CHAPTER 2. ANALYTICAL FRAMEWORK

TABLE OF CONTENTS

2.1 INTRODUCTION ........................................................................................................... 2-1

2.2 MARKET AND TECHNOLOG Y ASSESSMENT ........................................................ 2-4

2.2.1 Market Assessment .......................................................................................................... 2-4

2.2.2 Technology Assessment

................................ ................................ ................................... 2-4

2.3 SCREENING ANALYSIS .............................................................................................. 2-4

2.4 ENGINEERING ANALYSIS .......................................................................................... 2-5

2.5 MARKUPS ANALYSIS ................................................................................................. 2-6

2.6 ENERGY USE ANALYSIS ............................................................................................ 2-6

2.7 LIFE

- CYCLE COST AND PAYBACK PERIOD ANALYSIS ..................................... 2-7

2.8 SHIPMENTS ANALYSIS .............................................................................................. 2-7

2.9 NATIONAL IMPACT ANAL YSIS ................................................................................ 2-9

2.10 CUSTOMER SUBGROUP AN ALYSIS ....................................................................... 2-10

2.11 MANUFACTURER IMPACT ANALYSIS

................................ .................................. 2-10

2.12 EMISSIONS ANALYSIS .............................................................................................. 2-11

2.13 MONETIZING CARBON DIOXIDE AND OTHER EMISSIONS

REDUCTIONS .............................................................................................................. 2-13

2.14 UTILITY IMPACT ANALY SIS ................................................................................... 2-14

2.15 EMPLOYMENT IMPACT AN ALYSIS ....................................................................... 2-14

2.16 REGULATORY IMPACT AN ALYSIS ....................................................................... 2-15

FIGURE

Figure 2.1.1 Flow Diagram of Analyses for the Rulemaking Process ..................................... 2-2

2-iCHAPTER 2. ANALYTICAL FRAMEWORK

2.1 INTRODUCTION

Section 6313 (a) (6)(A) (ii) of 42 United Standards Code (U.S.C. ), requires the U.S. Department of Energy (DOE) to establish energy conservation standards that are technologically feasible and economically justified and w ill result in significant energy conservation

. This chapter describes the general analytical framework that DOE uses in developing such standards, as well as aspects specific to the analysis of standards for small, large, and very large, commercial package air conditioning and heating equipment (also referred to in this notice as small, large, and very large air

- co oled commercial unitary air conditioners, CUAC, and small, large, and very large air -cooled commercial unitary heat pumps, CUHP). T he analytical

framework summarizes the methodologies, analytical tools, and relationships among the various analyses that are part of a standards rulemaking

.

Figure 2.1.1 summarizes the analytical components of the standards- setting process

. The

column labeled Approaches lists the methodologies DOE uses to perform the various steps and analyses in the process. The primary focus of the figure is the column labeled Analyses

. The

columns labeled Key I nputs and Key O utputs show how the analyses fit into the rulemaking process and how they relate to each other . Key inputs are the types of data and information that the analyses require . Some key inputs can be found in public databases; other inputs DOE

collects from interested parties or expert s having specialized knowledge. Key outputs are the analytical results that feed directly into the standards

- setting process . L ines with arrows connecting analyses show the types of information that feed from one analysis to another.

2-1Figure 2.1.1 Flow Diagram of Analyse s for the Rulemaking Process Utility Impact

Analysis

Notice of Proposed Rulemaking (NOPR)

Final Rule Approaches Key Inputs Analyses Key Outputs

Market and Technology

Assessment

Screening Analysis

Engineering Analysis

Product Price

Determination Life

- Cycle Cost and Payback Period Analyses

National Impact Analysis Energy Use

Revise Preliminary Analyses

Life

- Cycle Cost
Sub

- Group Analysis

Manufacturer Impact Analysis Shipments Analysis

Employment Impact Analysis

Revise Analyses • Product Classes

• Technology Options

• Industry Cash Flow

• Sub

- Group Cash

- Flow

• Direct Employment Impacts

• Competitive Impacts

• Cumulative Regulatory Burden • Product Designs

• Life

- Cycle Costs

• Payback Periods

• National Energy Savings

• Net Present Values

• National Employment Impacts

• Revised Results • Characterize Industry

• Market Segmentation

• Non

- Regulatory Programs Framework Document

• Efficiency

- Level Approach

• Design Option Approach

• Energy Prices

• Installation Costs

• Maintenance & Repair Costs

• Accounting Approach

• Backcast and Forecast

• Market Saturation

• Stakeholder Comments

• Demographics

• Manufacturer Interviews

• GRIM Analysis

• Emission Rates

• National Energy Savings

• Stakeholder Comments • Identify Firms/Products

• Historical Shipments

• Retail Price Collection and Analysis

• Manufacturer Prices

• Average Costs

• Manufacturer Financial Data Design Options Product Classes

Retail

Prices Design Energy/ Use

Advance Notice of Proposed Rulemaking (ANO) • Efficiency/Performance • Commercial Products

Candidate Standard

Levels • Analysis of Energy Use

Data

Environmental

Assessment

Regulatory Impact Analysis Technology Options

• Emission Estimates • Utility Load Factors

• National Energy Savings

• Non

- Regulatory
Alternatives • NEMS

- BT

• ImSET

• NEMS

- BT • 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 • Analysis of Market Data

• Analysis of Product Data

• Life

- Cycle Costs

• Payback Periods • Installation Costs

• Maint Costs

• Repair Costs • UEC

• Energy Prices Annual Energy Use (UEC)

Preliminary 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 Product Designs

Utility Impact

Analysis

Notice of Proposed Rulemaking (NOPR)

Final Rule Approaches Key Inputs Analyses Key Outputs

Market and Technology

Assessment

Screening Analysis

Engineering Analysis

Product Price

Determination Life

- Cycle Cost and Payback Period Analyses

National Impact Analysis Energy Use

Analyses

Life

- Cycle Cost
Sub

- Group Analysis

Manufacturer Impact Analysis Shipments Analysis

Employment Impact Analysis

Revise Analyses • Product Classes

• Technology Options

• Industry Cash Flow

• Sub

- Group Cash

- Flow

• Direct Employment Impacts

• Competitive Impacts

• Cumulative Regulatory Burden • Product Designs

• Life

- Cycle Costs

• Payback Periods

• National Energy Savings

• Net Present Values

• National Employment Impacts

• Revised Results • Characterize Industry

• Market Segmentation

• Non

- Regulatory Programs Framework Document

• Efficiency

- Level Approach

• Design Option Approach

• Energy Prices

• Installation Costs

• Maintenance & Repair Costs

• Accounting Approach

• Backcast and Forecast

• Market Saturation

• Stakeholder Comments

• Demographics

• Manufacturer Interviews

• GRIM Analysis

• Emission Rates

• National Energy Savings

• Stakeholder Comments • Identify Firms/Products

• Historical Shipments

• Retail Price Collection and Analysis

• Manufacturer Prices

• Average Costs

• Manufacturer Financial Data Design Options Product Classes

Retail

Prices Design Energy/ Use

Publication of Preliminary Analyses • Efficiency/Performance • Commercial Products

Candidate Standard

Levels • Analysis of Energy Use

Data

Environmental

Assessment

Regulatory Impact Analysis Technology Options

• Emission Estimates • Utility Load Factors

• National Energy Savings

• Non

- Regulatory
Alternatives • NEMS

- BT

• ImSET

• NEMS

- BT • 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 • Analysis of Market Data

• Analysis of Product Data

• Life

- Cycle Costs

• Payback Periods • Installation Costs

• Maint Costs

• Repair Costs • UEC

• Energy Prices Annual Energy Use (UEC)

Preliminary 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 Product Designs

2-2The following analyses are performed for the notice of proposed rulemaking (NOPR)

.

• A market and technology assessment to characterize the relevant equipment markets and technology options, including prototype designs.

• A screening analysis to review each te chnology option and determine whether it is technologically feasible; is practical to manufacture, install, and service; would adversely affect equipment utility or availability ; or w ould have adverse impacts on health and safety.

• An engineering analysis to develop cost- efficiency relationships for equipment designs that passed the screening analysis ; the manufacturer ’s production costs (material, labor, and factory overhead) for achieving increased efficien cy are evaluated

.

• An energy use analysis to determine the annual energy use of the considered equipment at specific efficiency levels

.

• A markups analysis to convert the manufacturer costs estimated from the engineering analysis to consumer prices, which are then used in the life

- cycle cost (LCC) and payback period analysi s (PBP) and in the manufacturer impact analysis.

• A life -cycle cost and payback period analysis to calculate, at the c onsumer level, the discounted savings in op erating costs ( minus maintenance and repair costs) throughout the estimated average life of the covered equipment, compared to any

increase in the installed cost of the equipment likely to result directly from the imposition of the standard.

• A shipments an alysis to forecast equipment shipments, which then are used to calculate the national impacts of standards on energy consumption and costs, net present value (NPV), and future manufacturer cash flows.

• A national impact analysis to assess the aggregate impa cts nationwide of the NPV of total consumer LCC and national energy savings (NES).

• A consumer subgroup analysis to evaluate variations in consumer characteristics that might cause a standard to affe ct the LCC for particular consumer sub-populations differently than for the overall population.

• A manufacturer impact analysis to estimate the financial impact s of standards on

manufacturers and to calculate effe cts on competition, employment, and manufacturing capacity.

• An emissions analys is to estimate the effects of amended energy conservation standards on emissions of carbon dioxide (CO 2 ), sulfur dioxide (SO 2 ), nitrogen oxides (NO X ), and mercury (Hg ).

• A monetization of emission reduction benefits resulting from reduced emissions of

CO 2 and NO X associated with potential amended standards.

• A utility impact analysis to estimate the effects of proposed standards on the generation capacity and electricity generation of electric utilities.

• An employment impact analysis to assess the aggregate effe cts of standards on national employment.

• A regulatory impact analysis to evaluate alternatives to proposed amended energy conservation standards that could achieve substantially the same regulatory goal.

2-32.2 MARKET AND TECHNOLOG Y ASSESSMENT

The market and technology assessment characterizes the relevant equipment markets and technology options, including prototype designs, for considered equipment. Chapter 3 of this

TSD describes in detail the market and technology assessm ent for small, large, and very lar ge, air -cooled CUAC and CUHP

.

2.2.1 Market Assessment

When initiating a standards rulemaking, DOE develops information on the present and past industry structure and market characteristics for the equipment being studied. This activity assesses the industry and equipment, both quantitatively and qualitatively, based on publicly

available information . As such, for the considered equipment, DOE addresse d (1) manufacturer market share and characteristics; (2 ) current regulatory and nonregulatory initiatives for improving equipment efficiency; and (3) trends in equipment characteristics and retail markets

. This information serves as resource material throughout the rulemaking.

DOE reviewed equipment literature and interviewed manufacturers to develop an overall picture of the market for small, large, very large air -cooled CUAC and CUHP in the United

States . Industry publications and trade journals, government agencies, and trade organizations provided the bulk of th is inform ati on. The appropriate sections of this TSD , particularly chapter 3, describe the resulting information as DOE used it in the analysis.

2.2.2 Technology Assessment

DOE typicall y uses information relating to current and past technology options and prototype designs to determine what technologies manufacturers use to attain higher performance levels . In consultation with interested parties , DOE develops a list of technologies

for consideration. Initially, the list encompasses all the tec hnologies DOE believes are technologically feasible.

DOE developed a list of technologically feasible design options through consultation

with manufact urers of components and systems, from trade publications and technical papers

. Since many options for improving equipment efficiency are available in existing units, equipment literature and direct examination provided additional information.

2.3 SCREENING ANALYSIS

As described in section 2.2.2 , DOE develops an initial list of efficiency enhancement options from the technologies identified as technologically feasible . Then DOE , in consultation

with interested parties, reviews the list to determine whether th ose options (1) are technologically feasible; (2) are practicable to manufacture, install, and service; (3) have an adverse impact on equipment utility or availability; or (4) have adverse impacts on health and safety. In addition,

DOE remove s from the list any technology options for which energy consumption data are

2-4lacking as well as any for which the energy consumption c an not be measured adequately by DOE test procedures. Chapter 4 of this TSD describes the screening analysis. In the engineering analysis, DOE furthe r considers those efficiency enhancement options that were not eliminated in the screening analysis

.

2.4 ENGINEERING ANALYSIS

In the engineering analysis (chapter 5 of this TSD ) , DOE evaluates a range of equipment efficiency levels and their associated manufa cturing costs in order to establish the relationship between the cost and the efficiency of small, large, and very large, air-cooled CUAC and CUHP

. This relationship serves as the basis for cost/benefit calculations related to individual consumers, manufacturers, and the nation . C hapter 5 discusses the equipment classes DOE analyzed, the representative baseline units, the incremental efficiency levels, the methodology DOE used to develop manufacturing costs, the methodology it used to develop the energy consumption model,

the cost

- efficiency curves, and the effect of efficiency improvements on the covered equipment.

The purpose of the engineering analysis is to estimate the incremental manufacturing production costs associate d with increasing equipment efficiency above the level of the baseline

model in each equipment class. The engineering analysis generally considers technologies not eliminated in the screening analysis, although certain technologies were not analyzed because they offered negligible incremental improvements to efficiency. DOE considers the remain ing technologies, designated design options, in developing cost

- efficiency curves, which subsequently are used for the LCC and PBP analysi s. For each equipment class

, DOE selected efficiency levels and obtained incremental cost data at each level

.

DOE typically structures its engineering analysis around one of three methodologies: (1) the design -option approach, which calculates the incremental costs of adding specif ic design options to a baseline model; (2) the efficiency- level approach, which calculates the relative costs of achieving increases in energy efficiency levels without regard to the particular design options used to achieve such increases; and/or (3) the reverse

- engineering or cost -assessment approach, which involves a “bottom-up” manufacturing cost assessment based on a detailed bill of materials derived from teardowns of the equipment being analyzed. A supplementary method called a catalog teardown uses published manufacturer catalogs and supplementary component data to estimate the major physical differences between a piece of equipment that has been physically disassembled and another piece of similar equipment for which catalog data is

available to det ermine the cost of the latter equipment.

DOE conducted the engineering analyses using the reverse

- engineering approach

. This approach involved the disassembly of units, analysis of the materials and manufacturing processes, and development of a spreadsheet cost model based on a clear and consistent manufacturing cost assessment methodology. DOE built a detailed cost assessment model that accurately predicts manufacturing cost s. The model reports th ose costs in aggregated form to

maintain confiden tiality of the data

.

2-52.5 MARKUPS ANALYSIS

In the markups analysis (chapter 6 of this TSD), DOE uses manufacturer- to

- customer markups to convert the manufacturer selling price estimates from the engineering analysis to customer prices, which are then used in the LCC and PBP analysis and in the manufacturer impact analysis. Retail prices are necessary for the baseline efficiency level and all other

efficie ncy levels under consideration. To develop markups

, DOE identif ied distribution channels ( i.e. , how the eq uipment are distributed from the manufacturer to the consumer). After identifying appropriate distribution channels, DOE utilized econom ic census data from the U.S. Census Bureau and input from the industry to define how equipment are marked up from the

manufacturer to the customer

.

2.6 ENERGY USE ANALYSIS

The energy use analysis (chapter 7 of this TSD ) provides estimates of the annual energy consumption of small, large, and very large air -cooled CUAC equipment at the considered

effic iency levels. DOE uses these values in the LCC and PBP analyses and in the NIA. DOE did not analyze air -cooled CUHP equipment because the energy modeling discussed in chapter 4 was performed only for air -cooled CUAC equipment.

DOE developed energy consump tion estimates only for the air -cooled CUAC equipment classes that have electric resistance heating or no heating. For equipment classes with all other types of heating, the incremental change in IEER for each efficiency level is identical to that for

the equipment classes with electric resistance heating or no heating. Therefore, DOE estimated that the energy savings for any efficiency level relative to the baseline would be identical for both sets of equipment classes. In turn, the energy savings estima tes for the efficiency levels associated with the equipment classes that have electric resistance heating or no heating were used by DOE in the LCC and PBP analysis and the NIA to represent both sets of equipment

classes.

The energy use analysis for small, large, and very large air -cooled CUAC consists of two related parts. In the first part, DOE calculated energy savings for small, large, and very large air

cooled CUAC at the considered efficiency levels based on modifications to the energy use

simulatio ns conducted for the 2004 ANOPR. These building simulation data are based on the 1995 Commercial Building Energy Consumption Survey (CBECS). Because the simulation data reflect the building stock in 1995 that uses air-cooled CUAC equipment, in the second p art, DOE developed a “generalized building sample” to represent the current installation conditions for the equipment covered in this rulemaking. This part involved making adjustments to update the building simulation data to reflect the building stock tha t uses air -cooled CUAC equipment in

2011.

2-62.7 LIFE

- CYCLE COST AND PAYBA CK PERIOD ANALYSIS

The LCC and PBP analysis (chapter 8 of this TSD) analyze s the effects of potential amended energy conservation standards on customers of small, large, and very large ai r-cooled commercial package air conditioning and heating equipment by determining how a potential amended standard affects their operating expenses (usually decreased) and their total installed costs (usually increased).

The LCC is the total customer exp ense over the life of the equipment, consisting of equipment and installation costs plus operating costs over the lifetime of the equipment (expenses for energy use, maintenance, and repair). DOE discounts future operating costs to the time of purchase usi ng customer discount rates. The PBP is the estimated amount of time (in years) it takes customers to recover the increased total installed cost (including equipment and installation costs) of a more efficient type of equipment through lower operating costs . DOE calculates the PBP by dividing the change in total installed cost (normally higher) due to a standard by the change in annual operating cost (normally lower) that results from the standard.

For any given efficiency level, DOE measures the PBP and the change in LCC relative to

an estimate of the base

- case efficiency level. The base

- case estimate reflects the market in the absence of amended energy conservation standards, including the market for equipment that exceeds the current energy conservation s tandards.

DOE analyze d the potential for variability and uncertainty by performing the LCC and PBP calculations on a representative sample of individual commercial buildings. The approach utilizes the sample of buildings developed for the energy use analysis and the corresponding simulations results. Within a given building, one or more air -conditioning units may serve the building’s space-conditioning needs, depending on the cooling load requirements of the building. As a result, DOE expresses the LCC and PBP results as the number of units experiencing economic impacts of different magnitudes. DOE models both the uncertainty and the variability in the inputs to the LCC and PBP analysis using Monte Carlo simulation and probability

distributions. As a resul t, the LCC and PBP results are displayed as distributions of impacts compared to the base case conditions.

DOE conducted an LCC and PBP analysis for the CUAC equipment classes. T he energy savings estimates for the efficiency levels associated with the equipment classes that have electric resistance heating or no heating were used in the LCC and PBP analysis to represent the equipment classes with all other types of heating. DOE did not perform an LCC and PBP analysis for the CUHP equipment for the reasons discussed in section 2.6.

2.8 SHIPMENTS ANALYSIS

Forecasts of s hipments are required to calculate the national impacts of standards on energy consumption, NPV, and future manufacturer cash flows. To project shipments of small, large, and very large air -cooled CUAC and CUHP, DOE considered specific market segments,

2-7the results for which are then aggregated to estimate total shipments. DOE accounted for three market segments: (1) shipments to new construction, (2) replacement shipments going into existing buildings, and (3) existing buildings acquiring new equipment for the first time.

For existing buildings replacing broken equipment, the shipments model uses a stock accounting framework. Given t he equipment entering the stock in each year and a retirement function based on the lifetime distribution developed in the LCC analysis, the model predicts how many units reach the end of their lifetime in each year. For CUAC and CUHP, end of lifetime is g enerally associated with compressor failure. The customer has the choice of repairing the existing unit by installing a new compressor, thereby extending its life considerably, or purchasing a new unit. To model the repair vs. replacement decision, for the small and large CUAC and CUHP equipment classes DOE used a consumer choice model that estimates customer sensitivity to total installation cost. A sensitivity parameter was calculated using efficiency market share data for years 1999−2001, along with estimates of equipment prices and installation costs by efficiency level. DOE applied this sensitivity to the difference between the total installed cost of a new unit and the repair cost of the existing unit. For the very large CUAC and CUHP equipment classe s, at the first failure DOE assumed that all customers repair the unit because the total installed cost of a new unit is so high.

The repair/replace model is a binary choice model with two parameters, “alpha” and “gamma.” "Alpha" represents customer sens itivity to the efficiency

- weighted average cost difference between total installed cost of replacement and repair costs. Since repair costs are generally lower than total installed costs of equipment, "gamma" is a scenario parameter that

limits the number of repairs and can be thought of as representing "unknown replacements."

For existing buildings acquiring new equipment for the first time, DOE first estimated saturation values (percentages of total floor space served by different cooling capacities or types of equipment) for the stock. DOE used a logistic regression procedure to fit the historical stock saturations to get a smooth time series of saturation estimates for the analysis period. Shipments for existing buildings acquiring new equipment for t he first time in each future year are estimated by multiplying the difference in projected stock saturation values between the future year and the previous year with the estimated floor space without CUAC and CUHP equipment in the previous year.

For new commercial buildings acquiring equipment, shipments are estimated by multiplying new construction floor space in each future year by saturation values (percentages of new floor space served by different cooling capacities or types of equipment). The shipments

model relies on AEO for forecasts of new construction floor space. It assumes that the saturation value in new commercial buildings is the same as the stock

- average saturation for each year.

The methods described above provide total shipments in each equipment class for each year. To estimate the market shares of the considered efficiency levels in future shipments, DOE developed a customer choice model. The model was calibrated by estimating values for two parameters, representing customer sensitivity to total installation cost and annual operating cost. To estimate values for the parameters, DOE used a non -linear regression approach that

2-8minimized the sum of the squared difference between historical market shares and the model predicted values at each efficiency level. Starting in 2013, application of the parameters, along with data on the installed cost and operating cost at each efficiency level considering this rulemaking, determines the market shares of each efficiency level.

2.9 NATIONAL IMPACT ANAL YS IS

The national impact analysis , described in chapter 10 of this TSD, assesses the NES and the national NPV of total customer costs and savings that would be expected to result from amended standards at specific efficiency levels. To make the analysis more accessible and transparent to all stakeholders, DOE prepared an NES s preadsheet model in Microsoft Excel to forecast energy savings and the national costs and savings resulting from amended standards.

The NES s preadsheet model does not use probability distributions for inputs or outputs. To

assess the effe ct of input uncertainty on the NES and NPV results, DOE can conduct sensitivity analyses by running scenarios on input variables that are of interest to stakeholders.

The NIA calculations are based on the annual energy consumption and total installed cost data from the energy use analysis and the LCC analysis. DOE forecasted the lifetime energy savings, energy cost savings, equipment costs, and NPV of customer benefits for each equipment class for equip ment sold from 2019 through 2048.

DOE evaluated the impacts of potential new and amended standards for small, large, and very large air -cooled commercial package air conditioning and heating equipment by comparing

base -case projections with standards-case projections. The base- case projections characterize energy use and customer costs for each equipment class in the absence of new and amended energy conservation standards. DOE compared these projections with those characterizing the

market f or each equipment class if DOE were to adopt amended standards at specific energy efficiency levels (i.e., the standards cases) for that class.

As stated in section 2.7, air-cooled CUHP were not analyzed in the LCC and PBP analysis. Nevertheless, DOE dev eloped the inputs necessary for determining the NES and customer NPV that would result from higher CUHP efficiency levels.

The inputs for determining NES are (1) annual energy consumption per unit, (2) shipments, (3) equipment stock , (4) national energy consumption, and (5) site

- to -source conversion factors. DOE calculated the national energy consumption by multiplying the number of units, or stock, of equipment (by vintage) by the unit energy consumption (also by vintage ). a

DOE calculated national annua l energy sa vings as the difference between national energy consumption in the base case (without new efficiency standards) and in each higher- efficiency standards case. Cumulative energy saving s are the sum of the annual NES throughout the forecast period

.

a Vintage represents the age of the product

.

2-9DOE estimate s energy consumption and savings based on site energy, then converts the electricity consumption and savings in to primary energy (power sector consumption). DOE also

uses full

- fuel

- cycle (FFC) measures of energy use based on multipliers derived using EIA’s National Energy Modeling System (NEMS).

The stock of equipment depend s on annual shi pments and the lifetime of the equipment.

DOE projected shipments under the base- case and for vari ous standards case s. DOE determined

that projected shipments were lower under the standards cases than under the base case
, as the higher installed costs would cause some consumers to forego equipment purchases.

The inputs for determining NPV are (1) total annual installe d cost, (2) total annual operating cost savings , (3) discount factor, (4) present value of costs, and (5) present value of savings. DOE calculated NPV as the difference between the present value of operating cost savings and the present value of in creased total installed costs. It calculated net savings each year as the difference between total operating cost savings (including savings in electricity, repair,

and maintenance cost s ) and increases in total installed costs ( equipment price). DOE calculated

sav ings over the life of the equipment, accounting for differences in yearly energy rates, and

used a discount factor to discount future costs and savings to the present.

DOE calculated increases in total installed costs as the product of the difference in the

total installed cost between the base case and standards case and the annual shipments in the standards case. DOE expressed operating cost savings as decreases in operating costs associated

with the lower energy consumption of equipment bought in the standards case compared to the

base efficiency case. Total operating cost savings are the product of savings per unit and the number of units of each vintage surviving in a particular year.

2.10 C USTO MER SUBGROUP ANALYSIS

The consumer subgroup analysis (chapter 11 of the TSD) evaluates economic impacts of standards on identifiable groups of consumers who might be disproportionately affected by new or amended energy efficiency s tandards. DOE evaluate s the effects on particular subgroups of consumers in part by using the LCC s preadsheet model to analyze the LCC and PBP for tho se particular c onsu mers . For the NOPR, DOE evaluated impacts on a small business subgroup using the LCC spreadsheet model. The customer subgroup analysis is discussed in detail in chapter 11 of the TSD.

2.11 MANUFACTURER IMPACT ANALYSIS

The manufacturer impact analysis (MIA) assesses the impacts of new energy efficiency

standards on manufacturers of small, large, and very large, air

- cooled CUAC and CUHP

. Potential impacts include financial effects, both quantitative and qualitative, that might l ead to changes in the manufacturing practices for the equipment. DOE identif ies th o se potential impacts through interviews with manufacturers and other interested parties

.

2-10As described in chapter 12 of this TSD, DOE conduct ed the MIA for the covered equipment in three phases, and further tailor ed the analytical framework based on stakeholder

comments . In Phase I, DOE create d a profile of the industry and analyzed publicly available financial information to derive preliminary inputs for the GRIM. In Phase II, an industry cash flow model and an interview questionnaire were prepared to guide subsequent discussions. In

Phase III , manufacturers were interviewed, and the impacts of standards were assessed both quantitatively and qualitatively

. DOE assessed i ndustry and sub-group cash flow and NPV through use of the Government Regulatory Impact Model. E ffe cts on competition, manufacturing capacity, employment, and cumulative regulatory burden were assessed based on feedback and discussions during manufacturer interview s.

2.12 EMISSIONS ANALYSIS

In the emissions analysis (chapter 13) , DOE estimate s the reduction in power sector emissions of carbon dioxide (CO 2 ), nitrogen oxides (NO X ), sulfur dioxide (SO 2 ) and mercury (Hg) from potential energy conservation standards for the considered products. In addition, DOE

estimate s emissions impacts in production activities (extracting, processing, and transporting fuels) that provide the energy inputs to power plants. These are referred to as “upstream” emissions. Together, these emissions account for the full- fuel

- cycle (FFC). In accordance with

DOE’s FFC Statement of Pol icy (76 FR 51282 (Aug. 18, 2011)), the FFC analysis includes impacts on emissions of methane and nitrous oxide, both of which are recognized as greenhouse

gases.

DOE conducts the emissions analysis using emissions factors derived from data in the

lates t version of EIA’s Annual Energy Outlook (AEO) , supplemented by data from other sources. EIA prepares the Annual Energy Outlook using NEMS. Each annual version of NEMS incorporates the projected impacts of existing air quality regulations on emissions. Th e text
below refers to AEO 2013, which generally represents current legislation and environmental regulations, including recent government actions, for which implementing regulations were available as of December 31, 2012.

SO 2 emissions from affected electric generating units (EGUs) are subject to nationwide and regional emissions cap and trading programs. Title IV of the Clean Air Act sets an annual emissions cap on SO 2 for affected EGUs in the 48 contiguous states and the District of Columbia (D.C.). SO 2 emissions from 28 eastern states and D.C. were also limited under the Clean Air Interstate Rule (CAIR), which created an allowance -based trading program that operates along with the Title IV program in those States and D.C. 70 FR 25162 (May 12, 2005). CA IR was remanded to EPA by the U.S. Court of Appeals for the District of Columbia Circuit (D.C. Circuit), but it remained in effect. See North Carolina v. EPA , 550 F.3d 1176 (D.C. Cir. 2008);

North Carolina v. EPA , 531 F.3d 896 (D.C. Cir. 2008). On July 6, 2011 EPA issued a replacement for CAIR, the Cross -State Air Pollution Rule (CSAPR). 76 FR 48208 (August 8, 2011). On August 21, 2012, the D.C. Circuit issued a decision to vacate CSAPR. See EME Homer City Generation, LP v. EPA , 696 F.3d 7, 38 (D.C. Cir. 2012). The court ordered EPA to

2-11continue administering CAIR. AEO 2013 assumes that CAIR remains a binding regulation through 2040.

The attainment of emissions caps is typically flexible among EGUs and is enforced through the use of emissions allowances and tradable permits. Under existing EPA regulations, any excess SO 2 emissions allowances resulting from the lower electricity demand caused by the adoption of an efficiency standard could be used to permit offsetting increases in SO 2 emissions by any reg ulated EGU. In past rulemakings, DOE recognized that there was uncertainty about the effects of efficiency standards on SO 2 emissions covered by the existing cap

- and

- trade system, but it concluded that no reductions in power sector emissions would occur f or SO 2 as a result of standards.

Beginning in 2015, however, SO 2 emissions will fall as a result of the Mercury and Air Toxics Standards (MATS) for power plants, which were announced by EPA on December 21, 2011. 77 FR 9304 (Feb. 16, 2012). In the final MATS rule, EPA established a standard for HCl as a surrogate for acid gas hazardous air pollutants (HAP), and also established a standard for

SO 2 (a non- HAP acid gas) as an alternative equivalent surrogate standard for acid gas HAP. The

same controls are us ed to reduce HAP and non-HAP acid gas; thus, SO 2 emissions will be reduced as a result of the control technologies installed on coal-fired power plants to comply with the MATS requirements for acid gas. AEO 2013 assumes that, in order to continue operating , coal plants must have either flue gas desulfurization or dry sorbent injection systems installed by 2015. Both technologies, which are used to reduce acid gas emissions, also reduce

SO 2 emissions. Under the MATS, NEMS shows a reduction in SO 2 emissions w hen electricity demand decreases (e.g., as a result of energy efficiency standards). Emissions will be far below the cap that would be established by CSAPR, so it is unlikely that excess SO 2 emissions allowances resulting from the lower electricity demand would be needed or used to permit offsetting increases in SO 2 emissions by any regulated EGU. Therefore, DOE believes that efficiency standards will reduce SO 2 emissions in 2015 and beyond.

CAIR established a cap on NO X emissions in eastern States and the District of Columbia. Energy conservation standards are expected to have little or no physical effect on these emissions in those States covered by CAIR because excess NO

x emissions allowances resulting from the

lower e lectricity demand could be used to permit offsetting increases in NO

x emissions. However, standards would be expected to reduce NO

x emissions in the States not affected by the caps, so DOE estimates NO X emissions reductions from potential standards in the States where emissions are not capped.

The MATS limit mercury emissions from power plants, but they do not include emissions caps and, as such, DOE’s energy conservation standards would likely reduce Hg emissions. DOE

estimate D mercury emissions reductio n using emissions factors based on AEO 2013 , which incorporates the MATS.

Power plants may emit particulates from the smoke stack, which are known as direct particulate matter (PM) emissions. NEMS does not account for direct PM emissions from power plant s. DOE is investigating the possibility of using other methods to estimate reduction in PM

2-12emissions due to standards. The great majority of ambient PM associated with power plants is in the form of secondary sulfates and nitrates, which are produced at a significant distance from power plants by complex atmospheric chemical reactions that often involve the gaseous emissions of power plants, mainly SO 2 and NO

x . The monetary benefits that DOE estimates for

reductions in SO 2 and NO

x emissions resulting from s tandards are in fact primarily related to the

health benefits of reduced ambient PM.

2.13 MONETIZING CARBON DI OXIDE AND OTHER EMIS SIONS

REDUCTIONS

DOE estimated monetary benefits likely to result from the reduced emissions of CO 2 and

NO X that are expected to result from each of the standard levels considered (see chapter 14 of the

TSD ).

To estimate the monetary value of benefits resulting from reduced emissions of CO 2 , DOE use s the most current Social Cost of Carbon (SCC) values developed and/or agreed to by an interagency process. 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 ecosystem 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 quantification and monetization, the SCC can be used to provide

estimates of the social benefits of reductions in GHG emissions.

The Interagency Working Group on Social Cost of Carbon released an update of its previous report in 2013. b The most recent estimates of the SCC in 2015, expressed in 2012$, are $12.9, $40.8, $62.2, and $117 per metric ton of CO 2 avoided. For emissions reductions that occur in later years, these values grow in real terms over time. Additionally, the interagency group determined that a range of valu es from 7 percent to 23 percent should be used to adjust the global SCC to calculate domestic effects, although DOE give s preference to consideration of the global benefits of reducing CO 2 emissions.

DOE multiplies the CO 2 emissions reduction estimated for each year by the SCC value for that year in each of the four cases. To calculate a present value of the stream of monetary values, DOE discounts the values in each of the four cases using the discount rates that had been

used to obtain the SCC values i n each case.

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 value s are subject to change.

b Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866

. Interagency Working Group on Social Cost of Carbon, United States Government, May 2013. http://www.whitehouse.gov/sites/default/files/omb/inforeg/social_cost_of_carbon_for_ria_2013_update.pdf

2-13DOE also estimates the potential monetary benefit of reduced NO X emissions resulting from the standard levels it considers. Estimates of monetary value for reducing NOx from stationary sources range from 468 to $4,809 per ton in 2012$. c DOE calculates monetary benefits using a medium value for NO X emissions of $2,639 per short ton (in 2012$), and real discount rates of 3 percent and 7 percent.

DOE is evaluating appropriate valuation of avoided SO 2 and Hg emissions. It did no t
monetize reduction in these emissions for the NOPR.

2.14 UTILITY IMPACT ANALY SIS

To estimate the impacts of potential energy conservation standards c on the electric utility industry, DOE uses a variant of the EIA’s National Energy Modeling System called NEMS- BT. d
NEMS is a large, multi

- sectoral, partial -equilibrium model of the U.S. energy sector that EIA has developed over several years, primarily for the purpose of preparing the AEO . NEMS produces a widely recognized forecast for the United States through 2040 and is available to the public.

The utility impact analysis is a comparison between the NEMS -BT model results for the

base case and standard cases. The utility impact analysis reports the changes in installed capacity and generation that result from each standard level by plant type. DOE models the anticipated energy savings impacts from potential amended energy conservation standards using NEMS- BT to generate forecasts that deviate from the AEO Reference Case.

2.15 EMPLOYMENT IMPACT AN ALYSIS

Energy conservation standards can affe ct employment both directly and indirectly. Direct employment effe cts are changes

, resulting from produced by new standards, in the number of employees at the plants that produce covered equipment and at affiliated distributi on and service companies. DOE evaluate s direct employment impacts in the MIA. Indirect employment impacts may result if the imposition of standards causes expenditures to shift between goods (the substitution effect) and /or create changes in income and ove rall expenditure levels (the income effect)

.

c U.S. 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

, Washington, DC

.

d 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 (March 2000), available at: http://tonto .eia.doe.gov/ftproot/forecasting/05812000.pdf . 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 un der various policy scenarios that are variations on EIA assumptions, DOE refers to the model by the name NEMS

- BT. (“BT” refers to DOE’s Building Technologies Program, under whose aegis this work is performed.)

2-14DOE utilizes Pacific Northwest National Laboratory’s ImSET model to investigate the combined direct and indirect employment impacts. The ImSET model, which was developed for DOE’s Office of Planning, Budget, and Analysis, estimates the employment and income effects

energy -saving technologies produced in buildings, industry, and transportation. In comparison with simple economic multiplier approaches, ImSET allows for more complete and automated analysis of the economic impacts of energy conservation investments.

2.16 REGULATORY IMPACT AN ALYSIS

In the NOPR stage, DOE prepared a regulatory impact analysis (RIA) pursuant to Executive Order 12866, Regulatory Planning and Review, 58 FR 51735, October 4, 1993, which

is subject to review by the Office of Information and Regulatory Affairs at the Office of Management and Budget. The RIA addresses the potential for non-regulatory approaches to supplant or augment energy conservation standards in order to improve the energy ef ficiency or reduce the energy consumption of the equipment covered under this rulemaking.

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

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