CHAPTER 11: NATIONAL IMPACT ANALYSIS 

TABLE OF CONTENTS 

11.1 INTRODUCTION ......................................................................................................... 11-1 

11.2 BASE CASE AND STANDARDS CASE FORECASTED EFFICIENCIES .............. 11-2 

11.3 NATIONAL ENERGY SAVINGS ............................................................................... 11-4 

11.3.1 NES Definition............................................................................................................... 11-4 

11.3.2 NES Inputs..................................................................................................................... 11-5 

11.3.2.1 Annual Energy Consumption per Unit ........................................................ 11-5 

11.3.2.2 Shipments..................................................................................................... 11-7 

11.3.2.3 Equipment Stock.......................................................................................... 11-8 

11.3.2.4 National Annual Energy Consumption........................................................ 11-8 

11.3.2.5 Energy Site-to-Source Conversion Factors.................................................. 11-8 

11.4 NET PRESENT VALUE............................................................................................... 11-9 

11.4.1 NPV Definition .............................................................................................................. 11-9 

11.4.2 NPV Inputs................................................................................................................... 11-11 

11.4.2.1 Total Installed Cost per Unit...................................................................... 11-11 

11.4.2.2 Annual Operating Cost Savings per Unit................................................... 11-12 

11.4.2.3 Total Annual Installed Cost Increases ....................................................... 11-13 

11.4.2.4 Total Annual Operating Cost Savings ....................................................... 11-14 

11.4.2.5 Discount Factors ........................................................................................ 11-14 

11.4.2.6 Present Value of Costs............................................................................... 11-15 

11.4.2.7 Present Value of Savings ........................................................................... 11-15 

11.5 NES AND NPV RESULTS......................................................................................... 11-15 

11.5.1 NES and NPV Input Summary .................................................................................... 11-15 

11.5.2 NES Results ................................................................................................................. 11-16 

11.5.3 Annual Costs and Savings ........................................................................................... 11-17
 

11.5.4 NPV Results................................................................................................................. 11-18 

11.6 IMPACT OF STANDARDS ON NATURAL GAS AND ELECTRICITY 

PRICES AND ASSOCIATED CONSUMER BENEFITS.......................................... 11-19 

11.6.1 Impact on Natural Gas Prices ...................................................................................... 11-19 

11.6.2 Impact on Electricity Prices ......................................................................................... 11-23 

LIST OF TABLES 

Table 11.2.1 Top-Loading Commercial Clothes Washers: Base Case and Standards 

Case Efficiency Distributions in 2013 ............................................................... 11-3 

Table 11.2.2 Front-Loading Commercial Clothes Washers: Base Case and Standards 

Case Efficiency Distributions in 2013 ............................................................... 11-4 

Table 11.3.1 National Energy Saving Inputs .......................................................................... 11-5 

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EERE-2006-STD-0127 COMMENT 69.1
Table 11.3.2 Top-Loading Commercial Clothes Washers: Base Case and Standards 

Case Shipment-Weighted Average Per-Unit Annual Energy and Water 

Consumption in 2013......................................................................................... 11-6 

Table 11.3.3 Front-Loading Commercial Clothes Washers: Base Case and Standards 

Case Shipment-Weighted Average Per-Unit Annual Energy and Water 

Consumption in 2013......................................................................................... 11-7 

Table 11.3.4 Site-to-Source Conversion Factors for Electricity and Natural Gas.................. 11-9 

Table 11.4.1 Net Present Value Inputs ................................................................................. 11-11 

Table 11.4.2 Top-Loading Commercial Clothes Washers: Base Case and Standards 

Case Shipment-Weighted Average Per-Unit Total Installed Costs in 2013.... 11-12 

Table 11.4.3 Front-Loading Commercial Clothes Washers: Base Case and Standards 

Case Shipment-Weighted Average Per-Unit Total Installed Costs in 2013.... 11-12 

Table 11.4.4 Top-Loading Commercial Clothes Washers: Base Case and Standards 

Case Shipment-Weighted Average Per-Unit Annualized Repair Costs in 

2013.................................................................................................................. 11-13 

Table 11.4.5 Front-Loading Commercial Clothes Washers: Base Case and Standards 

Case Shipment-Weighted Average Per-Unit Annualized Repair Costs in 

2013.................................................................................................................. 11-13 

Table 11.5.1 NES and NPV Inputs ....................................................................................... 11-16 

Table 11.5.2 Commercial Clothes Washers: Cumulative NES and NWS Results.............. 11-17 

Table 11.5.3 Commercial Clothes Washers: Cumulative NES and NWS Results 

Discounted at Seven Percent and Three Percent.............................................. 11-17 

Table 11.5.4 Commercial Clothes Washers: Cumulative NPV Results based on SevenPercent and Three-Percent Discount Rates...................................................... 11-19 

Table 11.6.1 Impact of Max Tech Standard Levels on Natural Gas Consumption and 

Average Wellhead Price in 2030 ..................................................................... 11-21 

Table 11.6.2 Implicit Natural Gas Inverse Price Elasticity from Seven Energy Models ..... 11-23 

Table 11.6.3 Impact of Max Tech Standard Levels on Electricity Consumption and 

Price in 2030 .................................................................................................... 11-25 

LIST OF FIGURES 

Figure 11.5.1 Non-Discounted Annual Installed Cost Increases and Annual Operating 

Cost Savings for Top-Loading Clothes Washers, TSL 3................................. 11-18 

Figure 11.6.1 Wellhead Natural Gas Price Change in 2030 Resulting from Reduced 

Natural Gas Consumption Associated with Max Tech Standard Level .......... 11-21 

Figure 11.6.2 Inverse Natural Gas Price Elasticity from NEMS Analysis for Commercial
 

Clothes Washer Max Tech Standard Level ..................................................... 11-22 

Figure 11.6.3 Electricity Price Change in 2030 Resulting from Reduced Electricity
 

Consumption Associated with Max Tech Standard Level............................... 11-24 

Figure 11.6.4 Inverse Electricity Price Elasticity from NEMS Analysis for Commercial 

Clothes Washer Max Tech Standard Levels.................................................... 11-25 

11-ii 

EERE-2006-STD-0127 COMMENT 69.1
 

CHAPTER 11. NATIONAL IMPACT ANALYSIS
 

11.1 INTRODUCTION 

This chapter describes the method for estimating national impacts for commercial clothes 

washers, i.e., the quantity and net value to consumers of future national energy savings (NES) 

and water savings from possible trial standard levels (TSL). Chapter 9 provides identifies and 

describes the TSLs for commercial clothes washers. Results described here include: (1) national 

energy and water consumption and savings, (2) monetary value of energy savings to the Nation 

due to TSLs, (3) increased total installed costs to the Nation due to TSLs, and (4) the net present 

value (NPV) of energy savings (difference between value of energy savings and increased total 

installed costs). When NES is discussed throughout this chapter, it includes national water 

savings in addition to national energy savings. 

DOE determined both the NES and NPV for all of the TSLs considered for commercial 

clothes washers. It performed all calculations for each of the considered products using a 

Microsoft Excel spreadsheet model, which is accessible on the Internet 

(http://www.eere.energy.gov/buildings/appliance_standards/). The spreadsheet model, referred 

to as the National Impact Analysis (NIA) Model, combined the calculations for determining the 

NES and NPV as well as input from the relevant Shipments Model. Details and instructions for 

using each of the NIA Models are provided in Appendix 11A. 

The important facets of national energy consumption of include: (1) shipments of the 

equipment, (2) customer response to changes in total installed cost (i.e., purchase price plus 

installation costs), operating expense, and household income, and (3) voluntary programs 

promoting higher energy efficiency of equipment. 

Chapter 10 provides a detailed description of the Shipments Models that DOE used to 

forecast future purchases of commercial clothes washers. Included in the discussion are detailed 

descriptions of consumers’ sensitivities to total installed cost, operating expense, and income 

(otherwise known as elasticities), and how DOE captured them within the model. 

Concerning voluntary programs, although they may increase the share of energy efficient 

equipment prior to the implementation date of any new TSLs, DOE was not able to obtain 

information that quantified how such programs affect equipment efficiencies on a national basis. 

Consequently, DOE did not explicitly incorporate the impact of market-based initiatives into the 

shipments forecasts detailed in Chapter 10. 

This chapter presents information and results pertaining solely to CCWs. As described in 

section 1.3 of chapter 1 of this technical support document (TSD), DOE is continuing the 

rulemaking for energy conservation standards for microwave oven standby power, and analyses 

related to these products will be published in a separate TSD. In addition, DOE issued a final 

rule1

 adopting energy conservation standards for conventional cooking products (i.e., cooktops 

11-1 

EERE-2006-STD-0127 COMMENT 69.1
 

 

and ovens) and microwave oven energy factor (EF), and details of the analyses for these products 

are contained in the corresponding final rule TSD.2 

11.2 BASE CASE AND STANDARDS CASE FORECASTED EFFICIENCIES 

A key component of DOE’s estimates of NES and NPV is the energy efficiencies 

forecasted over time for the base case (without new standards) and each of the standards cases 

(with new standards). The forecasted efficiencies represent the annual shipment-weighted 

energy efficiency of the products under consideration over the forecast period (i.e., from the 

assumed effective date of a new standard to 30 years after the standard becomes effective). 

Because key inputs to the calculation of the NES and NPV are dependent on the estimated 

efficiencies, these efficiencies are of great importance to the analysis. In the case of the NES, the 

per-unit annual energy and water consumption is a direct function of product efficiency. Chapter 

6, Energy and Water Use Determination, describes how the per-unit energy and water 

consumption vary as a function of equipment efficiency. With regard to the NPV, two inputs, 

the per-unit total installed cost and the per-unit annual operating cost, are dependent on 

efficiency. The per-unit total installed cost is a direct function of efficiency while the per-unit 

annual operating cost, because it is a function of the per-unit annual and water consumption, is 

indirectly dependent on product efficiency. Section 8.2.1 of Chapter 8, Life-Cycle Cost (LCC) 

and Payback Period (PBP) Analysis, describes how per-unit total installed costs vary as a 

function of efficiency for each of the considered products. The above NES and NPV inputs, as 

well as all other inputs to the calculation of the NES and NPV, are also discussed below in 

sections 11.3.1 and 11.4.1. 

DOE based the development of the product efficiencies in the base case on the 

assignment of equipment efficiencies in the base case for the year 2009. In other words, DOE 

determined the distribution of product efficiencies currently in the marketplace to develop a 

shipment-weighted efficiency for the year 2009. For a complete discussion of the assignment of 

efficiencies in the base case for each of the considered products, refer to section 8.2.6 of Chapter 

8, LCC and PBP Analysis. 

Using the shipment-weight efficiency for the year 2009 as a starting point, DOE 

developed base case forecasted efficiencies based on assumptions regarding future efficiency 

growth. For the period spanning 2009–2013 (2013 being the assumed effective date of a new 

standard), DOE assumed that there would be no growth in the shipment-weighted efficiency (i.e., 

no change in the distribution of product efficiencies). Because there are no historical data to 

indicate how product efficiencies have changed over time, DOE estimated that forecasted 

efficiencies remained frozen at the 2013 efficiency level until the end of the forecast period (30 

years after the assumed effective date—the year 2043). Although DOE recognizes the 

possibility that product efficiencies may change over time, DOE does not want to speculate as to 

how these product efficiencies may change without historical information. 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

For its determination of standards-case forecasted efficiencies, DOE assumed a “roll-up” 

scenario to establish the shipment-weighted efficiency for the year that standards are assumed to 

become effective (i.e., 2013). DOE assumed that product efficiencies in the base case that did 

not meet the standard under consideration would “roll up” to meet the new standard level. Also, 

DOE assumed that all product efficiencies in the base case that were above the standard under 

consideration would not be affected. Using the shipment-weighted efficiency in the year 2013 as 

a starting point, DOE developed standards-case forecasted efficiencies based on assumptions 

regarding future efficiency growth. DOE made the same assumptions regarding standards-case 

efficiency growth rates as for the base case— namely, that forecasted efficiencies remain frozen 

at the 2013 efficiency level until the end of the forecast period. By maintaining the same growth 

rate for forecasted efficiencies in the standards case as in the base case (i.e., zero growth), DOE 

retained a constant efficiency difference or gap between the two cases over the length of the 

forecast period. Although frozen trends may not reflect what happens to base case and standards 

case product efficiencies in the future, DOE believes that maintaining a frozen efficiency 

difference between the base case and standards case provides a reasonable estimate of the impact 

that standards have on product efficiency. The NIA spreadsheet models for each of the 

considered products also incorporated user options of one percent and two percent for the growth 

rates of the base-case and standards-case forecasted efficiencies. 

Tables 11.2.1 and 11.2.2 show the base case and TSL product efficiency distributions in 

the year 2013, corresponding to the modified energy factor (MEF) and water factor (WF) of toploading and front-loading clothes washing equipment, respectively, that DOE used in its national 

impact analysis for commercial clothes washers. The TSLs are comprised of the candidate 

standard levels analyzed in the LCC and PBP Analysis. The TSLs are also shown in Tables 

11.2.1 and 11.2.2. Note that DOE considered all the candidate standard levels in the TSLs that it 

developed for commercial clothes washers. Also included in the table below is the SWEF 

associated with the base case and each TSL. 

Table 11.2.1	 Top-Loading Commercial Clothes Washers: Base Case and Standards Case 

Efficiency Distributions in 2013 

CSL TSL 

Efficiencies Market Shares 

Base Case 

Trial Standard Level 

MEF WF 1 2 3 4 5 

Baseline ­ 1.26 9.50 64.8% - - - - -

1 1, 2 1.42 9.50 33.8% 98.6% 98.6% - - -

2 3, 4, 5 1.60 8.50 1.4% 1.4% 1.4% 100% 100% 100% 

SWEF (MEF) 1.32 1.42 1.42 1.60 1.60 1.60 

SWEF (WF) 9.49 9.49 9.49 8.50 8.50 8.50 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

 

 

 

Table 11.2.2 Front-Loading Commercial Clothes Washers: Base Case and Standards 

Case Efficiency Distributions in 2013 

CSL TSL 

Efficiencies Market Shares 

Base Case 

Trial Standard Level 

MEF WF 1 2 3 4 5 

Baseline - 1.72 8.00 3.5% - ­ ­ - -

1 1 1.80 7.50 0.0% 3.5% - - - -

2 2, 3 2.00 5.50 73.7% 73.7% 77.2% 77.2% - -

3 4 2.20 5.10 22.8% 22.8% 22.8% 22.8% 100% -

4 5 2.35 4.40 0.0% 0.0% 0.0% 0.0% 0.0% 100% 

SWEF (MEF) 2.04 2.04 2.05 2.05 2.20 2.35 

SWEF (WF) 5.50 5.48 5.41 5.41 5.10 4.40 

Based on the assumption of a zero-percent growth rate in the forecasted efficiencies for 

the base case and all standards cases, DOE maintained the SWEFs shown above in Tables 11.2.1 

and 11.2.2 throughout the entire forecast period, i.e., from 2013 to 2043. 

11.3 NATIONAL ENERGY SAVINGS 

11.3.1 NES Definition 

As shown in the following equation, DOE calculates annual national energy savings as 

the difference between two projections: a base case (without new standards) and a standards 

case (with new standards). Positive values of NES correspond to energy savings (i.e., national 

energy consumption with standards is less than national energy consumption in the base case). 

_ NESy = AECBASE AEC STD 

Cumulative energy savings are the sum over the forecast period, extending from the 

assumed effective date, i.e., 2013, to 30 years after the effective date, i.e., 2043, of the annual 

national energy savings. This calculation is represented by the following equation: 

NES cum = ∑ NES y 

DOE calculated the national annual energy consumption by multiplying the number or 

stock of the given product (by vintage) by its unit energy consumption (also by vintage). The 

calculation of the national annual energy consumption is represented by the following equation: 

AEC = ∑STOCKV ×UECV 

For the above expressions, DOE defined the various quantities as follows: 

11-4 

EERE-2006-STD-0127 COMMENT 69.1
 

 

 

AEC = Annual national energy consumption each year in quadrillion British 

thermal units (Btus) – or quads, summed over vintages of the product stock, 

STOCKV, 

NES = Annual national energy savings (quads), 

STOCKV =	 Stock of product (millions of units) of vintage V surviving in the year for 

which DOE calculated annual energy consumption (vintages range from five 

to approximately 15.5 years, depending on the retirement function of the 

washer based on its product application), 

UECV = Annual energy consumption per product in either kilowatt-hours (kWh) or 

million Btus (MMBtu) (electricity and gas consumption are converted from 

site energy to source energy (quads) by applying a time-dependent 

conversion factor), 

V = Year in which the product was purchased as a new unit, and 

y = Year in the forecast (i.e., 2013 to 2043). 

The stock of equipment is dependent on annual shipments and the lifetime of the 

equipment. As described in Chapter 10, DOE conducted shipments projections under the base 

case and standards cases. DOE determined that the shipments projections under the standards 

cases were slightly lower than those in the base case projection, due to the higher purchase prices 

of the more-efficient equipment. In other words, DOE believes that the higher purchase prices 

would cause some consumers to forego new equipment purchases. 

DOE assumed that any drop in shipments caused by standards would result in the 

purchase of used machines. Therefore, DOE explicitly accounted for the energy and water 

consumption of the used washers in the standards cases. 

11.3.2 NES Inputs 

Table 11.3.1 lists the inputs for the determination of NES. 

Table 11.3.1 National Energy Saving Inputs 

Annual Energy Consumption per Unit (UEC) 

Shipments 

Equipment Stock (STOCKV) 

National Annual Energy Consumption (AEC) 

Site-to-Source Conversion Factor (src_conv) 

11.3.2.1 Annual Energy Consumption per Unit 

DOE presented the per-unit annual energy and water consumption as a function of 

product efficiency in both Chapter 6, Energy and Water Use Determination, and section 8.2.2.1 

of Chapter 8, LCC and PBP Analysis. Because the per-unit annual energy and water 

consumption is directly dependent on efficiency, DOE used the base case and standards case 

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EERE-2006-STD-0127 COMMENT 69.1
 

SWEFs presented above in section 11.2, in combination with the annual energy and water use 

data presented in Chapters 6 and 8, to estimate the shipment-weighted average annual per-unit 

energy and water consumption under the base case and standards cases. 

Using the relationship between clothes washer MEF and WF and annual energy and 

water consumption described in Chapter 8, Tables 11.3.2 and 11.3.3 present the per-unit annual 

electrical and gas energy use, and water consumption, based on the SWEFs corresponding to the 

base case and each TSL for top-loading and front-loading washers, respectively. Because 

establishments that use commercial clothes washers use either electric or gas water heaters and 

dryers, the per-unit annual energy use values in the table below are provided by fuel type. The 

energy and water use values shown in Tables 11.3.2 and 11.3.3 are weighted-average values 

reflecting the market share of washers in multi-family buildings (85 percent) and laundromats 

(15 percent), as provided by the Consortium for Energy Efficiency (CEE).3

 The water heating 

and drying energy consumption data reflect the percentage of gas and electric water heaters and 

dryers in the combined multi-family and laundromat market. Based on data from the CEE, in the 

combined market, 17 and 83 percent of water heaters are electric and gas, respectively, while 34 

and 66 percent of dryers are electric and gas, respectively.3 

As described in Chapter 10, section 10.3, DOE assumed that market share of washers in 

multi-family buildings and laundromats will remain constant at current levels. But because the 

assumed shares of laundromats and multi-family housing in shipments can have an effect on 

overall CCW shipments and, in turn, the NES and NPV results, DOE conducted a sensitivity 

analysis in which it used data from Alliance Laundry System’s 2008 10-K report, coupled with a 

number of assumptions, to estimate the shares of laundromats and multi-family housing in 

shipments of CCWs in 2008. The analysis, which is described in appendix 11C, yields an 

estimate of a 66 percent share for multi-family housing and a 34 percent share for laundromats. 

Table 11.3.2 Top-Loading Commercial Clothes Washers: Base Case and Standards Case 

Shipment-Weighted Average Per-Unit Annual Energy and Water 

Consumption in 2013 

Base 

Case 

Trial Standard Level 

1 2 3 4 5 

SWEF (MEF) 1.32 1.42 1.42 1.60 1.60 1.60 

SWEF (WF) 9.49 9.49 9.49 8.50 8.50 8.50 

Annual 

Energy Use 

Electric (kWh/yr) 950 902 902 812 812 812 

Gas (MMBtu/yr) 8.30 7.52 7.52 6.60 6.60 6.60 

Annual Water Use (1000 gal/ yr) 36.9 36.9 36.9 33.0 32.2 33.0 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

 

Table 11.3.3	 Front-Loading Commercial Clothes Washers: Base Case and Standards 

Case Shipment-Weighted Average Per-Unit Annual Energy and Water 

Consumption in 2013 

Base 

Case 

Trial Standard Level 

1 2 3 4 5 

SWEF (MEF) 2.04 2.04 2.05 2.05 2.20 2.35 

SWEF (WF) 5.50 5.48 5.41 5.41 5.10 4.40 

Annual 

Energy Use 

Electric (kWh/yr) 683 682 680 680 643 610 

Gas (MMBtu/yr) 4.96 4.94 4.92 4.92 4.51 4.19 

Annual Water Use (1000 gal/ yr) 21.4 21.3 21.0 21.3 19.8 17.1 

As noted above in section 11.2, DOE assumed that forecasted efficiencies in the base 

case and standards cases remain frozen at the efficiency levels in 2013. Therefore, because the 

per-unit annual energy and water consumption are a function of efficiency, DOE held the values 

shown above in Tables 11.3.2 and 11.3.3 constant over the forecast period (2013–2043). 

As described in section 10.4 of Chapter 10, Shipments Analysis, DOE forecasted a slight 

drop in commercial clothes washer shipments due to purchase price increases caused by 

standards-related efficiency increases. DOE assumed that those establishments forgoing the 

purchase of a commercial clothes washer due to standards would instead purchase a used clothes 

washer with an efficiency equal to the baseline level, i.e., 1.26 MEF/9.5 WF for top-loading 

washers and 1.72 MEF/8.0 WF for front-loading washers. In the NIA Model for commercial 

clothes washers, DOE accounted for the number of used washers purchased in order to quantify 

the energy and water impacts of those establishments that were estimated to forgo a new 

commercial clothes washer purchase. 

11.3.2.2 Shipments 

DOE forecasted shipments for the base case and all standards cases. Several factors, 

including total installed costs (purchase price plus installation costs), operating cost, household 

income, and equipment lifetime, all impact forecasted shipments. Of the above factors, total 

installed cost was the primary driver in forecasting the impact of standards on shipments. As 

noted earlier, the increased total installed cost of more-efficient equipment causes some 

customers to forego equipment purchases. Consequently, shipments forecasted under the 

standards cases are lower than under the base case. 

As described in Chapter 8, section 8.2.6 and Chapter 10, section 10.3, DOE estimated 

that 70 percent of the market is comprised of top-loading washers and 30 percent is comprised of 

front-loading washers. DOE estimated that the market share of top-loading and front-loading 

washers would remain fixed at 70 percent and 30 percent, respectively, through the forecast 

period. 

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EERE-2006-STD-0127 COMMENT 69.1
 

As detailed in Chapter 10, section 10.3, DOE based its Shipments Model on the 

assumption that the relative market shares of the two product applications, laundromats and 

common-area laundry facilities in multi-family housing, are constant over time. DOE did not 

have sufficient data to forecast whether the market shares of laundromats and multi-family 

housing will vary over time. Therefore, DOE assumed that market shares will remain constant at 

current levels. DOE relied on a report from CEE to estimate that multi-family buildings and 

laundromats comprise 85 percent and 15 percent of the commercial clothes washer market, 

respectively. As noted above in section 11.3.2.1, because the assumed shares of laundromats and 

multi-family housing in shipments can have an effect on overall CCW shipments and, in turn, the 

NES and NPV results, DOE conducted a sensitivity analysis to estimate the shares of 

laundromats and multi-family housing in shipments of CCWs in 2008. The analysis, which is 

described in appendix 11C, yields an estimate of a 66 percent share for multi-family housing and 

a 34 percent share for laundromats. 

An extensive description of the methodology for conducting and generating the 

shipments forecasts for each of the considered products can be found in Chapter 10, Shipments 

Analysis. 

11.3.2.3 Equipment Stock 

The equipment stock in a given year is the number of products shipped from earlier years 

that survive in the given year. The NIA Models keep track of the number of units shipped each 

year. DOE assumes that the products have an increasing probability of retiring as they age. The 

probability of survival as a function of years-since-purchase is the survival function. See 

Chapter 10, Shipments Analysis, for further details on the survival functions that DOE used in its 

analysis. 

11.3.2.4 National Annual Energy Consumption 

The national annual energy consumption is the product of the annual energy consumption 

per unit and the number of units of each vintage. This approach accounts for differences in unit 

energy consumption from year to year. The equation for determining the annual energy 

consumption was shown above in section 11.3.1 and is repeated below. 

AEC = ∑STOCKV ×UECV 

In determining national annual energy consumption, DOE initially calculated the annual 

energy consumption at the site, and then applied a conversion factor to calculate primary energy 

consumption (see section 11.3.2.5). 

11.3.2.5 Energy Site-to-Source Conversion Factors 

In determining national annual energy consumption, DOE initially calculated the annual 

energy consumption at the site (e.g., for electricity, the energy in kWh consumed at the 

11-8 

EERE-2006-STD-0127 COMMENT 69.1
household or establishment). It then calculated primary (source) energy consumption from site 

energy consumption by applying a conversion factor to account for losses associated with the 

generation, transmission, and distribution of electricity and gas. The site-to-source conversion 

factor is the multiplicative factor used for converting site energy consumption into primary or 

source energy consumption, expressed in quads. DOE used annual site-to-source conversion 

factors based on the version of the National Energy Modeling System (NEMS) that corresponds 

to the DOE-Energy Information Administration’s (EIA) Annual Energy Outlook 2008 

(AEO2008).4

 The factors used are marginal values, which represent the response of the system to 

an incremental decrease in consumption. Natural gas losses include pipeline leakage, pumping 

energy, and transportation fuel. The AEO2008 forecasts losses of about seven percent for the 

natural gas used on site, with only slight variation from year to year. For electricity, the 

conversion factors vary over time, due to projected changes in generation sources (i.e., the power 

plant types projected to provide electricity to the country). DOE assumed that conversion factors 

remain constant at 2030 values throughout the remainder of the forecast. Table 11.3.4 shows the 

site-to-source conversion factors from 2005 to the end of the forecast period (2043). 

Table 11.3.4 Site-to-Source Conversion Factors for Electricity and Natural Gas 

Year 

Electricity 

Btu/kWh 

Natural Gas 

Btu/Btu Year 

Electricity 

Btu/kWh 

Natural Gas 

Btu/Btu 

2005 11500 1.085 2019 7917 1.087 

2006 11500 1.085 2020 7917 1.091 

2007 11200 1.085 2021 7900 1.094 

2008 10250 1.082 2022 7557 1.094 

2009 10000 1.084 2023 6765 1.094 

2010 10000 1.086 2024 6327 1.095 

2011 10000 1.086 2025 6327 1.095 

2012 10000 1.086 2026 6327 1.095 

2013 10000 1.087 2027 6327 1.096 

2014 9500 1.086 2028 6327 1.096 

2015 7917 1.086 2029 6327 1.096 

2016 7917 1.087 2030 7917 1.087 

2017 7917 1.086 2031–2043 7917 1.091 

2018 7917 1.086 

Source: NEMS, 2008. 

11.4 NET PRESENT VALUE 

11.4.1 NPV Definition 

The NPV is the value in the present of a time series of costs and savings. The NPV is 

described by the equation: 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

 

_ NPV = PVS PVC 

where: 

PVS = Present value of operating cost savings (including energy, water, repair, and 

maintenance costs), and 

PVC = Present value of increased total installed costs (including equipment and 

installation). 

DOE determined the PVS and PVC according to the following expressions: 

PVS = ∑OCSy × DFy 

PVC = ∑TICy × DFy 

DOE calculated the total annual operating cost savings by multiplying the number or 

stock of the given product (by vintage) by its per-unit operating cost savings (also by vintage). 

DOE calculated the total annual installed cost increases by multiplying the number or stock of 

the given product (by vintage) by its per-unit total installed cost increase (also by vintage). The 

calculation of the annual operating costs savings and total annual installed cost increases is 

represented with the following equations: 

OCS y = ∑STOCKV ×UOCSV 

TIC y = ∑STOCKV ×UTICV 

For the above expressions, DOE defined the various quantities as follows: 

OCS = Total annual operating cost savings each year summed over vintages of the 

product stock, STOCKV, 

TIC = Total annual installed cost increases each year summed over vintages of the 

product stock, STOCKV, 

DF = Discount factor in each year, 

STOCKV = Stock of product (millions of units) of vintage V surviving in the year for 

which DOE calculated annual energy consumption (vintages range from five 

to approximately 15.5 years, depending on the retirement function of the 

washer based on its product application), 

UOCSV = Annual operating cost savings per unit, 

UTICV = Annual total installed cost increase per unit, 

V = Year in which the product was purchased as a new unit, and 

y = Year in the forecast (i.e., 2013 to 2043). 

11-10 

EERE-2006-STD-0127 COMMENT 69.1
DOE determined the PVC for each year, from the effective date of the standard to the 

year 2043. It determined the PVS for each year, from the effective date of the standard to the 

year when units purchased in 2043 retire. DOE calculated costs and savings as the difference 

between a standards case and a base case (i.e., without new standards). 

DOE calculated a discount factor from the discount rate and the number of years between 

the “present” (i.e., year to which the sum is being discounted) and the year in which the costs and 

savings occur. The NPV is the sum over time of the discounted net savings. 

11.4.2 NPV Inputs 

Table 11.4.1 summarizes the inputs to the NPV calculation. 

Table 11.4.1 Net Present Value Inputs 

Total Installed Cost per Unit 

Annual Operating Cost Savings per Unit 

Total Annual Installed Cost Increases 

Total Annual Operating Costs 

Discount Factor 

Present Value of Costs 

Present Value of Savings 

The increase in the total annual installed cost is equal to the annual change in the per-unit 

total installed cost (difference between base case and standards case) multiplied by the shipments 

forecasted in the standards case. As with the calculation of the NES, DOE assumed that any 

drop in shipments caused by standards would result in the purchase of used machines. 

The total annual operating cost savings are equal to the change in the annual operating 

costs (difference between base case and standards case) per unit multiplied by the shipments 

forecasted in the standards case. The annual operating cost includes energy, water, repair, and 

maintenance costs. 

11.4.2.1 Total Installed Cost per Unit 

DOE first presented the per-unit total installed cost as a function of product efficiency in 

section 8.2.1.5 of Chapter 8, LCC and PBP Analysis. Because the per-unit total annual installed 

cost is directly dependent on efficiency, DOE used the base case and standards case SWEFs 

presented above in section 11.2, in combination with the total installed costs presented in 

Chapter 8, to estimate the shipment-weighted average annual per-unit total installed cost under 

the base case and standards cases. 

11-11 

EERE-2006-STD-0127 COMMENT 69.1
 

The total installed cost includes both the equipment price and the installation cost. DOE 

based average equipment prices on average manufacturer costs multiplied by average overall 

markup values. Using the relationship between commercial clothes washer MEF and WF and 

total installed cost presented in Chapter 8, Tables 11.4.2 and 11.4.3 show the per-unit total 

installed cost based on the SWEFs corresponding to the base case and each TSL for top-loading 

and front-loading washers, respectively. 

Table 11.4.2	 Top-Loading Commercial Clothes Washers: Base Case and Standards Case 

Shipment-Weighted Average Per-Unit Total Installed Costs in 2013 

Base Case 

Trial Standard Level 

1 2 3 4 5 

SWEF (MEF) 1.32 1.42 1.42 1.60 1.60 1.60 

SWEF (WF) 9.49 9.49 9.49 8.50 8.50 8.50 

Total Installed Cost (2008$) $805 $885 $885 $975 $975 $975 

Table 11.4.3 Front-Loading Commercial Clothes Washers: Base Case and Standards 

Case Shipment-Weighted Average Per-Unit Total Installed Costs in 2013 

Base Case 

Trial Standard Level 

1 2 3 4 5 

SWEF (MEF) 2.04 2.04 2.05 2.05 2.20 2.35 

SWEF (WF) 5.50 5.48 5.41 5.41 5.10 4.40 

Total Installed Cost (2008$) $1,398 $1,398 $1,399 $1,399 $1,429 $1,472 

As noted above in section 11.2, DOE assumed that forecasted efficiencies in the base 

case and TSLs remain frozen at the efficiency levels in 2013. Therefore, because the per-unit 

total installed costs are a function of efficiency, DOE held the values shown above in Tables 

11.4.2 and 11.4.3 constant over the forecast period (2013–2043). 

11.4.2.2 Annual Operating Cost Savings per Unit 

The per-unit annual operating cost includes the energy, water, repair, and maintenance 

costs. 

Annual Energy and Water Costs 

DOE determined the per-unit annual energy and water cost savings by taking the per-unit 

annual energy (and water) consumption savings developed for each product and multiplying it by 

the appropriate energy (and water) price. 

For all of the considered products, estimates of the per-unit annual energy and water 

consumption for the base case and each standards case were presented earlier in section 11.3.2.1. 

As described previously, DOE forecasted the per-unit annual energy (and water) consumption 

for the base case and each standards case for all products by freezing the consumption at levels 

estimated for the year 2013. 

11-12 

EERE-2006-STD-0127 COMMENT 69.1
 

 

Energy and water prices are described in section 8.2.2.2 of Chapter 8. DOE forecasted 

energy prices based on EIA’s AEO2009.

5

 DOE forecasted water prices based on trends in the 

national water price index as provided by the Bureau of Labor Statistics.6

 The energy and water 

price trends are described in section 8.2.2.3 of Chapter 8. 

Annual Repair and Maintenance Costs 

As described in section 8.2.2.4 of Chapter 8, DOE estimated increased repair and 

maintenance costs for commercial clothes washers. DOE estimated that repair costs would 

increase as a function of equipment efficiency. Using the relationship between clothes washer 

MEF and WF and repair described in Chapter 8, Tables 11.4.4 and 11.4.5 present the per-unit 

annualized repair cost based on the SWEFs corresponding to the base case and each TSL for toploading and front-loading washers, respectively. The repair costs shown in Tables 11.4.4 and 

11.4.5 are weighted-average values reflecting the market share of washers in multi-family 

buildings (85 percent) and laundromats (15 percent), as provided by the Consortium for Energy 

Efficiency (CEE). 

Table 11.4.4	 Top-Loading Commercial Clothes Washers: Base Case and Standards Case 

Shipment-Weighted Average Per-Unit Annualized Repair Costs in 2013 

Base Case 

Trial Standard Level 

1 2 3 4 5 

SWEF (MEF) 1.32 1.42 1.42 1.60 1.60 1.60 

SWEF (WF) 9.49 9.49 9.49 8.50 8.50 8.50 

Annualized Repair Cost (2008$) $30 $34 $34 $38 $38 $38 

Table 11.4.5 Front-Loading Commercial Clothes Washers: Base Case and Standards 

Case Shipment-Weighted Average Per-Unit Annualized Repair Costs in 2013 

Base Case 

Trial Standard Level 

1 2 3 4 5 

SWEF (MEF) 2.04 2.04 2.05 2.05 2.20 2.35 

SWEF (WF) 5.50 5.48 5.41 5.41 5.10 4.40 

Annualized Repair Cost (2008$) $58 $58 $58 $58 $60 $62 

As noted above in section 11.2, DOE assumed that forecasted efficiencies in the base 

case and TSLs remain frozen at the efficiency levels in 2013. Therefore, because the per-unit 

total installed costs are a function of efficiency, DOE held the values shown above in Tables 

11.4.4 and 11.4.5 constant over the forecast period (2013–2043). 

11.4.2.3 Total Annual Installed Cost Increases 

The total annual installed cost increase for any given standards case is the product of the 

total installed cost increase per unit due to the standard and the number of units of each vintage. 

This approach accounts for differences in total installed cost from year to year. The equation for 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

 

 

 

determining the total annual installed cost increase for a given standards case was shown in 

section 11.4.1 and is repeated below. 

TIC = ∑STOCKV ×UTICV 

As noted earlier for commercial clothes washers, DOE accounted for the total installed 

cost of those establishments that were forced into purchasing used clothes washers due to 

standards. Therefore, the total annual installed cost increase takes into account the total installed 

cost of the used washers that were purchased in lieu of the purchase of new washers. 

11.4.2.4 Total Annual Operating Cost Savings 

The total annual operating cost savings for any given standards case is the product of the 

annual operating cost savings per unit due to the standard and the number of units of each 

vintage. This approach accounts for differences in annual operating cost savings from year to 

year. The equation for determining the total annual operating cost savings for a given standards 

case was shown above and is repeated below. 

OCS = ∑STOCKV ×UOCSV 

As noted earlier, DOE accounted for the energy and water use of those establishments 

that were forced into purchasing used washers due to standards. Therefore, the total annual 

operating cost savings take into account the energy and water costs of the used washers that were 

purchased in lieu of the purchase of new washers. 

11.4.2.5 Discount Factors 

DOE multiplies monetary values in future years by a discount factor to determine the 

present value. The discount factor (DF) is described by the equation: 

1

DF = _ ( y yp ) (1+ r ) 

where: 

r = discount rate, 

y = year of the monetary value, and 

yP = year in which the present value is being determined. 

DOE estimated national impacts with both a three-percent and a seven-percent real 

discount rate as the average real rate of return on private investment in the U.S. economy. It 

used these discount rates in accordance with the Office of Management and Budget (OMB)’s 

guidance to Federal agencies on the development of regulatory analysis (OMB Circular A-4, 

11-14 

EERE-2006-STD-0127 COMMENT 69.1
September 17, 2003), and section E., “Identifying and Measuring Benefits and Costs,” therein. 

DOE defines the present year as 2009. 

11.4.2.6 Present Value of Costs 

The present value of increased installed costs is the annual installed cost increase in each 

year (i.e., the difference between the standards case and base case), discounted to the present, 

and summed for the time period over which DOE is considering the installation of equipment 

(i.e., from the effective date of standards, 2013, to the year 2043). 

The increase in total installed cost refers to both equipment cost and installation cost 

associated with the higher energy efficiency of equipment purchased in the standards case 

compared to the base case. DOE calculated annual increases in installed costs as the difference 

in total installed cost for new equipment purchased each year, multiplied by the shipments in the 

standards case. 

11.4.2.7 Present Value of Savings 

The present value of operating cost savings is the annual operating cost savings (i.e., the 

difference between the base case and standards case) discounted to the present, and summed over 

the period from the effective date, 2013, to the time when the last unit installed in 2043 is retired 

from service. 

Savings are decreases in operating costs (including electricity, repair, and maintenance 

costs) associated with the higher energy efficiency of equipment purchased in the standards case 

compared to the base case. Total annual operating cost savings are the savings per unit 

multiplied by the number of units of each vintage surviving in a particular year. Equipment 

consumes energy over its entire lifetime, and for units purchased in 2043, the consumption 

includes energy consumed until the unit is retired from service. 

11.5 NES AND NPV RESULTS 

The NIA Model provides estimates of the NES and NPV due to various candidate 

standards levels. The inputs to the NIA Model have been discussed earlier in sections 11.3.2 

(NES Inputs) and 11.4.2 (NPV Inputs). DOE generated the NES and NPV results using a 

Microsoft Excel® spreadsheet, which is accessible on the Internet 

(http://www.eere.energy.gov/buildings/appliance_standards/). Details and instructions for using 

the spreadsheet are provided in Appendix 11A. 

11.5.1 NES and NPV Input Summary 

Table 11.5.1 summarizes the inputs to the NIA Model. For each input a brief description 

of the data source is given. 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

Table 11.5.1 NES and NPV Inputs 

Input Data Description 

Shipments Annual shipments from Shipments Model. (See Chapter 10.) 

Effective Date of Standard 2013. 

Base Case Forecasted Efficiencies SWEF determined in the year 2009. SWEF held constant over 

forecast period of 2009–2042. (See Section 11.2.) 

Standards Case Efficiencies Roll-up scenario assumed for determining SWEF in the year 2013 for 

each standards case and for each of the considered products. SWEF 

held constant over forecast period of 2013–2043. (See Section 11.2.) 

Annual Energy Consumption per Unit Annual weighted-average values are a function of SWEF. (See 

Section 11.3.2.1.) 

Total Installed Cost per Unit Annual weighted-average values are a function of SWEF. (See 

Section 11.4.2.1.) 

Energy and Water Cost per Unit Annual weighted-average values are a function of the annual energy 

consumption per unit and energy (and water) prices. (See Section 

8.2.2.3 of Chapter 8 for energy and water prices.) 

Repair Cost and Maintenance Cost per Unit Annual weighted-average values are a function of SWEF. (See 

Section 8.2.2.4 of Chapter 8 for repair and maintenance costs.) 

Escalation of Energy and Water Prices Energy Prices: EIA AEO2009 forecasts (to 2030) and extrapolation to 

2043. (See Section 8.2.2.3 of Chapter 8.) 

Water Prices: Linear extrapolation off historical trend in national 

water price index. (See Section 8.2.2.3 of Chapter 8.) 

Energy Site-to-Source Conversion Conversion varies yearly and is generated by DOE/EIA’s NEMS* 

program (a time series conversion factor; includes electric generation, 

transmission, and distribution losses). 

Discount Rate 3 percent and 7 percent real. 

Present Year Future expenses are discounted to year 2009. 

* Chapter 14 on the Utility Impact Analysis and the Environmental Assessment Report provide more detail on NEMS. 

11.5.2 NES Results 

The following sections provide NES results and national water savings (NWS) results for 

the TSLs analyzed for commercial clothes washers. NES results are cumulative to 2043 and are 

shown as primary energy savings. NWS results are expressed in billions of gallons. DOE based 

the inputs to the NIA Model on weighted-average values, yielding results that are discrete point 

values, rather than a distribution of values as in the LCC and PBP Analysis. 

Table 11.5.2 shows the NES and NWS results for the TSLs analyzed for commercial 

clothes washers. The results are based on the estimate that multi-family buildings and 

laundromats comprise 85 percent and 15 percent of the commercial clothes washer market, 

respectively. As noted earlier in section 11.3.2.1, because the assumed shares of laundromats and 

multi-family housing in shipments can have an effect on overall CCW shipments and, in turn, the 

NES and NPV results, DOE conducted a sensitivity analysis to estimate the shares of 

laundromats and multi-family housing in shipments of CCWs in 2008. The analysis, which is 

described in appendix 11C, yields an estimate of a 66 percent share for multi-family housing and 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

 

 

 

 

 

 

a 34 percent share for laundromats. The impact of the sensitivity on NES and NWS is nine 

percent and approximately 10 percent, respectively. 

Table 11.5.2	 Commercial Clothes Washers: Cumulative NES and NWS Results 

Top-Loading Washers Front-Loading Washers 

NWS NWS 

NES billion NES billion 

CSL TSL MEF/WF quads gallons TSL MEF/WF quads gallons 

1 1, 2 1.42/9.50 0.04 0 1 1.80/7.50 0.00 1 

2 3, 4, 5 1.60/8.50 0.10 135 2, 3 2.00/5.50 0.00 6 

3 4 2.20/5/10 0.01 26 

4 5 2.35/4.40 0.02 72 

Table 11.5.3 shows the magnitude of the NES and NWS if the savings are discounted at 

rates of seven percent and three percent. 

Table 11.5.3	 Commercial Clothes Washers: Cumulative NES and NWS Results 

Discounted at Seven Percent and Three Percent 

CSL 

Top-Loading Washers Front-Loading Washers 

TSL MEF/WF 

7% Disc Rate 3% Disc Rate 

TSL MEF/WF 

7% Disc Rate 3% Disc Rate 

NES 

quads 

NWS 

billion 

gallons 

NES 

quads 

NWS 

billion 

gallons 

NES 

quads 

NWS 

billion 

gallons 

NES 

quads 

NWS 

billion 

gallons 

1 1, 2 1.42/9.50 0.01 0 0.02 0 1 1.80/7.50 0.00 0 0.00 1 

2 3, 4, 5 1.60/8.50 0.03 37 0.05 75 2, 3 2.00/5.50 0.00 2 0.00 3 

3 4 2.20/5/10 0.00 7 0.01 14 

4 5 2.35/4.40 0.01 19 0.01 39 

11.5.3 Annual Costs and Savings 

To illustrate the basic inputs to the NPV calculations, Figure 11.5.1 presents the nondiscounted annual installed cost increases and annual operating cost savings at the national level 

for TSL 3 for top-loading washers. The figure also shows the net savings, which is the 

difference between the savings and costs for each year. The annual equipment cost is the 

increase in the total installed cost for products purchased each year over the period 2013–2043. 

The annual operating cost savings is the savings in operating costs for products operating in each 

year. The NPV is the difference between the cumulative annual discounted savings and the 

cumulative annual discounted costs. DOE could create figures like the one shown below for 

each of the standard cases. 

11-17 

EERE-2006-STD-0127 COMMENT 69.1
 

-0.025 

0.000 

0.025 

0.050 

0.075 

0.100 

2013 2016 2019 2022 2025 2028 2031 2034 2037 2040 2043 2046 2049 2052 2055 2058 

Year 

Billion of 2008 Dollars 

Equipmetnt Cost 

Operating Cost Savings 

Net Savings 

Figure 11.5.1	 Non-Discounted Annual Installed Cost Increases and Annual Operating 

Cost Savings for Top-Loading Clothes Washers, TSL 3 

11.5.4 NPV Results 

The following sections provide NPV results for the candidate standards levels considered 

for the product classes of commercial clothes washers. Results are cumulative and are shown as 

the discounted value of these savings in dollar terms. DOE based the inputs to the NIA Model 

on weighted-average values, yielding results that are discrete point values, rather than a 

distribution of values as in the LCC and PBP Analysis. 

The present value of increased total installed costs is the total annual installed cost 

increase (i.e., the difference between the standards case and base case), discounted to the present, 

and summed over the time period in which DOE evaluates the impact of standards (i.e., from the 

effective date of standards, 2013, to the year 2043). 

Savings are decreases in operating costs (including energy and water) associated with the 

higher energy efficiency of equipment purchased in the standards case compared to the base 

case. Total operating cost savings are the savings per unit multiplied by the number of units of 

each vintage (i.e., the year of manufacture) surviving in a particular year. Equipment consumes 

energy and must be maintained over its entire lifetime. For units purchased up through 2043, the 

operating cost includes energy and water consumed until the last unit is retired from service. 

11-18 

EERE-2006-STD-0127 COMMENT 69.1
 

 

 

NPV results based on discount rates of seven percent and three percent are provided for 

the standard levels considered for commercial clothes washers. Table 11.5.4 shows the NPV 

results for the candidate standard levels. Under the base case (i.e., without standards), the 

cumulative national equipment and operating costs of commercial clothes washers based on a 

seven-percent discount rate equal $2.0 billion and $9.7 billion, respectively. Based on a threepercent discount rate, the cumulative national equipment and operating costs equal $3.6 billion 

and $19.2 billion, respectively. Detailed results showing the breakdown of the NPV into 

national equipment costs and national operating costs are provided in Appendix 11B. 

The results in Table 11.5.4 are based on the estimate that multi-family buildings and 

laundromats comprise 85 percent and 15 percent of the commercial clothes washer market, 

respectively. As noted earlier in section 11.3.2.1, because the assumed shares of laundromats and 

multi-family housing in shipments can have an effect on overall CCW shipments and, in turn, the 

NES and NPV results, DOE conducted a sensitivity analysis to estimate the shares of 

laundromats and multi-family housing in shipments of CCWs in 2008. The analysis, which is 

described in appendix 11C, yields an estimate of a 66 percent share for multi-family housing and 

a 34 percent share for laundromats. For TSLs 3, 4, and 5, the impact of the sensitivity on NPV is 

approximately 14 percent based on a seven-percent discount rate and approximately 11 percent 

based on a three-percent discount rate. 

Table 11.5.4	 Commercial Clothes Washers: Cumulative NPV Results based on SevenPercent and Three-Percent Discount Rates 

Top-Loading Washers Front-Loading Washers 

NPV @ 

7% 

Billion 

NPV @ 

3% 

Billion 

NPV @ 7% 

Billion 

NPV @ 3% 

Billion 

CSL TSL MEF/WF 2008$ 2008$ TSL MEF/WF 2008$ 2008$ 

1 1, 2 1.42/9.50 0.01 0.07 1 1.80/7.50 0.004 0.01 

2 3, 4, 5 1.60/8.50 0.34 0.86 2, 3 2.00/5.50 0.01 0.03 

3 4 2.20/5/10 0.07 0.17 

4 5 2.35/4.40 0.17 0.39 

11.6	 IMPACT OF STANDARDS ON NATURAL GAS AND ELECTRICITY 

PRICES AND ASSOCIATED CONSUMER BENEFITS 

11.6.1 Impact on Natural Gas Prices 

DOE conducted an analysis on the potential impact on natural gas prices resulting from 

the promulgation of new standards on commercial clothes washers at maximum technologically 

feasible (i.e., “Max Tech”) standard levels. “Max Tech” standard levels correspond to TSL 5 for 

commercial clothes washers. The analysis used a version of NEMS called NEM-BT, modified to 

account for energy savings associated with the proposed standards. As described in Chapter 14 

on the utility impact analysis, using NEMS-BT for such an analysis typically involves using 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

 

higher-decrement runs to isolate the impacts of the standards from numerical noise. DOE 

derived the price effect results associated with the energy savings resulting from the Max Tech 

standards using a regressed interpolation toward the origin. 

Figure 11.6.1 shows the change in total natural gas consumption for the year 2030 (on the 

x-axis) resulting from Max Tech standard levels and the corresponding change in U.S. average 

wellhead natural gas price (on the y-axis). The points in Figure 11.6.1 that are labeled with 

“100x” and “125x” represent the results for a series of higher decrement runs assuming various 

multiples of the savings resulting from the Max Tech scenarios. Each scenario has multiple 

points that represent the results using the Annual Energy Outlook (AEO ) 2008 Reference Case.7 

The interpolated results for the Max Tech standard level is shown in the upper right hand corner 

of Figure 11.6.1. For the Max Tech standard level, NEMS predicts that the 2030 average 

wellhead natural gas price will remain unchanged for commercial clothes washer standards. As 

shown in Table 11.6.1, relative to AEO 2008 Reference Case values, the forecasted wellhead 

price decline in 2030 is zero percent. Other outputs from NEMS show that the predicted 

reduction in the average-customer natural gas price in 2030 is also unchanged.a 

Because the results shown in Table 11.6.1 show that commercial clothes washer energy 

efficiency standards at the Max Tech level have no impact on average well head prices, 

efficiency standards for commercial clothes washers, even at the Max Tech level, will have no 

effect on natural gas consumer prices. 

a

 The main customer sectors are electric power, industry, residential and commercial. 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

CLW Max Std 

100xCLW 

125xCLW 

-0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 

Change in Total Natural Gas Consumption (Quads) 

0.02 

Change in Wellhead Natural Gas Price (2006 

$/MBtu) 

0.00 

-0.02 

-0.04 

-0.06 

-0.08 

-0.10 

0.0 

Figure 11.6.1	 Wellhead Natural Gas Price Change in 2030 Resulting from 

Reduced Natural Gas Consumption Associated with Max Tech 

Standard Level 

Table 11.6.1	 Impact of Max Tech Standard Levels on Natural Gas Consumption and 

Average Wellhead Price in 2030 

No-Standard Case Max Tech Scenario Result 

Nat Gas 

Consumption 

Nat Gas 

Price 

Nat Gas 

Consumption 

Change in 

Consumption 

Nat Gas 

Price 

Change in 

Price 

Quads 

2006$/ 

MMBtu Quads Quads % 

2006$/ 

MMBtu 

2006$/ 

MMBtu % 

Commercial 

Clothes Washer 

Max Tech 

21.4 6.63 21.4 0.00 0.0 6.63 0.00 0.0 

The inverse price elasticity seen in NEMS to estimate the effect of consumption on price 

varies over the forecast period due to the dynamics of natural gas supply and demand in NEMS 

11-21 

EERE-2006-STD-0127 COMMENT 69.1
 

(Figure 11.6.2).b The average value over the forecast period is 0.02 for commercial clothes 

washer standards. 

-0.50 

-0.40 

-0.30 

-0.20 

-0.10 

0.00 

0.10 

0.20 

0.30 

Inverse Price Elasticity 

2015201620172018201920202021202220232024202520262027202820292030 

Year 

Figure 11.6.2	 Inverse Natural Gas Price Elasticity from NEMS Analysis for Commercial 

Clothes Washer Max Tech Standard Level 

The average inverse price elasticity (0.02) reported above is generally consistent with 

other studies that used various versions of NEMS to examine the impacts to natural gas prices 

resulting from reductions in natural gas demand. In a review of a number of such studies, Wiser 

and Bollinger8

 examined analyses that reported the reduction in national natural gas demand 

from certain energy policies and the resulting decline in the wellhead gas price. Examining the 

average values of the inverse price elasticity over the forecast period in each study, they found 

the average values to range from 0.7 to 4.7. It is important to note that the average inverse price 

elasticities in 13 of 19 analyses were between 0.8 and 2.0, and the average value from DOE's 

current analysis falls below this range. 

Although NEMS provides a detailed characterization of natural gas supply, it is 

understandable that NEMS may not accurately represent the long-run supply of natural gas of the 

country since all aspects of the future are not certain. However, other widely used complex 

energy demand/supply models produce results that are similar to NEMS results, and NEMS is 

recognized as a reliable analytical tool. Table 11.6.2 compares the results of modeling studies of 

the response of natural gas price to change in gas consumption. These results are summarized in 

a 2003 study by Stanford's Energy Modeling Forum.9

 While the magnitude of the price response 

b

 Since the demand reduction in the early years after the standard takes effect is small, the model results for those 

years may be less accurate than in later years. 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

 

 

 

(as summarized by the inverse price elasticity) varies considerably among the models reviewed, 

in general, they confirm that a sizable price impact is associated with changes in natural gas 

consumption.c It is worth noting that the NEMS long-run (2020) response is smaller than that of 

most of the other models. 

Table 11.6.2 Implicit Natural Gas Inverse Price Elasticity from Seven Energy Models 

2005 2010 2015 2020 Average 

NEMS 1.8 2.2 0.53 0.11 1.2 

POEMS 2.4 1.8 2.5 1.8 2.1 

CRA 3.5 2.5 1.1 0.9 2.0 

NANGAS 5.4 7.0 7.6 5.1 6.3 

E2020 1.5 1.0 1.0 0.7 1.1 

MARKAL N/A 2.0 N/A 2.1 2.1 

NARG 8.7 12.4 5.6 2.4 7.3 

NEMS (National Energy Modeling System, 2002); POEMS (Policy Office Electricity Modeling System), CRA 

(Charles River Associates), NANGAS (North American Natural Gas Analysis System), E2020 (Energy 2020), 

MARKAL (MARKet ALlocation), NARG (North American Regional Gas model) 

Source: Based on EMF, 2003 

In addition to the models listed in Table 11.6.2, there exist studies conducted by the 

National Petroleum Council10 and the National Commission on Energy Policy11 that are based on 

the EEA model. The EEA model shows higher inverse price elasticities (between 4.0 and 16.8), 

leading to larger natural gas price reductions for a given demand decrease, than those predicted 

by NEMS and most of the other national energy models. 

11.6.2 Impact on Electricity Prices 

DOE also conducted an analysis on the potential impact on electricity prices resulting 

from the promulgation of new standards on commercial clothes washers at maximum 

technologically feasible (i.e., “Max Tech”) standard levels. “Max Tech” standard levels 

correspond to TSL 5 for commercial clothes washers. The analysis used a version of NEMS 

called NEMS-BT, modified to account for energy savings associated with the proposed 

standards. Again, using NEMS-BT for such an analysis typically involves using higherdecrement runs to isolate the impacts of the standards from numerical noise. DOE derived the 

price effect results associated with the energy savings resulting from the Max Tech standards 

using a regressed interpolation toward the origin. 

Figure 11.6.3 shows the change in total electric power consumption for the year 2030 (on 

the x-axis) resulting from Max Tech standard levels and the corresponding change in U.S. 

c

 The EMF scenarios actually modeled the impact of increased gas demand on price. Assuming a smooth supply 

curve over the long term, however, the elasticities implied by an increase in demand should be essentially equivalent 

to those implied by a decrease in demand. Two of the models (NANGAS and NARG) report somewhat anomalous 

inverse elasticities for undetermined reasons. 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

average electricity price (on the y-axis). The points in Figure 11.6.3 that are labeled with 

“100x”, “125x”, or “150x” represent the results for a series of higher decrement runs assuming 

various multiples of the savings resulting from the Max Tech scenarios. Decrement runs for 

commercial clothes washers are labeled as “CLW”. Each scenario has multiple points that 

represent the results using the Annual Energy Outlook (AEO) 2008 Reference Case.4 The 

interpolated results for the Max Tech standard level is shown in the upper right hand corner of 

Figure 11.6.3. For the Max Tech standard levels, NEMS predicts that the 2030 average 

electricity price will remain unchanged for commercial clothes washer standards. As shown in 

Table 11.6.3, relative to AEO 2008 Reference Case values, the forecasted electricity price 

decline in 2030 is zero percent. Other outputs from NEMS show that the predicted reduction in 

the average-customer electricity price in 2030 is also unchanged.d 

Because the results shown in Table 11.6.3 show that commercial clothes washer energy 

efficiency standards at the Max Tech level have no impact on average electricity prices, 

efficiency standards for commercial clothes washers, even at the Max Tech level, will have no 

effect on the average electricity price to end users. 

125xCLW 100xCLW 

150xCLW 

0.08 

0.07 

0.06 

0.05 

0.04 

0.03 

0.02 

0.01 

0.00 

$/MBtu) 

CLW Max Std -5.0 -4.0 -3.0 -2.0 -1.0 0.0 

Change in Total Electricity Consumption (Quads) 

Change in Electricity Price (2006-

Figure 11.6.3	 Electricity Price Change in 2030 Resulting from Reduced Electricity 

Consumption Associated with Max Tech Standard Level 

d

 The main customer sectors are electric power, industry, residential and commercial. 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

 

 

Table 11.6.3 Impact of Max Tech Standard Levels on Electricity Consumption and Price 

in 2030 

No-Standard Case Max Tech Scenario Result 

Electricity 

Consumption 

Electricity 

Price 

Electricity 

Consumption 

Change in 

Consumption 

Electricity 

Price 

Change in 

Price 

Quads 

2006$/ 

MMBtu Quads Quads % 

2006$/ 

MMBtu 

2006$/ 

MMBtu % 

Commercial 

Clothes Washer 

Max Tech 

49.21 25.93 49.19 -0.02 -0.02% 25.93 0.00 0.0 

The inverse price elasticity seen in NEMS is used to estimate the effect of consumption 

on price varies over the forecast period due to the dynamics of energy supply and demand in 

NEMS (Figure 11.6.4).e

 The average value over the forecast period is 0.30 for commercial 

clothes washer standards. 

-0.30 

-0.20 

-0.10 

0.00 

0.10 

0.20 

0.30 

0.40 

0.50 

0.60 

0.70 

0.80 

2015201620172018201920202021202220232024202520262027202820292030 

Year 

Inverse Price Elasticity 

Figure 11.6.4 Inverse Electricity Price Elasticity from NEMS Analysis for Commercial 

Clothes Washer Max Tech Standard Levels 

e

 Since the demand reduction in the early years after the standard takes effect is small, the model results for those 

years may be less accurate than in later years. 

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EERE-2006-STD-0127 COMMENT 69.1
 

 

 

 

 

 

 

 

 

 

 

 

REFERENCES
 

1	 U.S. Department of Energy-Office of Energy Efficiency and Renewable Energy, Energy 

Conservation Standards for Certain Consumer Products (Dishwashers, Dehumidifiers, 

Microwave Ovens, and Electric and Gas Kitchen Ranges and Ovens) and for Certain 

Commercial and Industrial Equipment (Commercial Clothes Washers); Final Rule. Federal 

Register, 2009. 74(66): pp. 16040-16096. 

2	 U.S. Department of Energy-Office of Energy Efficiency and Renewable Energy. Technical 

Support Document: Energy Efficiency Program for Consumer Products and Commercial and 

Industrial Equipment: Residential Dishwashers, Dehumidifiers, Cooking Products, and 

Commercial Clothes Washers, March, 2009. Washington, DC. 

<http://www1.eere.energy.gov/buildings/appliance_standards/residential/cooking_products_final_rul 

e_tsd.html> 

3	 Consortium for Energy Efficiency. Commercial Family-Sized Washers: An Initiative 

Description of the Consortium for Energy Efficiency, 1998. Boston, MA. 

4	 U.S. Department of Energy-Energy Information Administration. Annual Energy Outlook 

2008 with Projections to 2030, February, 2008. Washington, DC. DOE/EIA-0383(2008). 

5	 U.S. Department of Energy-Energy Information Administration. An Updated Annual Energy 

Outlook 2009 Reference Case Reflecting Provisions of the American Recovery and 

Reinvestment Act and Recent Changes in the Economic Outlook, April, 2009. Washington, 

DC. SR/OIAF/2009-03. 

<http://www.eia.doe.gov/oiaf/servicerpt/stimulus/pdf/sroiaf(2009)03.pdf> 

6	 U.S. Department of Labor-Bureau of Labor Statistics. Consumer Price Indexes, Item: Water 

and sewerage maintenance, Series Id: CUUR0000SEHG01, U.S. city average (not seasonally 

adjusted), 2008. Washington, DC. <http://www.bls.gov/cpi/home.htm#data> 

7	 U.S. Department of Energy - Energy Information Administration, Annual Energy Outlook 

2008 (Revised Early Release) with Projections to 2030. 2008: Washington, DC. 

<http://www.eia.doe.gov/oiaf/aeo/> 

8	 Ryan Wiser, Mark Bolinger, and Matt St. Clair, Easing the Natural Gas Crisis: Reducing 

Natural Gas Prices through Increased Deployment of Renewable Energy and Energy 

Efficiency. 2005, Lawrence Berkeley National Laboratory. 

9	 Natural Gas, Fuel Diversity and North American Energy markets, Energy Modeling Forum, 

Stanford University. 

10	 Balancing Natural Gas Policy - Fueling the Demands of a Growing Economy, Vol. I 

Summary of Findings and Recommendations, National Petroleum Council. 

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EERE-2006-STD-0127 COMMENT 69.1
 

 11 National Commission on Energy Policy, Increasing U.S. Natural Gas Supplies: A Discussion 

Paper and Recommendations from the National Commission on Energy Policy. 2003. 

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EERE-2006-STD-0127 COMMENT 69.1