to the analysis, based on the 2010 version of the AEO ( AEO2010 ). Results of the environmental assessment will be similar to those provided in AEO2010

.
The intent of the environmental impact assessment is to fulfill requirements to properly quantify and consider the envir onmental effects of all new Federal rules. DOE intends the environmental assessment to provi de emissions results to policym akers and other stakeholders, and to fulfill requirements that the environmental effects of all new Federal rules be properly quantified and considered.

The primary environmental effects of ener gy conservation standards for central air conditioners and heat pumps would be reduced power plant emissions resulting from reduced consumption of electricity; ther e are also reduced household emi ssions from gas appliances. The environmental assessment considers th ree pollutants— sulfur dioxide (SO 2 ), nitrogen oxides (NO x ), and mercury (Hg)—as well as carbon emis sions. The only form of carbon emissions tracked by NEMS-BT is carbon dioxide (CO 2 ), so the carbon discussed in this report is in the form of CO 2 . For each of the trial standard levels, DOE will calculate power sector emissions using NEMS-BT, using additional external analysis as needed.

DOE notes that the Clean Air Act requires the U.S. Environmental Protection Agency (EPA) to set National Ambient Air Quality Standards for the following six common air pollutants, also know as “criteria pollutants”: (1 ) ozone, (2) particulate matter (PM), (3) carbon monoxide (CO), (4) nitrogen dioxide, (5) SO 2 , and (6) lead. 2 None of the “criteria pollutants” not already considered (i.e., ozone, PM, CO, and lead) are driven significantly by either electric utility power plants or fuel-fired appliances. Therefore, DOE does not intend on addressing them in the environmental assessment. In the case of ozone and particulate matte r, other pollutants are precursors to their formation a nd atmospheric conditions are the driver behind their formation. Also, SO 2 and NO x are the primary precursors to ozone and PM, respectively, and will already

a For more information on NEMS, please refer to the U.S. Department of Energy, Energy Information Administration documentation. A useful summary is National Energy Modeling System: An Overview 2003

, DOE/EIA-0581(2003), March 2003. EIA approves use of the name NEMS to describe only an official version of the model without any modification to code or data. Because this analysis entails some minor code modifications and the model is run under various policy scenarios that are variations on EIA assumptions, DOE refers to the model as NEMS-BT (BT is DOE’s Building Technologies Program). NEMS-BT was previously called NEMS-BRS.

15-1be addressed by the environmental assessment. In the case of CO, electric utilities and fuel-fired appliances are not significant sources. Finally, with regard to lead, i ndustrial processes (not electric utilities), including primary and secondary lead smelters and battery manufacturers, are responsible for most of the lead emissions.

15.2 METHODOLOGY

DOE plans to conduct the utility impact analysis as a policy deviation from the 2010
version of the AEO ( AEO2010 ), 1 applying the same basic set of assumptions. For example, the emissions characteristics of an electricity generating plant will be exactly those used in AEO2010 . The NEMS reference case and alternative growth scenarios are as described in the utility impact analysis (see Chapter 13 of the preliminary technical support document). Below are descriptions of the air emissions that DOE will analyze in the environmental assessment.

15.2.1 Air Emissions

Carbon Dioxide (CO 2 )

Carbon dioxide (CO 2 ) is not a regulated or criteria pollu tant, but it is of interest because of its classification as a greenhouse gas (GHG). G HGs trap the sun’s radiation inside the Earth’s atmosphere and either occur naturally in the atmosphere or result from human activities. Naturally occurring GHGs include water vapor, CO 2 , methane (CH 4 ), nitrous oxide (N 2 O), and ozone (O 3 ). Human activities, however, add to the levels of most of these naturally occurring gases. For example, CO 2 is emitted to the atmosphere when solid waste, fossil fuels (oil, natural gas, and coal), wood, and wood products are burne d. During the past 20 years, about threequarters of anthropogenic (i.e., human-made) CO 2 emissions resulted from burning fossil fuels.

Concentrations of CO 2 in the atmosphere are naturally regulated by numerous processes, collectively known as the “carbon cycle.” The mo vement of carbon betwee n the atmosphere and the land and oceans is dominated by natural proce sses, such as plant photosynthesis. While these natural processes can absorb some of the anthropogenic CO 2 emissions produced each year, billions of metric tons are added to the atmosphere a nnually. In the U. S., CO 2 emissions from both energy generation and industrial processe s account for 84.6 percent of total U.S. GHG emissions.

In the absence of any Federal emissions cont rol regulation of power plant emissions of CO 2 , a DOE standard is likely to result in reductions of these emissions. The CO 2 emission reductions likely to result from a standard will be estimated using NEMS-BT and national energy savings estimates drawn from the NIA spreadsheet model. The net benefit of the standard is the difference between emissions estimated by NEMS-BT at each standard level considered and the AEO Reference Case. NEMS-BT tracks CO 2 emissions using a deta iled module that provides results with broad coverage of all sector s and inclusion of interactive effects.

Sulfur Dioxide (SO 2 )

15-2DOE has preliminarily determined that SO 2 emissions from affected Electric Generating Units (EGUs) are subject to nationwide and regional emissions cap and trading programs that are likely to eliminate the standards’ impact on SO 2 emissions. The costs of meeting such emission cap requirements are reflected in the electricity prices and forecasts used in DOE’s analysis of the standards. Title IV of the Clean Ai r Act sets an annual emissions cap on SO 2 for all affected EGUs. SO 2 emissions from 28 eastern States and the District of Columbia (DC) are also limited under the Clean Air Interstate Rule (CAIR, published in the Federal Register on May 12, 2005. 70 FR 25162 (May 12, 2005)), which creates an allowance-based trading program that will gradually replace the Title IV program in thos e States and DC. (The recent legal history surrounding CAIR is discussed below.) The attainme nt of the emissions caps is flexible among EGUs and is enforced through the use of emissions allowances and tradable permits. Under existing EPA regulations, any excess SO 2 emission allowances resulting from the lower electricity demand caused by the imposition of an efficiency standard could be used to permit offsetting increases in SO 2 emissions by any regulated EGU. However, if the standard resulted in a permanent increase in the quantity of unused emission allowances, there would be an overall reduction in SO 2 emissions from the standards. While th ere remains some uncertainty about the ultimate effects of efficiency standards on SO 2 emissions covered by the existing cap and trade system, the NEMS-BT modeling system that DOE plans to use to forecast emissions reductions currently indicates that no phys ical reductions in power sector emissions would occur for SO 2

.
Even if there is no significant redu ction in the overall emissions of SO 2 that results from the standard, there may still be some ec onomic benefit from reduced demand for SO 2 emission allowances that is not fully reflected in the co st savings experienced by individual consumers. Electricity savings that decrease the overall demand for SO 2 emissions allowances could lower allowance prices and thereby result in some econo mic benefits for all electricity consumers, not just those that reduced their electricity use as a result of an efficiency standard. DOE does not plan to monetize this particular benefit because the effect on the allowance price from any single energy conservation standard is likely small and highly uncertain.

Nitrogen Oxides (NO X )

Nitrogen oxides , or NO X , are the generic term for a group of highly reactive gases, all of which contain nitrogen and oxygen in varying amounts. Many of the nitrogen oxides are colorless and odorless. However, one common pollutant, nitrogen dioxide (NO 2 ), along with particles in the air can often be seen as a re ddish-brown layer over many urban areas. NO 2 is the specific form of NO X reported in this document. NO X is one of the main ingredients involved in the formation of ground-level ozone, which can tr igger serious respiratory problems. It can contribute to the formation of acid rain, and can impair visibility in areas such as national parks. NO X also contributes to the formation of fi ne particles that can impair human health. 3

Nitrogen oxides form when fossil fuel is bur ned at high temperatures, as in a combustion process. The primary manmade sources of NO X are motor vehicles, electric utilities, and other industrial, commercial, a nd residential sources that burn fossil fuels. NO X can also be formed naturally. Electric utilities account for about 22 percent of NO X emissions in the United States. 3

15-3NEMS-BT has an algorithm for estimating NO X emissions from power generation. The impact of these emissions, however, will be affected by the CAIR, which the Environmental Protection Agency (EPA) issued on May 12, 2005. CAIR will permanently cap emissions of NO X in 28 eastern states and the District of Columbia. 70 FR 25162 (May 12, 2005)..

Much like SO 2 emissions, a cap on NO X emissions means that energy conservation standards may have little or no physical effect on these emissions in the 28 eastern States and DC covered by CAIR. Although CAIR has been re manded to the EPA by the DC Circuit, it will remain in effect until it is replaced by a rule consistent with the Court’s July 11, 2008, opinion in North Carolina v. EPA. 531 F.3d 896 (DC Cir. 20 08); see also North Carolina v. EPA, 550 F.3d 1176 (DC Cir. 2008). Because all States covered by CAIR opted to reduce NO X emissions through participation in cap-and-trade progra ms for electric generating units, emissions from these sources are capped across the CAIR region.

Standards may produce an envi ronmental-related ec onomic benefit in the form of lower prices for emissions allowance credits. .As with SO 2 emissions, a cap on NO X emissions means that equipment efficiency standards may have no physical effect on these emissions in the 28 eastern States and DC covered by CAIR. While the emissions cap may mean that physical emissions reductions will not result from standards in those states covered by CAIR, standards could produce an environmental -related economic benefit in the form of lower prices for emissions allowance credits.

As with SO 2 allowance prices, DOE does not plan to monetize this particular benefit because the effect on the NO X allowance price from any single energy conservation standard is likely small and highly uncertain.

Accordingly, DOE plans to use NEMS-BT to estimate the emissions reductions from possible standards in the 22 States where emissions are not capped.

Mercury (Hg)

Coal-fired power plants emit Hg found in coal during the burning process. While coalfired power plants are the largest remaining s ource of human-generated Hg emissions in the United States, they contribute very little to the global Hg pool or to contamination of U.S. waters. U.S. coal-fired power plants emit Hg in three different forms: oxidized Hg (likely to deposit within the United States); elemental Hg , which can travel thousands of miles before depositing to land and water; and Hg that is in particulate form. Atmospheric Hg is then deposited on land, lakes, rivers, and estuaries through rain, snow, and dry deposition. Once there, it can transform into methylmercury and accumulate in fish tissue through bioaccumulation.

Americans are exposed to methylmercury primarily by eating contaminated fish. Because the developing fetus is the most sensitive to the toxic effects of methylmercury, women of childbearing age are regarded as the populati on of greatest concern. Children exposed to methylmercury before birth may be at increased risk of poor performa nce on neurobehavioral

15-4tasks, such as those measuring attention, fine motor function, language skills, visual-spatial abilities, and verbal memory.

Similar to emissions of SO 2 and NO X , future emissions of Hg would have been subject to emissions caps. In May 2005, EPA issued th e Clean Air Mercury Rule (CAMR). 70 FR 28606 (May 18, 2005). CAMR would have permanently capped emissions of mercury for new and existing coal-fired power plants in all States by 2010. However, on February 8, 2008, the DC Circuit issued its decision in New Jersey v. Environmental Protection Agency , in which the DC Circuit, among other actions, vacated the CAMR. 517 F.3d 574 (DC Cir. 2008). EPA has decided to develop emissions standards for pow er plants under the Clean Air Act (Section 112), consistent with the DC Circ uit’s opinion on the CAMR. See http://www.epa.gov/air/mercuryr ule/pdfs/certpetition_withdrawal.pdf . Pending EPA's forthcoming revisions to the rule, DOE is excluding the CAMR from its Environmental Analysis. In the absence of CAMR, energy conservation standards would likely reduce Hg emissions, and DOE plans to use NEMS-BT to estimate these emission reductions.

Particulate Matter

DOE acknowledges that particulate matter (PM) impacts are of concern due to human exposures that can impact health. However, imp acts of PM emissions reduction are much more difficult to estimate than other emissions reductions due to the complex interactions between PM, other power plant emissions, meteorology, and atmospheric chemistry that impact human exposure to particulates. Human exposure to PM us ually occurs at a significant distance from the power plants that are emitting particulates and particulate precursors. When power plant emissions travel this distance, they undergo highly complex atmospheric chemical reactions. Although the EPA does keep inventories of direct PM emissions of power plants, in its source attribution reviews, the EPA doe s not separate direct PM emissions from power plants from the sulfate particulates indirectly produced through complex atmos pheric chemical reactions. The great majority of PM emissions from power plan ts are of these seconda ry particles (secondary sulfates). Thus, it is not useful to examine how the amended standard impacts direct PM emissions independent of indir ect PM production and atmospheric dynamics. Therefore, DOE is not planning to assess the impact of these standa rds on particulate emissions. Further, even the cumulative impact of PM emissions from power plan ts and indirect emissions of pollutants from other sources is unlikely to be significant.

15.2.2 Monetization of Emissi on Reductions Benefits

For those emissions for which real nationa l emission reductions are anticipated (CO 2 , Hg, and NO X for 22 states), ranges of estimated economic values based on environmental damage studies of varying quality and applicability are available. Therefore, DOE plans on reporting estimates of monetary benefits derived using these values and plans to consider these benefits in weighing the costs and benefits of each of the standard levels considered.

Carbon Dioxide (CO 2 )

In order to estimate the monetary value of benefits resulting from reduced emissions of CO 2 emissions, it is DOE’s intent to use in its an alysis the most current Social Cost of Carbon

15-5(SCC) values developed a nd/or agreed to by interagency reviews. The SCC is intended to be a monetary measure of the incremental damage resulting from greenhouse gas (GHG) emissions, including, but not limited to, net agricultural productivity loss, human health effects, property damage from sea level rise, and changes in ecosy stem services. Any effort to quantify and to monetize the harms associated with climate change will raise serious questions of science, economics, and ethics; but with full regard for the limits of both quantifi cation and monetization, the SCC can be used to provide estimates of the social benefits of reduc tions in GHG emissions.

At the time of this notice, the most recen t interagency estimates of the potential global benefits resulting from reduced CO 2 emissions in 2010 are $4.7, $21.4, $35.1, and $64.9 per
metric ton in 2007 dollars. These values are th en adjusted to 2009$ using the standard GDP deflator value for 2008 and 2009. For emissions (or emission reductions) that occur in later years, these values grow in real terms over time . Additionally, the interagency group determined that a range of values from 7 percent to 23 per cent should be used to adjust the global SCC to calculate domestic effects, although preference will be given to consideration of the global benefits of reducing CO 2 emissions. To calculate a present value of the stream of monetary values, DOE will discount the values in each of the four cases using the discount rates that had been used to obtain the SCC values in each case. See appendix A of the Annex to this chapter for the full range of annual SCC estimates from 2010 to 2050.

DOE recognizes that scientific and economic knowledge continues to evolve rapidly as to the contribution of CO 2 and other GHG to changes in the future global climate and the potential resulting damages to the world economy. Thus, these values are subject to change.

Nitrogen Oxides (NOx)

As discussed earlier, with respect to NOx the CAIR rule has been reinstated by the courts. Therefore, NOx emissions in those states covered by CAIR will be subject to a cap with corresponding annual allowances openly traded.

For those states not covered by CAIR, DOE plans on estimating the monetized benefits of NOx emissions reductions in these states based on environmental damage estimates from the literature. Available esti mates suggest a very wide range of monetary values for NOx emissions, ranging from $370 per ton to $3,800 per ton of NOx from stationary sources, measured in 2001$, (equivalent to a range of $447 to $4,591 per ton in 2009$). 4

Mercury (Hg)

DOE plans on estimating the monetized benefits of Hg emissions reductions based on environmental damage estimates from the literature. For Hg emissions reductions, DOE has previously determined that t he basic science linking mercury e missions from power plants to impacts on humans is considered highly uncertai n. However, DOE identified two estimates of the environmental damages of mercury based on two estimates of the adverse impact of childhood exposure to methyl mercury on IQ for American children, and subsequent loss of lifetime economic productivity resulting from these IQ losse s. The high-end estimate is based on an estimate of the current aggregate cost of the loss of IQ in American children that results from

15-6exposure to mercury of U.S. power plant origin

─ $1.3 billion per year in 2000$, which translates to $33.7 million per ton emitted per year in 2009$. 5 DOE derived the low-end estimate of $0.66 million per ton emitted in 2004$, or $0.745 million pe r ton in 2009$, from a published evaluation of mercury control using different methods and assumptions from the first study, but also based on the present value of the lifetime earnings of children exposed to mercury. 6 b

For both NO X and Hg, DOE will conduct two calcula tions of the monetary benefits derived using each of the economic values used, one using a real discount rate of 3 percent and another using a real discount rate of 7 per cent, in accordance with the U.S. Office of Management and Budget (OMB) guidance. c

15.3 RESULTS

The results for the environmental assessmen t are similar to a complete NEMS run, as published in the AEO2010 . These include emissions for SO 2 , NO X , mercury, and CO 2 in fiveyear forecasted increments, extrapolated to the year 2045. DOE will report the outcome of the analysis for each trial standard level as a deviation from the AEO2010 reference case results.

b The estimate was derived by back-calculating the annual benefits per ton from the net present value of benefits reported in the study.

15-7REFERENCES

1. Energy Information Administration, Annual Energy Outlook 2010 with Projections to 2035 , March 2010. Washington, DC. Re port No. DOE/EIA-0383(2010).

2. U.S. Environmental Protection Agency, National Ambient Air Quality Standards, 2008. (Last accessed March 11, 2008.) < http://www.epa.gov/air/urbanair / >

3. U.S. Environmental Protection Agency, Nitrogen Oxides Health and Environmental Impacts of NOx (Posted May 26th, 2009)

< http://www.epa.gov/air/urbanair/nox/hlth.html >

4. Office of Management and Budget Office of Information and Regulatory Affairs, 2006 Report to Congress on the Costs and Benefits of Federal Regulations and Unfunded Mandates on State, Local, and Tribal Entities , 2006. Washington, DC.

< http://www.whitehouse.gov/omb/inforeg/2006_cb/2006_cb_final_report.pdf >

5. Trasande, L., C. Schechter, K.A. Haynes, and P.J. Landrigan,, Applying Cost Analyses to Drive Policy That Protects Children : Mercury as a Case Study . Annals of the New York Academy of Sciences , 2006. 1076

6. Ted Gayer and Robert Hahn, Designing Environmental Policy: Lessons from the Regulation of Mercury Emissions,” 2004. AEI-Brookings Joint Center For Regulatory Studies. A version of this paper was published in the Journal of Regulatory Economics in 2006.

15-8CHAPTER 16. REGULATORY IMPACT ANALYSIS FOR PROPOSED ENERGY CONSERVATION STANDARDS FOR CENTRAL AIR CONDITIONERS AND HEAT PUMPS

TABLE OF CONTENTS

16.1 INTRODUCTION

......................................................................................................... 16- 1 16.2 METHODOLOGY

........................................................................................................ 16-1

LIST OF TABLES

Table 16.1.1 Non-Regulatory Alternatives to Standards

........................................................ 16-1

16-iCHAPTER 16. REGULATORY IMPACT ANALYSIS FOR PROPOSED ENERGY CONSERVATION STANDARDS FOR CENTRAL AIR CONDITIONERS AND HEAT PUMPS

16.1 INTRODUCTION

Under the Process Rule ( Procedures for Consideration of New or Revised Energy Conservation Standards for Consumer Products , 61 FR 36974 (July 15, 1996)), the U.S. Department of Energy (DOE) is committed to continually explore non-regulatory alternatives to standards. DOE will prepare a draft regulatory impact analysis pursuant to E.O. 12866, “Regulatory Planning and Review,” which will be subject to review under the Executive Order by the Office of Management and Budget’s Offi ce of Information and Regulatory Affairs. 58 FR 51735. DOE has identified seven major alternatives to standards as representing feasible policy options to reduce consumer product energy consum ption. It will evaluate each alternative in terms of its ability to achieve significant energy savings at a reasonable cost, and will compare the effectiveness of each one to the eff ectiveness of the proposed standards rule.

The non-regulatory means of achieving energy savings that DOE proposes to analyze are listed in Table 16.1.1. The technical support docum ent (TSD) in support of DOE’s notice of proposed rulemaking will include a complete quantitative analysis of each alternative, the methodology for which is di scussed briefly below.

Table 16.1.1 Non-Regulatory Alternatives to Standards No new regulatory action
Consumer tax credits
Manufacturer tax credits
Performance Standards
Rebates Voluntary energy efficiency targets Early replacement Bulk government purchases

16.2 METHODOLOGY

DOE will use the national impact analysis (NIA) spreadsheet models for each of the two products to calculate the national energy savings and the net present value (NPV) corresponding to each alternative to the proposed standards. The NIA model for each of the two products is discussed in chapter 10 of the TSD. To compare each alternative quantita tively to the proposed energy conservation standards, DOE will need to quantify the effect of each alternative on the purchase and use of energy efficient room ai r conditioners and clothes dryers. Once it has quantified each alternative, DOE will make the appropriate revi sions to the inputs in the NIA models. Key inputs that DOE may revise in these models are:

• Energy prices and escalation factors;

16-1• Implicit market discount rates for tradin g off purchase price against operating expense when choosing product efficiency;

• Consumer purchase price, operating cost, and income elasticities;

• Consumer price-versus-effi ciency relationships; and

• Product stock data (purchase of new products or turnove r rates for inventories).

The key measures of the impact of each alternative will be:

• Energy use: Cumulative energy use of the product from the effective date of the new standard to the year 2045. DOE will report el ectricity consumption as primary energy.

• National energy savings: Cumulative national energy use from the base case projection minus the alternative policy case projection.

• Net present value: The value of future operating cost savings from products bought in the period from the effective date of the new standard 2016 to the year 2045. DOE will calculate the NPV as the difference between the present value of product and operating expenditures (including energy) in the base case, and the present value of expenditures in each alternative policy cas e. DOE will discount future operating and product expenditures to 2010 using a seven-pe rcent and three-percent real discount rate. It will calculate operating expenses (including energy costs) for the life of the products.

16-2CHAPTER 17. REGIONAL STANDARDS IMPACTS ON MARKET PARTICIPANTS

TABLE OF CONTENTS

17.1 Introduction

................................................................................................................... .. 17-1 17.1.1 Issues on Which DOE Seeks Comment

.............................................................. 17-1 17.1.2 Regional Standards Overview

............................................................................. 17-2 17.1.2.1 Regional Standards vs. National Standard

............................................. 17-5 17.1.3 Discussion of Non Enforcement vs. Enforcement Issues

.................................... 17-6 17.2 Market Participants

......................................................................................................... 17- 7 17.2.1 Definition of Terms

............................................................................................. 17-7 17.2.1.1Distributors

............................................................................................ 17-7 17.2.1.2 Contractors

............................................................................................. 17-7 17.2.1.3 Dealers

................................................................................................... 17-7 17.2.1.4Installers

................................................................................................. 17-8 17.2.1.5 Builders

.................................................................................................. 17-8 17.3 Distribution Chain

........................................................................................................... 17 -8 17.3.1 Overview

............................................................................................................. 17-8 17.3.2 Vertical Integration

.............................................................................................. 17-9 17.3.3 Distributors

........................................................................................................ 17-10 17.3.3.1 Market Overview

................................................................................. 17-10 17.3.3.2Distributor Business Model

................................................................. 17-10 17.3.4 Contractors

........................................................................................................ 17-13 17.3.4.1 Market Overview

................................................................................. 17-13 17.3.4.2Business Model

.................................................................................... 17-13 17.3.5 General Contractor

............................................................................................ 17-14 17.3.5.1 Market Overview

................................................................................. 17-14 17.3.5.2Business Model

.................................................................................... 17-14 17.3.6 Retailers

............................................................................................................. 17-15 17.4 Discussion of Regional Standard Impacts

.................................................................... 17-15 17.4.1 Distributor Impacts

............................................................................................ 17-15 Non-enforcement Issues for Distributors

.......................................................... 17-15 Enforcement Issues for Distributors

.................................................................. 17-17 17.4.2 Contractor Impacts

............................................................................................ 17-18 Non-enforcement Issues for Contractors

........................................................... 17-18 Enforcement Issues fo r Contractors

.................................................................. 17-18 17.4.3 General Contractor Impacts

............................................................................... 17-19 Non-enforcement Issues for General Contractors

............................................. 17-19 Enforcement Issues for Ge neral Contractors

..................................................... 17-19 17.5 Analysis of Regional Standard Impacts

........................................................................ 17-19 17.5.1 Profitability Analysis of Regi onal Standard Impacts

........................................ 17-20 17.5.1.1 Data Sources

........................................................................................ 17-20 17.5.1.2 Sample Inventory Calculation fo r Southeastern Border CACHP Wholesaler

......................................................................................................... 17-23 17.5.1.3 CACHP Profitability Calculation

........................................................ 17-25 17.5.1.4 Sample Furnace Inventory Calcula tion for Border Wholesalers

......... 17-26

17-i17.5.1.5 Furnace Profitability Calculation

......................................................... 17-27 17.5.2 Preliminary Analysis of the Impacts of Regional Standards on Furnace and CACHP markups

........................................................................................................... 17-28 17.5.2.1 Furnace Markups

................................................................................. 17-28 17.5.2.2 Firm Markups Far From the Border Region

........................................ 17-28 17.5.2.3 Border Region Markups

....................................................................... 17-30 17.5.2.4 Central Air Conditioners and Heat Pumps

........................................... 17-32 17.6 Additional Distributor Data

.......................................................................................... 17-32 17.7 Additional Contractor Data

........................................................................................... 17-47 17.8 Additional General Contractor s and Homebuilders Data

............................................. 17-57

LIST OF TABLES

Table 17.1.1. States and Regions for Re sidential CACHP Ru lemaking*

................................. 17-3

Table 17.6.13 Revenue and Cost Items, Typical CACHP Distributors, Hot-Humid Region and

Table 17.6.14 Revenue and Cost Items, Typical CACHP Distributors, Hot-Dry Region and Table 17.1.2 States and Regions for Resi dential Furnaces Rulemaking*

................................. 17-4 Table 17.1.3 Border States by Re gion for CACHP Rulemaking

............................................... 17-5 Table 17.1.4 Border States by Region for Furnaces Rulemaking

.............................................. 17-6 Table 17.5.1 Typical Southeastern Wholesaler Assets, Liabilitie s, and Profitability

.............. 17-22 Table 17.5.2 Border Wholesaler Required Inventory

.............................................................. 17-24 Table 17.5.3 Profitability Impacts of CA CHP Inventory Cost Increases

............................... 17-26 Table 17.5.4 Return on Net Worth Impacts of CACHP Inventory Cost Increases

................ 17-26 Table 17.5.5 Number of Units of Inventory of Furnaces in the Border Region

..................... 17-27 Table 17.5.6 Profitability Sensitivity Analysis for Furnaces in Border States

........................ 17-27 Table 17.5.7 Return on Net Worth Analysis for Furnaces in Bo rder States

............................ 17-28 Table 17.5.8 Northern Region Markups

.................................................................................. 17-29 Table 17.5.9 Southern Region Markups

.................................................................................. 17-29 Table 17.5.10 Saturation Rate of Condensing Furnaces in the Northern Border Region

........ 17-30 Table 17.5.11 Saturation Rate of Condensing Furnaces in the Southern Border Region

........ 17-31 Table 17.5.12 Border Region Markups

.................................................................................... 17-31 Table 17.5.13 Central Air Conditioner and Heat Pump Markups

........................................... 17-32 Table 17.6.1 Distributor Enterprise Sta tistics for Hot-Humid Region (2002)

........................ 17-33 Table 17.6.2 Distributor Enterprise St atistics for Hot-Dry Region (2002)

............................. 17-33 Table 17.6.3 Distributor Enterprise Statis tics for Rest of Country (2002)

............................. 17-34 Table 17.6.4 Establishments, Employment, and Payroll Trends in Hot-Humid Region

........ 17-35 Table 17.6.5 Establishments, Employment, and Payroll Trends in Hot-Dry Region

............. 17-35 Table 17.6.6 Establishments, Employment, and Payroll Trends in Rest of Country

............. 17-36 Table 17.6.7 Income Statement Items, Typical CACHP Distributors, Hot–Humid Region

.. 17-37 Table 17.6.8 Balance Sheet, Typical CACHP Distributors, Hot-Humid Region

................... 17-37 Table 17.6.9 Income Statement Items, Typical CACHP Distributors, Hot–Dry Region

....... 17-38 Table 17.6.10 Balance Sheet, Typical CACH P Distributors, Hot-Dry Region

...................... 17-38 Table 17.6.11 Income Statement Items, Typical CACHP Distributors, Rest of Country

...... 17-39 Table 17.6.12 Balance Sheet, Typical CACHP Distributors, Rest of Country

...................... 17-39

Border States

.................................................................................................................. .......... 17-40

Border States

.................................................................................................................. .......... 17-40

17-iiTable 17.6.15 Revenue and Cost Items, Typical CACHP Distributors, Rest of Country Region and Border States

.............................................................................................................. ....... 17-41

Table 17.6.17 Geographic Area Series, Hardware, Plumbing, and Heating Equipment Merchant

Table 17.7.1 Revenue and Cost Items, Typical CACHP Mechanical Contractors, Hot-Humid

Table 17.7.2 Revenue and Cost Items, Typical CACHP Mechanical Contractors, Hot-Dry

Table 17.7.3 Revenue and Cost Items, Typical CACHP Mechanical Contractors, Rest of

Table 17.7.8 Mechanical Contract or Establishments, Employment, and Payroll Trends, HotTable 17.7.9 Mechanical Contract or Establishments, Employment , and Payroll Trends, Hot-Dry

Table 17.7.10 Mechanical Contractor Establishments, Employment, and Payroll Trends, Rest of

Table 17.8.4 General Contractor Establishments , Employment, and Payroll Trends, Hot-Humid

Table 17.8.5 General Contractor Establishments , Employment, and Payroll Trends, Hot-Dry

Table 17.8.6 General Contractor Establishments , Employment, and Payroll Trends, Rest of Table 17.6.16 Distributor Financial Da ta by HARDI Region for 2009

.................................. 17-42

Wholesalers

.................................................................................................................... .......... 17-45

Region

......................................................................................................................... ............. 17-49

Region

......................................................................................................................... ............. 17-50

Country

........................................................................................................................ ............ 17-51 Table 17.7.4 Geographic Area Series, Pl umbing and HVAC Constructors

........................... 17-52 Table 17.7.5 Enterprise Statistics on Mechanical Contractors in the Hot-Humid Region

..... 17-54 Table 17.7.6 Enterprise Statistics on Mechanical Contractors in the Hot-Dry Region

.......... 17-54 Table 17.7.7 Enterprise Statistics on Mechanical Contractors in the Rest of Country

........... 17-55

Humid Region

................................................................................................................... ....... 17-56

Region

......................................................................................................................... ............. 17-56

Country Region

................................................................................................................. ....... 17-57 Table 17.8.1 Enterprise Statistics on General Contractors in the Hot-Humid Region

........... 17-58 Table 17.8.2 Enterprise Statistics on General Contractors in the Hot-Dry Region

................ 17-59 Table 17.8.3 Enterprise Statistics on General Contractors in the Rest of Country

................. 17-60

Region

......................................................................................................................... ............. 17-61

Region

......................................................................................................................... ............. 17-61

Country

........................................................................................................................ ............ 17-62 Table 17.8.7 Revenue and Cost Items, Typical General Contractors, Hot-Humid Region

............................................................................................................................... ................... 17-63 Table 17.8.8 Revenue and Cost Items, Typical General Contractors, Hot-Dry Region

........ 17-64 Table 17.8.9 Revenue and Cost Items, Typical General Contractors, Rest of Country

........ 17-65

LIST OF FIGURES

Figure 17.3.1 Distribution Chain in Replacement Market

........................................................ 17-9 Figure 17.3.2 Distribution Chain in New Construction Market

............................................... 17-9

17-iiiCHAPTER 17. MARKET AND TECHNOLOGY ASSESSMENT

17.1 INTRODUCTION

The Energy Policy and Conservation Act (EPCA), as amended by the Energy Independence and Security Act of 2007 (EISA; Pub. L. 110-140), directs the U.S. Department of Energy (DOE) to “consider the impact of additional regional standards on consumers, manufacturers, and other market pa rticipants, including distributor s, dealers, contractors, and installers,” before establishing additional regional standards.” ( 42 U.S.C. 6295(o)(6)(D)(ii)) This technical support document (TSD) chapter represents an important step in DOE’s efforts toward fulfilling this statutory obligation. Specifically, the language of EPCA affects the current energy conservation standards rulemaki ngs for residential central ai r conditioners and heat pumps (CACHP) and furnaces. The substance of this chapter will also be included in the furnaces TSD because the analysis generally applies to both the CACHP and furnaces rulemakings and DOE is evaluating regional standards for each rulemaking. Where indicated, the analysis is specific to either CACHP or furnaces. The purpose of this chapter is to establish a common framework and understanding of the HVAC distribution chain and market dynamics to fa cilitate discussion of regional standards among DOE and interested par ties. This chapter also affords the early opportunity for stakeholders to comment on DOE’s understanding of key market factors as well as DOE’s initial analytical methodology and c onclusions regarding the impacts of regional standards.

This chapter is structured as follows: Fi rst, DOE provides an overview of the issues raised by regional standards as they relate to the market participants specified in EPCA. Second, DOE defines the market participants and the interaction of those participants the distribution chain. DOE examines the general business models of the key participants in the market independently. Next, DOE investigates how regi onal standards could affe ct those models based on industry research, initial discu ssions with manufacturers, distri butors and contractors, and the comments received in response to the centr al air conditioner and heat pump framework document and public meeting. Lastly, when possible given data availability, DOE quantitatively assesses the impacts of regional standards on the analyzed market participants, conducting two analyses: (1) an investigation of the impact of changes in inventory holdings on distributor profitability and (2) a presentation of preliminary estimates of the impact of regional standards on distributor and contractor (installer) markups for central air conditioners, heat pumps and furnaces. The markups for these products are es timated for different regions of the country, and based on limited available data about the current distributi on of equipment efficiency and projected changes to equipment efficiency. Th ese estimates will be updated as more information becomes available.

17.1.1 Issues on Which DOE Seeks Comment

DOE is particularly interested in receiving comments and views of interested parties concerning the following issues:

17-11. The impacts of additional regional st andards on distributors, mechanical contractors, and general contractors 2. The impact of regional standards enforcement mechanisms on the HVAC distribution chain 3. How regional standard impacts are different from the impacts resulting from amended national energy conservation standards 4. How DOE can best capture incorporate the impacts identified above in its analysis 5. The conclusions drawn in this chapter

17.1.2 Regional Standards Overview

DOE is considering regional standards for residential air conditioners and heat pumps for two multi-state regions (Hot-Humid and Hot-Dry) in addition to a base national standard that would prevail in states throughout the rest of the country. For impact analysis purposes in the CACHP rulemaking, the rest of the country is considered a third region called Rest of Country (called the “North” in this chapter for simplicity). By statute, the regions must include whole, contiguous states. (42 U.S.C. 6295(o)(6)(C)) The st ates are grouped such that the populations of the two hot regions generally experience more than 1200 annual cooling hours (CLH), and the Hot-Humid region has high relative humidity while the Hot-Dry region does not

The boundary between Hot-Humid and Rest of Country is approximately at the 4500 annual heating degree-day (HDD) line. The states currently included in each region in the CACHP rulemakings are listed in Table 17.1.1. For reasons described belo w, DOE distinguishes between states that border other regions a nd those that do not. States that are on the border of two regions are italicized in the table. All states in the Hot-Dry region have at least one border with another region.

17-2Table 17.1.1 States and Regions for Re sidential CACHP Rulemaking* Hot-Humid Hot-Dry Rest of Country

Alabama Arizona Alaska Arkansas California Colorado

Florida Nevada Connecticut Georgia New Mexico Delaware Hawaii Dist. of Col. Louisiana Idaho Mississippi Illinois North Carolina Indiana Oklahoma Iowa South Carolina Kansas
Tennessee Kentucky
Texas Maine Maryland Massachusetts Michigan Minnesota
Missouri
Montana Nebraska
New Hampshire
New Jersey
New York North Dakota Ohio Oregon Pennsylvania Rhode Island South Dakota Utah
Vermont Virginia Washington
West Virginia

Wisconsin Wyoming

* Italics indicate border state

17-3DOE is also considering regional standards for residential furnaces — which is a separate rulemaking from CACHP — that would have two regions (North and South) for impact assessment purposes.

The regional boundary for the states in the Furn aces rulemaking is approximately at the 5,000 HDD line. The states included in each furnace rulemaking regions are listed in Table 17.1.2.

Table 17.1.2 States and Regions for Resi dential Furnaces Rulemaking*
Furnaces-North Furnaces-South

Alaska Alabama
Colorado Arizona
Connecticut Arkansas
Idaho California
Illinois Delaware
Indiana Florida

Iowa Georgia
Kansas Hawaii
Maine Kentucky
Massachusetts Louisiana Michigan Maryland
Minnesota Mississippi
Missouri Nevada
Montana New Mexico
Nebraska North Carolina New Hampshire Oklahoma New Jersey South Carolina
New York Tennessee
North Dakota Texas
Ohio Virginia Oregon Pennsylvania
Rhode Island
South Dakota
Utah
Vermont Washington West Virginia

Wisconsin Wyoming
* Italics indicate border state

17-417.1.2.1 Regional Standards vs . National Standard

It is important to differentiate between the impacts of an amended national standard and the impact of introducing regional standards. Th e following sections do not assess the impact on market participants of more stri ngent energy conservation standards. Rather, this chapter focuses on the impacts on market participants in the HVAC distribution chain of having different standards affecting different geographic markets. For example, the impacts of physically larger HVAC units on distributors (due to a more stringent standard) are not discussed in this chapter because such an impact would occur under an increase in the base national standard as well. This chapter considers only the impacts of additional regional standards on these market participants. For example, the imp act on a distributor of having to alter inventory systems to serve regions with differential efficiency leve ls is an impact that would be considered. Ultimately, DOE must determine whether regiona l standards are economically justified, after considering the impacts on market participants attributable to such standards.

For firms located farther from the borders delineating applicability of the regional standards and serving only small areas, the impact of regional standards is expected to be very similar to the impact of a national energy conservation standa rd. However, firms located near the border between regions and serving two (or three, in th e case of CACHP) regions are expected to be most strongly impacted because they may have to respond to different efficiency requirements for each region in which they operate. For exam ple, distributors located near the border between standards regions may sell equipment meeting diff erent standards in the different regions and need to carry more inventory or manage their inventory differently to meet the separate needs of customers in each region. Table 17.1.3 and Table 17.1.4 display the states on the borders of the CACHP and furnaces regions, respectively.

Table 17.1.3 Border States by Region for CACHP Rulemaking

CAC-CHP Hot-Humid CAC-CHP Hot-Dry CAC-CHP Rest of Country

Arkansas Arizona Colorado

North Carolina California Idaho

Oklahoma Nevada Kansas

Tennessee New Mexico Kentucky

Texas Missouri

Oregon

Utah

Virginia

17-5Table 17.1.4 Border States by Region for Furnaces Rulemaking

Furnaces North Furnaces South

Colorado Arizona

Idaho Arkansas

Illinois California

Indiana Delaware

Kansas Kentucky

Missouri Maryland

New Jersey Nevada

Ohio New Mexico

Oregon Oklahoma

Pennsylvania Tennessee

Utah Virginia

West Virginia

17.1.3 Discussion of Non Enforceme nt vs. Enforcement Issues

For the purposes of this chapter, DOE gr oups potential impacts of regional standards on market participants into two categories: (1 ) non-compliance issues and (2) compliance-related issues. Non-compliance issues are those that arise from regional standards regardless of the enforcement plan established by DOE. Complianc e-related issues are those impacts that would vary depending on the enforcement path proposed by DOE (e.g., certific ation, verification, and labeling costs).

At this stage, while DOE is considering va rious enforcement plans, no mechanisms or requirements are proposed here. As such, DOE do es not attempt to quan tify enforcement-related impacts in this chapter. EPCA requires DOE to begin an enforcement rulemaking not later than 90 days after the issuance of a final rule es tablishing regional standards and complete the rulemaking not later than 15 months followi ng the issuance of the rule. (42 U.S.C. 6295(o)(6)(G)(ii)).

17-617.2 MARKET PARTICIPANTS

17.2.1 Definition of Terms

As discussed previously, EPCA directs DOE to consider the impacts of additional regional standards on market participants, includi ng “distributors, dealers, contractors, and installers.” (42 U.S.C. 6295(o)(6 )(D)(ii)) Based on DOE’s in itial research and comments from stakeholders, some of the market participants enumerated in EPCA have overlapping or identical functions in the HVAC marketplace. Industry of ten uses the various terms interchangeably to describe the same market participant. Therefore, it is important to clarify what market roles are associated with each term for the purposes of th is analysis. Below is a brief description of DOE’s understanding of each player in the dist ribution chain (for more detailed descriptions, refer to 17.3).

17.2.1.1 Distributors

Also known as ‘wholesalers,’ distributors purchase HVAC equi pment directly from the original equipment manufacturers (OEMs). Distributors absorb short-term imbalances in supply and demand and sell equipment to contractors at a markup to cover operating expenses and profit.

17.2.1.2 Contractors

There are two basic types of contract ors of relevance to the HVAC market:

General contractors. In the new construction market, general contractors manage and oversee reside ntial and commercial constr uction projects. General contractors often lack the necessary technical expertise to install and inspect HVAC systems. As a result, they hire HVAC trade specialists, or mechanical contractors, to install equipment. Genera l contractors usually have no significant role in the residential replacement market, except for cases of major retrofits.

Mechanical contractors. Mechanical contractors are specialized contractors that install and maintain HVAC systems, pl umbing, wiring, et c. Mechanical contractors purchase HVAC systems from di stributors and install them for their customers. Contractors often service ex isting HVAC systems as well. Again, in the new construction market, they are usuall y hired by general contractors. In the replacement market, they are hired by homeowners and are considered synonymous with dealers (below).

17.2.1.3 Dealers

Much like mechanical contractors, HVAC dealers purchase systems from distributors. Often they may have a more formal relationship with a manufacturer. Dealers resell the equipment to the end-user at a mark-up, nearly always installing the HVAC system as well. Dealers also inspect, maintain, and repair existing systems.

17-717.2.1.4 Installers

The industry uses installers interchangeably with mechanical contractors and dealers. Because the HVAC market is very rarely a do-it-yourself market, DOE includes homeowners who install their own systems in this category. In general, the impact of regional standards on homeowners is assessed in the LCC analysis.

17.2.1.5 Builders

For the purposes of this chapter, builder s serve the same function in the HVAC marketplace as general contractors.

Given the above similarities and overlapping roles in the distribution chain, DOE believes that EPCA’s requirement to analyze the impacts on product distributors, dealers, contractors, and installers is sa tisfied by an analysis of the potential impact of regional standards on three categories of market participants:

• Distributors

• Mechanical contractors

• General contractors

The category of “mechanical contractors” includes dealers, mechanical contractors, and installers. The category of “general contractors” comprises builders and ge neral contractors. In accordance with comments received and consiste nt with the markups analysis, DOE believes such a grouping is appropriate for this analysis and allows DOE to consider the economic impact of regional standards on the relevant market pa rticipants as required by EPCA. Impacts on manufacturers are assessed in the manufacturer impact analysis, while impacts on consumers are assessed in the life-cycle cost analysis.

17.3 DISTRIBUTION CHAIN

17.3.1 Overview

A single distribution channel represents the vast majority of the HVAC market. Simply, the OEM assembles the system and sells it to a distributor; the distribut or warehouses and sells the unit to a contractor; and the contractor sells the unit to the final consumer and performs the installation. The final consumer varies in the re placement and in the new construction market. In the replacement market, the final consumer is usually the home or business owner, as illustrated in Figure 17.3.1. In the new construction market, a builder or general contractor is effectively the final end-user, as shown in Figure 17.3.2.

17-8Figure 17.3.1 Distribution Chain in Replacement Market

Figure 17.3.2 Distribution Chain in New Construction Market

After installation, mechanical contractors typically perform additional lifecycle service on the system, including inspecti on, maintenance, and repair.

17.3.2 Vertical Integration

In some cases, a single entity can perform one or more of the basic steps along the HVAC distribution channel. For example, most manuf acturers own at least so me distribution centers, which operate much like the independent distributi on companies. In fact, all major manufacturers maintain at least some distribution capability in-house. In this distribution model, the OEM ships units to its own subsidiaries, which ope rate distribution centers and sell product to

contractor s . Manufacturers usually employ this strategy in areas where they have limited relationships with distributors for a given product line.

Historically, the degree of vertical integr ation has ebbed and flow ed with the economic well-being of the industry. In good times, OEMs ha ve historically been more likely to acquire a distribution presence. Conversely, in bad times, th ey have been more likely to seek to shed the costs and risks associated with the distribution function. According to the U.S. Census Bureau, in 2002, 74 percent of HVAC sales went through independent distributors. 1 Currently, the percentage of the dollar value of HVACR products that go through independent distributors is estimated to be around 80 percent. 2

Lennox International Inc. (LII), a large e quipment manufacturer, has one of the largest distribution presences in the industry. It owns several subsidiaries whic h operate as distributors and even as contractors, as is the case with LII subsidiary, Service Experts. 3 While Service Experts is a wholly owned subsidiary, it ope rates independently fro m LII’s manufacturing

17-9operations. Service Experts carries heating and cooling equipment inventory and offers service for HVAC equipment from various manufacturers. 4

Importantly, while some entities may have a controlling interest over multiple steps in the distribution chain, the costs, markups, and business processes in the distribution chain ultimately remain relativel y equivalent. That is, the distribut or and contractor markups (and the resulting pricing) for the manufacturer-owned distributor and contractor businesses are roughly equivalent to the markups that occur wh ere those businesses operate independently.

The business models of distributors, contractor s, and general contractors are described in greater detail below.

17.3.3 Distributors

17.3.3.1 Market Overview

The HVAC distribution market is a well-esta blished yet fragmented industry consisting of approximately 1,300 distribution companies. In dependent distributors ar e responsible for the majority of the business in the industry, but a ll major manufacturers have some type of factoryowned distribution. The vast majority of indepe ndent distributors are smal l, private companies. In 2002, there were 5,468 total distribution branches, 5,156 of which were independent distribution branches and 312 of wh ich were owned by manufacturers. 5

17.3.3.2 Distributor Business Model

Distributors link the handful of CACHP/furn ace manufacturers to the tens of thousands of contractors. Distributors receive shipment s from manufacturers and resell the equipment to contractors at a markup that cove rs distributor operating expenses and profit. Manufacturers rely on distributors to consolidate and forecast pr oduct demand at the regional and local levels. Contractors rely on distributors to hold enough in ventory and parts to meet their day-to-day business needs. As the only player along the di stribution chain that holds significant inventory, distributors add value by absorbing short-te rm imbalances in supply and demand while still satisfying the needs of the homeowner (and, by extension, the contractor) for fast deliveries. 6

The distributor’s warehouse is usually the only stop for HVAC equipment on the way to the final installation site; however, in some markets distributors utilize regional distribution centers that supply secondary distribution warehouses. In either case, shipments are warehoused as distributor inventory until sold to customers. Although it can vary widely, typically sixty to seventy percent of revenue comes from unitary equipment, with the remainder coming from parts and other supplies.

Distribution is a highly competitive and low-margin business. The critical driver of profitability is the ability to manage inventory efficiently. Traditionally, distributors tended to receive large-volume pre-season shipments from original equipment manufacturers (OEMs). However, the market has migrated away from that model as industry lead times (the time it takes to receive an order from the OEM) have fallen. Most distributors now operate in somewhat of a

17-10blend between just-in-time supply and the traditional model. To streamline inventory management, distributors often conduct extensive demand forecas ting to estimate the timing and quantity of their orders. Key factors include historical demand, new construction, OEM lead times, new products and lines, and weather patterns. The typical lead time of an average residential HVAC system is 2-3 weeks, although different parts or components, as well as more intricate HVAC systems, may have different lead times. Some of the more advanced coils, for example, can have lead times of 6-8 weeks.

Financing and credit, closely related to inventory, play a critical role in the distribution business model. With the high working capital re quirements due to inventory needs, short-term credit availability is the lifeblood of many small wholesalers. Distributors typically purchase equipment from manufacturers on credit, with the ba lance being paid within 30 days, often with discounts for early payment. Historically, OEMs have offered financing to their distributor clients, but have generally exite d that business. Instead, mostdistributors now are financed through local banks. In turn, distributors often ex tend lines of credit to certain contractors based on the amount business volume, profitability of th e relationship, and previous experience with the contractor. As a result, distributors incur the carrying costs associated with the difference between the financing terms that they receive from their creditors and the terms they extend to their contractor customers. Effectively, the distributor incurs as a cost the difference between these two rates over the period of time after the distributor pays the OEM for the unit and until it receives payment from the contractor.

Because of this dynamic, a key financial metric driving profitability is days sales outstanding (DSOs), a measure of the number of da ys it takes a company to collect revenue after a sale has been made. DSOs in the industry av erage between 40-45 days; if they grow higher, the increased carrying costs can threaten the th in margins under which distributors operate. In extending credit to their customer s, distributors also assume the risks involved with floating the receivables (i.e., the contractor goes out of business or otherwise fails to pay).

Changes in market dynamics, which can lead to changes in the quantity and type of product demanded, may cause distri butors to incur one-time costs associated with temporary increases in inventory, inventory obsolescence, or the opportunity costs represented by the failure to meet customer needs. Increased market uncertainty forces distributors to hold greater

than-usual inventory to reduce the ri sk of not meeting customer needs. 7 Failure to do could mean losing customers to competition. 8 However, if certain products do not sell, distributors absorb the costs of unsold inventory. 9 Typically, following an initial learning curve associated with these market changes, distributors adjust to th eir customers’ demands and are able to adjust inventory levels accordingly. 10

The increasing use of information technolog y in distribution has helped wholesalers adapt to market transitions. Sales and orders are usually made electronically at each step along the distribution chain. IT systems exist that allow distributors to forecast demand, source and purchase supplies, manage and track inventory, streamline the supply chain, and manage various sales channels. 11 Many distributors give contractors th e ability to place orders online after-hours so that the orders are ready for pickup the followi ng morning, while others give some customers a direct link into a computer system for automatic inventory replenishment. 12

17-11At the distribution center, inventory is generally organized by model and SEER/HSPF/AFUE rating. Units are stacked vert ically and, depending on their size, may be transported with forklifts. The layout of wa rehouse and placement of product affect order processing and inventory efficiency. 13 It is important for distributors to organize inventory in a manner that minimizes the order cost and minimizes mistakes that lead to costly reprocessing. The average cost of processing an order, from receipt of the order until payment is received, is $ 35-$45. 14 Cycle counts are performed frequent ly to minimize and document inventory shrinkage.

Beyond the manufacturer selling price (cost of goods sold), the largest cost considerations are those that imp act inventory and transportation costs. The size of an HVAC system impacts both. Larger, more efficient units require more warehouse space to inventory. The switch from 10 SEER to 13 SEER in 2006, for example, required 35-40% more floor space for every condensing unit. 15 Fewer units can fit on trucks and forklifts, requiring more time per unit for transportation and handling, absent new and upgraded equipment. 16 The larger units can require two people to offload them instead of one. 17

Manufacturer-to-Distributor Interactions

The relationships between ma nufacturers and distributors ar e generally well-established, long-term relationships. In most markets, di stributors are the exclusive carrier of a given manufacturer product. Distributors will often car ry a second brand from the same manufacturer, which has a different price point targeting a second market segment.

Most manufacturers will not allow distribut ors to carry products from a competitor, unless the manufacturer does not offer a product applicable to the market. In that case, distributors may partner with a second manufactur er. However, the terms of agreements can vary significantly depending on a wide range of factors, including sales volume, the extent of contractor relationships, strength of the brand in the area, and projected market growth. If a distributor carries a product line, it also has th e parts business associated with that line.

Manufacturers are generally responsible fo r getting the equipment to distributors’ warehouses and incur the associated costs, whic h they embed in their prices. Manufacturers usually hire a shipping company to transport the equipment and pass on these costs to the distributors in the sales price. Almost all inbound freight shipped to distributors is shipped FOB Origin Freight Prepaid, which means that once th e manufacturer ships the freight, the distributor owns it. 18 This can lead to problems when ite ms are damaged or broken upon arrival, representing another risk in the distributor business model. 19

Distributor-to-Contractor Interactions

Because there is relatively low manufacturer brand loyalty among consumer end-users, distributors compete actively over contractor customers. While OEMs focus on general brand awareness and product demand, distributors are frequently involved in providing multifunctional support to their contractors. To in crease competitiveness and revenues, distributors are increasingly offering value-added services , such as business planning help, financial

17-12management classes, and support for advertising, to their contractor customers beyond their supply function. This is also a strategy for increasing profitability—a contractor that is unprofitable cannot pay the distributor in a timely fash ion, if at all. Thus, successful distributors are heavily invested in their contractors’ success. 20

In the vast majority of cases, contractor s purchase the unit over the counter at the distributor’s warehouse. Becaus e most contractors do not carry much or any inventory, thetransaction will include a specific unit needed for a single job. The contractor can generally callin, order online, or fax in an order and go pick up the needed unit on the same day. At the warehouse, the distributor loads the unit onto th e contractor’s truck (s ome distributors have “drive through” warehouses) and contractor can be on the way to the job site in minutes. While business is primarily done in this over-the-counter model, distributors also make onsite deliveries for their customers.

17.3.4 Contractors

17.3.4.1 Market Overview

The HVAC contractor market is even more fr agmented than the distribution industry. There are 36,345 HVAC branches that specialize 51 percent or more in HVAC, 25,496 of which specialize entirely in the industry. 21 The large majority of c ontractors operate as small businesses, as defined by the U.S. Small Business Association (see Section 17.7 for more information on small business contr actors). Partly due to the very low barriers to entry in the market, the industry has resisted consolidation. Approximately 60 percent of branches in the industry generate less than $500,000 in revenue annually and 76 percent generate less than $1,000,000 annually. 22 Comfort Systems USA is the larg er of two public HVAC contractor companies that DOE was able to find. Its 2008 revenues ($1,328,465,000 23 ) accounted for approximately 3 percent of the $49,425,445,000 24 HVAC contractor industry (although the company does provide ancillary services). 25 Most independent contractors work with a variety of HVAC brands, although some sp ecialize in one particular bra nd, or have a relationship as a licensed dealer of a specific manufacturer.

17.3.4.2 Business Model

HVAC contractors primarily install and serv ice HVAC systems. Contractors are the interface with the end-users, installing new HVAC systems to their specifications as well as inspecting, servicing, or repairing existing systems. Contractors must balance two very different aspects of their business to be successful. First, contractors must fulfill the technical role of installing and servicing the HVAC systems. This requires a staff that is knowledgeable about HVAC principles in general and adept at installa tion and service on many different HVAC units. Second, contractors must also opera te the commercial aspects of th eir business. Because of the high level of competition, advertising, customer service, and sales skills are integral aspects of the contractor’s business. Rarely do HVAC comp anies achieve sufficient scale to have staff specialize in a single business practice.

17-13Contractors have the largest influence on which system a consumer will purchase. 26 For their part, contractors tend to gravitate to ward the products with which they are familiar. 27 Contractors often employ a good-better-best selling philosophy to up-sell consumers on premium products. 28 The minimum SEER model is a “good” syste m; there is a “better” system that is rated a few SEER points higher; and finally, ther e is a “best” system which has a very high SEER rating. 29 A sample good-better-best set of syst ems might be 13 SEER -16 SEER-20 SEER; however, this is dependent on minimum efficiency requirements. 30 Customers are more likely than they used to be to purchase energy-efficie nt and environmentally friendly products, in spite of the higher cost associated with them, because they have become more sensitive to the environment and the cost of energy. 31 Increasing tax credits and utility rebates can defray some of the higher incremental first cost as well.

While some contractor s have exclusive relationships w ith manufacturers, most compete by offering a large variety of product offerings an d by being trained to install, inspect, service, and repair those offerings. As with distributors, the size and weight of HVAC systems affect the business of contractors. While the vast majority of inventory is held by distributors, some contractors do carry a small amount of inventory and could be likewise affected by larger units. Larger systems are also more difficult to trans port from the distributor to the job site, possibly even requiring special precautions or equipment to load or unload the unit in extreme cases.

A contractor’s labor costs related to the installation and service of HVAC systems remain relatively constant regardless of the HVAC syst ems that the company installs and services. 32 Once the technicians are trained, the time spent installing an HVAC unit does not vary greatly from system to system. 33

17.3.5 General Contractor

17.3.5.1 Market Overview

As discussed above, for the purposes of th is chapter and consistent with comments received DOE considers general contractors and ho mebuilders to have essentially the same role in the distribution chain. Thus, DOE believes the two will have similar concerns and face similar potential impacts from regional standards. As with m echanical contractors, the general contractor and builder market is highly fragmented and local ized. According to the U.S. Census, there were more than 200,000 general contractor establishments in 2002. 34

17.3.5.2 Business Model

General contractors manage ne w construction and significant renovation projects. When supervising a project, the general contractor hi res a mechanical contractor to perform the installation. In this situation, the general contractor functions as th e final step in the distribution chain. The general contractor may purchase the H VAC system from the di stributor and hire the mechanical contractor to it or purchase the system from the installing mechanical contractor. When projects are larger—a townhouse developmen t, for example—a distributor may seek to establish a supplying relationship with the genera l contractor and deliver the units in bulk. The general contractor would then hire a mechanical contractor to perform the installation. For a

17-14custom-built home or renovation, the mechanical contractor may purchase the unit to the specifications requested by the general contractor.

17.3.6 Retailers

Retailers such as Home Depot, Lowe’s and Sears can also be involved in the distribution process. However, DOE’s understanding of these re tailers is that they function mostly as a leadgenerating system for contractors, as the HVAC mark et is very rarely a do-it-yourself market. When the so-called “Big Box” retailers are involve d, customers go to a retailer and ask to be put into contact with a contractor. A distributor usually still supplie s a contractor, who still performs the installation. In the end, the costs and mar kups reflect those in the standard distribution model. Furthermore, DOE believe s this reflects a small portion of overall unit sales. Therefore, for the purposes of this analysis, DOE does not consider the role of retailers in this analysis.

17.4 DISCUSSION OF REGIONAL STANDARD IMPACTS

Through public notices, public meetings, and interviews with industry trade groups, DOE has solicited comments on the impact of region al standards on CACHP and Furnace industry participants. This chapter discusses DOE’s understanding of the potential impacts on key players in the distribution chain.

As noted in Section 17.1.2.1, it is important to differentiate the difference between the impacts of a higher base national standard and of regional standards. The following sections do not assess the impact on market participants of an increase in the base national efficiency standard. Rather, this chapter focuses on the impacts of having different standards affecting different geographic markets.

The impacts of regional standards are se parated here into two categories: non

enforcement issues and enforcement issues. Non- enforcement issues are those issues that arise irrespective of the actions taken to enforce the re gional standards. Enforcement issues are those impacts and costs that are directly related to ensuring compliance or that arise from non

compliance. Because DOE has not established an enforcement plan for regional standards, DOE is not able to capture any enforcement impacts in this analysis.

17.4.1 Distributor Impacts

Non-enforcement Issues for Distributors

In written comments and at the CACHP fra mework public meeting, Heating Air conditioning & Refrigeration Distributors Intern ational (HARDI) raised several concerns regarding the implementation of regional standa rds and the potential impact of those standards on their businesses. Their concerns center largely on the premise that there will be differences between regional standard boundaries and existing distribution boundaries.

17-15HARDI noted that EPCA requires regional boundaries to be drawn along state lines, which are usually different from the market bound aries for central air c onditioners, heat pumps, and furnaces. Existing market boundaries are determined by multiple factors, including utility service areas, composition of building types within an area, natural climatic regions, and localized microclimates. HARDI identified a range of negative impacts resulting from the incongruence of regional standards boundaries an d existing distribution boundaries (HARDI, No. 32 at pp. 5-6):

• Increased costs due to increased inventory complexity

• Increased costs due to lost economies of scale in purchasing

• Reduced sales where cooling or heating demands are modest

• Constraints on business growth near borders

Based on its analysis and research, DOE believes that distributors that serve multiple regions will be impacted by additional (i.e., differentiated) regional standards. Distributors serving markets entirely within a single re gion will not experience non-enforcement impacts distinguishable from a national amended energy conservation standard.

DOE understands there to be two types of di stributors that will serve multiple standard regions and could be affected by the differentia ted regional standards: (1) central distributors shipping to local distributors in multiple regions and (2) local distributors selling to contractors in multiple regions. In general, distributors located near borders are more likely to serve multiple standard regions

DOE agrees that distributors serving multiple standard regions may be compelled to manage more variation in dema nd. Under a national standard, di stributors could expect the bulk of demand to be at the base national level (e.g., 13 SEER for CACHP). Under regional standards, however, distributors near boundaries may experience bimodal demand, with the one large portion of shipments at th e national standard efficiency level (e.g., 13 SEER) and a second large portion at a different regional efficiency level (e.g., 14 SEER). DOE believes that this bimodal demand does not signify a doubling of nece ssary inventory, but rather a more diverse inventory. The resulting change in product mix for distributors serving multiple regions could increase inventory management costs and increase overall investment in i nventory, because more product models of equipment ar e required to meet demand.

In Section 17.5.1, DOE performs a sensitivity analysis that investigates the impact of regional standards on inventory holdings and profitability. The analysis estimates a reasonable range of inventory increases based on industry data and then calculates the impact of those inventory changes on distributor profitability based on sample distributor financials. In general, the analysis finds that only small inventories ch anges would be required fo r distributors to meet product demand for multiple regions . Additionally, the sensitivity analysis finds the potential changes in inventory to have only small impacts on distributor profitability. See Section 17.5.1.3 for more details.

Another concern for the industry is that, with a wider variation in product, the number of particular product models purchas ed will be smaller, leading to fewer volume discounts. Along

17-16the same vein, national and regi onal distributors stated that th ey would face decreases in economies of scale due to the smaller size of regional markets. (HARDI, No. 2 at p. 2) Specifically, if certain products c ould not be sold throughout the entire country, then the cost of those products would be driven up. (HARDI, No. 2 at p. 2)

In response, DOE analyzes the impact of re gional standards in reducing economies of scale for manufacturers and leading to higher cost of goods sold for all distributors (including those not serving multiple regions) in its ma rkups and national impacts analyses for both CACHP and furnaces. The analysis assumes that those costs are passed on down the distribution chain to contractors and consumers. DOE will perform additional investigation on the cost impacts of smaller orders on distributors through interviews with manufacturers during the MIA

process.

Distributors also noted that sales in areas where cooling demands are more modest would likely be depressed since high-efficiency coo ling equipment would not be as well justified. (HARDI, No. 32 at 4) These comments address the issues of elasticity of demand and the question of how customers “roll-up” or “shift” to different efficiency levels based on the economics they face, given a climate. In this re spect, greater uncertainty about prospective sales is a not a function of having different standards by region, but simply having higher standards. The fact that cooling and heating demand varies by location is not exacerbated by regional standards. The question over the new efficiency distribution for each CACHP and furnace distributor is the same under na tional and regional standards. Optimizing inventory for the new demand distribution will be part of the transition cost in either standards case.

In sum, DOE does expect the transition due to amended standards to inject uncertainty into the market, which could temporarily cause di stributors to incur higher costs. However, DOE believes these costs are associated with a chan ge in standards, not the advent of additional regional standards.

Enforcement Issues for Distributors

DOE understands that many distributors do business in more than one region. Furthermore, the contractors to whom these dist ributors sell often do busin ess in more than one region. In light of these facts, it may be necessary for DOE to work with participants in the distribution chain to document the installation of CACHP and furnace units. If such reporting is used to support enforcement, it is possible that distributors will incur new compliance costs as a result additional record-keeping and reporting relate d to the regional standards. This would add some percentage to administrative labor costs of distribution channel partic ipants, some of which could vary with the number of units sold and some of which could be fixed. Any additional costs would be incorporated in this analysis of the impacts of regional standards.

At this time, however, DOE is not able to accurately assess impacts of compliance requirements on distributors. In the Preliminary Analysis for CACHP and in this chapter, DOE requests comment on appropriate measures for enforcement of regional standards for CACHP and furnaces.

17-1717.4.2 Contractor Impacts

Non-enforcement Issues for Contractors

Air-Conditioning Contractors of America (ACCA) commented that larger units would cause higher transport and handling costs and, in many cases, would not fit in the residential space that housed the previous unit. (ACCA, Public Meeting Transcript, No. 23 at p. 252)

In response, DOE notes that this issue is a function of higher sta ndards, not differential regional standards. As such, probl ems with larger units are not considered in this chapter. To the extent that regional standards affect co st of goods sold, above and beyond a national standard, DOE expects incorporate that effect in its normal markups analysis. DOE is unaware of any other contractor concerns with regional st andards that do not involve enforcement issues.

Enforcement Issues for Contractors

ACCA and HARDI stated that regional standards will increase non-compliance and would create a major competitive disadvantage for contractors that seek to comply. (ACCA, No. 23 at p. 2; HARDI, No. 32 at p. 5) HARDI argued th at this situation already exists in California after implementation of Title 24 requirements. Kent & O’Connor stated that splitting a metropolitan area with regional standards would have a significant competitive impact, particularly if a price difference exists between the higher regional efficiency and the national standard units. (Kent & O’Connor, No. 13 at p. 231)

As with distributors, in general DOE believes that contractors near regional borders could potentially be impacted by enforcement-relate d competitive issues surrounding differential regions. DOE acknowledges that non-compliance can be a problem for contractors following the codes and licensing requirements, as there is an incentive for non-compliance in the form of being able to offer unknowing homeowners a lower price point for HVAC service. DOE recognizes that along border regions, differentia l standards could exacer bate this disadvantage for complying contractors, particularly if the price difference between the regional-compliant products is significant.

DOE acknowledges that depending on the enforcement mechanisms put in place following a DOE rulemaking, contractors may incur additional administrative compliance costs associated with regional standards, including re cording keeping or verification costs. However, as noted above, at this point DOE cannot accurately assess any impacts of compliance due to regional standards because no enforcement mech anisms and compliance requirements have yet been established. DOE seeks comment on poten tial compliance and enforcement options for regional standards.

17-1817.4.3 General Contractor Impacts

Non-enforcement Issues for General Contractors

DOE received no comments on any non-enforcement related regional standard impacts on builders and general contractors, and is not aware of any impacts. DOE seeks comment on any non-enforcement impacts these market player s may encounter under regional standards.

Enforcement Issues for General Contractors

The National Association of Home Builders (NAHB) commented that a general contractor usually will not have any special HVAC expertise. Therefore, if regional standards are implemented, a builder is likely to use more time and effort double-checking that units are compliant. The extra cost of this effort s hould be included in the payback analysis, the cumulative regulatory burden, the employment impact analysis, and the regulatory impact analysis. NAHB also commented that regional st andards would affect home builders, most of which are small businesses; as such, a regulato ry flexibility analysis would be necessary. (NAHB, No. 21 at pp. 1, 2)

DOE recognizes that there may be impacts on general contractors operating in two different regions. For instance, DOE believes general contractors working on projects near regional standard borders may experience greater risk of mistakenly installing non-compliant systems—or hiring contractors who do so—and c onsequently incur greater cost under regional standards than they would under a single nationa l standard. Although DOE expects this impact to be short run in nature as contractors adjust to the new standards, DOE seeks comment on the likelihood of this and other impacts due to operating in multiple regions.

17.5 ANALYSIS OF REGIONAL STANDARD IMPACTS

The focus of this section is the impact of re gional standards on distri butors, particularly those operating near boundary regions. DOE attemp ts to quantify the financial implications of imposing different efficiency standards in multiple geographic regions. As previously noted, until DOE has further developed the enforcement plan for regional standards, it is not possible to provide detailed analysis of enforcement impacts. Two primary analyses are presented here:

• Analysis of inventory cost impacts under regional standards and the consequent impacts on profitability for CACHP and Furnaces Distributors

• Preliminary Markups Analysis on Distributors and Contractors

The inventory and profitability cost impact analysis provides a framework for understanding the magnitude of inventory change s that may result from regional standards and the impact of those cost changes on distributor profitability. As discussed in 17.3.3, DOE believes the key driver of distributor profitability is inventory. Therefore, this quantitative analysis only addresses changes in inventory costs.

17-19The second analysis investigates the impact of regional standards on product markups. The analysis considers the impact of regional standards on product markups far from the border region and near the border region. For states wher e there will likely be a change in distributors’ product mix, the analysis anticipates what the new mix will be and analyzes markups in parts of the country that currently have that anticipated product mix.

17.5.1 Profitability Analysis of Regional Standard Impacts

The following analysis provides guidance on the potential impacts of regional standards on profitability for distributors serving more than one standard region. The analysis has two components. First, the change in inventory re sulting from regional standards is calculated for a distributor serving two regions. Second, the impact of changes in inventory holdings on distributor profitability is calculated. The analysis is based on an example firm’s financial data, which is modeled after actual distributor data from HARDI.

In general, DOE believes distributors operating in a single standard region will not see any inventory impacts that are different from the impacts resulting from a change in the national standard. However, distributors operating in multiple regions or that are near a border may have to adjust to business impacts that are unique to the introduction of multiple standard regions. This analysis finds that the inventory impacts resulting from regional standards are likely to be mild. A prototypical distributor that sells to two regions is modeled to have an increase in inventory of less than 2 percent. The resulting impact on distributor profitability is also mild at the expected levels of inventory change.

17.5.1.1 Data Sources

This analysis of the profitability impacts of distributors relies on three sources of information: Heating, Air conditioning a nd Refrigeration Distri butors International 2009 Profit Report (2008 Data), 2002 Economic Census, a nd 2007 County Business Patterns. The following information can be obtained from these sources:

• Number of firms; total and population-weig hted average sales; total and average employment; and firm size distribution by revenue (2002 Economic Census and 2007 County Business Patterns).

These values are reported for the Nation and by State. It is possible to calculate these values for each of the regions affected by th e standard (Hot-Humid, Hot-dry, and Rest of Country) and for each of the 17 stat es that borders these regions.

• Number of small businesses as defined by the Small Business Administration (SBA). The SBA maximum threshold to qualify as a “small business” for NAICS 42373 is one hundred employees. In 2002, out of 2,773 fi rms with 5,942 individual establishments nation-wide, only five firms (0.2%) had one hundred or more employees. The nationallevel data shows that the dist ributors are overwhelmingly sma ll businesses. Data is not available at the regional level, but regional an alysis would be unlikely to show a different result.

17-20• Typical cost structure and profitability ( HARDI data, 2002 Census). Variation among firm sizes and types (HARDI data).

The annual HARDI reports have detailed cost structure data for typical firms, including pro-forma income statements and balanc e sheets (see sample data in Table 17.5.1and Table 17.1.1). Data related to costs a nd potential markups are available at the national level and for seven geographic regions. The HARDI geographi c regions do not match with the rule-making regions. However, it is possible to assign the typical income statements to firms in each state in the HARDI regions and then develop weighted-average balance sheets for each rule-making region.

Economic Census data is not as financially detailed but has greater geographic specificity. It is used to i ndicate variation of profitability around the regional averages, and whether border state establishments are significantly different than the regional average.

To see how the impact of additional standards is calculated with an estimate of additional inventories, consider the model of a “typical” di stributor in the Southeas tern United States shown in Table 17.5.1.

17-21Table 17.5.1 Typical Southeastern Wholesaler A ssets, Liabilities, and Profitability Profit Margin Asset Turnover

Profit before Taxes $457,467 Total Assets $9,842,389

Net Sales $24,077,230 Net Sales $24,077,230

Ratio 1.9% 2.45

Income Statement Profit Before Taxes Assets Breakdown

Cash and Marketable Net Sales $24,077,230 Securities $125,202

Cost of Goods Sold $17,793,073 Accounts Receivable $2,783,329

Gross Margin $6,284,157 Inventory $5,287,361

Operating Expenses $5,874,844 Other $1,435,003

Operating Profit $409,313 Total $9,630,895

Other Income/Expenses $48,154

Profit Before Taxes $457,467

Financial Leverage Return on Net Worth

Total Assets

Total Net Worth $9,630,895

$5,065,851

Ratio 1.90 9.0%

Original % of Asset Value Original Liabilities Modified Liabilities

$2,224,736.75

$587,485

$760,841

$3,573,062

$991,982

$4,565,044

$5,065,851 Accounts Payable

Notes Payable

Other Current Liabilities

Total Current Liabilities

Long-Term Liabilities

Total Liabilities

Net Worth 23.1%

6.1%

7.9%

37.1%

10.3%

47.4%

52.6% $2,224,737

$587,485

$760,841

$3,573,062

$991,982

$4,565,044

$5,065,851

SOURCE: HARDI Profit Report 2009

The values in the shaded cells in Table 17.5.1 can be changed in percentage terms to estimate the sensitivity of profitability, as defined by return on net worth. Data are not currently available to perform comparable calculations on the costs of record-keeping and reporting activities (changes in operating expenses).

17-2217.5.1.2 Sample Inventory Calculation for Southeastern Border CACHP Wholesaler

A simple illustrative example follows in which a Southeastern border wholesaler financially looks like the typical firm in Table 17.5.1. The wholesaler makes half of its sales in its home region (Hot-Humid Region) and half in a different region (Rest of Country). The example border wholesaler is assumed to have the following characteristics:

• Sales to dealers and contractors average 200 units a week, 100 in each region.

• Sales of different efficiency products have the same approximate distribution as the national sales of split-system air conditioners.

• Sales at each efficiency level follo w a Poisson statistical distribution.

• The wholesaler orders monthly from the manu facturer and keeps enough inventories on hand to meet quarterly sales forecasts.

Based on Table 17.5.1, known manufacturer costs, and wholesale markups for CAC and CHP equipment, the assumed 200 units per week is close to the sales of a “typical” HARDI wholesaler in the southeastern United States in 2008. Based on HARDI information, an average order cycle of 4 weeks and forecast period of 14 weeks are reasonable. The average lead time from placement of order to receiving units for inventory is about 5.1 weeks. Wholesale markup factors are 1.37 and estimated deliver ed cost of a unit of inventory is $1,200. These values are consistent with observations that complete units constitute 70% of sales, that average stock turnover is 3.6 times per year, and the values of sales and inventories in Table 17.5.1. Sales are distributed as follows by efficiency level based on approximate national sales of split-system air conditioners (numerical results are somewhat affected by the percentages, but the general takeaway does not change with a different efficiency mix):

• SEER 13: 81.0%

• SEER 14: 6.0%

• SEER 15: 5.0%

• SEER 16: 5.0%

• SEER 18 (above 16): 3.0%

Sales at each efficiency level follow a Poisson statistical distribution. This distribution is commonly used in applied statistics to characterize the probability and number of comparatively rare observed events (for example, purchase of ai r conditioning units by a household) that occur in repeated samples (for example, weekly totals of sales). It is used frequently in studies of inventory and other logistics probl ems. A convenient attribute of a Poisson distribution is that the variance of the distribution equals its mean and th erefore its standard devi ation equals the square root of the mean.

The wholesaler orders monthly from the ma nufacturer and keeps enough inventories on hand to meet quarterly sales forecasts. Because sales vary week to-week, the wholesaler’s “standard of service” is that it always carries enou gh inventory to meet a level of quarterly sales of any of its offered products at least two standa rd deviations above the mean, plus 1 unit. This gives the wholesaler a 98% chance of meeting any order.

17-23Four cases showing different shifts in demand for CAC and CHP equipment are considered, driven by a SEER 14 minimum efficiency standard.

• Case 1: SEER 14 is imposed in both regions. The result is a “rollup” of demand, which shifts all SEER 13 demand to SEER 14 wit hout affecting weekly demand for SEER 15, 16, or 18. SEER 14 sales change from 5 percen t to 86 percent of sales in both regions after the shift. SEER 15, 16, and 18 sales are unaffected

• Case 2: SEER 14 is imposed only in the Hot-Humid Region, while SEER 13 remains the standard in the Rest of Country region. Th e impact on demand is a “rollup” but only in the Hot-Humid region.

• Case 3: Same as Ca se 1, but the percentages of sale s at levels above SEER 14 are significantly affected (efficiency distributi on shift). The average distribution in both regions after the SEER 14 standard is imposed are:

o SEER 13: 0.0%

o SEER 14: 49.0%

o SEER 15: 23.0%

o SEER 16: 15.0%

o SEER 18: 13.0%

• Case 4: Same as Case 3, but the new after-standard sale s percentage percentages apply only in the Hot-Humid region.

The results of this analysis for these four cases are shown in Table 17.5.2.

Table 17.5.2 Border Wholesaler Re quired Inventory
Scenario No. Units in Inventory

Base Case 3380

Case 1 3355

Case 2 3400

Case 3 3400

Case 4 3425

Impact of Regional Standards on Value of Inventories
Rollup (Case 2 / Case 1) 1.3 % Increase

Shift (Case 4 / Case 3) 0.7 % Increase

17-24The base case scenario shows the inventory holdings required if there are no changes in the efficiency standard. The wholesaler must hold 3380 units in inventory in order to meet the “standard of service” conditions of the model.

Case 1 shows the impact of a single national stan dard with a rollup scenario. In this case, SEER 13 units are no longer sold, and it is no l onger necessary to stock them. There is some compensating increase in inventory for SEER 14 units, but the overall inventory service is simpler and the inventory stock drops.

Case 2 corresponds to a regional standard with a rollup scenario. It is still necessary for the border wholesaler to stock slightly more than half as many SEER 13 units as before to serve the Rest of Country, although these units can no longer be sold in the Hot-Humid region. In addition, more SEER 14 inventory must be carried to serve both regions. The net difference of Case 1 from the Base Case is 0.7 percent less inventory in this example due to the savings of SEER 13 inventory; however, Case 2 (regional standard) requires about 1.3 percent more inventory than Case 1 (national standard).

Case 3 corresponds to a single national stan dard with a market shift scenario. The national standard in Case 3 spreads the increases in sales of efficien t equipment over several efficiency levels that previously had low sales, so the overall required inventories go up slightly compared with the Base Case (about 0.6 percent).

Case 4 corresponds to a regional standard with a market shift scenario. This case requires 0.7 percent more inventory than Case 3.

17.5.1.3 CACHP Profitability Calculation

The increases in required physical units of i nventory thus appear to be on the order of 1 to 2 percent higher for a regional standard than with a national standard for distributors serving two regions. Table 17.5.3 and Table 17.5.4 present the modeled impacts of these inventory changes on ‘profit as a percentage of total sales’ and on ‘return on net worth,’ respectively. The tables also present the impacts of changes in inventory changes that are twice as large (4 percent increase) and five times as large (10 percent increase) to demonstrate the sensitivity of profitability to such changes.

The values in Table 17.5.3 and Table 17.5.4 are derived from the model in Table 17.5.1 by assuming increases to inventory and the associated increase in interest expense necessary to finance that additional working capital. Additionally, for illustrative purposes, DOE applied a range of interest rates for the capital requi red to finance the additional inventory.

Table 17.5.3 indicates that the impacts of additi onal inventory on profitability are not observable at one percent and two percent inve ntory change, except at the highest modeled interest rates. Table 17.5.3 also indicates that an inventory in crease of 10 percent financed at 12 percent interest could reduce pretax margins by approximately 20 basis points, a decline of approximately 10 percent.

17-25Table 17.5.3 Profitability Impacts of CACHP Inventory Cost Increases Profit before Taxes (% of Sales)
% Change in Inventory
Interest Rate for Inventory 0% 1% 2% 4% 10%

6% 1.9% 1.9% 1.9% 1.8% 1.8%

1.9% 1.9% 1.9% 1.8% 1.7% 8%

1.9% 1.9% 1.9% 1.8% 1.7% 10%

1.9% 1.9% 1.8% 1.8% 1.7% 12%

Table 17.5.4 shows the impact of inventory changes on distributor Return on Net Worth

, which is calculated as pretax profit divided by net worth, where net wo rth equals assets less liabilities. At the expected one to two percent inventory change, impacts on return on net worth are again small. However, the impacts could be significant for distributors with high borrowing costs and where there are significantly higher inventory requirements.

Table 17.5.4 Return on Net Worth Impacts of CACHP Inventory Cost Increases

Return on Net Worth
% Change in Inventory
Interest Rate for Inventory 0% 1% 2% 4% 10%

6% 9.0% 9.0% 8.9% 8.8% 8.4%

9.0% 8.9% 8.9% 8.7% 8.2% 8%

9.0% 8.9% 8.8% 8.6% 8.0% 10%

9.0% 8.9% 8.8% 8.5% 7.5% 12%

17.5.1.4 Sample Furnace Inventory Calcul ation for Border Wholesalers

Following the methodology above, it is possibl e to estimate changes in Furnace inventory in the border region resulting from both national and regional standards based on HARDI financial data. As shown in Table 17.5.5, this approach suggests that a regional standard will not significantly increase Furnace inventories.

17-26Table 17.5.5 Number of Units of Inventory of Furnaces in th e Border Region Base Case National Standard Case Regional Standard Case
Condensing 852 1667 1667
Non-Condensing 2476 1667 1667

Total 3328 3334 3334

Source: HARDI Profit Report 2009 , “Regional Analysis” distributors

As the standard increases beyond 80% AFUE, ther e is a significant change in the inventory ratio of condensing to non-condensing furnace units. However, the introduction of regional standards does not require inve ntories that are different from a national standard.

17.5.1.5 Furnace Profitability Calculation

DOE conducted an additional sensitivity anal ysis of the impact of a change in distributors’ inventory needs. Based on Table 17.6.16 and Table 17.6.17, DOE estimated the financial expenditure and profit figures for furnace distributors operating in border states. Then, following the process outlined in Section 17.5.1.3 “CACHP Profitabilit y Calculation,” the impact of inventory changes on firm profitability (measured as pretax income/sales and return on net worth) are examined at a range of interest rates.

Table 17.5.6 and Table 17.5.7 provide detailed es timates of the dist ributor profitability impact of inventory cost changes. Generally, this analysis suggests that carrying a slightly larger inventory may slightly decrease firm pre-tax pr ofits and return on net worth in the short run.

Table 17.5.6 Profitability Sensitivity Analysis for Furnaces in Border States

Pretax Income (% of Sales) % Change in Inventory Interest Rate for Inventory 0% 1% 2% 4% 10%
6% 1.7% 1.7% 1.7% 1.7% 1.6%
1.7% 1.7% 1.7% 1.7% 1.6% 8%
1.7% 1.7% 1.7% 1.6% 1.5% 10%
1.7% 1.7% 1.7% 1.6% 1.5% 12%

17-27Table 17.5.7 Return on Net Worth Analysis for Furna ces in Border States
Return on Net Worth % Change in Inventory Interest Rate for Inventory 0% 1% 2% 4% 10%
6% 12.9% 12.8% 12.7% 12.6% 12.1%
12.9% 12.8% 12.7% 12.5% 11.8% 8%
12.9% 12.8% 12.6% 12.4% 11.5% 10%
12.9% 12.7% 12.6% 12.3% 11.3% 12%

17.5.2 Preliminary Analysis of the Impacts of Regional Standards on Furnace and CACHP markups

17.5.2.1 Furnace Markups

During the 2007 Furnace rulemaking, DOE pr oposed two regional standards for furnaces, divided between north and south. The Northern re gion represents those states with average HDD greater or equal to 5,000 and southern region repr esents those states with average HDD less than 5,000. In the preliminary analysis, distributors and contractors in the furnace industry are divided into north, south and border region subgroups. The imp act of regional standards is expected to be stronger on distributors and contractors located close to the border region than on firms located far from the border region. Thus, for the purpos e of addressing the imp act of differentiated regional standards, we focus on the change in markups to firms located (1) far from the border and (2) near the border.

17.5.2.2 Firm Markups Far From the Border Region

In the section, DOE analyzes how markups migh t change for firms located far from border regions. DOE first addresses such firms in the northern region and then looks at those in the southern region. According to a report published by Energy Center of Wisconsin in 1997, the percentage of high efficiency furnaces sold in Wisconsin was approxima tely 70% of all units 1996. a The historical data from GAMA 2005 also supports this statement, indicating that Wisconsin has the highest average saturation ra te of condensing furnaces in the country. b Since high efficiency furnaces currently dominate the Wisconsin market to a degree expected in the rest of the Northern Region following regional standards, markups in Wisconsin are used to predict markups in the rest of the Northern region. Table 17.5.8 below compares the weighted average baseline markup in the Northern region and in Wisconsin.

a For this report, high efficiency furnace has an AFUE of at least 90%.

b In GAMA report, condensing furnace is defined as those having an AFUE of at least 88%.

17-28Table 17.5.8 Northern Region Markups Region Distributor Markup Mechanical Contractor Markup General Contractor Markup
Northern Region 1.38 1.36 1.21

Wisconsin 1.37 1.33 1.16

Source: HARDI Profit Report 1999, 2002, 2005, 2008, 2009, “Regional Analysis” distributors and 2002 US Economic Census

The average baseline markup in Wisconsin is lower than the baseline markup in the Northern region for distributors, mechanical contractors and ge neral contractors. DOE assumes that Wisconsin has completed a transition from providing a mix of low and high efficiency furnaces in the past to providing primarily hi gh efficiency furnaces today. As a result, Wisconsin firms have lower markups than firms in other Northern states. Assuming a future regional standard that requires high-efficiency furnaces in the north like those that exist in Wisconsin, DOE expects that all firms in the Northern region will have inventories and markups similar to those currently in Wisconsin.

In Southern States, high efficiency furnaces are not as widely used as in Northern states. The condensing furnace saturation rate in the Sout h already reaches 14% a nd this saturation rate is not expected to change after regional standards take effect. 35 Thus, higher standards in the South are not expected to have a significant impac t on firm inventories or markups in that region. Here Oklahoma is used as a reference case; 15% of the furnaces sold in Oklahoma are condensing furnaces, similar to the expected satura tion of the South after regional standards take effect. Table 17.5.9 summarizes the results:

Table 17.5.9 Southern Region Markups Region Distributor Markup Mechanical Contractor Markup General Contractor Markup
Southern Region 1.35 1.35 1.24

Oklahoma 1.35 1.35 1.24

Source: HARDI Profit Report 2008, “Regional Analysis” distributors and 2002 US Economic Census

As shown above, there is currently no difference between markups in Oklahoma and the rest of the Southern region. This implies that regional standards are not likely to imposesignificant impacts on the Southern region because the existing mixture of condensing and noncondensing furnaces already sufficiently refl ects the steady state of long run impact.

We conclude that the regional standards will not greatly impact firms located in far from the border region. In both the Northern and Sout hern regions, this analysis indicates that standards will not require higher inventories and therefore are not likely to bring about changes in markups.

17-2917.5.2.3 Border Region Markups

Under regional standards, distributors located near the border between standards regions may have to sell equipment meeting different st andards in the two regions and need to carry more inventories or manage their inventory differently to meet the separate needs of customers in each region. DOE highlights these impacts by assuming that firms located in the border region of each State have sales, inventor ies, and markup practices similar to those of firms in the rest of that State.

Based on the data below, DOE assumes most of the firms in the northern part of the border region already maintain a mix of more high e fficiency and less low efficiency furnaces, so regional standards are unlikely to impose any a dditional changes on inventory costs to these firms. Saturation rates of condensing furnaces in the Northern border region from GAMA Report 2005 (Table 17.5.10) show that the sale of condensin g furnaces in these States increased noticeably from 1997 to 2003. Therefore, the current markups in this region could be considered as the upper bound of the future markups because of the possible simplifi cation of inventories resulting from regional standards. Only firms in the southern part of the border region are likely to be significantly affected by the standards. These firms currently sell mostly low efficiency furnaces and new regional standards could force th em to carry a mix of more high efficiency (to serve their cross-border market) and fewer low efficiency furnaces, as shown in Table 17.5.11. As a result, they may incur higher inventory costs from storing more high efficiency furnaces.

Table 17.5.10 Saturation Rate of Condensing Furn aces in the Northe rn Border Region

State 1997 1998 1999 2000 2001 2002 2003

PA 45.26% 46.79% 43.20% 45.54% 49.12% 50.45% 55.28%

IN 25.69% 28.60% 27.51% 29.61% 35.83% 35.29% 44.87%

IL 27.40% 26.91% 26.96% 23.71% 32.23% 32.50% 36.15%

UT 30.41% 27.57% 26.68% 25.99% 29.93% 27.43% 28.24%

KS 24.12% 23.64% 21.87% 23.86% 32.90% 26.11% 29.59%

NJ 23.15% 25.11% 26.91% 23.52% 28.42% 31.96% 40.68%

ID 22.14% 22.53% 23.90% 25.58% 30.18% 30.85% 35.58%

OR 21.95% 22.18% 21.11% 20.88% 26.96% 27.04% 28.45%

MO 27.63% 29.28% 29.11% 28.65% 4.11% 2.85% 2.46%

CO 9.74% 9.07% 9.96% 9.70% 14.43% 15.96% 21.77%

Source: GAMA Report 2005

17-30Table 17.5.11 Saturation Rate of Condensing Furnaces in the South ern Border Region

State 1997 1998 1999 2000 2001 2002 2003

KY 34.00% 32.73% 32.09% 34.17% 39.86% 39.05% 46.72%

AZ 8.73% 9.55% 8.33% 9.14% 10.71% 15.27% 15.67%

CA 9.27% 6.34% 6.08% 6.33% 11.14% 11.19% 12.04%

OK 4.55% 5.49% 6.91% 6.55% 10.09% 9.21% 10.39%

NV 7.36% 5.45% 6.09% 5.12% 6.57% 10.45% 12.32%

AR 5.21% 2.97% 2.77% 3.01% 4.86% 5.36% 6.27%

NM 4.82% 2.86% 3.13% 1.77% 2.61% 3.18% 5.14%

Source: GAMA Report 2005

Table 17.5.12 Border Region Markups Region Distributor
Markup Mechanical Contractor Markup General Contractor Markup

Northern part of the border region 1.38 1.36 1.21

Southern part of the border region 1.35 1.35 1.24

Average border region 1.36 1.36 1.27

Source: HARDI Profit Report 1999, 2002, 2005, 2008, 2009, “Regional Analysis” distributors and 2002 US Economic Census

The average border region markups shown in Table 17.5.12 are the weighted average markups using the fractions of distributors a nd contractors located in the metropolitan areas within the designed border region in each border state. The numbers shown here reflect existing markups instead of predicted markups; however, the differences with northern border region markups and southern border regional markups provide a sense of what the potential impact will be in these two sub-border regions respectively. Based on the analysis above, markups in the Northern part of the border region are expected to remain the same as the rest of the current Northern region markups in the short run. As for the Southern part of the border region, markups are expected to increase due to higher inventor y costs from having to serve a greater mix of product. In the long run, markups in both parts of the border are expected to converge to one single border markup. Markups in the Northern pa rt of the border may stay at the current upper bound level or slightly decrease to the level th at meets the long-term southern border region markups due to the possible produc t simplification in the North. Thus, the future border region markups are predicted to be bounded between cu rrent northern border markups and southern border markups.

17-3117.5.2.4 Central Air Conditioners and Heat Pumps

In the CACHP rulemaking, DOE described potential regional standards for three climatic regions: Hot-Humid, Hot-Dry and Rest of the co untry. Theoretically, an analogical method similar to that used for furnaces above could be adopted for CACHP. However, DOE lacks the regional CACHP efficiency data needed to conduct that analysis. DOE calculated regional markups for distributors, mechanical contractors and general c ontractors in the CACHP market, and the results are summarized in Table 17.5.13. DOE requests comment on how these markets will change for regional standards.

Table 17.5.13 Central Air Conditioner and Heat Pump Markups

Region Distributor
Markup Mechanical Contractor Markup General Contractor Markup

Hot-Humid 1.33 1.34 1.24

Hot-Dry 1.37 1.37 1.22
Rest of the country 1.37 1.36 1.23

Source: HARDI Profit Report 1999, 2002, 2005, 2008, 2009, “Regional Analysis” distributors and 2002 US Economic Census

17.6 ADDITIONAL DISTRIBUTOR DATA

Tables detailing the number of establishments, total and average sales, and total and average employment (2002 Economic Census) follow for each region. Sample distributors data are shown in Table 17.6.16. Please note that the basis for the count of establishments and all other associated data concepts is based on self -reporting for the Economic Census, while there is some reliance on administrative records for Count y Business patterns. Thus these two data sources may report different values for the same data concept in the same year. For example, the Census Bureau notes that: “some large companies report different activities at the same location as separate profit centers. Th e County Business Patterns program treats each profit center as a separate establishment. The 2002 Economic Census may combine the profit centers into one establishment. This results in establishment c ount differences.” Thus, data for the number of establishments, employment per establishment, and payroll in Table 17.6.4 do not necessarily match those in Table 17.6.13 for 2002. Similar comparability issues arise in other tables where Economic Census and County Bu siness Patterns data overlap.

17-32Table 17.6.1 Distributor Enterprise Statis tics for Hot-Humid Region (2002) Region Number of Establishments* Total Sales

($1,000) Sales per Establishment

($1,000) Total Employment Average Employment

per Establishment

Hot-Humid

Region 1,608 8,727,826 5,428 17,284 10.7

Border States 916 6,528,439 7,127 11,762 12.8

Texas 472 3,503,698 7,423 5,144 10.9

Oklahoma 79 N/A N/A N/A N/A

Arkansas 61 821,723 13,471 610 10.0

Tennessee 152 1,422,277 9,357 4,042 26.6

North Carolina 231 780,741 3,380 1,966 8.5

* Because Alabama, Georgia and Oklahoma are incomplete data sets, they have been excluded from the total count of establishments. SOURCE: 2002 Economic Census

Table 17.6.2 Distributor Enterprise Statis tics for Hot-Dry Region (2002)

Region Number of Establishments Total Sales

($1,000) Sales per Establishment

($1,000) Total Employment Average Employment

per Establishment

Hot-Dry region 556 2,415,481 4,344 5,502 9.9

Border States 556 2,415,481 4,344 5,502 9.9

Arizona 94 475,254 5,056 1,168 12.4

California 391 1,707,447 4,367 3,777 9.7

Nevada 46 172,035 3,740 430 9.3

New Mexico 25 60,745 2,430 127 5.1

SOURCE: 2002 Economic Census

17-33Table 17.6.3 Distributor Enterprise Statisti cs for Rest of Country (2002) Region Number of Establishments* Total Sales

($1,000) Sales per Establishment

($1,000) Total Employment Average Employment

per Establishment

Rest of Country 2,480 9,669,627 3,899 24,504 9.9

Border States 615 2,807,946 4,566 6,362 10.3

Colorado 75 466,041 6,214 804 10.7

Idaho 30 63,920 2,131 180 6.0

Kansas 47 163,282 3,474 541 11.5

Kentucky 87 364,016 4,184 1,045 12.0

Missouri 122 709,542 5,816 1,407 11.5

Oregon 50 354,704 7,094 562 11.2

Utah 48 170,744 3,557 492 10.3

Virginia 156 515,697 3,306 1,331 8.5

* Because Iowa, Massachusetts, New Jersey, New Hampshire, North Dakota, and Rhode Island are incomplete data sets, they have been excluded from the total count of establishments. SOURCE: 2002 Economic Census

17-34Table 17.6.4 Establishments, Employment, and Payroll Trends in Hot-Humid Region Region Number of Establishments* Employment per Establishment Payroll per Establishment

($1,000)

2002 2007 2002 2007 2002 2007

Hot-Humid Region 2,057 2,017 11 10 461 502

Border States 1,007 1,032 13 10 570 552

Texas 532 498 12 12 550 674

Oklahoma 94 77 7 6 277 266

Arkansas 55 78 N/A 7 N/A 307

Tennessee 145 166 27 11 1,177 575

North Carolina 236 213 9 8 361 443

* Because Arkansas is an incomplete data set, it has been excluded from the total count of establishments

Table 17.6.5 Establishments, Employment, and P ayroll Trends in Hot-Dry Region Region Number of Establishments* Employment per Establishment Payroll per Establishment

($1,000)

2002 2007 2002 2007 2002 2007

Hot-Dry region 544 545 10.1 11.9 508 636

Border States 544 545 10.1 11.9 508 636

Arizona 88 93 13.2 12.8 603 701

California 415 387 9.5 10.9 493 608

Nevada 41 43 10.1 21.8 463 835

New Mexico 24 22 N/A 6.7 N/A 452

* Because New Mexico is an incomplete data set, it has been excluded from the total count of establishments

17-35Table 17.6.6 Establishments, Employment, and P ayroll Trends in Rest of Country

Region Number of Establishments* Employment per Establishment Payroll per Establishment

($1,000)

2002 2007 2002 2007 2002 2007

Rest of Country 2857 2851 10.1 10.2 499 574

Border States 657 606 10.1 10.8 470 577

Colorado 83 70 10.9 10.7 537 614

Idaho 31 24 6.6 8.8 237 164

Kansas 56 56 10.8 12.0 508 434

Kentucky 110 86 11.5 12.8 470 659

Missouri 121 129 11.1 10.2 603 616

Oregon 56 47 11.3 14.3 526 715

Utah 42 48 9.5 11.9 439 573

Virginia 158 146 8.1 8.7 352 432

*Because Iowa, Massachusetts, New Jersey, New Hampshire, North Dakota, and Rhode Island are incomplete data sets, they have been excluded from the total count of establishments.

Cost structure and profitability for distributors vary among the regions as shown in Table 17.6.7 through Table 17.6.12 are derived from 2008 HARDI data. Variation also occurs within the regions among subareas, e.g. border stat es (2002 Census), as illustrated in Table 17.6.13 through Table 17.6.15.

17-36Table 17.6.7 Income Statement Items, Typical CACHP Distributors, Hot–Humid Region

Income Statement

Net Sales $21,818,352

Cost of Goods Sold $16,094,671

Gross Margin $5,723,681

Operating Expenses $5,343,678

Operating Profit $380,003

Other Income/Expenses $109,092

Profit Before Taxes $378,185

Profit as a % of Sales 1.7%

SOURCE : HARDI Data

Table 17.6.8 Balance Sheet, Typical CACHP Distributors, Hot-Humid Region

Assets Liabilities

Cash $130,254 Accounts Payable $1,670,615

Accounts Receivable $2,423,599 Notes Payable $1,036,908

Inventory $4,854,516 Othe r Current Li abilities $633,707

Other $162,451 Total Current Liabilities $3,341,230

Total $8,781,157 Long- Term Liab ilities $717,860

Total Liabilities $4,059,090

Net Worth $4,722,067

Profit as a % of Net Worth 8.0%

SOURCE : HARDI Data

17-37Table 17.6.9 Income Statement Items, Typica l CACHP Distributors, Hot–Dry Region

Income Statement

Net Sales $16,811,857

Cost of Goods Sold $12,085,323

Gross Margin $4,726,533

Operating Expenses $4,309,599

Operating Profit $466,529

Other Income/Expenses $109,757

Profit Before Taxes $416,093

Profit as a % of Sales 2.5%

SOURCE : HARDI Data

Table 17.6.10 Balance Sheet, Typical CACHP Di stributors, Hot-Dry Region

Assets Liabilities

Cash $219,485 Accounts Payable $835,161

Accounts Receivable $1,666,602 Notes Payable $1,225,771

Inventory $3,731,253 Othe r Current Li abilities $308,768

Other $182,285 Total Current Liabilities $2,369,699

Total $7,440,186 Long- Term Liab ilities $370,149

Total Liabilities $2,739,849

Net Worth $4,700,338

Profit as a % of Net Worth 8.9%

SOURCE : HARDI Data

17-38Table 17.6.11 Income Statement Items, Typical CACHP Distributors, Rest of Country

Income Statement

Net Sales $28,362,901

Cost of Goods Sold $20,506,377

Gross Margin $7,856,524

Operating Expenses $7,005,637

Operating Profit $703,400

Other Income/Expenses $198,540

Profit Before Taxes $650,726

Profit as a % of Sales 2.29%

SOURCE : HARDI Data

Table 17.6.12 Balance Sheet, Typical CACHP Di stributors, Rest of Country Assets Liabilities

Cash $208,790 Accounts Payable $1,391,081

Accounts Receivable $2,913,118 Notes Payable $1,153,316

Inventory $5,488,196 Othe r Current Li abilities $725,794

Other $208,790 Total Current Liabilities $3,121,908

Total $9,942,383 Long-Te rm Liabilitie s $60,648,537

Total Liabilities $3,728,394

Net Worth $6,213,989

Profit as a % of Net Worth 10.472%

SOURCE: HARDI Data

17-39Table 17.6.13 Revenue and Cost Items, Typical CACHP Distributors, Hot-Humid Region and Border States Region Average Sales

per Establishment

($1,000) Average Payroll Costs

($1,000) Average Operating Costs

($1,000) Average Inventory

($1,000)

Hot-Humid Region 5,428 453 822 545

Border States 7,127 553 1,035 664

Texas 7,423 496 982 584

Oklahoma N/A N/A N/A N/A

Arkansas 13,471 396 663 300

Tennessee 9,357 1,112 2,077 1,528

North Carolina 3,380 342 557 352

*Because Alabama, Georgia and Oklahoma are incomplete data sets, they have been excluded from the total count of establishments. SOURCE: Economic Census Data

Table 17.6.14 Revenue and Cost Items, Typical CACHP Distributors, Hot-Dry Region and Border States Region Average Sales per Establishment

($1,000) Average Payroll Costs

($1,000) Average Operating Costs

($1,000) Average Inventory

($1,000)

Hot-Dry region 4,344 483 810 520

Border States 4,344 483 810 520

Arizona 5,056 548 875 774

California 4,367 490 837 478

Nevada 3,740 409 687 467

New Mexico 2,430 252 365 307

SOURCE: Economic Census Data

17-40Table 17.6.15 Revenue and Cost Items, Typical CACHP Distributors, Rest of Country Region and Border States Region Average Sales per Establishment

($1,000) Average Payroll Costs

($1,000) Average Operating Costs

($1,000) Average Inventory

($1,000)

Rest of Country 3,899 450 755 437

Border States 4,566 456 781 460

Colorado 6,214 514 1,003 477

Idaho 2,131 225 428 259

Kansas 3,474 537 801 344

Kentucky 4,184 435 721 365

Missouri 5,816 614 1,018 640

Oregon 7,094 478 854 664

Utah 3,557 448 675 416

Virginia 3,306 330 591 437

* Because District of Columbia, Iowa, Massachusetts, Minnesota, New Jersey, New Hampshire, North Dakota, and Rhode Island are incomplete data sets, they have been excluded from the total count of establishments. SOURCE: Economic Census Data

17-41Table 17.6.16 Distributor Financial Data by HARDI Region for 2009

South South North Eastern Mid-Atlantic Eastern Great Lakes Central Western Western

Number of Firms Reporting 8 16 10 19 27 8 6

Typical Sales Volume $19,851,509 $42,068,508 $24,077,238 $20,107,850 $28,362,901 $17,946,312 $16,762,766

Sales Change (2007-2008) -0.60% -0.10% -2.60% 1.20% 0.50% 0.20% -3.70%

Strategic Profit Model Ratios

Profit Margin 1.00% 1.60% 1.90% 2.20% 3.10% 1.10% 3.10%

Asset Turnover 2.9 3 2.5 2.5 2.4 2.6 2.2

Return on Assets 2.90% 4.80% 4.70% 5.50% 7.40% 2.90% 6.80%

Financial Leverage 2.3 2.2 1.9 2.1 1.6 1.9 1.5

Return on Net Worth 6.70% 10.60% 8.00% 11.50% 11.80% 5.50% 10.20%

Income Statement

Net Sales 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%

Cost of Goods Sold 70.3 73.9 73.9 72.2 72.3 74.3 70.7

Gross Margin 29.7 26.1 26.1 27.8 27.7 25.7 29.3

Payroll Expenses

Executive Salaries & Bonuses 2.1 1.5 2.1 2.1 2.1 2.2 1.8

Branch Manager Salaries &
Bonuses 1.3 1.1 1.2 1.3 1.3 1.8 1.4

Sales Executive Salaries & Commissions 0.8 0.5 0 0.3 0.3 0.9 0.5

Outside Sales Salaries & Commissions 2.7 2.1 2.3 2.3 2.3 1.8 1.7

Inside/Counter Sales Wages 2.1 2.5 2.9 2.8 2.6 2.2 2.9

Purchasing Salaries/Wages 0.5 0.4 0.5 0.4 0.5 0.5 0.6

Credit Salaries/Wages 0.3 0.2 0.1 0.1 0.2 0.2 0.2

IT Salaries/Wages 0 0.2 0 0.1 0.2 0.1 0.2

Warehouse Salaries/Wages 2.3 1.4 2.1 1.6 1.3 1.5 1.7

Accounting Salaries/Wages 0.6 0.4 0.6 0.4 0.6 0.4 0.7

Delivery Salaries/Wages 1.1 1.2 0.7 0.7 0.8 0.8 1

All Other Salaries/Wages &
Bonuses 0.8 0.9 0.6 0.8 0.6 0.7 0.5

17-42Total Salaries, Wages,
Bonuses 14.6 12.6 13.1 12.9 12.8 13.1 13.2

Payroll Taxes (FICA, unemp., workers' comp.) 1.5 1 1.2 1.1 1.1 1 1.1

Group Insurance (medical, hospitalization, etc.) 1.2 1.5 1.1 1.2 1.1 1 1.2

Benefit Plans (profit sharing, pension, etc.) 1 0.4 0.3 0.3 0.7 0.3 0.5

Total Payroll Expenses 18.3 15.3 15.7 15.5 15.7 15.4 16

Occupancy Expenses

Utilities (heat, light, power, water) 0.5 0.4 0.4 0.5 0.4 0.4 0.4

Telephone 0.3 0.3 0.4 0.4 0.3 0.3 0.5

Building Repairs & Maintenance 0.3 0.2 0.2 0.4 0.2 0.2 0.2

Rent or Ownership I Real
Estate 2.6 2.6 2.3 2.6 2.6 2.4 3.1

Total Occupancy Expenses 3.7 3.5 3.3 3.9 3.5 3.3 4.2

Other Operating Expenses

Sales Expenses 1.1 0.4 0.5 1 1 0.5 1

Insurance 0.1 0.2 0.3 0.2 0.2 0.2 0.2

Depreciation 0.5 0.3 0.2 0.4 0.3 0.3 0.3

Vehicle Expenses 1.9 1.3 1.2 1.3 1.2 1.4 1.3

Personal Property Taxes/Licenses 0.1 0.1 0.1 0.1 0.1 0.4 0.2

Collection Expenses 0.2 0.2 0.2 0.3 0.2 0.3 0.6

Bad Debit Losses 0.8 0.5 0.5 0.3 0.4 0.5 0.6

Data Processing 0.1 0.1 0.2 0.3 0.1 0.2 0.3

Employee Training 0.1 0 0.1 0.1 0 0 0

All Other Operating Expenses 1.5 2.4 2.1 1.7 2 1.8 1.2

Total Other Operating Expenses 6.4 5.5 5.4 5.7 5.5 5.6 5.7

Total Operating Expenses 28.4 24.3 24.4 25.1 24.7 24.3 25.9

Operating Profit 1.3 1.8 1.7 2.7 3 1.4 3.4

Other Income 0.7 0.4 0.6 0.85 0.7 0.3 0.6

17-43Interest Expense 0.7 0.6 0.4 0.9 0.6 0.6 0.9

Other Non-operating Expenses 0 0 0 0.41 0 0 0

Profit Before Taxes & Discretionary Bonuses 1.3 1.6 1.9 2.2 3.1 1.1 3.1

Owners' & Officers' Discretionary Bonus 0.3 0 0 0 0 0 0

Profit Before Taxes 1.00% 1.60% 1.90% 2.20% 3.10% 1.10% 3.10%

Source: HARDI Profit Report 2009

17-44Table 17.6.17 Geographic Area Series, Hardware, Plumbing, and Heating Equipment Merchant Wholesalers

State Number of establishments Sales ($1,000) Annual payroll ($1,000) Operating

expenses ($1,000) Beginning of Year Inventory

($1,000)

Alabama 306 1,223,718 126,231 219,926 163,992

Alaska 31 184,756 18,121 30,881 17,215

Arizona 344 1,555,529 144,201 262,373 207,328

Arkansas 169 1,577,287 68,528 112,045 91,665

California 2,093 9,770,865 1,035,007 1,859,068 1,255,661

Colorado 322 1,593,598 158,231 279,359 163,671

Connecticut 241 1,238,563 159,154 279,517 109,123

Florida 1,280 3,918,873 421,244 760,139 578,251

Hawaii 73 206,004 23,882 44,417 24,540

Idaho 102 219,215 23,060 45,551 29,404

Illinois 938 5,750,240 546,503 982,350 711,919

Indiana 414 3,396,118 208,166 357,442 230,198

Iowa 183 559,770 72,145 126,079 90,495

Kentucky 211 738,568 81,571 141,007 72,962

Louisiana 255 620,835 77,327 133,347 71,160

Maine 78 280,267 33,846 50,711 36,874

Maryland 343 1,440,771 175,311 300,946 157,414

Massachusetts 418 1,626,690 230,519 372,701 205,585

Michigan 624 2,455,784 307,000 554,638 346,760

Minnesota 353 1,730,533 188,264 320,040 206,794

Mississippi 142 290,404 32,238 53,345 33,450

Missouri 373 1,904,740 190,634 342,332 204,189

17-45Montana 60 188,933 22,151 37,160 25,178

Nebraska 135 476,152 55,311 91,961 62,781

Nevada 143 581,330 63,655 112,143 76,965

New Mexico 97 222,570 24,992 40,809 26,685

New York 1,150 3,890,419 477,194 827,149 490,905

North Carolina 653 2,529,035 275,455 519,139 339,490

North Dakota 51 246,502 19,359 33,087 29,214

Ohio 797 3,506,149 411,644 772,598 470,068

Oklahoma 259 1,811,538 114,841 163,518 89,065

Oregon 232 1,024,631 95,172 179,566 103,318

Pennsylvania 830 3,013,246 377,209 662,680 387,216

Rhode Island 65 553,057 39,277 119,343 71,139

South Carolina 275 1,469,195 105,672 218,044 150,214

South Dakota 62 187,376 22,113 37,867 31,395

Tennessee 379 2,315,179 275,360 482,817 285,502

Texas 1,470 6,923,744 627,464 1,151,278 729,352

Utah 172 659,361 75,092 122,588 56,829

Vermont 43 145,259 15,814 31,678 22,770

Virginia 444 1,696,293 173,599 334,708 184,142

Washington 443 1,630,891 181,491 306,265 199,740

West Virginia 90 216,126 23,579 42,842 30,321

Wisconsin 349 2,175,191 199,934 380,668 233,187

Wyoming 23 34,617 3,355 6,475 3,018

Source: 2002 U.S. Economic Census, Geographic Area Series, Hardware, Plumbing & Heating Equipment & Supply Merchant Wholesalers

17-4617.7 ADDITIONAL CONTRACTOR DATA

The analysis of general and mechanical c ontractors relies on the 2002 Economic Census and 2007 County Business Patterns as sources of in formation. As discussed previously, general contractors and mechanical contr actors have different roles in the distribution channels for CAC and CHP equipment. Data is reported separately for general contractors and for mechanical contractors so that the economic impact of regional efficiency standards and their enforcement can be better judged for each contractor type. The following information can be obtained from these sources:

• Total and average sales, total and averag e employment (2002 Census of Business and County Business Patterns).

No industry-published equivalent of th e HARDI data appears to exist for dealers/contractors/installers . These values are reported for the 2002 Economic Census and 2007 County Business Patterns for 2007 for the Nation, each region (Hot-Humid, Hot-dry, and Rest of Country), and for each of the 17 states that lie on the border of one region with another.

Data from the 2002 Economic Census incl udes all plumbing, heating, and airconditioning contractors. The total industry accounted for $118,740,885,000 of business in 2002, of which $49,425,445,000 was attributed to the HVAC contractor subsector. 36 Data from the entire plumbing, heating, a nd air-conditioning contractors industry was used, as the 2002 Economic Census provided stat e-level data for this industry but not for the HVAC contractor subsector. The 2002 Econo mic Census state-leve l data for all of the construction industry (NAICS 2-digit level) shows, among other things, which states’ construction industry sales are in other st ates as compared with the home state (construction in Kentucky by Oh io construction establishments). This data is used to indicate where cross-border sales are importa nt for the three CAC analysis regions.

• Number of small businesses (SBA definition and size distribution).

The SBA definition of small business de fines $33.5 million in annual sales as the maximum for building contractors (both residential and commercial, which together are the general contractors of interest fo r CAC and CHP rulema king) and $14 million in annual sales as the maximum for plumbing, heating, and A/C contractors. Among general contractors’ residen tial construction establishments counted nationally by the Census Bureau in 2002, only 3,648 establishmen ts out of the total of 171,652 (2.1%) had more than $10 million in sales, one-third of th e small business cutoff value. Residential builders are overwhelmingly small businesses. Among commercial builders, the figures are 4,415 out of 37,208 (11.9%) with sales mo re than $10 million. Clearly, commercial contractors also are predominantly small businesses, although not by as large a margin as residential construction firms. Mechanical contractors have a lowe r small business sales cutoff value, but nationally in 2002, only 1,832 out 87,501 mechanical contractors (2.1%) had sales of at least $10 million. As with general contractors, it is clear from the national-level data that the mechanical contractor sector is overwhelming composed of

17-47small businesses. Regional analysis of th is question is not possible, but it is also unnecessary, as DOE expects the same results.

• Cost structure and profitability (2002 Census).

The 2002 Economic Census provide s some detail on the cost structure of construction firms, although in less detail than that provided by the HARDI data for wholesale distributors. Air Conditioning C ontractors of America 2005 publication Financial Analysis for the HVACR Contracting Industry is another source for financial data for contractors that is less detaile d than the 2002 Economic Census. The Economic Census data includes sales (value of business, value of cons truction work, net value of construction work), employment, payroll, costs of materials, costs of subcontractors, total rental costs, capital expenditures excluding land, and total value of assets. This data allows a rough computation of the profitability of construction firms (general and mechanical contractors) at the regional level, which can be compared with the more detailed industry data at the national level (see U.S. Cens us Bureau, 2002: Plumbing, Heating, and Air-Conditioning Contr actors: 2002. Report EC02-231-238220, Table 4, Detailed Statistics for Esta blishments: 2002 and Commercia l and Institutional Building Construction: 2002. Repor t EC02-231-236220, Table 4, De tailed Statistics for Establishments: 2002). Geographic Series da ta on NAICS subsectors do not include costs of selected purchased services and do not include deprecia tion. Profits cannot be computed directly.

Selected basic supporting data is shown inTable 17.6.17. Selected data for General Contractors is shown in Table 17.7.4.

17-48Table 17.7.1 Revenue and Cost Items, Typica l CACHP Mechanical Contractors, HotHumid Region Region Average Value of Construction

Work per Establishment

($1,000) Average Payroll Costs

($1,000) Cost of materials, components and Fuels Operating Costs

($1,000) Cost of Work Subcontracted Out

($1,000) Rental Costs ($) End of
Year Gross Value of
Assets

($1,000)

Hot-Humid Region 1212 355 437 121 20 171

Border States 1253 373 452 122 20 174

Texas 1426 434 511 143 22 182

Oklahoma 783 222 295 67 12 117

Arkansas 765 201 292 63 13 137

Tennessee 1674 468 618 147 27 231

North

Carolina 1085 334 379 114 19 166

SOURCE: Economic Census Data

17-49Table 17.7.2 Revenue and Cost Items, Typical CACHP Mechanical Contractors, Hot-Dry Region Region Average Value of Construction

Work per Establishment

($1,000) Average Payroll Costs

($1,000) Cost of materials, components and Fuels Operating Costs

($1,000) Cost of Work Subcontracted Out

($1,000) Rental Costs ($) End of
Year Gross Value of
Assets

($1,000)

Hot-Dry region 1614 496 540 146 28 190

Border States 1614 496 540 146 28 190

Arizona 1297 387 514 94 23 180

California 1698 529 553 161 30 197

Nevada 2195 653 705 157 34 184

New Mexico 908 247 320 85 14 135

SOURCE: Economic Census Data

17-50Table 17.7.3 Revenue and Cost Items, Typical CACH P Mechanical Contractors, Rest of Country Region Average Value of Construction

Work per Establishment

($1,000) Average Payroll Costs

($1,000) Cost of materials, components and Fuels Operating Costs

($1,000) Cost of Work Subcontracted Out

($1,000) Rental Costs ($) End of
Year Gross Value of
Assets

($1,000)

Rest of Country 1367 421 439 152 22 168

Border States 1231 386 430 122 19 159

Colorado 1168 374 408 117 20 138

Idaho 920 287 356 80 15 116

Kansas 1269 380 447 160 18 163

Kentucky 1113 335 385 100 19 175

Missouri 1398 442 468 152 18 174

Oregon 1397 461 491 129 22 152

Utah 1133 304 397 128 19 143

Virginia 1192 393 422 100 19 157

SOURCE: Economic Census Data

17-51Table 17.7.4 Geographic Area Series, Plumbing and HVAC Constructors

State* Number of Establishments Value of Business

Done ($1,000) Cost of Materials ($1,000) Construction Work Subcontracted

Out ($1,000) Total Payroll ($1,000)

Alabama 1,425 1,517,258 547,075 151,240 430,252

Arizona 1,510 1,967,940 776,733 141,885 584,412

Arkansas 1,045 809,435 305,198 65,491 209,991

California 7,272 12,409,267 4,018,408 1,172,183 3,845,532

Colorado 2,015 2,382,111 821,432 235,012 753,883

Connecticut 1,321 1,593,622 505,340 156,607 466,149

Delaware 306 464,881 150,096 42,001 156,056

Florida 5,069 6,314,034 2,270,555 616,097 1,828,108

Georgia 2,534 3,459,031 1,226,368 380,819 944,212

Hawaii 280 363,486 129,870 36,053 96,844

Idaho 594 558,889 211,341 47,466 170,635

Illinois 3,848 6,135,124 1,770,254 605,868 2,054,379

Indiana 1,867 2,993,560 869,816 418,904 991,316

Iowa 1,066 1,216,575 428,842 133,934 371,492

Kansas 966 1,236,292 431,331 155,011 367,519

Kentucky 1,219 1,363,485 469,639 121,960 408,927

Louisiana 1,469 1,448,482 497,169 174,283 419,948

Maine 458 399,172 138,587 36,149 114,586

Maryland 2,024 3,925,032 1,251,986 583,237 1,130,739

Massachusetts 2,520 3,545,394 1,038,151 503,155 1,007,916

Michigan 3,051 4,369,139 1,338,229 492,957 1,319,863

Minnesota 1,635 2,893,239 958,849 280,556 838,879

Mississippi 655 757,148 283,993 70,985 184,163

17-52Missouri 1,816 2,559,173 849,770 276,621 802,027

Montana 432 362,598 135,009 44,987 92,496

Nebraska 683 825,160 321,124 90,582 236,196

Nevada 498 1,098,147 350,851 78,259 325,164

New Hampshire 531 540,005 179,259 52,209 179,570

New Jersey 3,551 4,229,237 1,230,617 466,668 1,321,095

New Mexico 599 546,210 191,757 51,116 148,012

New York 5,750 7,601,402 2,335,220 949,038 2,308,194

North Carolina 2,978 3,258,502 1,127,518 339,388 993,337

North Dakota 272 293,910 105,405 34,971 87,633

Ohio 3,514 4,646,807 1,470,907 502,061 1,442,425

Oklahoma 1,158 913,670 341,921 77,207 256,922

Oregon 1,031 1,459,251 506,559 132,523 475,266

Pennsylvania 3,653 5,971,127 1,766,004 639,074 1,639,278

Rhode Island 397 491,915 171,994 60,217 136,580

South Carolina 1,472 1,401,320 518,386 111,394 461,409

South Dakota 337 337,590 141,297 22,754 83,704

Tennessee 1,370 2,301,759 846,426 201,748 641,092

Texas 5,653 8,131,851 2,889,320 807,501 2,451,016

Utah 892 1,014,532 353,958 113,775 270,911

Vermont 282 210,388 77,251 19,987 62,090

Virginia 2,547 3,068,896 1,074,309 254,085 1,000,173

Washington 1,602 2,378,599 773,211 222,282 772,633

Wisconsin 1,839 2,643,604 941,806 193,399 855,624

Source: 2002 U.S. Economic Census, Geographic Area Series, NAICS: 2382 Plumbing and HVAC Constructors by State *Note: AK, DC, WV, WY are left out in this analysis because of limited data provided from Census

.

17-53Table 17.7.5 Enterprise Statistics on Mechanical Contractors in the Hot-Humid Region Region Number of Establishments Total Value of Construction Work Done ($1000) Sales per Establishment

($1,000) Total Employment Average Employment

per Establishment

Hot-Humid Region 25,108 30,423,332 1,212 276,994 11.0

Border States 12,204 15,291,654 1,253 139,797 11.5

Texas 5,653 8,061,607 1,426 72,778 12.9

Oklahoma 1,158 906,621 783 8,403 7.3

Arkansas 1,045 799,157 765 7,757 7.4

Tennessee 1,370 2,292,875 1,674 19,547 14.3

North

Carolina 2,978 3,231,394 1,085 31,312 10.5

SOURCE: 2002 Economic Census Data

Table 17.7.6 Enterprise Statistics on Mechanical Contractors in the Hot-Dry Region Region Number of Establishments Total Value of Construction Work Done ($1000) Sales per Establishment

($1,000) Total Employment Average Employment

per Establishment

Hot-Humid Region 25,108 30,423,332 1,212 276,994 11.0

Border States 12,204 15,291,654 1,253 139,797 11.5

Texas 5,653 8,061,607 1,426 72,778 12.9

Oklahoma 1,158 906,621 783 8,403 7.3

Arkansas 1,045 799,157 765 7,757 7.4

Tennessee 1,370 2,292,875 1,674 19,547 14.3

North

Carolina 2,978 3,231,394 1,085 31,312 10.5

SOURCE: 2002 Economic Census Data

17-54Table 17.7.7 Enterprise Statistics on Mechanical Contractors in the Rest of Country Region Number of Establishments Total Value of Construction Work Done ($1000) Sales per Establishment

($1,000) Total Employment Average Employment

per Establishment

Rest of Country 52,019 71,109,956 1,367 546,642 10.5

Border States 9,065 11,155,228 1,231 97,279 10.7

Colorado 2,015 2,354,183 1,168 20,146 10.0

Idaho 594 546,349 920 5,313 8.9

Kansas 966 1,225,986 1,269 10,036 10.4

Kentucky 1,219 1,357,063 1,113 12,557 10.3

Missouri 1,816 2,538,706 1,398 19,847 10.9

Oregon 1,031 1,440,390 1,397 11,598 11.2

Utah 892 1,010,317 1,133 8,374 9.4

Virginia 2,547 3,036,417 1,192 29,554 11.6

SOURCE: 2002 Economic Census Data

17-55Table 17.7.8 Mechanical Contractor Establishments, Employment, and Payroll Trends, Hot-Humid Region Region Number of Establishments Employment per Establishment Payroll per Establishment

($1,000)

2002 2007 2002 2007 2002 2007

Hot-Humid Region 26,017 29,671 10 11 333 425

Border States 12,922 13,981 11 11 349 449

Texas 5,866 6,384 12 12 400 510

Oklahoma 1,218 1,332 7 7 208 273

Arkansas 903 996 8 9 231 310

Tennessee 1,523 1,679 13 12 406 473

North Carolina 3,412 3,590 10 11 317 435

Table 17.7.9 Mechanical Contractor Establishments, Employment, and Payroll Trends, Hot-Dry Region Region Number of Establishments Employment per Establishment Payroll per Establishment

($1,000)

2002 2007 2002 2007 2002 2007

Hot-Dry region 10,406 12,495 11.1 12.1 463.5 578.0

Border States 10,406 12,495 11.1 12.1 463.5 578.0

Arizona 1,610 2,062 11.0 12.7 363.2 489.1

California 7,641 9,001 11.1 11.6 490.9 584.4

Nevada 524 720 15.7 19.2 637.2 979.0

New Mexico 631 712 7.7 9.1 243.5 349.2

17-56Table 17.7.10 Mechanical Contractor Establishments, Employment, and Payroll Trends, Rest of Country Region Region Number of Establishments Employment per Establishment Payroll per Establishment

($1,000)

2002 2007 2002 2007 2002 2007

Rest of Country 53,918 58,640 9.2 9.2 395.6 465.9

Border States 11,470 12,923 9.3 11.9 392.9 486.3

Colorado 2,064 2,339 9.1 8.4 362.1 388.2

Idaho 606 831 7.5 8.0 245.3 286.0

Kansas 1,006 1,049 8.9 10.3 352.7 421.0

Kentucky 1,288 1,278 9.5 9.5 312.0 380.2

Missouri 1,884 2,014 9.7 9.4 428.0 476.3

Oregon 1,134 1,346 8.7 9.5 372.9 453.2

Utah 936 1,209 7.9 8.4 276.9 348.5

Virginia 2,552 2,857 10.6 11.3 375.1 490.3

Cost structure and profitability vary among s ubareas (i.e., border states) for mechanical contractors. Selected data required to generate net operating profit estimates is not available on subsectors of construction at the regional le vel (specifically, Total Purchased Services, Depreciation), although the da ta is available nationally.

17.8 ADDITIONAL GENERAL CONTRACTORS AND HOMEBUILDERS DATA

Statistical tables follow for Ge neral Contractors in each region. Selected data for General Contractors are shown in Table 17.7.4.

17-57Table 17.8.1 Enterprise Statistics on General Contractors in the Hot-Humid Region Region Number of Establishments* Total Value of Construction Work Done

($1,000) Sales per Establishment

($1,000) Total Employment Average Employment

per Establishment

HotHumid Region 58,480 168,947,696 2,889 484,826 8.3

Border States 32,894 96,197,405 2,924 277,605 8.4

Texas 9,625 39,038,019 4,056 95,829 10.0

Oklahoma 1,942 1,454,942 749 12,445 6.4

Arkansas 10,716 36,945,606 3,448 90,624 8.5

Tennessee 2,982 3,173,248 1,064 27,440 9.2

North Carolina 7,629 15,585,590 2,043 51,267 6.7

* Because Mississippi is an incomplete data set, the state has been excluded from the total count of establishments SOURCE: 2002 Economic Census

17-58Table 17.8.2 Enterprise Statistics on General Contractor s in the Hot-Dry Region Region Number of Establishments Total Value of Construction Work Done

($1,000) Sales per Establishment

($1,000) Total Employment Average Employment

per Establishment

Hot-Dry region 28,405 84,436,053 2,973 255,534 9.0

Border States 28,405 84,436,053 2,973 255,534 9.0

Arizona 3,574 13,737,839 3,844 33,276 9.3

California 21,671 63,504,624 2,930 193,975 9.0

Nevada 1,400 4,671,330 3,337 17,627 12.6

New Mexico 1,760 2,522,260 1,433 10,656 6.1

SOURCE: 2002 Economic Census

17-59Table 17.8.3 Enterprise Statistics on General Contractors in the Rest of Country Region Number of Establishments* Total Value of Construction Work Done ($1000) Sales per Establishment

($1,000) Total Employment Average Employment

per Establishment

Rest of Country 127,558 221,929,611 1,740 883,611 6.9

Border States 27,031 45,794,848 1,694 197,421 7.3

Colorado 5,223 8,969,090 1,717 37,926 7.3

Idaho 1,638 N/A N/A 8,412 5.1

Kansas 2,185 3,792,200 1,736 13,467 6.2

Kentucky 2,336 4,985,602 2,134 17,810 7.6

Missouri 4,714 4,060,799 861 39,744 8.4

Oregon 4,098 5,980,885 1,459 23,426 5.7

Utah 2,200 2,251,069 1,023 15,178 6.9

Virginia 6,275 15,755,203 2,511 49,870 7.9

* Because Idaho and the District of Columbia are incomplete data sets, they have been excluded from the total count of establishments used in other calculations. SOURCE: 2002 Economic Census

17-60Table 17.8.4 General Contractor Establishments , Employment, and Payroll Trends, HotHumid Region Region Number of Establishments Employment per Establishment Payroll per Establishment

2002 2007 2002 2007 2002 2007

Hot-Humid Region 50,365 61,077 7.7 7.2 297 344

Border States 23,783 27,140 7.6 7.4 296 359

Texas 9,686 10,914 9.1 8.9 402 474

Oklahoma 1,829 2,075 6.3 5.8 188 221

Arkansas 1,488 1,740 6.9 6.2 203 229

Tennessee 3,124 3,524 7.4 7.9 275 374

North Carolina 7,656 8,887 6.2 6.0 213 270

Table 17.8.5 General Contractor Establishments , Employment, and Payroll Trends, HotDry Region

Region Number of Establishments Employment per Establishment Payroll per Establishment

($1,000)

2002 2007 2002 2007 2002 2007

Hot-Dry region 28,374 34,143 7.9 8.4 343.7 443.8

Border States 28,374 34,143 7.9 8.4 343.7 443.8

Arizona 3,752 4,729 8.3 9.3 337.7 476.2

California 21,564 25,624 7.7 8.1 343.1 435.1

Nevada 1,350 1,647 12.0 12.8 571.5 757.7

New Mexico 1,708 2,143 6.3 6.4 183.9 234.8

17-61Table 17.8.6 General Contractor Establishments, Employment, and Payr oll Trends, Rest of Country

Region Number of Establishments Employment per Establishment Payroll per Establishment

($1,000)

2002 2007 2002 2007 2002 2007

Rest of Country 131,205 145,679 6.0 5.8 249.9 288.9

Border States 29,265 34,360 6.1 5.8 240.3 283.6

Colorado 5,121 5,598 6.4 6.2 290.3 327.5

Idaho 1,759 2,661 2.6 4.8 75.1 164.7

Kansas 2,153 2,288 6.4 5.7 218.1 232.4

Kentucky 2,348 2,421 7.4 7.4 242.6 287.2

Missouri 4,452 4,752 7.1 7.8 283.0 369.0

Oregon 4,186 5,174 4.3 4.8 157.9 206.3

Utah 2,633 3,224 5.4 6.2 183.7 247.2

Virginia 6,613 8,242 7.0 6.4 271.1 308.0

Cost structure and profitability varies among subareas (e.g. border states) for General Contractors. Selected data required to generate net operating profit estimates are not available on subsectors of construction at the regional level (Total Purchased Servic es, Depreciation), but they are available nationally.

17-62Table 17.8.7 Revenue and Cost Items, Typical Ge neral Contractors, Hot-Humid Region Region Average Value of Construction Work per Establishment ($1,000)* Average Payroll Costs ($1000) Cost of materials, components and Fuels Operating Costs ($1,000) Cost of Work Subcontracted Out ($1,000) Rental Costs ($1,000) End of
Year Gross Value of
Assets ($1,000)

HotHumid Region 2889 306 720 1,327 19 153

Border States 2924 313 742 1,367 19 158

Texas 4056 398 951 1,750 24 167

Oklahoma 749 183 531 882 13 117

Arkansas 3448 321 762 1,512 19 174

Tennessee 1064 335 598 1,222 21 149

North Carolina 2043 216 558 859 14 137

* Because Mississippi is an incomplete data set, the state has been excluded from the total count of establishments used in other calculations. SOURCE: 2002 Economic Census

17-63Table 17.8.8 Revenue and Cost Items, Typical General Contractors, Hot-Dry Region Region Average Value of Construction Work per Establishment ($1,000) Average Payroll Costs ($1000) Cost of materials, components and Fuels Operating Costs ($1,000) Cost of Work Subcontracted Out ($1,000) Rental Costs ($1,000) End of
Year Gross Value of
Assets ($1,000)

Hot-Dry region 2973 357 473 1,429 21 120

Border States 2973 357 473 1,429 21 120

Arizona 3844 337 580 1,931 23 128

California 2930 364 465 1,417 22 122

Nevada 3337 534 493 1,350 16 121

New Mexico 1433 172 329 630 9 81

SOURCE: Economic Census

17-64Table 17.8.9 Revenue and Cost Items, Typical Ge neral Contractors, Rest of Country Region Average Value of Construction Work per Establishment ($1,000)* Average Payroll Costs ($1000) Cost of materials, components and Fuels Operating Costs ($1,000) Cost of Work Subcontracted Out ($1,000) Rental Costs ($1,000) End of
Year Gross Value of
Assets ($1,000)

Rest of Country 1740 255 447 899 15 114

Border States 1694 262 492 947 15 117

Colorado 1717 285 423 700 17 123

Idaho N/A 149 416 666 9 84

Kansas 1736 196 469 790 14 118

Kentucky 2134 245 577 945 14 149

Missouri 861 304 489 1,281 12 139

Oregon 1459 201 350 703 10 64

Utah 1023 232 576 1,057 17 112

Virginia 2511 292 592 1,080 20 121

* Because Idaho and the District of Columbia are incomplete data sets, they have been excluded from the total count of establishments used in other calculations. SOURCE: Economic Census

17-651 US Census Bureau. Electrical, Hardware, Plumbing, and Heating Equipment and Supplies: 2002.

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3 http://www.alliedair.com / (Last accessed: February 8, 2010)

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6 http://www1.eere.energy.gov/buildings/appliance_standards/residential/pdfs/fb_fr_tsd/chapter_

7 Hall, John R. “Consultants Address Inventory Is sues: Adjusting Inventory Levels to Current Conditions Is the Name of the Game.” Air Conditioning, Heating & Refrigeration News July 2007: pp. 14. Web. 04 Nov. 2009.

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13 Trimbach, Jason. “Benchmarking Time Allocati on for Warehouse Employees: Part 1: Use of Warehouse Capacity.” HVACR Distribution Business August 2007: pp. 44. Web. 04 Nov. 2009

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15 Peric’, Tom S. “A View from the Top.” HVACR Distribution Business Feb. 2006: pp. 48. Web. 04 Nov. 2009. 5.pdf pp. 5-2

8 IBID 7

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16 IBID 7

17 IBID 7

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19 “Inbound Freight: Are We Paying Close Attention?” pp. 39

20 Maynard, Michael. “Staying Ahead of the Technology Curve.” HVACR Distribution Business June 2007: pp. 17. Web. 04 Nov. 2009.

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.

22 US Census Bureau. Plumbing, Heating, and Air-Conditioning Contractors: 2002

.

23 http://phx.corporate

ir.net/External.File?item=UGFyZW50SUQ9 MzMyMTA2fENoaWxkSUQ9MzE0MzY5fFR5cG U9MQ==&t=1 pp. 55

24 US Census Bureau, Plumbing, Heating, and Air-Conditioning Contractors: 2002

.

25 http://phx.corporate

ir.net/External.File?item=UGFyZW50SUQ9 MzMyMTA2fENoaWxkSUQ9MzE0MzY5fFR5cG U9MQ==&t=1 pp. 14

26 “Sanyo HVAC Solutions is World-Class.” pp. 18.

27 “Sanyo HVAC Solutions is World-Class.” pp. 18.

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29 “Life After 13 SEER: The Sales Pr ocess, What People Want.” pp. 6

30 “Economics Challenge Contractors: Workfor ce Issues and Home Building Slowdown.” pp. 28.

31 “Staying Ahead of the Technology Curve.” pp. 17.

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34 IBID 1

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.

17-67