CHAPTER 2. ANALYTICAL FRAMEWORK

TABLE OF CONTENTS

2.1 INTRODUCTION

........................................................................................................... 2- 1 2.2 BACKGROUND

............................................................................................................. 2- 4 2.3 MARKET AND TECHNOLOGY ASSESSMENT

........................................................ 2-4 2.3.1 Market Assessment

.............................................................................................. 2-4 2.3.2 Technology Assessment

....................................................................................... 2-5 2.4 SCREENING ANALYSIS

.............................................................................................. 2-5 2.4.1 Technology Screening

......................................................................................... 2-5 2.5 ENGINEERING ANALYSIS

.......................................................................................... 2-5 2.5.1 Manufacturing Cost Model

.................................................................................. 2-6 2.5.2 Energy Consumption Model

................................................................................ 2-6 2.6 ENERGY USE CHARACTERIZATION

....................................................................... 2-6 2.7 MARKUPS TO DETERMINE EQUIPMENT PRICE

................................................... 2-7 2.8 LIFE-CYCLE COST AND PAYB ACK PERIOD ANALYSES

.................................... 2-8 2.9 SHIPMENTS ANALYSIS

............................................................................................... 2-9 2.10 NATIONAL IMPACT ANALYSIS

................................................................................ 2-9 2.10.1 National Energy Savings Analysis

....................................................................... 2-9 2.10.2 Net Present Value Analysis

............................................................................... 2-10 2.10.3 Efficiency Scenarios and Trends

....................................................................... 2-10 2.11 LIFE-CYCLE COST SUB-GROUP ANALYSIS

......................................................... 2-11 2.12 MANUFACTURER IMPACT ANALYSIS

.................................................................. 2-12 2.13 UTILITY IMPACT ANALYSIS

................................................................................... 2-12 2.14 EMPLOYMENT IMPACT ANALYSIS

....................................................................... 2-13 2.15 ENVIRONMENTAL ASSESSMENT

.......................................................................... 2-13 2.16 REGULATORY IMPACT ANALYSIS

........................................................................ 2-14 2.17 DEPARTMENT OF JUSTICE REVIEW

..................................................................... 2-14

LIST OF FIGURES

Figure 2.1.1 Flow Diagram of Analyses for the Beverage Vending Machine Rulemaking Process

............................................................................................................. 2-2

2-i BVM_FINAL_FR_TSD_Chapter2_08-14-09.docCHAPTER 2. ANALYTICAL FRAMEWORK

2.1 INTRODUCTION

Section 6295(o)(3)(B) of Title 42, United Stat es Code (42 U.S.C.), as directed by 42 U.S.C. 6316(a)(1)

─ (3), requires the U.S. Department of Energy (DOE) to set forth energy conservation standards that are technologically feasible and ec onomically justified, and would achieve the maximum improvement in energy effi ciency. This chapter describes the general analytical framework that DOE uses in developi ng such standards and, in particular, standards for beverage vending machines. The analytical framework is a description of the methodology, analytical tools, and relationships among the vari ous analyses that are part of this rulemaking. For example, the methodology that addresses the st atutory requirement for economic justification includes analyses of life-cycle cost (LCC); economic impact on manufacturers and users; national benefits; impacts, if any, on utility companies; and impacts, if any, from lessening competition among manufacturers. DOE will also solicit the views of the Department of Justice (DOJ) on any lessening of competition likely to result from the imposition of a standard.

Figure 2.1.1 summarizes the analyt ical components of the standards-setting process. The columns labeled “Key Inputs” and “Key Outputs” show how the analyses fit into the rulemaking process, and how they relate to each other. Key inputs are the types of da ta and information that the analyses require. Some key inputs exist in pu blic databases; DOE also collects other inputs from interested parties and pe rsons with special knowledge. Key outputs are analytical results that feed directly into the standards-setting pr ocess. Arrows connecting analyses show types of information that feed from one analysis to another.

2-1 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docUtility Impact Analysis

Notice of Proposed Rulemaking (NOPR) Approaches Key Inputs Analyses Key Outputs

Market and Technology Assessment

Screening Analysis

Engineering Analysis

Markups for Equipment Price

Determination Life-Cycle Cost and Payback Period Analyses

National Impact Analysis Energy Use

Revise ANOPR 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 • Cost-Efficiency Relationship

• 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

• Define Distribution Channels • Economic Census Data Analysis • 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 (ANOPR) • Efficiency/Performance • Manufacturing Cost

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 Cost-Efficiency Relationship

Final Rule

Figure 2.1.1 Flow Diagram of Analyses for the Beverage Vending Machine Rulemaking Process

2-2 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docThe analyses performed in the advance not ice of proposed rulemaking (ANOPR) stage and reported in this technical suppor t document (TSD) are listed below.

 A market and technology assessm ent is conducted to character ize the relevant equipment markets and existing technology optio ns, including prototype designs.

 A screening analysis is conducte d to review each technology op tion and determine if it is technologically feasible ; is practical to manufacture, inst all, and service; would adversely affect equipment utility or equipment availa bility; or would have adverse impacts on health and safety.

 An engineering analysis is conducted to deve lop the cost-efficiency relationship, which is the increased manufacturer sell ing prices (material, labo r, factory overhead, selling, general and administrative expenses, research and development costs, and profit) of more efficient equipment.

 An equipment price markup analysis is conduc ted to convert the ma nufacturer’s sellingprice estimates from the engine ering analysis to customer pr ices, which are then used in the LCC and payback period (PBP) analyses and the manufacturer impact analysis (MIA).

 An energy use analysis is conducted to determ ine the annual energy us e characteristics of beverage vending machines located inside and outside of manufacturing facilities and other commercial buildings.

 LCC and PBP analyses are conducted to calcula te, at the customer level, the discounted savings in operating costs (less maintenan ce and repair costs) throughout the estimated average life of the covered equipment compared to any increase in the installed cost for the equipment likely to result directly from the imposition of the standard.

 A shipments analysis is conducted which forecas ts equipment shipments. This analysis is then used to calculate the national impacts of standards on energy consumption and costs, net present value (NPV), and fu ture manufacturer cash flows.

 A national impact analysis is conducted to a ssess the aggregate impacts at the national level of NPV of total consumer LC C and national energy savings (NES).

 A preliminary MIA is conducted to assess the potential impacts of energy conservation standards on manufacturers such as capital conversion expenditures, marketing costs, shipments, and research and development costs.

The analyses performed in the notice of proposed rulemaking (NOPR) stage include those listed below. In addition, DOE re-analyze s the work done in the ANOPR stage. These analyses were subsequently revised for the final rule stage and reported in this final rule TSD.

 A LCC sub-group analysis is conducted to eval uate variations in commercial business type characteristics (e.g., en ergy prices, equipment use pa tterns, and installation and maintenance costs) that might cause a sta ndard to affect particular customer subpopulations, such as specific building owners or other customers that purchase and use beverage vending machines different ly than the overall population.

2-3 BVM_FINAL_FR_TSD_Chapter2_08-14-09.doc A manufacturer impact analysis is conducted to estimate the fi nancial impact of standards on manufacturers and to calculate im pacts on competition, employment, and manufacturing capacity.

 A utility impact analysis is conducted to es timate the effects of standards on electric utilities.

 An employment impact analysis is conducted to assess the aggregat e impacts on national employment.

 An environmental assessment is conducted to provide estimates of changes in emissions of pollutants from electricity ge neration (i.e., carbon dioxide (CO 2 ), oxides of nitrogen (NO x ), mercury (Hg), and sulfur dioxide (SO 2 ).

 A regulatory impact analysis is conducted to present major alternatives to standards that could achieve substantially the same regulatory goal at a lower cost.

2.2 BACKGROUND

DOE developed and documented the analytical framework for the beverage vending machine rulemaking in the Rulemaking Framework for Refrigerated Bottled or Canned Beverage Vending Machines , and presented the analytical appro ach to interested parties during a public meeting on July 11, 2006. This document is available at http://www.eere.energy.gov/buildin gs/appliance_standards/comme rcial/pdfs/vending_machines

_ framework.pdf . The following sections describe the di fferent analytical components of the rulemaking framework.

2.3 MARKET AND TECHNOLOGY ASSESSMENT

The market and technology assessment charact erizes the relevant product markets and existing technology options, in cluding prototype designs.

2.3.1 Market Assessment

When initiating a standards rulemaking, DOE develops information on the present and past industry structure and mark et characteristics for the equi pment concerned. This activity assesses the industry and equipment both quantit atively and qualitative ly, based on publicly available information. DOE addresses the fo llowing: (1) manufacturer market share and characteristics; (2) existing regulatory and non -regulatory equipment efficiency improvement initiatives; and (3) trends in pr oduct characteristics and retail mark ets. This information serves as resource material thr oughout the rulemaking.

For this rulemaking, DOE reviewed existing l iterature and interviewed manufacturers to get an overall picture of the be verage vending machine market in the United States. Industry publications and trade journals, government agencies, and trade organizations provided the bulk of the information. The appropriate sections of th e final rule describe th e analysis and resulting information as reported in the TSD.

2-4 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docDOE uses the most reliable and accurate data available at the time of each analysis in its rulemakings. All data is av ailable for public review.

2.3.2 Technology Assessment

DOE typically uses information about existi ng and past technology options and prototype designs to help determine which technologies manufacturers use to attain higher energy performance levels. In consultation with interest ed parties, DOE develops a list of technologies for consideration. Initially, these technologies encompass all those it believes are technologically feasible.

For this rulemaking, DOE developed a list of technologically feasible design options after consultation with manufacturers of components a nd systems, and from trade publications and technical papers. Since many options for improv ing equipment efficiency are available in existing equipment, product litera ture and direct examination of the beverage vending machine equipment provided additional information, as described in chapter 3 of the TSD.

2.4 SCREENING ANALYSIS

In the screening analysis, DOE screens out technologies that are not technologically feasible; not practicable to manufacture, install, or service; have an adverse impact on equipment utility or availability; or have adverse impacts on health and safety. In the engineering analysis, DOE further considers design options that remain after the screening process.

2.4.1 Technology Screening

As described in chapter 4 of the TSD, DOE grouped technologies into the following categories: (1) technologies that do not affect daily energy consumption; (2) screened-out technologies; and (3) remaining technologies that reduce beverage vending machine energy consumption under DOE’s test procedure.

Because the energy descriptor for beverage vending machines is daily energy consumption and the test procedure uses a steady state approach, DOE did not include technologies or designs that improve energy consumption under varying ambient conditions (e.g., expansion valves, variable-speed compre ssors). Therefore, only those technology and design options that improve the daily energy consumption rating were considered viable for review and applicati on in the rulemaking.

2.5 ENGINEERING ANALYSIS

As presented in chapter 5, the engineering an alysis establishes the relationship between the price and efficiency of beve rage vending machines. This relati onship serves as the basis for cost/benefit calculations for individual customers, manuf acturers, and the Nation. The engineering analysis discusses co st-efficiency curves, equipment cl asses analyzed, representative baseline units, the methodology used to devel op manufacturing selli ng prices, the methodology used to develop the energy consumption model, and the use of alternative refrigerants.

2-5 BVM_FINAL_FR_TSD_Chapter2_08-14-09.doc2.5.1 Manufacturing Cost Model

DOE used a cost model to estimate the core cost of refrigerated beverage vending machines. This cost model is based on work DOE conducted in support of the rulemaking on commercial refrigeration equipment (refer to http://www1.eere.energy.gov/buildings/appliance_standards/ commercial_products.html for further details on and validation of the cost mode l). The approach for commercial refrigeration equipment involved the disassembly of a piece of commercial refrigeration equipment, an analysis of the materials and manufacturing processes, and th e development of a parametric spreadsheet model. DOE then modified the commercial refrigeration equipment model to analyze the core costs of refrigerated bevera ge vending machines. DOE obtained input from interested parties on the refrigerated beverage vending machine manufacturer selling prices estimates and assumptions to confirm their accuracy.

2.5.2 Energy Consumption Model

The energy consumption model estimates the daily energy consumption of refrigerated beverage vending machines in kilowatt hours atvarious performance levels using a designoptions approach. DOE developed the energy consumption model as a Microsoft Excel spreadsheet. Appendix A provides instru ctions for using the spreadsheet.

For a given equipment class, the model estim ates the daily energy consumption for the baseline and several levels of performance above the baseline. The model calculates each performance level separately. For the baseline level, the cost model calculates a corresponding cost; for each level above the baseline, the cost increases of the various design options are used to recalculate the final cost.

2.6 ENERGY USE CHARACTERIZATION

The energy use characterizati on analysis assessed the annua l energy consumption of the refrigerated beverage vending machines that woul d be located inside a nd outside industrial and commercial buildings. DOE modified the ener gy consumption model developed during the engineering analysis to re flect the equipment’s thermal and compressor performance characteristics in order to simulate a realisti c performance of the machine exposed to varying temperature and relative humidity conditions. DO E developed another spreadsheet-based model (described in chapter 7 of th e TSD) to determine the beverage vending machine’s hourly, and hence annual, energy consumption under varyin g climate conditions around the country. DOE developed a State-by-Stat e distribution of beverage vending machines using population weights to determine annual energy consumption of mach ines located outdoors. Th e machines that are typically located inside industrial and commercia l buildings were assumed to be in conditioned spaces, and hence are exposed to the same te mperature and relative humidity conditions (75 degrees Fahrenheit and 45 percent re lative humidity) throughout the year.

Most beverage vending machines are locate d inside conditioned spaces and will add to the cooling load in the summer and reduce the h eating load in the winter. DOE believes these impacts are fairly modest in most cases. DOE also believes that the added complexity of determining the overall impact on building space-c onditioning loads is not worth the effort

2-6 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docinvolved in accurately quantifying th is effect, particularly given the variety of building types and vending machine locations (e.g., outside, inside, or in vestibules) that w ould need to be taken into account.

2.7 MARKUPS TO DETERMINE EQUIPMENT PRICE

DOE used manufacturer-to-consumer markups to convert the manufa cturer selling-price estimates from the engineering analysis to custom er prices, which were then used in the LCC, PBP, and manufacturer impact analyses. Because retail prices are required for the baseline performance level and all othe r performance levels under consideration, DOE obtained these retail prices by applying manufacturer-to-custom er markups to the manufacturer selling-price estimates.

Before it can develop markups, DOE must iden tify distribution channels (i.e., how the equipment is distributed from the manufacturer to the customer). On ce it established proper distribution channels for each of the equipment classes, DOE relied on economic data from the U.S. Census Bureau and input from the indus try to determine how much product prices are increased as they pass from the manufacturer to the customer (see chapter 6 of the TSD).

DOE’s review of the information revealed that a set of three distri bution channels would be appropriate, as described below:

1. Equipment Manufacturer  Vending Machine Operator (e.g., bottler, beverage distributor)

2. Equipment Manufacturer  Distributor  Vending Machine Operator

3. Equipment Manufacturer  Distributor  Site Owner
In the first distribution channel, the equi pment manufacturer makes the equipment to meet machine performance spec ifications provided by the beve rage company (i.e., the vending machine operator) and sells it directly to a bot tler or beverage distribut or. The vending machine operator owns the machine, places it on site through a “location contract,” maintains the machine and stocks it, and receives a certa in percentage of coin-box revenue. The site owner, in this case, allows the machine to be placed on site, receives a percentage of coin-box revenue and/or other remuneration, and most importantly, pays the electric bill.

In the second channel, the vending machin e operator purchases the equipment from a distributor instead of directly from the equipment manufacturer.

In the third channel, a site owner (e.g., large retail store ch ain) may purchase the vending machines from the distributor and install them inside or outside a retail store location. Other site owners (e.g., gas stations) may purchase vending machines from a distributor and stock the machines for the entire coin-box revenue.

The first distribution channel creates a “split-incentive syst em” where bottling companies or distributors purchase and inst all a significant portion of the vending machines from equipment manufacturers, but do not pay the utility bills associated with the machines’ operation. The site owner may be paid a commission as pa rt of the location contract to defray part of the electricity

2-7 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docbill. Therefore, the equipment purchaser has no economic incentive to purchase a more efficient machine. Nonetheless, there may be a growi ng market for energy-efficient beverage vending machines because environmentally conscious beverage companies are asking for energy-efficient machines, and certain site owners are demanding th at energy-efficient machines be installed to reduce energy costs.

2.8 LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSES

New energy conservation standards on equipm ent usually reduce operating expenses and increase customer prices. DOE analyzed the net effect of new sta ndards on customers by evaluating the net LCC using the cost-efficiency re lationship derived in th e engineering analysis, as well as the energy costs derived from the ener gy use characterization an alysis. Inputs to the LCC calculation include the installed cost to the cu stomer (customer price plus installation cost), operating expenses (energy expenses and maintenan ce costs), the lifetime of the appliance, and a discount rate. These inputs are described in detail in chapter 8 of the TSD.

The installed cost typically increases and operating cost typically decreases in response to new standards. Thus, there is a specific time in the life of higher-than-baseline efficiency equipment when the net operating-cost benefit (i n dollars) from the time of purchase is equal to the incremental first cost of purchasing the more efficient equipment. The length of time required for equipment to reach this cost-equivalence point is known as the payback period.

DOE conducted the LCC and PBP analyses using typical values to reflect the conditions in the field for equipment life, equipment retail price, national or regional energy costs, energy consumption, and discount rates. The LCC subgr oup analysis includes an assessment of impacts on customer subgroups.

For beverage vending machines, it was necessary to determine several of the input values for the LCC estimation, including retail prices; el ectricity prices; discount rate; maintenance, service, and installation costs; and equipment lifetimes.

DOE reviewed the Energy Information Admi nistration’s (EIA) energy price data for beverage vending machines to establish electrici ty prices. DOE relied on regional average energy price data for the commercial and industrial sectors (manufacturing facilities). DOE used projections of these energy prices for commercia l and industrial customers to estimate future energy prices in the LCC and PBP analyses. DOE used EIA’s Annual Energy Outlook (

AEO ) as the default source of projections for future energy prices.

DOE developed discount rates by estimating th e cost of capital to companies that purchase beverage vending machines covered under this rulemaking. DOE commonly uses the cost of capital to estimate the present value of cash flows to be derived from a typical company project or investment. Most comp anies use both debt and equity capital to fund i nvestments, so the cost of capital is the weighted-average cost to the firm of equity and debt financing. This corporate finance approach is referred to as the weighted-average cost of capital.

DOE considered expected changes to maintena nce, repair, and inst allation costs for the equipment covered in this rulemaking. Typical ly, small incremental changes in equipment efficiency incur no, or only very small, change s in repair and maintenance costs over baseline

2-8 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docefficiency products. There is a greater probability that equipment with efficiencies that are significantly greater than the baseline will incur increased repair and maintenance costs since such equipment is more likely to incorporate technologies that are new to the industry and not widely available. DOE relied on input from manuf acturers and other interest ed parties to develop appropriate repair and maintenance costs. Unless the efficiency increases considered for this rulemaking result in significantly larger or heav ier products, DOE determined that more efficient beverage vending machines would not incur increased installation costs.

DOE used information from various literat ure sources (e.g., Automatic Merchandising and American Society of Heating, Refrigerati ng, and Air-Conditioning Engineers Refrigeration Handbook) and input from manufacturers and other interested parties to establish average equipment lifetimes for use in the LCC and subsequent analyses.

2.9 SHIPMENTS ANALYSIS

Shipment forecasts are required to calculat e the national impacts of standards on energy, NPV, and future manufacturer cash flows. DOE developed shipment forecasts based on an analysis of key market drivers for beverage vending machines (see ch apter 10 of the TSD).

For each equipment class, DOE developed a se t of shipment forecasts for the beverage vending machines for each set of standards anal yzed. These standards case forecasts were used to evaluate the impacts of standards on product shipments. Standards case forecasts were derived using the same data sets as base case forecasts . The data required to develop sensitivities of shipments to customer price and operating cost savings were limited. Therefore, DOE modeled standards case shipments forecasts with scenar ios (i.e., specific impacts on product shipments) rather than developing sensitivities to customer price or operating cost savings. Comments from interested parties on the shipment s forecasts at the ANOPR stage i ndicated that future shipments likely will not increase from present levels and will occur for replacement purposes only, with any sales to new locations offset with reductions at existing loca tions. This flat-sales scenario was adopted by DOE for the shipments forecast.

2.10 NATIONAL IMPACT ANALYSIS

The national impact analysis assesses the NPV of total customer LCC and NES. DOE determined both the NPV and NES for the performance levels considered for the equipment classes analyzed. To make the analysis more acce ssible and transparent to all interested parties, DOE prepared an NES spreadsheet model in Micr osoft Excel to forecast energy savings and the national economic costs and savings resulting from new standards. The NES spreadsheet model does not use probability distribut ions for inputs or outputs. To assess the impact of input uncertainty on the NES and NPV results, DOE can conduct sensitivity analyses for future analyses by running scenarios on input variable s of concern for interested parties. DOE conducted an assessment of the aggregate economic impacts at the national level as described in chapter 11 of the TSD.

2.10.1 National Energy Savings Analysis

The inputs for determining NES are (1) annual energy consumption per unit, (2) shipments, (3) equipment stock, (4) national en ergy consumption (calculated from consumption

2-9 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docper unit and equipment stock), and (5) site-to- source conversion factors. DOE calculated the national energy consumption by multiplying the numb er of units, or stock, of beverage vending machines (by vintage) by the unit energy consump tion (also by vintage, which represents the age of the equipment). Then, DOE calculated national annual energy savings from the difference between national energy consumption in the base cas e (without new efficiency standards) and in each higher efficiency standard case. DOE estim ated energy consumption and savings based on site energy, and converted the el ectricity consumption and savings to source energy. Cumulative energy savings are the sum of the annual NES, which DOE determined over specific time periods.

The stock of beverage vending machines depends on annual shipments and equipment lifetimes. DOE conducted shipments projections under the base efficiency case and higher efficiency standards cases for a variety of possi ble equipment efficiency scenarios and trends. DOE used the flat replacement-sales-only total shipments forecast from the shipments analysis for all efficiency scenarios.

2.10.2 Net Present Value Analysis

The inputs for determining NPV are (1) tota l annual installed cost; (2) total annual operating cost savings; (3) discoun t factor; (4) present value of costs (values calculated in the analysis); and (5) present value of savings (als o calculated values). DOE calculated net savings each year as the difference between total operating-c ost savings (including electricity, repair, and maintenance cost savings) and increases in tota l installed costs (incl uding equipment price and installation cost). DOE calcula ted savings over the life of the equipment, accounting for differences in yearly energy rates. DOE calcula ted NPV as the difference between the present value of operating cost savings and the present value of increased total installed costs. DOE discounted future costs and savings to the present with a discount factor.

DOE calculated increases in total installed co sts as the product of the difference in the total installed cost between th e base case and standards case and the annual shipments in the standards case. Because costs of more effici ent equipment bought in the standards case are higher than the costs of equipment bought in the base case, price increases appear as negative values in the NPV.

DOE expressed operating cost savings as decrea ses in operating costs associated with the lower energy consumption of equipment bought in the standards case compared to the base efficiency case. Total operati ng-cost savings are the product of savings per unit and the number of units of each vintage surv iving in a particular year.

2.10.3 Efficiency Scenarios and Trends

Several of the inputs for determining NES (e.g., the annual energy consumption per unit) and NPV (e.g., the total annual installed cost and the total annual operating-cost savings) depend on the efficiency of the equipment. Thus, DOE developed base case and standards case efficiency trends. The efficiency trends specify the annual historical and forecasted shipmentweighted average equipment efficiencies.

2-10 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docAt the ANOPR stage stakeholder comments i ndicated that the efficiency of purchased equipment is strongly dependent on the corpor ate purchasing policies of a handful of buyers. Chapter 11 of the TSD describes the baseline scen arios developed by DOE to describe the effects of these polices on historical and fu ture baseline efficiency trends.

DOE based its standards case forecasts (i.e., fore casts of efficiency trends after standards take effect) on the use of a roll- up efficiency scenario and parall el growth trend. Under a roll-up scenario, all equipment at perfor mance levels below a prospective standard are moved or rolled up to the minimum performance level allowed u nder the new standard. The distribution of equipment at higher efficiency standard levels is unaffected (i.e., this equipment remains at its pre-standard performance levels). The roll-up efficiency scenario dictates how DOE determined efficiency distributions in the first year a ne w standard takes effect, but does not define how equipment efficiency will be distributed in th e future. DOE assumes that the initial jump in shipment-weighted efficiency that occurs wh en the standard first becomes effective is maintained throughout the forecast.

2.11 LIFE-CYCLE COST SUB-GROUP ANALYSIS

The LCC sub-group analysis evaluates ec onomic impacts on virtually any group of customers, for example, customers of different business types that might be adversely affected by a change in the national energy efficiency st andard levels for beverage vending machines. During the NOPR stage, DOE evaluated the impact s of particular sub-groups of customers in part by analyzing the LCC and PBP for these customers.

DOE evaluated variations both in regional ener gy prices and use that might affect the NPV of an energy-efficiency standard to cust omer sub-groups. To the extent possible, DOE sought estimates of the variability of each input parameter and considered this variability in calculating customer impacts.

Then, DOE determined the impact on customer sub-groups using the LCC spreadsheet model. The spreadsheet model used for the LCC anal ysis can be used with different data inputs. The standard LCC analysis includes various commercial building types that use beverage vending machines. Moreover, DOE can analyze the LCC for any sub-group by using the LCC spreadsheet model and only sampling that sub-group. Details of this model are explained in the section describing the LCC and PBP analyses.

DOE considered which categories would be likeliest to be adversely affected. Manufacturing facilities th at own their own beverage vending m achines were considered to be the likeliest businesses to be adversely affected since they had the highest financing costs for new equipment of any group of beverage vending m achine owners (leading to the highest initial equipment cost) and faced the lowest electricity prices (thus showing the lowest value of energy savings). As a result, the LCC and payback calcula tions would be least favorable for this group.

DOE aims to avoid a negative economic imp act on any identified customer sub-group, such as small businesses with low annual revenues that might not be able to afford a significant increase in the price of beverage vending mach ines. The Small Business Administration defines a small business from a customer perspective by either its annual receipts ( i.e ., revenues) or its

2-11 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docnumber of employees. Manufact uring businesses are generall y defined to be small if employment of the entire business is 500 pe rsons or less. DOE does not have sufficient information to correlate employment with the co sts of more efficient beverage vending machines to identify the sub-group of small businesse s in the manufacturing sample. However, DOE believes that the results from the LCC sub-gr oup analysis found in chapter 12 of the TSD provide an adequate indicati on of whether the small manuf acturing businesses might be disproportionately advantaged or disadvantaged by a standard.

2.12 MANUFACTURER IMPACT ANALYSIS

DOE performed an MIA to estimate the fina ncial impact of higher energy conservation standards on beverage vending machine manufactur ers, and to calculate the impact of such standards on domestic manufacturing employme nt and plant capacity. The MIA has both quantitative and qualitative aspect s. The quantitative part of th e MIA primarily relies on the Government Regulatory Impact Model (GRIM) - an industry-cash-flow model customized for this rulemaking. The GRIM inputs are data characte rizing the industry cost structure, shipments, and revenues. The key output is the industry net present value. Different sets of assumptions (scenarios) produce different results . The qualitative part of the MIA addresses factors such as equipment characteristics, charac teristics of particular firms, and market and equipment trends, and includes an assessment of the impacts of standards on subgroups of manufacturers.

DOE conducted the manufacturer impact analys is in three phases. Phase 1 consisted of preparing an industry ch aracterization and identifying key is sues. Phase 2 addressed the broader industry, where DOE would use the Government Regulatory Impact Model to perform an industry cash flow analysis. DOE also devel oped a questionnaire for interviewing beverage vending machine manufacturers about the pote ntial impacts of new energy conservation standards on their business dur ing Phase 2. Phase 3 involved in terviewing manufacturers and adjusting the industry cash flow analysis as needed. Phase 3 also examined any additional impacts on competition, manufactur ing capacity, direct employme nt, and the cumulative burden of other regulations on manufacturers. The comple te MIA is outlined in chapter 13 of the TSD.

2.13 UTILITY IMPACT ANALYSIS

The utility impact analysis includes an anal ysis of the impact of higher efficiency standards on the electri c utility industry. DOE is consider ing adapting EIA’s National Energy Modeling System (NEMS) for this analysis. Su mmary documentation of NEMS can be found in National Energy Modeling System: An Overview 2003 , DOE/EIA-0581(2003), March 2003. The AEO2008 versions of the submodels used in th e utility and environmental analyses are documented on EIA’s website: www.eia.doe.gov/oiaf/forecasting.html . NEMS is a large multi

sectoral partial-equilibri um model of the U.S. energy sector that has been developed over the past decade, primarily for the purpose of preparing DOE’s AEO . In prior rulemakings, a variant of NEMS (currently termed NEMS-BT, BT referring to the DOE’s Building Technologies Program) was developed to better address the specific impacts of an equipment efficiency standard.

NEMS produces a widely recognized baseline energy forecast for the United States through 2030. The typical NEMS outputs include forecas ts of electricity sales, price, and avoided

2-12 BVM_FINAL_FR_TSD_Chapter2_08-14-09.docelectric generating capacity. DOE modeled the energy savings impacts from amended energy conservation standards using NEMS-BT to ge nerate forecasts that deviate from the AEO reference case.

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 the plants that produce the covered equipment and at affiliated distribution a nd service companies. DOE evaluates the direct employment impacts in the manufacturer imp act analysis. Indirect employment impacts may result from expenditures shifting between goods (t he substitution effect) and changes in income and overall expenditure levels (the income effect). The combined direct a nd indirect employment impacts will be investigated in the employment impact analysis using the Pacific Northwest National Laboratory’s “Impact of Sector En ergy Technologies” (ImSET) model. The ImSET model was developed for DOE’s Office of Pla nning, Budget, and Analysis to estimate the employment and income effects of energy-sa ving technologies on buildings, industry, and transportation. Compared to simple economic multiplier approaches, ImSET allows for more complete and automated analysis of the economic impacts of energy conservation investments.

2.15 ENVIRONMENTAL ASSESSMENT

The primary environmental effects of ener gy conservation standards for the beverage vending machines covered under this rulemaking will be decreased emissions resulting from reduced electrical energy consumption. The environmental assessment in TSD chapter 16 tracked the impact of possible standards on CO 2 , NO x , Hg, and SO 2 . DOE based these calculations on the NEMS-BT modeling work for th e utility impact analysis. This approach has the advantage of examining the marginal impact of higher efficiency standards for the covered equipment on the utility generation mix and the subsequent environmental emissions.

CO 2 emissions are tracked in NEMS-BT by a de tailed module that produces robust results because of its broad coverage of all sectors and inclusion of in teractive effects. NEMS-BT also includes a module for SO 2 - allowance trading and NO x - allowance trading in the 28 states where NO x -allowance trading occurs, a nd delivers a forecast of SO 2 -allowance and NO x -allowance prices. Simulation of national SO 2 trading and regional NO x trading tends to imply that physical emissions effects will be zero where this trading occurs. However, there is an SO 2 benefit and a NO x benefit from conservation in the form of a lo wer allowance price and, if big enough to be calculable by NEMS, this value can be reported. NEMS-BT also has an algorithm for estimating untraded NO x emissions from power generation. Hg emissions were estimated based on electricity generation by fuel type in NEMS and a range of Hg emission factors.

In addition to the estimation of reductions in physical emissions from an energy conservation standard DOE also considered th e monetary benefits a ssociated with these reductions. The monetary values were based on values found in the environmental economic literature. Details can be found in Chapter 16 of the TSD.

2-13 BVM_FINAL_FR_TSD_Chapter2_08-14-09.doc2.16 REGULATORY IMPACT ANALYSIS

In the NOPR stage, DOE prepared a regulat ory impact analysis (RIA) pursuant to Executive Order 12866, “Regulatory Planning an d Review,” 58 FR 51735 (October 4, 1993), which is subject to review under the Execu tive Order by the Office of Information and Regulatory Affairs at th e Office of Management and Budget. The RIA addressed the potential for non-regulatory approaches to supplant or augment energy conservation standards to improve the energy efficiency or reduce the energy c onsumption of the beverage vending machines covered under this rulemaking.

Voluntary and other non-regul atory efforts by manufacturer s, utilities, and other interested parties can result in substantial impr ovements to energy efficiency or reductions in energy consumption. DOE considered and qualitatively evaluated a number of non-regulatory approaches in chapter 17 of the TSD. Based on th e qualitative review, DOE is not confident that any of the alternatives DOE examined would save as much energy as today’s final rule, and the financial incentives in particul ar may engender significant free ri dership issues. Also, several of the alternatives would require new enabling le gislation, since authority to carry out those alternatives does not exist.

2.17 DEPARTMENT OF JUSTICE REVIEW

Section 325(o)(2)(B)(i)(V) of the Energy Policy and Conserva tion Act states that before the Secretary of Energy may prescribe a new or amended energy cons ervation standard, the Secretary shall ask the Attorney General to make a determination of “the impact of any lessening of competition...that is likely to result from th e imposition of the standard.” (42 U.S.C. 6295) Pursuant to this requirement, DOE will solicit the views of the DOJ on any lessening of competition that is likely to result from the imposition of a standard and will give the views provided full consideration in assessing the economic justification of a standard. DOE may consult with DOJ at earlier stages in the sta ndards development process to seek preliminary views on competitive impacts.

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