14. Pierre, Bo, Kytlteknisk Tidskript, 3, May 1957, p. 129.

15. Lockhart, R. W., and Martinelli, R. C., "Pr oposed Correlation of Data for Isothermal TwoPhase, Two-Component Flow in Pipes," Ch emical Engineering Progress, 45, 1, pp. 39-48.

16. Wang,, Chi-Chuan, “Recent Progress on the Air-si de Performance of Fin-and-Tube Heat Exchangers,” International Journal of H eat Exchangers 1524-5608 (Vol 1 (2000), pp. 49-76.

17. Mirth, D.R. and Ramadhyani, S ., “Correlations for Predicting the Air-Side Nusselt Numbers
and Friction Factors in Chilled -Water Cooling Coils,” Expe rimental Heat Transfer, 7:143

- 162, 1994.

18. Bansal, P.K. and Chin, T.C., “Modeling and Op timization of Wire-and-Tube Condenser,”
International Journal of Refrigeration 26 (2003) 601-613.

19. Tagliafico, L. and Tanda, G., “Radiation and Na tural Convection Heat Transfer from Wire

and-Tube Heat Exchangers in Refrigerati on Appliances,” International Journal of Refrigeration, 20 (1997) 461-469.

20. Vera-Garcia, F., et al., “Assessment of Conde nsation Heat Transfer Correlations in the Modeling of Fin and Tube Heat Exchangers,” International Journa l of Refrigeration 30 (2007) 1018-1028.

21. Shah, M.M., “A General Correlation for Heat Tran sfer During Film Conde nsation in Pipes,”
International Journal of Heat and Mass Transfer 22 (1979) 547-556.

22. Lee, Tae-Hee, et al, “Determination of Airside Heat Transfer Coefficient on Wire-on-Tube Type Heat Exchanger,” International Jour nal of Heat and Mass Transfer 44 (2001) 1767

- 1776.

23. http://www.ornl.gov/~wlj/hpdm/Mark_VI_Notes.html

24. Lemmon, E.W., Huber, M.L. and McLinden, M.O., “Reference Fluid Thermodynamic and Transport Properties,” NIST Standard Reference Database 23, Version 8.0.

25. Lemmon, E.W., “Pseudo-Pure Fluid Equations of State for the Refrigerant Blends R-410A, R-404A, R-507A, and R-407C,” International Jour nal of Thermophysics, Vol 24, No 4, July 2003, pp. 991-1006.

26. Rice, C.K., “The ORNL Modulating Heat Pump Design Tool – Mark IV User’s Guide,” Oak Ridge National Laboratory Repor t ORNL/CON-343, September 2001.

5-B-19CHAPTER 6. MARKUPS FOR EQUI PMENT PRICE DETERMINATION

TABLE OF CONTENTS

6.1 INTRODUCTION ........................................................................................................... 6-1
6.1.1 Distribution Channels .................................................................................................... .. 6-1
6.2 MARKUP CALCULATION PROCEDURE .................................................................. 6-1 6.2.1 Approach for Manufacturer Markups .............................................................................. 6-2 6.2.2 Approach for Retailer Markups ....................................................................................... 6-2
6.3 MANUFACTURER MARKUPS .................................................................................... 6-4
6.4 RETAILER MARKUP .................................................................................................... 6-5
6.5 SALES TAXES ............................................................................................................... 6 -6
6.6 SUMMARY OF MARKUPS .......................................................................................... 6-7

LIST OF TABLES

Table 6.3.1 Major Appliance Manufactur er Gross Margins and Markups............................. 6-5
Table 6.4.1 Data Used to Calculate Retail er Markups for Residential Refrigeration
Products................................................................................................................ 6-5 Table 6.5.1 Average Sales Tax Rates by Ce nsus Division and Large State........................... 6-6 Table 6.5.2 Average Sales Tax Rates by Product................................................................... 6-7 Table 6.6.1 Summary of Markups .......................................................................................... 6-7

6-iCHAPTER 6. MARKUPS FOR EQUIPMENT PRICE DETERMINATION

6.1 INTRODUCTION

To carry out its analyses, DOE needed to determine the cost to the consumer of baseline products and the cost of more-efficient units. As discussed in chapter 8, DOE developed retail prices for baseline products usi ng proprietary retail price data collected by The NPD Group. For products with higher-than-baseline efficiency, DOE estimated the consumer prices by applying appropriate markups to the manufacturer in cremental equipment costs estimated in the engineering analysis.

6.1.1 Distribution Channels

The appropriate markups for determining c onsumer equipment prices depend on the type of distribution channels through which products move from manufacturers to purchasers. At each point in the distribution channel, companies mark up the price of the equipment to cover their business costs and profit margin.

Data from the Association of Ho me Appliance Manufacturers (AHAM) 1 indicate that an overwhelming majority of resident ial appliances are sold through retail outlets. Because DOE is not aware of any other distribu tion channel that plays a sign ificant role for residential refrigeration products, DOE assumed that all of the residential products are purchased by consumers from retail outlets. DOE did not include a separate dist ribution channel for refrigeration products included as part of a new home, as it did not have information on the extent to which these products are “p re-installed” by builders in new homes.

6.2 MARKUP CALCULATION PROCEDURE

As just discussed, at each point in the di stribution channel, companies mark up the price of the equipment to cover their business costs a nd profit margin. In fina ncial statements, gross margin is the difference between the company reve nue and the company cost of sales or cost of goods sold ( CGS ). Inputs for calculating the gross ma rgin are all corporate costs—including overhead costs (sales, general, and administ ration); research and development (R&D) and interest expenses; depreciation, and taxes—and profits. In order for sales of a product to contribute positively to company cash flow, th e product’s markup must be greater than the corporate gross margin. Individual pr oducts may command a lower or higher markup, depending on their perceived added value and the competition they face from similar products in
the market.

In developing markups for manufacturers and retailers, DOE obtained data about the

revenue, CGS , and expenses of firms that produce and sell the products of interest. For retailers, DOE’s approach categorizes the expenses into two categories: labor-scaling costs ( LSC ), which

6-1are fixed labor and occupancy expenses that increase in proportion to the amount of labor required to produce or sell the pr oduct, and non-labor-scaling costs ( NLSC ), which are variable operating costs that do not scale with labor and vary in proportion to CGS

.

6.2.1 Approach for Manufacturer Markups

DOE uses manufacturer markups to transfor m a manufacturer’s equipment costs into a manufacturer sales price. Using the CGS and gross margin, DOE calculated the manufacturer markup ( MU MFG ) with the following equation:

CGS + GM MFG MFG MU MFG = CGS MFG where:

MU MFG = Manufacturer markup,
CGS MFG = Manufacturer’s cost of goods sold or Manufacturer Production Cost ( MPC ), and
GM MFG = Manufacturer’s gross margin.

The manufacturer’s CGS (or MPC) plus its GM equals the manufact urer selling price ( MSP ).

6.2.2 Approach for Retailer Markups

DOE based the retailer markups for reside ntial refrigeration produc ts on financial data from the U.S. Census Business Expenditure Surv ey. DOE organized the financial data into balance sheets that break down cost compone nts incurred by firms that sell the products. a The key assumptions that DOE used to estimate the re tailer markups using these financial data were:

1. The balance sheets faithfully represent the various average costs incurred by firms selling home appliances.

2. These costs can be divided into two categories:

a. Costs that vary in proportion to the manu facturer sales price (variable costs); and
b. Costs that do not vary with the manu facturer sales price (fixed costs).

3. Retailer sales prices vary in proportion to retailer costs that are included in the balance
sheets.

In support of the first assumption, the balanc e sheets itemize firm costs into a number of expense categories, including CGS , operating labor and occupancy costs, and other operating

a The retailers to whom these financial data refer handle multiple commodity lines.

6-2costs and profit. Although retailers tend to handle multiple commodity lines, the data provide
the most accurate available indicat ion of home appliance expenses.

Information obtained from the trade literatu re pertaining to the h eating, ventilation, and air-conditioning (HVAC) contracti ng industry tends to support the second assumption. This information indicates that retailer markups shoul d vary according to the quantity of labor and
materials used to sell or dist ribute the equipment, with mar kups on labor tending to be much larger than markups on materials. 2 This information also describes markups as varying much
more in relation to sales volume than in relation to other factors, including appliance efficiency. This last finding strongly sugge sts that labor inputs vary more with sales volume than with appliance cost or efficiency. In the discu ssion that follows in s ection 6.3, DOE assumes a
division of costs between those th at do not scale with the manufact urer sales price (fixed costs— labor and occupancy expenses referred to above as LSC ), and those that do (variable costs— operating expenses and profit referred to above as NLSC ). This division of costs led to the estimate of retailer markups described below in section 6.3.

In support of the third assumption, the retailer industries are relatively competitive, and consumer demand for residential home appliances is relatively inelastic, i.e. the demand is not expected to decrease significantl y with a relatively small increase in price. The large number of household appliance stores listed by the U.S. Census Bureau in its Statistics of U.S. Businesses indicates the competitive nature of the market. 3 For example, there are more than 10,000 household appliance store establishments and ove r 5000 merchant wholesaler establishments of service equipment in the U.S. b According to standard economic theory, competitive firms facing inelastic demand either set prices in line with costs or quickly go out of business. 4

Using the above assumptions, DOE developed baseline and incremental markups to
transform the manufacturer sales price into a consumer equipment price. DOE used the baseline markups, which cover all of a retailer’s costs (i.e., both LSC and NLSC ), to determine the sales price of baseline models. The baseline markup rela tes the manufacturer sales price to the retailer sales price. DOE considers baseline models to be equipm ent sold under existing market conditions (i.e., without new ener gy efficiency standards). DOE calculated the baseline markup ( MU BASE ) for retailers using the following equation:

CGS RTL / DIST + GM RTL / DIST CGS RTL / DIST + ( LSC RTL / DIST + NLSC RTL / DIST ) MU = = BASE CGS CGS RTL / DIST RTL / DIST

where:

MU BASE = Baseline retailer markup,
CGS RTL/DIST = Retailer’s cost of goods sold,
GM RTL/DIST = Retailer’s gross margin,

b DOE determined the number of establishments for household appliance stores based on the following North American Industry Classification System (NAICS) code and description: 443111, Household Appliance Stores

.

6-3LSC RTL/DIST = Retailer’s labor-scaling costs, and
NLSC RTL/DIST = Retailer’s non-labor-scaling costs.

Incremental markups cover only those co sts that scale with a change in the manufacturer’s sales price (i.e., NLSC ). Incremental markups are co efficients that relate the change in the manufacturer sale s price of higher-efficiency models to the change in the retailer sales price. DOE considers higher-efficiency models to be equipment sold under market conditions with new efficiency standards. It calculated the incremental markup ( MU INCR ) for retailers using the following equation:

CGS + NLSC RTL / DIST RTL / DIST MU INCR = CGS RTL / DIST where:

MU INCR = Incremental retailer markup,
CGS RTL/DIST = Retailer’s cost of goods sold, and
NLSC RTL/DIST = Retailer’s non-labor-scaling costs.

6.3 MANUFACTURER MARKUPS

DOE developed an average manufacturer ma rkup by examining the annual Securities and Exchange Commission (SEC) 10-K reports filed by four publicly-t raded manufacturers primarily engaged in appliance manufacturing and whose combined product range includes residential refrigeration products. 5 The four manufacturers represent a nearly 50 pe rcent market share for major appliances. Because these companies ar e typically diversified, producing a range of different appliances, an industry average mar kup was assumed by DOE to be representative for the manufacture of refriger ation products. DOE evaluated markups for the years 2002

─ 2005.

Table 6.3.1 lists the average corporat e gross margin during the years 2002

─ 2005, and corresponding markups, for each of the four ma nufacturers. The average markup value based on these four companies is 1.26, which is the value that DOE used.

6-4Table 6.3.1 Major Appliance Manufacturer Gross Margins and Markups

Mfr A Mfr B Mfr C Mfr D

Average Net Revenues (Million) $372 $280 $4770 $12,682

Corporate Gross Margin 15% 28% 16% 22%

Markup 1.18 1.39 1.19 1.28

Source: SEC 10-K reports (2002-2005)

6.4 RETAILER MARKUP

DOE used financial data from the U.S. Ce nsus Business Expenditure Survey (BES), in the “Household Appliance Stores” ca tegory, to calculate markups used by retailers that apply to residential refrigeration products. c 6 Table 6.4.1 shows the BES data that DOE used and the estimated retail markups.

Table 6.4.1 Data Used to Calculate Retailer Ma rkups for Residential Refrigeration
Products

Item Million Dollars

Sales (revenue) 10343
Cost of Goods Sold (CGS) 7151
Gross Margin (GM) 3193
Labor-Scaling Costs (LSC)
Payroll 1366
Fringe Benefits 208

Contract Labor 69

Taxes and License Fees 53
Lease and Rental Payments 238
Telephone and Communications 58

Utilities 70
Repair and Maintenance 36

LCS Subtotal: 2098
Non-Labor-Scaling Costs (NLSC)
Depreciation and Amortization 94

Office Supplies 37
Packaging and Other Materials 0

Advertising Services 274

c DOE used the 1997 BES because the 2002 BES did not contain sufficient data for the calculation of gross margin or cost of goods sold.

6-5Legal Services 8
Accounting, Auditing, and Bookkeeping 19
Computer Related Services 10
Other Operating Expenses 389

Net Profit Before Taxes 263

NLCS Subtotal: 1094
Baseline Markup (MU BASE ) = (CGS+GM)/CGS 1.45
Incremental Markup (MU INCR ) = (CGS+NLSC)/CGS 1.15

6.5 SALES TAXES

The sales tax represents state and local sa les taxes that are applied to the consumer equipment price of the equipment. The sales tax is a multiplicative factor that increases the consumer equipment price.

DOE derived state and local taxes from da ta provided by the Sales Tax Clearinghouse. 7 DOE derived population-weighted aver age tax values for each Census division and large state, as
shown in Table 6.5.1 below.

Table 6.5.1 Average Sales Tax Rates by Census Division and Large State

Census Division/State Tax Rate
New England 4.96%

Mid Atlantic 6.54%

East North Central 6.93%

West North Central 6.77%

South Atlantic 6.17%

East South Central 7.90%

West South Central 8.37%

Mountain 6.50%

Pacific 5.20%

New York State 8.25%

California 9.00%

Texas 8.05%

Florida 6.70%

DOE then derived U.S. average tax valu es for each product (as shown in Table 6.5.2 below) based on the product’s sa turation within each Census di vision and large state. It
determined the saturations from the DOE En ergy Information Administration (EIA)’s 2005 Residential Energy Consumption Survey. 8

6-6Table 6.5.2 Average Sales Tax Rates by Product

Product Tax Rate
Refrigerators (Standard-size and compact) 7.08%
Freezers (Standard-size and compact) 6.94%

6.6 SUMMARY OF MARKUPS

Table 6.6.1 summarizes the markups at each st age in the distribution channel and the average sales tax.

Table 6.6.1 Summary of Markups
Markup Baseline Incremental

Manufacturer 1.26

Retailer 1.45 1.15

Sales Tax 1.069

6-7REFERENCES

1 Association of Home Ap pliance Manufacturers. AHAM 2003 Fact Book , 2003. Washington, DC. p. 25.

2 Skaer, M. What should you charge? Try these Tested Formulas. The Air Conditioning, Heating, and Refrigeration News , 2001.

< http://www.achrnews.com/CDA/ArticleInformation/ features/BNP_Features_Item/0,1338,23113,00.html >

3 U.S. Census Bureau. Statistics of U.S. Businesses , 2004. Washington, DC.

< http://www.census.gov/csd/susb/susb04.htm >

4 Pindyck, R.S. and D.L. Rubinfeld, Microeconomics, 5 th ed. , 2000. New Jersey: Prentice Hall.

5 Security Exchange Commission, SEC 10-K Reports, Various dates, 2002-2005, Security Exchange Commission. < http://www.sec.gov/ >

6 U.S. Census Bureau. 1997 Economic Census, Business Expenses Survey, Retail Trade, Household Appliance Stores , 1997. Washington, DC.

< http://www.census.gov/csd/bes/bes97.htm >

7 Sales Tax Clearinghouse, Inc. State sales tax rates along with combined average city and
county rates . < http://thestc.com/STrates.stm >

8 U.S. Department of Energy- Energy Information Administration. Residential Energy Consumption Survey, 2005Public Use Data Files. . Washington, DC.

< http://www.eia.doe.gov/emeu/recs/recspubuse05/pubuse05.html >

6-8CHAPTER 7. ENERGY USE DETERMINATION

TABLE OF CONTENTS

7.1 HOUSEHOLD SAMPLES FOR REFR IGERATION PRODUCTS............................... 7-4
7.2 APPROACH FOR STANDARD-SIZE PRODUCTS..................................................... 7-6
7.3 USAGE ADJUSTMENT FACTORS FO R STANDARD-SIZE PRODUCTS............... 7-9 7.3.1 Field Energy Consumption for One or More Refrigerators .................................. 7-9 7.3.2 Tested Energy Consumption ............................................................................... 7-11
7.3.2.1 Size ....................................................................................................... 7-11 7.3.2.2 Assigning Vintage and EN ERGY STAR Status .................................. 7-12 7.3.3 Energy Use of Second Refrigerators ................................................................... 7-18
7.3.4 Estimated Number of ENERGY STAR Refrigerators ........................................ 7-19 7.3.5 Validating Field Energy Consumption................................................................ 7-20 7.3.6 Maximum Usage Adjustment Factor .................................................................. 7-20 7.3.7 Minimum Usage Adjustment Factor ................................................................... 7-27 7.3.8 Results by Product Class ..................................................................................... 7-30 7.3.9 Distributions: Comparison with Other Studies ................................................... 7-36
7.4 ENERGY USE OF COMPACT RE FRIGERATION PRODUCTS.............................. 7-38
7.5 ANNUAL ENERGY CONSUMPTION BY EFFICIENCY LEVEL ........................... 7-38

LIST OF TABLES

Table 7.1.1 Refrigeration Products in Households by Product Class ..................................... 7-5
Table 7.3.1 Size Bins for Refr igerators and Freezers ........................................................... 7-12 Table 7.3.2 Parameters for Calculating Ad justed Volume from Total Volume of Refrigerator-Freezers ......................................................................................... 7-12 Table 7.3.3 Energy Conservation Standa rds for Refrigeration Products.............................. 7-13
Table 7.3.4 ENERGY STAR Criteria fo r Refrigeration Products........................................ 7-13 Table 7.3.5 Vintage Bins for Refrigeration Products............................................................ 7-14 Table 7.3.6 Refrigerator Survival Probabi lities Associated with Age Bins.......................... 7-18
Table 7.3.7 Market Share of ENERGY STAR Products ...................................................... 7-20 Table 7.3.8 Power Consumption for Ice Maker Components............................................... 7-21 Table 7.3.9 Theoretical Maximum Energy C onsumption for Baseline Product Class 3 Refrigerator-Freezers ......................................................................................... 7-23 Table 7.3.10 Theoretical Maximum Energy C onsumption for Baseline Product Class 5 Refrigerator-Freezers ......................................................................................... 7-23 Table 7.3.11 Theoretical Maximum Energy C onsumption for Baseline Product Class 7 Refrigerator-Freezers ......................................................................................... 7-24 Table 7.3.12 Theoretical Maximum Energy C onsumption for Baseline Product Class 9
Freezers.............................................................................................................. 7-24

7-1Table 7.3.13 Theoretical Maximum Energy Cons umption for Baseline Product Class 10
Freezers.............................................................................................................. 7-25 Table 7.3.14 Regression Parameters by Produc t Class for Maximum Usage Adjustment
Factor ................................................................................................................. 7-27 Table 7.3.15 Temperature Settings for Refriger ators Under Test and Ideal Conditions ........ 7-27 Table 7.3.16 Temperature Settings for Freezers Under Test and Ideal Conditions................ 7-28 Table 7.3.17 Model Errors by Product Class and Vintage...................................................... 7-28 Table 7.3.18 Regression Results Based on Unit Vintage ....................................................... 7-30 Table 7.3.19 Usage Adjustment Factors Be fore and After Excluding Minimums and
Maximums ......................................................................................................... 7-36 Table 7.4.1 Parameters for Calculating Ad justed Volume from Total Volume for Compact Refrigerators....................................................................................... 7-38 Table 7.5.1 Product Class 3, Top-Mount Refr igerator-Freezers Without Through-theDoor Ice Service: Average Annual En ergy Use by Efficiency Level ............... 7-39 Table 7.5.2 Product Class 5, Bottom-Mount Refrigerator-Freezers Without Throughthe-Door Ice Service: Average Annual Energy Use by Efficiency Level ......... 7-40 Table 7.5.3 Product Class 7, Side-by-side Refrigerator-Freezers with Through-theDoor Ice Service: Average Annual En ergy Use by Efficiency Level ............... 7-40 Table 7.5.4 Product Class 9, Upright Fr eezers: Average Annual Energy Use by Efficiency Level................................................................................................. 7-41 Table 7.5.5 Product Class 10, Chest Freeze rs: Average Annual Energy Use by Efficiency Level................................................................................................. 7-41 Table 7.5.6 Compact Refrigerators and Freezers: Average Annual Energy Use by Efficiency Level................................................................................................. 7-42

LIST OF FIGURES

Figure 7.3.1 Average Unit Energy Consumption, 1961 to 1990 Shipments.......................... 7-14 Figure 7.3.2 Weighted Households by Refrigerator Vintage................................................. 7-15 Figure 7.3.3 Survival Probability of Refrigerators by Age .................................................... 7-16 Figure 7.3.4 Survival Probability of Freezers by Age............................................................ 7-17 Figure 7.3.5 Maximum Usage Adjustment Factor by Product Age in 2005.......................... 7-26 Figure 7.3.6 Minimum Plausible Usage Adjust ment Factor as a Function of Product Age in 2005........................................................................................................ 7-29 Figure 7.3.7 Initial UAF Distribution for Standard-Size Top-Mount RefrigeratorFreezers (Product Class 3) ................................................................................. 7-31 Figure 7.3.8 Final UAF Distribution for St andard-Size Top-Mount RefrigeratorFreezers (Product Class 3) ................................................................................. 7-31 Figure 7.3.9 Initial UAF Distribution for St andard-Size Bottom-Mount RefrigeratorFreezers (Product Class 5) ................................................................................. 7-32 Figure 7.3.10 Final UAF Distribution for St andard-Size Bottom-Mount RefrigeratorFreezers (Product Class 5) ................................................................................. 7-32

7-2Figure 7.3.11 Initial UAF Distribution for St andard-Size Side-by- side RefrigeratorFreezers (Product Class 7) ................................................................................. 7-33 Figure 7.3.12 Final UAF Distribution for Sta ndard-Size Side-by-si de RefrigeratorFreezers (Product Class 7) ................................................................................. 7-33 Figure 7.3.13 Initial UAF Distribution for Standard-Size Upright Freezers (Product Class 9)............................................................................................................... 7-34 Figure 7.3.14 Final UAF Distribution for Sta ndard-Size Upright Fr eezers (Product Class 9) ........................................................................................................................ 7-34 Figure 7.3.15 Initial UAF Distribution for St andard-Size Chest Fr eezers (Product Class 10) ...................................................................................................................... 7-35 Figure 7.3.16 Final UAF Distribution for Sta ndard-Size Chest Freeze rs (Product Class 10) ...................................................................................................................... 7-35

7-3CHAPTER 7. ENERGY USE DETERMINATION

To perform the life-cycle cost (LCC) and pa yback period (PBP) calculations described in chapter 8, the U.S. Department (DOE) needed to determine the savings in operating cost that
consumers would derive from more effici ent products. DOE uses data on annual energy consumption, along with energy prices, to devel op the most significant component of consumer operating cost. (Maintenance and repair costs are the other components.) This chapter describes how DOE determined the annual energy c onsumption of refrigeration products.

The engineering analysis described in chapte r 5 reports energy use derived from the DOE test procedure. This test pr oduces standardized results that can be used o compare the performance of different brands of the same product class operating under similar conditions. Actual energy usage in the field, however, often di ffers from that estimated by the test procedure.
Researchers have conducted studies that measure the field consumption of refrigerator-freezers, comparing such measurements to the DOE test re sults. DOE’s review of se veral such studies is described in appendix 7-A and summarized in section 7.3.9. The review confirmed that energy
use measured in the field often differs consider ably from the usage measured by the DOE test procedure.

To determine the field energy use by pr oducts that would meet potential new energy efficiency standards, DOE used data from the Energy Information Administration’s 2005 Residential Energy Consumption Survey (RECS). 1 RECS queries a national sample of
households to collect statistical information on household consumption of and expenditures for energy, along with data on ener gy-related characteri stics of the housing units and households. RECS provides enough information to establish th e type of refrigeration product (the product class) used in each household, and provides an estimate of the household energy consumption attributable to refrigerators or freezers. As a result, DOE was able to develop a unique household sample for most of the representative product classes for standard-size units.

DOE did not use RECS to evaluate ener gy consumption by compact refrigerators and freezers, because many of those products are used outside the residential sector, such as in college dormitories, hotels and motels, and offices.

7.1 HOUSEHOLD SAMPLES FOR REFRIGERATION PRODUCTS

DOE developed household samples for refr igeration products from the 2005 RECS. The survey, which sampled 4,382 housing units, was constructed to represent the household population throughout the United States.

RECS results reveal whether a household uses a standard-size refriger ator or freezer. For
households that have a standard-s ize refrigerator, RECS specifies whether the freezer is top- or
bottom-mounted or is side-mounted. Thus units in the sample that have top-mounted freezers

7-4cannot be distinguished from those having bot tom-mounted freezers (product classes 3 and 5). For a household’s primary (or “first”) refrigerat or, RECS specifies whether there is through-thedoor ice service. For households that have stan dard-size freezers, RECS specifies whether the unit is upright or a chest-type. With the above data, DOE was able to assign each household record to one of the five product classes considered for potential new efficiency standards (Table 7.1.1).

Table 7.1.1 Refrigeration Products in Households by Product Class

Product Class Number of
Household
Records* Percent of Total
Household
Records* Relative Standard
Error Due to

Sampling* 3. Refrigerator-freezer:automatic defrost with topmounted freezer and no TTD †

ice service 2,303 52.6% 2.1% 5. Refrigerator-freezer:
automatic defrost with
bottom-mounted freezer and
no TTD ice service 7. Refrigerator-freezer:
automatic defrost with sidemounted freezer and TTD ice
service 1,026 23.4% 3.1%

9. Upright freezer with
automatic defrost 248 5.7% 6.4%

10. Chest freezer and all other freezers except compact
models 369 8.4% 5.2%

* From the Energy Information Administration’s 2005 Residential Energy Consumption Survey (RECS).

† Through-the-door.

The relative standard errors associated with the subsamples that contain specific product classes are not considered so large as to affect the validity of the derived results presented in this chapter. Specifically, the relative st andard error of a sample of size N , expressed as a percentage, is 100 divided by the square root of ( N -1). For the full 2005 RECS sample, the associated
relative standard error due to sampling is 1.5 percent. For the subsamples containing product classes 9 and 10, the associated relative sta ndard errors are 6.4 pe rcent and 5.2 percent, respectively. Although the st andard error for the smallest subsam ple is more than four times the error for the entire 2005 RECS, it s till is less than 10 per cent, a relative standa rd error considered small enough to yield meaningful results. Therefor e, DOE believes the results generated from the household samples for refrigerati on products are representative of U.S. households using those appliances.

7-57.2 APPROACH FOR STANDAR D-SIZE PRODUCTS

The Residential Energy Consumption Survey (RECS) reports the annual field energy consumption of each household’s refrigera tion product(s), a quantity referred to as FEC RECS

. DOE treated the reported energy consumption as the actual consumption of the refrigeration product(s) in each household. Because the energy consumed by a household’s refrigerator or freezer varies depending on operating conditions, user behavior, and other factors, DOE applied a multiplicative usage adjustment factor (UAF) to the labeled energy use of each product to
reflect those factors.

To develop a UAF for each RECS house hold, DOE utilized information that RECS provides on the interior volume a nd age of each refrigeration produc t. Using this information and the unit’s product class, DOE determined for eac h household unit the maximum allowable tested energy consumption, referred to as TEC STD , as stipulated by the energy conservation standard in
effect at the time the household purchased the product. Because TEC STD differentiates among current levels of energy efficiency, it guards against overestimating the energy savings to be derived from potential new standards. Using FEC RECS and TEC STD , DOE developed the UAF for each household to capture the combined effects of consumer behavior ( e.g. , door openings); operating conditions ( e.g. , room temperature and humidity ); and product characteristics ( e.g. , efficiency relative to the maximum allowable) . The UAF adjusts the maximum allowable energy
use when the unit was tested to arrive at th e field energy consumption of the refrigeration product. UAF is represented by the following expression.

F

E C R EC S UAF = TE C STD Eq. 7.1
Where:

UAF = usage adjustment factor;
FEC RECS = refrigeration product’s field energy consumption as reported for the RECS household; and
TEC STD = maximum allowable tested energy consum ption based on the standard in effect at the time the household purchased the refr igeration product; for products purchased before 1990 (when the first national standard came into effect), DOE used the shipments-weighted average energy consum ption for that vintage to scale the
standard.

DOE was better able to estimate the effi ciency of ENERGY STAR products and thus develop a UAF that more accurately represents only behavior and operating conditions. DOE
used an income-based statistical model, described in section 7.3.4, to identify households likely to own an ENERGY STAR appliance. In those cases, UAF was defined as follows.

7-6F E C R EC S UAF = TE C ES Eq. 7.2

Where:

UAF = usage adjustment factor,
FEC RECS = refrigeration product’s field energy consumption as reported for the RECS household, and
TEC ES

= tested energy consumption based on the ENERGY STAR criteria in effect at the time the household purchased the refrigeration product.

DOE conducted its analysis with an awaren ess of proposed revisions to the DOE test procedure for refrigerato r-freezers, which will stipulate lo wer temperatures for the fresh food compartment and the freezer than those the curre ntly prescribed. DOE has not identified how the tested energy consumption under the new procedur e will compare to that determined under the current procedure. DOE expects this adjustment to take the form of a multiplicative factor termed the “efficiency standard adjustment fact or,” or ESAF. The ESAF is expected to be multiplicative, because the energy use for a refr igeration unit is close to proportional to the difference between its interior and exterior temp eratures. For the current preliminary analysis,
DOE assumed that this factor is constant for each product class, and does not vary with product efficiency or adjusted volume. See chapter 5 for a complete discussion of the derivation of these values. DOE determined the preliminary value of the ESAF for refrigerator-freezers to be:

• 1.124 for product class 3,

• 1.18 for product class 5,

• 1.14 for product class 7,

• 1.00 for product class 9, and

• 1.00 for product class 10.

If the ESAF is multiplicative, it does not affect DOE’s estimate of appliance energy consumption by consumers, FEC The mathematical demonstration of this equivalence is shown below, after several additional terms are define d. Fundamentally, the valu e of the ESAF does not affect estimates of field energy use, because cha nges in the test procedure do not affect consumer behavior or operation of an a ppliance within a household. Fiel d energy consumption of future appliances built to meet a national standard, however, may be affected by the test procedure used to define the standard. For this reason, DOE assu med that the effects of consumer behavior and operating conditions, characterized by the UAF, ar e separate from the effects of the test procedure, characterized by the ESAF. DOE therefore separated the UAF values calculated from the RECS household sample from the ESAF, whic h does not vary across the household sample.

If appropriate, DOE will incorporate a more complete and accurate model for the ESAF based on ongoing analysis and additional inform ation collected from interested parties. Therefore, although a constant, multiplicative ESAF does not affect estimated annual energy use,

7-7DOE has chosen to show where the factor would enter into its calcula tions. To that end, DOE defined a new term, TEC STD-REV-TP , which is determined with the following expression.

TEC = ESAF × TEC Eq. 7.3 STD

− REV

− TP STD

− EXIST

− TP

Where:

TEC STD-REV-TP = maximum allowable tested energy consumption based on the standard in effect at the time the household purchased the refrigeration product, revised to reflect proposed lower temperatur es for the fresh food and freezer
compartments;
ESAF = efficiency standard adjustment factor; and
TEC STD-EXIST-TP = maximum allowable tested energy consumption based on the standard in effect at the time the household purchased the refrigeration product, reflecting current DOE test procedure conditions.

Substituting TEC STD-REV-TP for TEC STD in Eq. 7.1 produces the following expression for
UAF.

F E C R EC S UAF = E SA F × TE C STD

− E XIS T

− TP Eq. 7.4

After the UAFs were determined for each household within a given sample, DOE adjusted the tested energy consump tion for a new refrigeration product ( TEC NEW ) (such as those analyzed in the engineering analysis) into a fi eld-adjusted annual en ergy consumption, referred

to as FEC NEW , using the following expression.

FEC = TEC × UAF Eq. 7.5 NEW NEW

Where:

FEC NEW = field-adjusted annual energy consum ption of new refrigeration product, and
TEC NEW = tested energy consumpti on of new refrigeration product.

DOE assumed that the UAF a given household would be the sa me for products that meet some future energy efficiency standard as it is for their current appliance. In conducting the lifecycle cost analysis (chapter 8), DOE substituted the refrigeration product recorded in RECS with a new product of identical product class and size th at the household is assu med to purchase in the year when the new standard goes into effect.

If the ESAF is a multiplicative factor, as DOE assumed for this analysis, and the energy use required by the new standard is reduced from the current standard by a factor R ( e.g ., a 10­

7-8percent efficiency improvement would mean R = 0.1), then for an appliance that meets the new standard, tested under the new test proce dure, the field energy consumption is

FEC FEC = TEC × UAF = TEC × RECS

NEW

− STD NEW

− STD NEW

− STD ESAF × TEC STD

− EXIST

− TP TEC NEW

− STD TEC STD

− EXIST

− TP

= FEC RECS × ESAF Eq. 7.6 (1

− R ) × ESAF × TEC STD

− EXIST

− TP TEC STD

− EXIST

− TP

= FEC RECS × ESAF

= (1

− R ) × FEC RECS

A multiplicative ESAF therefore is not needed to calculate energy savings related to a higher efficiency standard, whic h can be calculated using only FEC RECS and R

.

7.3 USAGE ADJUSTMENT FACTORS FOR STANDARD-SIZE PRODUCTS

This section describes how DOE developed usage adjustment factors (UAFs) from the data provided for each household in RECS. It also describes how DOE developed minimum and maximum UAFs based on the highest and lowest plausible energy consumption of refrigeration products in the field. DOE’s methods of accon ting for second refrigerators and ENERGY STAR products are also described.

7.3.1 Field Energy Consumption for One or More Refrigerators

RECS reports the annual energy consumpti on of each household’s refrigerator(s) or
freezer in terms of thousands of British thermal units (BTUs) per year, which DOE converted to kilowatt-hours (kWh) per year. The reported end- use quantities were not based on data obtained by placing meters on individual app liances; rather, a regression t echnique was used to estimate
how much of the total annual el ectricity consumption for each household can be attributed to each end-use category. a The regression equations also were used to infer energy consumption when the billing data were missing or inadequa te. The refrigerator component for electricity consisted of all electricity used to operate refr igerators. The electricity used to operate freezers was assigned to a separate component unde r the category of “g eneral appliance.”

a The desire to use a large number of independent variables without using a large number of interaction terms and the desire to adapt the regression procedures to account for heteroscedastic error terms led to the use of a nonlinear regression technique. For more information, see: http ://www.eia.doe.gov/pub/consump tion/residential/append_c.pdf

7-9When a house has two or more refrigerators in RECS b , the energy consumption of all the refrigerators is included in the term for “electri c refrigerator use.” DOE’s analysis required separate consideration of each individual refrigerator in a household.

Total refrigerator field energy consumption ( FEC ) for households having two refrigerators can be expressed as:

FEC = ( UAF 1 × TEC STD 1 ) + ( Mon

× UAF 2 × TEC STD 2 ) Eq. 7.7 12

Where:

UAF = usage adjustment factor,
TEC = test energy consumption, and

Mon = number of months per year the second refrigerator is on. c The subscript numerals 1 and 2 refer to the fi rst and second refrigerator, respectively.

TEC STD refers to the maximum annual energy consumption allowed by the efficiency
standards in effect when th e product was manufactured. This value depends on the age and adjusted volume of the refrigerator. DOE assigned values for the age and adjusted volume of the second refrigerator the same way as for the firs t refrigerator. After these were assigned, the
TEC std for the second refrigerator was calculated.

The location of the second refrigerator, often in either a garage or basement, affects its
UAF. DOE assumed that for most h ouseholds, the second refrigerator is in the garage. In those cases the UAF of the second refriger ator is the same as that of th e first. If the second refrigerator operates for 12 months of the year, and the house is in the northern part of the country, however, the unit was assumed to be in a basement. (North is defined as Census Di stricts 1, 2, 3, and 4 plus New York, as well as other areas experien cing at least 5,000 heati ng degree-days. Because the operating environment of a basement on average is colder than that of the first refrigerator, DOE estimated the UAF of the second refrigerator to be 70 percent of the UAF of the first. This estimate was based on results of a simulation performed under basement conditions versus Results from the DOE test procedure. Although DOE did not use RECS to develop a household sample for compact refrigerators, DOE included in its analysis of standard -sized products those households having a second refrig erator that was a compact. The compact was assigned a
volume based on the volume distribution in the California Energy Commission appliance database, 2 and assigned a UAF as if it were standard-sized.

b Of the households in RECS 2005, 19.6 percent reported having two refrigerators; 1.2 percent reported having three. DOE considered only those households having one or two refrigerators.

c RECS reports months of operation for a second refrigerator.

7-10The UAF for each refrigerator can be cal culated based on the above assumptions. For most households, the UAF for both first and second refrigerators is calculated as:

FEC UAF = Eq. 7.8 ⎛ Mon ⎞ ⎜ TEC STD + ( 12 × TEC STD 2 ) ⎟ 1 ⎝ ⎠

For households in which the second refrigerat or is assumed to be in the basement, the UAF for the first refrigerator is calculated as:

FEC UAF 1 = Eq. 7.9 ⎛ Mon ⎞ ⎜ TEC STD + (0.70 × × TEC STD 2 ) ⎟ 1 ⎝ 12 ⎠

and the UAF for the second refr igerator is calculated as:

UAF = 0.70 × UAF Eq. 7.10 2 1

7.3.2 Tested Energy Consumption

For each refrigeration unit in a RECS ho me, the maximum allowable tested energy consumption based on the standard in effect at the time the refrigeration product was manufactured ( TEC STD ) depends on the unit’s product class, size, and age (vintage). If the household was assigned a refrig erator having an ENERGY STAR designation (using the model derived in section 7.3.4), DOE calculated the maximum allowed tested energy consumption for an ENERGY STAR unit of the appropriate vintage rather than the maximum allowed by the
concurrent standard.

Each unit’s product class was identified as de scribed in section 7.1. The size and vintage
were determined as described below.

7.3.2.1 Size

The possible answers to the RE CS question regarding the size of the first refrigerator or
freezer are shown in Table 7.3.1. The distribution of actual sizes is not uniform within the RECS size bins. To estimate the actual size of each unit, DOE estimated the distribution of sizes within each bin. To approximate that distribution, DOE used data on refrigerator models from the 2009 California Energy Commission (CEC ) appliance model database. 2 The figures in appendix 7-B show the number of models by size within each RECS size bi n for each considered product classes. The size assigned to a sample refrig erator within a RECS size bin was assigned randomly using probabilities derived from the CEC data.

7-11Table 7.3.1 Size Bins for Refrigerators and Freezers

Bin* Size of First Refrigerator cu ft †

1 Very small (10 or fewer)

2 Small (11 to 14)

3 Medium (15 to 18)

4 Large (19 to 22)

5 Very large (more than 22)

* Bins defined in Residential Energy Consumption Survey, 2005. † Cubic feet.

The maximum allowed energy consumpti on depends on the year the product was produced, its product class, and adjusted volume. For a refrigerator-freez er, the adjusted volume is equal to the internal volume of the fresh f ood compartment plus 1.63 times the internal volume of the freezer compartment. 3 Using the CEC database, 2 DOE used the following linear regression to calculate the adjusted volume ( Vol adj ) from the total volume ( Vol tot ):

Vol adj = Vol

tot × Slope + Intercept Eq. 7.11

DOE performed this calculation for each produc t class, deriving the parameters shown in
Table 7.3.2.

Table 7.3.2 Parameters for Calculating Adjusted Volume from Total Volume of Refrigerator-Freezers

Product Class Slope Intercept R 2 † Count 3. Refrigerator-freezers: automatic defrost with top-mounted freezer and no TTD* ice
service 1.2205 -1.1049 0.9691 1,803

5. Refrigerator-freezers: automatic defrost
with bottom-mounted freezer and no TTD
ice service 1.1851 0.0159 0.9929 778

7. Refrigerator-freezers: automatic defrost
with side-mounted freezer and TTD ice
service 1.3170 -1.9992 0.9906 1,866

*Through-the-door.

† R 2 is the coefficient of determination , a measure of how well the model fits the data.

7.3.2.2 Assigning Vintage and ENERGY STAR Status

The vintage of a refrigerator reflects the mini mum efficiency standards that were in effect at the time it was purchased. Table 7.3.3 lists the relevant energy efficiency standards and the

7-12dates each became effective. The formula that ex presses the standard is for maximum allowable kWh per year as a linear func tion of adjusted volume (AV). 4, 5

Table 7.3.3 Energy Conservation Standards for Refrigeration Products

Product Class 1990 Jan. 1, 1993 July 1, 2001 3. Top-mount refrigerator-freezers
without TTD* ice service 23.5AV+471 16.0AV + 355 9.80AV+276.0

5. Bottom-mount refrigerator-freezers
without TTD ice service 27.7AV+488 16.5AV + 367 4.60AV+459.0

7. Side-by-side refrigerator-freezers
with TTD ice service 30.9AV+547 16.3AV + 527 10.10AV+406.0

9. Upright freezers with automatic
defrost 16.0AV+623 14.9AV + 391 12.43AV+326.1

10. Chest freezers 14.8AV+233 11.0AV + 160 9.88AV+143.7 *Through-the-door.

The vintage also reveals which ENERGY STAR criteria were in effect. The effective dates of successive ENERGY STAR specifications are shown in Table 7.3.4. 6 7

Table 7.3.4 ENERGY STAR Criteria for Refrigeration Products

ENERGY STAR Criterion Effective Date

Refrigerators*
15% less energy than NAECA † 2001 maximum allowed January 1, 2004

10% less energy than NAECA 2001 maximum allowed January 1, 2001

20% less energy than NAECA 1993 maximum allowed June 1996

Freezers
10% less energy than NAECA 2001 maximum January 1, 2003

* The criteria that became effective in 2008 (20% less energy than NAEC A 2001 maximum) do not apply to

units described in RECS 2005.
† National Appliance Energy Conservation Act

RECS assigns the age of a refrigeration produc t to one of the five bins listed in Table
7.3.5.

7-13Table 7.3.5 Vintage Bins for Refrigeration Products

Bin* Age of Unit

years

1 Less than 2

2 2 to 4

3 5 to 9

4 10 to 19

5 20 or more

* Bins defined in Residential Energy Consumption Survey, 2005.

The dates refrigerator standards took effect do not correspond exactly to the age bins in RECS. When the age bin of a refrigerator is in sufficient to determine which standard applied, DOE chose a year from within the bin to assign as the vintage of that refrigerator. After the year was chosen using the survival curve developed for appliance lifetime, the standard appropriate to that vintage was applied.

For refrigeration products shipped before 1990, DOE derived an efficiency index based on trends in the average unit energy consumption (U EC) for historical shipments of refrigerators and freezers. Figure 7.3.1shows the trends in UEC from 1960 to 1990.

0 200 400 600 800 1000 1200 1400 1600 1800 2000

1960 1965 1970 1975 1980 1985 1990UEC

Refrigerators

Freezers

Source: AHAM Factbooks

Figure 7.3.1 Average Unit Energy Consumption, 1961 to 1990 Shipments

7-14There are likely to be fewer of the oldest refrigerators within any vintage bin, both because older refrigerators tend be replaced and because fewer refrigerators were produced in earlier years. This trend is revealed in Fi gure 7.3.2, which shows the weighted number of households by vintage from the 2005 RECS. For this figure, the refrigerators in each bin were assigned equally to each year. A better approach would be to assign more refrigerators to the more recent years within each bin by calculating th e survival probability [that is, the probability of a refrigerator surviving (remaining in use)] fo r a number of years. The survival probability is calculated using the number of refrigerators of each vintage bin reporte d by RECS as a fraction of the number of refrigerators shipped in that range of years. The survival probability accounts for the increases in shipments over time, as well as the refrigerators that retire from use. The survival probability function used to assign vintages is the same as the lifetime function derived for use in the life-cycle cost analysis. The deri vation of all parameter values is described in chapter 8.

0 2 4 6 8 10 12 1420052003200119991997199519931991198919871985198319811979197719751973197119691967

YearHouseholds (weighted, in millions)

Figure 7.3.2 Weighted Households by Refrigerator Vintage

The survival probability was calculated as:

⎛ ⎞ β ⎜ x

− θ ⎟

− ⎜ ⎟

⎜ α ⎟ P = 

## e ⎝ ⎠ for x > θ

P = 1 for x ≤ θ Eq. 7.12

Where:

x

= number of years (appliance age),

7-15α = 13.91, Weibull scale parameter, β

= 1.68, Weibull shape parameter, and
θ

= 5, Weibull delay parameter.

Figure 7.3.3 shows the surviv al probability curve for standard-sized refrigerators.

16.18

17.43

0.0 0.2 0.4 0.6 0.8 1.0 1.2Fraction surviving Survival function

Median lifetime

Mean lifetime

0 5 10 15 20 25 30 35 40 45 50

Age (years)

Figure 7.3.3 Survival Probability of Refrigerators by Age

The same fitting technique was used for freezer s. The scale, shape, and delay parameters
for freezers are:

α = 19.49, Weibull scale parameter, β

= 2.40, Weibull shape parameter, and
θ

= 5, Weibull delay parameter.

The survival curve for freezers ( Figure 7.3.4) does not fall off as quickly as does the one for refrigerators ( Figure 7.3.3), indi cating a longer mean product lifetime.

7-1621.73

22.28

0.0 0.2 0.4 0.6 0.8 1.0 1.2Fraction surviving Survival function

Median lifetime

Mean lifetime

0 5 10 15 20 25 30 35 40 45 50

Age (years)

Figure 7.3.4 Survival Probability of Freezers by Age

A multistep process was followed to assign an age to a given refrigeration product in a REC household. First, the produc t’s age range (based on RECS bin) was compared with the Weibull delay parameter. For both refrigerators and freezers, the delay was fixed at 5 years, which falls between two RECS age bins. If th e age bin contained appliances younger than the delay (in years), then an age w ithin the bin was assigned random ly to the product, with no age preferred. If the bin contained ap pliances older (in years) than the delay, a survival value was selected randomly from within the range given fo r the relevant bin. For this purpose, each bin was assumed to extend to the beginning of the next bin. Table 7.3.6 shows the survival values assigned to household refr igerators by age bin.

7-17Table 7.3.6 Refrigerator Survival Probabilities Associated with Age Bins
Age Bin Age years Survival Value

Start Less than Start End

1 0 2 NA NA

2 2 5 NA NA

3 5 10 1.000 0.8196

4 10 20 0.8196 0.3051

5 20 100 0.3051 0.0000

The age of the unit was calculated from the assigned survival value using the inverse survival probability function:

⎛ 1 ⎞ ⎜ ⎟ ⎛ ⎛ 1 ⎞ ⎞ ⎜ ⎜ ⎜ β ⎟ ⎟ ⎟

⎝ ⎠ Age = α × ⎜ ⎜ ln ⎜ ⎟ ⎟ ⎟ + θ Eq. 7.13 ⎝ ⎝ SP ⎠ ⎠

Where:

SP = randomly selected survival value,

α = Weibull scale parameter, β

= Weibull shape parameter, and
θ

= Weibull delay parameter.

After an age was assigned to the refrigerat or or freezer, it was clear what efficiency standards and (if applicable) ENERGY STAR speci fications were in effect when it was sold.

7.3.3 Energy Use of Second Refrigerators

When a household purchases a new refrigerat or, some first units become second units. See chapter 8 for a discussion of how DOE modeled the conversion of refrigerators from first to second units. A second refrigerator , generally located in a baseme nt or garage, enters a new operating environment and may be used less than year-round. For those units that become a second refrigerator, therefore, the annual energy consumption changes, presumably remaining at
the new level for the rest of its lifetime.

Field energy consumption for the first ( FEC 1) and second ( FEC 2) phases of a refrigerator’s lifetime can be expressed as:

FEC 1 = ( UAF 1 × TECstd ) Eq. 7.14

Mon FEC 2 = ( × UAF × TECstd ) Eq. 7.15 12 2

7-18Where:

UAF 1 = usage adjustment factor for first phase of the unit’s lifetime,
UAF 2 = usage adjustment factor for second phase, d

TEC = test energy consumption, and

Mon = number of months pe r year refrigerator is on.

7.3.4 Estimated Number of ENERGY STAR Refrigerators

As stated earlier, DOE used Eq. 7.2 to de rive the UAF for RECS households likely to own an ENERGY STAR appliance. Although RECS 2005 provides information on ownership of ENERGY STAR refrigerators purchased betwee n 2001 and 2005, the data seem to greatly overestimate the stock of ENERGY STAR refriger ators compared to data regarding shipments made during those years. DOE therefore deve loped a method that predicts ENERGY STAR ownership in the RECS sample based on annua l average market shares of ENERGY STAR refrigerators and on household income.

DOE based its approach on a st udy from Natural Resources Canada 8 that reported ENERGY STAR buyers based on three income ca tegories. DOE assumed that the relative behavior of each income category is the same in the United States as for Canadian consumers. After matching the three income categories to RE CS income bins, DOE assigned a probability of owning an ENERGY STAR unit to each household record as a function of its income. This probability was then scaled to reflect income levels in the RECS sample and national ENERGY STAR sales. The following equation was used.

Estar year = scale year × ( F low × P

_ Estar low + F mid × P

_ Estar mid + F high × P

_ Estar high ) Eq. 7.16

Where:

Estar year = percent of annual national refri gerator sales that were ENERGY STAR qualified;

F

low|mid|high = percent of weighted number of RECS 2005 households in low, medium, and high income bins; P_Estar low|mid|high = probability of households in an income bin buying an ENERGY STAR appliance; and
scale year = scaling factor to obtain the appropriate percent of ENERGY STAR refrigerators for each vintage.

Table 7.3.7 shows the market shares of ENERGY STAR refrigerators ( Estar year ), which were obtained from the ENERGY STAR program. 9 The market shares of ENERGY STAR
freezers are estimates.

d This UAF accounts for the changed operating environment during the second phase.

7-19Table 7.3.7 Market Share of ENERGY STAR Products

Year 1997 1998 1999 2000 2001 2002 2003 2004 2005

Refrigerators 25.3% 19.0% 25.0% 27.0% 17.3% 20.1% 25.7% 33.2% 32.9%

Freezers

- - - - - - 10% 10% 10%

The scaling factor for ea ch year was calculated as:


### Estar year 

### scale year 

### = Eq. 7.17 ( 

### F low 

### × P

_ Estar low 

### + F mid 

### × P

_ Estar mid 

### + F high 

### × P

_ Estar high )

A household in the low-income bin that purch ased a refrigerator in a given year was a assigned a probability Scale year times P_Estar low for having an ENERGY STAR refrigerator

. A similar approach was taken for households in the mid- and-high income bins.

7.3.5 Validating Field Energy Consumption

The values for refrigerator energy cons umption reported in RECS 2005 ranged from 6 kWh to more than 10,000 kWh for households having one refrigerator. DOE developed an approach that utilized the UAF s calculated for each household to confirm whether the reported values for refrigerators (and freezers) were re asonable. This approach required calculating maximum and minimum plausible UAFs fo r various refrigeration products.

A range of possible UAFs can apply to a given refrigerator, based on the range of possible refrigerator sizes and ages consistent wi th the household’s RECS response. If the range of UAFs for a given household was entirely outside the boundaries of what DOE considered to be plausible, DOE excluded the household from the LCC analysis. Such outliers occur if the maximum possible UAF for a record is lower than the minimum plausible UAF or if the minimum UAF is higher than the maximum plausible UAF.

If the range of UAFs for a given household intersected the range of plausible UAFs, the UAFs outside the boundaries were brought to the mi nimum or maximum plausible value. Thus, a household was not excluded from the sample if it had a plausible UAF.

7.3.6 Maximum Usage Adjustment Factor

To evaluate the maximum plausible UAF, DOE estimated the maximum plausible energy consumption of a refrigerator if it were running continuously. DOE ’s calculation of the maximum electricity consumption assumes that the compressor runs constantly, comparable to leaving the door open 24 hours a day for 365 days a year. The evaporator and condenser fans, the interior lights, and the gasket heater (found only on re frigerators built befo re 1993) also were assumed to run continuously. DOE assumed that both the refrigerator and freezer compartment have a 20-W light bulb. The defr ost cycle is often initiated based on the compressor run time.

7-20DOE assumed the defrost cycle runs for 10 minutes every 10 hours, which is the default input to the EPA’s refrigerator analysis (ERA) model. 10

Table 7.3.8 shows the power consumption and times DOE estimated for various components of each cycle for the ice maker. In real-world operation the compressor must run longer than indicated in Table 7.3.8 in order to extract the heat from the ice maker components, along with the latent heat of freezing from freezi ng water to make ice. To calculate the maximum theoretical electricity consumption, DOE assumed that the comp ressor already runs continuously, so there is no additional compresso r run time. The components consume a total of
6.3 Watt-hours per ice-making cycle. 11 The value used for maximum ice-making cycles per day
was nine. 12

Table 7.3.8 Power Consumption for Ice Maker Components
Component Watts Length of Cycle

Mold heater 185 2 minutes

Solenoid valve 20 8 seconds

Motorized ejector 3 2 minutes

The formula for calculating the maximum plausible UAF is:



### ( W Comp 

### + W Fans 

### + W Lights 

### + W Gasket 

### + W Defrost 

### × 1.7%) × 365 × 24 /1000 + kWh Ice 

### MaxUAF pl 

### =

, 

### TEC STD-EXIST-TP 

### × ESAF
Eq. 7.18

Where:

W

Comp = the power (in Watts) used by the compressor;

W

Fans = the power (in Watts) used by the fans;

W

Lights = the power (in Watts) used by the light;

W

Gasket = the power (in Watts) used by the gasket heater;

W

Defrost = the power (in Watts) used by the defrost cycle, which is active 1.7 percent of
the time
kWh Ice = the energy (in kWh) used to complete nine ice-making cycles per day (including mold heater, solenoi d, and ejector) in one year;

TEC STD-EXIST-TP = the test energy consumption; and
ESAF = the efficiency st andard adjustment factor.

DOE collected the wattage for most compone nts for the baseline models in several product classes from the Technical Support Docu ments (TSDs) developed in the analyses leading to the 2001 standard, the Ju ly 1995 notice of proposed rulemaking, 13 and the November
1989 final rule. 14 The earlier TSDs (March 1982 15 and June 1980 16 ) did not report baseline energy use for the compressor. The document s, however, do report the amount of time the

7-21refrigerator was running duri ng the test procedure. DOE cal culated the maximum plausible annual energy consumption by (1) increasing the test procedure output to wh at it would be if the refrigerator were running con tinuously and (2) adding a conti nuously burning 40-W light bulb.

The equation given above was used to calculate the maximum theoretical UEC and UAF for each baseline model in the TSDs. The theoretical maximum UAFs based on past TSDs for all of the analyzed product cl asses are shown in Tables 7.3.9 through 7.3.13.

7-22Table 7.3.9Theoretical Maximum Energy Consumption for Baseline Product Class 3 Refrigerator-FreezersBaseline(TSD)CompressorWEvaporatorFanWCondenserFanWLightsWGasketHeaterWDefrostWDefrost %Time On%IceMakingkWhTestProcedurekWhTimeon%MaxUEC*kWhMaxUAF†20011244.54.54004501.7%20.6544-1,5982.93Jul-951459.1124004501.7%20.6788-1,8912.40Nov-891861013.540194501.7%20.61,073-2,4362.27Mar-82---40----1,51865%2,4281.60Jun-80---40----1,80553%3,3811.87*Unit Energy Consumption.†Usage adjustment factor.Table 7.3.10Theoretical Maximum Energy Consumption for Baseline Product Class 5 Refrigerator-FreezersBaseline(TSD)CompressorWEvaporatorFanWCondenserFanWLightsWGasketHeaterWDefrostWDefrost %Time On%IceMakingkWhTestProcedurekWhTimeon%MaxUEC*kWhMaxUAF†20011334.54.54004501.7%20.6573-1,6773.69Jul-9514310.510.04004501.7%20.6845-1,8642.76Nov-8918710.013.540124501.7%20.61,324-2,3872.13Mar-82---40----2,20963%3,3401.79*Unit Energy Consumption.†Usage adjustment factor7-23Table 7.3.11Theoretical Maximum Energy Consumption for Baseline Product Class 7 Refrigerator-FreezersBaseline(TSD)CompressorWEvaporatorFanWCondenserFanWLightsWGasketHeaterWDefrostWDefrost %Time On%IceMakingkWhTestProcedurekWhTimeon%MaxUEC*kWhMaxUAF†20011418.04.5400.04501.7%20.67641,7772.33Jul-951508.011.6400.04501.7%20.69121,9202.11Nov-89186101440-01.7%20.61,7562,4421.39Mar-82---40----2,51752%4,5971.83Jun-80---40----2,42253%4,2841.77Note: The Max UAF derived from the 1989 TSD does notagree with the rest of the sample, making the R2drop from 0.99 to 0.41;thus it has been excluded from the regression.*Unit Energy Consumption.†Usage adjustment factorTable 7.3.12Theoretical Maximum Energy Consumption for Baseline Product Class 9 FreezersBaseline(TSD)CompressorWEvaporatorFanWCondenserFanWLightsWGasketHeaterWDefrostWDefrost %Time On%TestProcedurekWhTimeon%MaxUEC*kWhMaxUAF†kWh20011194.50.02004501.7%663-1,2601.90Jul-951269.00.02004501.7%759-1,3571.79Nov-8916910.00.02094501.7%1,088-1,8221.67Mar-82---20---1,30381%1,7841.37Jun-80---20---1,33287%2,1941.65*Unit Energy Consumption.†Usage adjustment factor7-24Table 7.3.13Theoretical Maximum Energy Consumptionfor Baseline Product Class 10 FreezersBaseline(TSD)CompressorWEvaporatorFanWCondenserFanWLightsWGasketHeaterWDefrostWDefrost %Time On%TestProcedurekWhTimeon%MaxUECkWhMaxUAF†kWh2001850020000.0%394-9162.32Jul-951010020000.0%472-1,0592.25Nov-891870020000.0%557-1,8133.26Mar-82---20---1,21580%1,6951.39Jun-80---20---115069%18421.60Note: The Baseline model from the 1989 TSD was excluded because its compressor power was100 W higher than to be expected if itfollowedthe trend in W/cu ft between 1995 and 2001.7-250 0.5

1 1.5

2 2.5

3 3.5

0 5 10 15 20 25 M a x U A F

Age PC3

PC5

PC7

PC9

PC10 The maximum annual energy consumption allo wed by a given standa rd scales linearly
with volume. DOE assumed that in the extreme case used to determine the maximum plausible energy consumption, annual energy consumption also scales linearly with volume. Therefore, the maximum theoretically possible UAF is constant for each production year and product class, regardless of volume.

Older refrigerators generally had low maximum plausible UAFs. As the minimum efficiency allowed by standards increased, compartments became better insulated and the refrigeration cycle more efficient. The compre ssor therefore uses less energy to maintain
conditions inside the cabinet and so runs for less time. Ordinary test procedure operation thus represents a smaller and smaller fraction of the extreme, all-out energy consumption used in the
calculations described in this section. Thus, the test proced ure energy use (TEC) for older refrigerators is closer to their maximum theoreti cally possible field energy consumption than it is for newer refrigerators.

The maximum theoretically possible UAF (Max UAF) scales linearly with age, as shown in Figure 7.3.5.

Figure 7.3.5 Maximum Usage Adjustment Factor by Product Age in 2005

7-26DOE performed a linear regression to fit Max UAF by vintage, thus providing a value of MaxUAF for a unit of any age. Table 7.3.14 show s the intercept and slope of the regression line for MaxUAF for each product class. The quality of the linear fit from the regression for each product class is shown by the R 2 value.

Table 7.3.14 Regression Parameters by Product Class for Maximum Usage Adjustment
Factor

Product

Class Description Slope Intercept R 2

3 Top-mount refrigerator-fre ezer -0.0554 3.0796 0.9033

5 Bottom-mount refrigerator-fr eezer -0.0733 3.0835 0.9298

7 Side-by-side refrigerator-freezer with
TTD ice service -0.0307 2.4140 0.9033

9 Upright freezer -0.0187 1.9671 0.6832

10 Chest freezer -0.0434 2.5638 0.9034

DOE compared the MaxUAF value to the sma llest possible UAF for the refrigerator for
each RECS record to determine whether the hous ehold’s refrigerator energy use was plausible and the RECS record should be retained in the analysis.

7.3.7 Minimum Usage Adjustment Factor

To estimate the least plausible UAF, DOE used EPA’s refrigerator analysis (ERA)
model. 10 DOE used the default models in ERA for product classes 3 and 10. Values for the other product classes were derived from the default models for those product classes. DOE assumed that product classes 3 and 5 have identical minimum UAFs.

For each year a TSD was published, DOE modifi ed the ERA input file to better match the
characteristics of the baseline model described in the TSD. Then the ERA model was run under test procedure conditions and under very favorab le conditions (such as in an air-conditioned kitchen or a basement). The temperature settings for the compartments were assumed to be the maximum allowed by the ERA model. DOE also assu med that any gasket heater was turned off. Tables 7.3.15 and 7.3.16 show the temperatur e settings used to model both these “ideal”
conditions and test conditions.
Table 7.3.15 Temperature Settings for Refrigerators Under Test and Ideal Conditions

Ambient

Temp. Air Entering
Condenser Air Under
Cabinet Fresh Food Compartment Freezer Compartment

Test
Conditions 32.2 °C (90.0 °F) 37.8 °C (100.0 °F) 35 °C (95.0 °F) 7.22 °C (45.0 °F) -15 °C (5.0 °F)

Ideal
Conditions 17 °C (62.6 °F) 19 °C (66.2 °F) 19 °C (66.2 °F) 10 °C (50.0 °F) -2 °C (28.4 °F)

7-27Table 7.3.16 Temperature Settings for Freezers Under Test and Ideal Conditions

Ambient

Temp. Air Entering
Condenser Air Under
Cabinet Freezer Compartment

Test
Conditions 32.2 °C (90.0 °F) 37.8 °C (100.0 °F) 35 °C (95.0 °F) -17.8 °C (0.0 °F)

Ideal
Conditions 12 °C (53.6 °F) 14 °C (57.2 °F) 14 °C (57.2 °F) -9.99 °C (14.0 °F)

In order to validate the model, DOE co mpared the ERA simulation model under test procedure conditions to the results of the test pr ocedure reported in each TSD. In addition to the temperatures listed in Tables 7.3.15 and 7.3.16, the other control settings during the test were:

• Defrost controls were not opera tive during the test procedure.

• Anti-sweat heater switch was set to the pos ition that consumes the maximum energy.

The 1995 TSD also mentions a correction fact or to adjust the ERA model results based on the tested consumption. Corr ection factors for DOE’s modeling for this analysis, as well as the values cited in the 1995 TSD, are listed in Tabl e 7.3.17. If the error per centage is greater than 0, it means that the ERA model overestimated the energy use in the test procedure, and the value
of CAL in Eq. 7.19 is greater than 1.

Table 7.3.17 Model Errors by Product Class and Vintage

Product Class DOE % Error Estimate from 1995
TSD % 1989 1995 2001

Top-Mount 5.93 4.14 22.29 5.93
Side-by-Side 12.15 5.16 8.54 12.15
Upright Freezer 19.67 15.54 17.74 19.67

Chest Freezer 0.64 12.11 11.84 0.64

The simulation models produced the same range of error as those specified in the 1995 TSD. When calculating the minimum UAF, this calibration factor cancels out, as shown in the following equation, because the ERA model also over-estimates the energy use in the ideal conditions by the same factor. DOE de fined the minimum plausible UAF as:

FEC Ideal RECS FEC ERA CAL MinUAF = = Eq. 7.19 TEC × ESAF TEC × ESAF
ERA RECS CAL
Where:

FEC Ideal_ERA = minimum field energy consumption modeled in ERA under ideal conditions,
TEC ERA = test energy consumption modeled in ERA under existing test procedure conditions,
FEC RECS = field energy consumption of the RECS record,
7-28TEC RECS = test consumption calculated based on the volume and age designated for the UAF calculation,
CAL = calibration factor defined by the ra tio between the results from the ERA model and the test procedure,
ESAF = efficiency standard adjustment factor.

Figure 7.3.6 shows the results of calculating the minimum pl ausible UAF as a function of vintage.

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40

0 5 10 15 20 M i n U A F

Age Top Mount Side by Side
Chest Freezer Upright Freezer

Figure 7.3.6 Minimum Plausible Usage Adjustme nt Factor as a Function of Product Age in 2005

DOE performed a linear regression for each pr oduct class in order to model the relation between the minimum UAF and the vintage of a unit. The following table shows the resulting
parameters.

7-29Table 7.3.18 Regression Results Ba sed on Unit Vintage

Product Class Slope Intercept R 2

Top-Mount -0.0048 0.2496 0.909

Side-by-Side -0.0033 0.2356 0.8022

Upright Freezer -0.0025 0.3000 0.8107

Chest Freezer -0.0055 0.3325 0.6448

DOE assumed that minimum UAFs are constant across volu mes, that bottom-mount and top-mount products have the same minimum UAF, and that through-the- door ice service does
not affect the minimum UAF.

7.3.8 Results by Product Class

Figures 7.3.7 through 7.3.16 show the distri bution of UAFs for the RECS households in the subsample that represents each standard -sized product class. Each figure shows the
distribution of UAFs before and after the truncation produced by applying the minimum and
maximum UAFs. The distribution used for LCC analysis is the dist ribution after removing households having implausible UAFs.

7-30Frequency Chart

.000 .006 .013 .019 .025

0 62.5 125 187.5 250

0. 117 0. 754 1. 391 2. 027 2. 664 10,000 Trials 9, 800 Displ ayed Forecast : UAF (1)

Figure 7.3.7 Initial UAF Distribution for Standard-Size Top-Mount Refrigerator-Freezers (Product Class 3)

Frequency Chart

.000 .007 .013 .020 .027

0 66.5 133 199.5 266

0. 181 0. 804 1. 427 2. 050 2. 673 10,000 Trials 9, 858 Displ ayed Forecast : UAF (1)

Figure 7.3.8 Final UAF Distribution for Standard-Size Top-Mount Refrigerator-Freezers (Product Class 3)

7-31Frequency Chart

.000 .007 .014 .020 .027

0 68.25 136.5 204.7 273

0. 153 0. 708 1. 263 1. 818 2. 373 10,000 Trials 9, 853 Displ ayed Forecast : UAF (1)

Figure 7.3.9 Initial UAF Distribution for Standard-Size Bottom-Mount Refrigerator-Freezers (Product Class 5)

Frequency Chart

.000 .006 .013 .019 .025

0 63 126 189 252

0. 137 0. 698 1. 258 1. 818 2. 379 10,000 Trials 9, 899 Displ ayed Forecast : UAF (1)

Figure 7.3.10 Final UAF Distribution for Standard-Size Bottom-Mount Refrigerator-Freezers (Product Class 5)

7-32Frequency Chart

.000 .006 .012 .019 .025

0 62 124 186 248

0. 199 0. 833 1. 467 2. 100 2. 734 10,000 Trials 9, 889 Displ ayed Forecast : UAF (1)

Figure 7.3.11 Initial UAF Distribution for Standard-Size Side-by-side Refrigerator-Freezers (Product Class 7)

Frequency Chart

.000 .005 .011 .016 .021

0 53 106 159 212

0. 233 0. 778 1. 323 1. 869 2. 414 10,000 Trials 9, 997 Displ ayed Forecast : UAF (1)

Figure 7.3.12 Final UAF Distribution for Standard-Size Side-by-side Refrigerator-Freezers (Product Class 7)

7-33Frequency Chart

.000 .006 .012 .018 .024

0 60.5 121 181.5 242

0. 372 1. 234 2. 096 2. 958 3. 820 10,000 Trials 9, 825 Displ ayed Forecast : UAF (1)

Figure 7.3.13 Initial UAF Distribution for Standard-Size Upright Freezers (Product Class 9)

Frequency Chart

.000 .010 .020 .030 .040

0 99.25 198.5 297.7 397

0. 331 0. 736 1. 140 1. 544 1. 948 10,000 Trials 9, 919 Displ ayed Forecast : UAF (1)

Figure 7.3.14 Final UAF Distribution for Standard-Size Upright Freezers (Product Class 9)

7-34Frequency Chart

.000 .006 .012 .018 .024

0 59.25 118.5 177.7 237 10,000 Trials 9, 885 Displ ayed Forecast : UAF (1)

0.103 1.416 2.729 4.042 5.356

Figure 7.3.15 Initial UAF Distribution for Standard-Size Chest Freezers (Product Class 10)

Frequency Chart

.000 .008 .017 .025 .034

0 84 168 252 336

0. 343 0. 898 1. 453 2. 008 2. 564 10,000 Trials 10,000 Di spl ayed Forecast : UAF (1)

Figure 7.3.16 Final UAF Distribution for Standard-Size Chest Freezers (Product Class 10)

The maximum plausible UAF limits the freezer sample more than the refrigerator-freezer sample. The maximum is more restrictive for fr eezers because their compressors are assumed to run more than 80 percent of the time in normal opera tion, as opposed to 52 percent to 65 percent of the time for refrigerators. As a result, in creasing appliance energy use to its theoretical maximum, to reflect a compressor that runs 100 percent of the time, has a smaller effect for freezers. RECS also has a simpler model for estim ating household energy use for freezers than it does for refrigerator-freezers, which may contri bute to the wide range of energy consumption assigned to freezers across the household sample . The minimum and maximum UAF thresholds enabled DOE to remove from the sample households having unrealistic freezer energy consumption.

7-35Table 7.3.19 summarizes the characteristics of the UAFs before and after the final sample
was selected.

Table 7.3.19 Usage Adjustment Factors Before a nd After Excluding Minimums and
Maximums

Product Class Complete RECS Sample After Selecting Sample Based On
Min and Max Plausible UAF

Mean
UAF Min
UAF Max
UAF Sample
Size Mean
UAF Min
UAF Max
UAF Sample
Size
Top-mount refrigerator-freezer 1.254 0.115 4.203 2,303 1.227 0.134 3.08 2,231

Bottom-mount refrigerator- freezer 1.079 0.097 3.155 2,303 1.077 0.134 2.888 2,242

Side-by-side refrigerator-freezer 1.46 0.17 4.219 1,026 1.437 0.201 2.414 871

Upright freezer 1.7988 0.324 5.367 248 1.37 0.316 1.967 170

Chest freezer 2.248 0.103 7.795 369 1.479 0.343 2.564 243

7.3.9 Distributions: Comparison with Other Studies

The variation in UAFs within the national RECS sample has several causes, including indoor temperature, appliance age, and varying usage patterns. Meier et al. 17 and Miller and

Pratt 18 indicate that refrigerator energy use varies significan tly in response to ambient temperature, which implies that climate contri butes to variation in household energy use. In addition, refrigerators generally use more energy as they age, 19 and the RECS sample includes appliances having a wide range of ages. Hous ehold choices regarding the frequency of door opening and how often and how much warm food is loaded into the unit, along with the ambient temperature in the kitchen, likely add to variabi lity. In addition, the DOE test procedure does not measure energy consumed by ice making, so it is not reflected in the labeled energy consumption. The presence or absence of an auto matic ice maker, as well as variation in the amount of ice made, also contribute to the varia tion in UAF within and be tween product classes.

In addition to their significant width, th e UAF distributions shown in Figures 7.3.7 through 7.3.16 do not have a mean value of 1, indicating that the average energy use for a refrigerator drawn from the American residential st ock differs from the labeled energy use of that same refrigerator when it was new. This result is consistent with reports in the literature. A full literature survey, available in appendix 7-A, is summarized here. Refriger ator energy use may be characterized by three measures:

(A) the label on the product when new, de rived from the DOE test procedure;

7-36(B) the results of the DOE test procedure on a particular appliance after it has been used in the field; and (C) the in situ (ideally directly measured) ener gy consumption in a user’s home.

The UAF for a given refrigerat or is the ratio of (C) to (A ). Studies described in the
literature examined two classes of refrigerators: new or likely ne w (installed in new homes), for which the usual comparison is (C) to (A); and recycled/disposed refrigerators, for which all possible pairs of measures have been compared.

Studies of new (or likely new) refrigerators in consumers’ homes reveal a wide variation in energy use among consumers. The mean energy consumption cited in those studies lies within 40 percent of the appliance label. 20 The literature indicates that re frigerators in cooler climates tend to use less energy than their labeled energy consumption, 19 whereas those in warmer locations tend to use more energy than labeled. This difference contributes to the width of the
national UAF distributions.

Studies of non-new refrigerator s generally examine refrigerator s collected as part of early replacement programs operated by electric utilities. Such studies are used to measure the effect of the utility program and to obtain credit for the energy reductions resu lting from replacing old appliances. The non-new refrigerator s described in the lit erature, which must be in use by their owners, commonly are relative ly old. Measurements, both in situ and from the DOE test procedure, show these refrigerators use significan tly more energy than the labeled consumption.

KEMA 21 used the DOE procedure to test 136 such re frigerators. This comparison of (B) to (A) isolates the effect of age from those of user behavior or environment. KEMA found that the median increase in energy consumption relative to labeled use was 46 percent, and that roughly 15 percent of the sample used more than twice the labeled energy. Only 7 percent of the sample
used less than labeled. When Peterson et al. 22 combined the data from several studies (of a total of 193 recycled refrigerators), they found that the average incr ease in energy consumption, as measured by the DOE test procedure, was 50 percent, with 25 percent of refrigerators using more than 1.7 times their labeled energy. Miller and Pratt 18 performed a regression analysis on in-use refrigerators in New York public housing [a (C ) to (A) comparison], deducing an average 1.4­ percent increase in energy use per year. These studies indicate th at the UAF distribution for old refrigerators is expected to be wide and to have a mean significantly higher than 1.

Several aspects of in-use refrigerator operation are not reflected in the DOE test procedure and therefore affect the UAF. In particular, the DOE test does not measure the energy used by ice makers. Estimates of the effect of th is omission range from 5 percent to 26 percent, 11 with a rough estimate of 10 percent being common and consistent with published direct measurements. Through-the-door (TTD) ice maki ng may consume more energy than non-TTD ice making. DOE therefore expects the UAF dist ribution from product cla sses that include TTD ice makers to have a somewhat higher mean than classes that do not. The size of the difference depends on the fraction of non-TTD refrigerators that use ice make rs, and the possible difference in ice-making behavior among users of va rious product classes. Meier and Martinez 11 also report that ice-making energy may increase over time, co mpounding the increased energy use with age.

7-37A national sample of refrigerators, such as RECS, covers refrigerators in various climate zones and of various ages. As such, DOE exp ects those two factors (as well as behavioral differences among users) to pr oduce significant scatter in the UAF. If new refrigerators use energy at close to their labeled rate as determined by the DOE test, and refr igerators at retirement use significantly more energy when tested using the same procedure, the national mean UAF is expected to be greater than 1. DOE could not conclude from the li terature that a particular value or distribution should be assigne d to the UAF, Therefore, DOE ca nnot justify further adjusting
the UAF distribution derived from RECS.

7.4 ENERGY USE OF COMPACT REFRIGERATION PRODUCTS

As mentioned in the introduc tion to this chapter, compact refrigerators and freezers are used in homes, college dormitories, hotels and motels, and some commercial buildings. DOE found no data on the typical field energy consum ption of compact refrigeration products. It therefore assumed that the average field energy use of compact refrigerators and freezers of a given size is the same as the maximum energy use allowed by the DOE standard, as measured in the DOE test procedure. In effect, DOE assumed that variation in field energy use of compact products is a function solely of volume. To repr esent the distribution of volumes in the field, DOE used data from the 2008 CEC appliance model database. 2 Figures in appendix 7-B show the distribution of appliance sizes represented within the database.

DOE used the CEC database to develop a li near equation relating listed total volume to adjusted volume for product class 11. The parameters of the equation are list ed in Table 7.4.1. For compact freezers, the adjusted volume is equal to 1.73 times the volume. 3 DOE then used the relation between adjusted volume and energy use de scribed by the DOE test procedure to relate
the distribution of volumes in the CEC databa se to a distribution of energy use values.

Table 7.4.1 Parameters for Calculating Adjusted Vo lume from Total Volume for Compact Refrigerators Product Category Slope Intercept R 2 Count Compact Refrigerators 1.0458 -0.0905 0.9822 187

7.5 ANNUAL ENERGY CONSUMPTIO N BY EFFICIENCY LEVEL

This section reports the annual field ener gy consumption calculated for refrigeration products that meet new efficiency standards if they were used in RECS 2005 homes. As described in section 7.2, DOE calculated fiel d-adjusted annual energy consumption for each home’s refrigeration product by multiplying the tested energy consumption of a new refrigeration product, measured using the existin g test procedures, by th e efficiency standard adjustment factor (ESAF), which is a constant for each product class, and by the UAF for that
household.

7-38As discussed in chapter 5, DOE analyzed sp ecific efficiency levels for the considered product classes. Tables 7.5.1 through 7.5.6 s how the considered efficiency levels and corresponding annual energy consumption for each pr oduct class. The tables for standard-sized products show the average annual energy consum ption according to the proposed DOE test procedure (“proposed test”) a nd in the average en ergy use based on the corresponding RECS 2005 household subsamples (“field”). The tables for compact appliances (product classes 11 and 18) show the average annual energy consumption according to the proposed DOE test procedure, using a distribution of product volumes based on the CEC appliance database.

Table 7.5.1 Product Class 3, Top-Mount Refrigerator-Freezers Without Through-theDoor Ice Service: Average Annual Energy Use by Efficiency Level
Efficiency Level (percent less than baseline energy use) Proposed Test Field

kWh/year kWh/year

Baseline 534 657
1 (10%) 481 591
2 (15%) 454 558
3 (20%) 428 526
4 (25%) 401 493
5 (30%) 374 460
6 (35%) 347 427
7 (40%) 321 394
8 (45%) 294 361

7-39Table 7.5.2 Product Class 5, Bottom-Mount Refrigerator-Freezers Without Through-theDoor Ice Service: Average Annual Energy Use by Efficiency Level
Efficiency Level (percent less than baseline energy use) Proposed Test Field

kWh/year kWh/year

Baseline 652 699
1 (10%) 587 629
2 (15%) 554 594

3 (20%) 522 559
4 (25%) 489 524
5 (30%) 456 489
6 (35%) 424 454
7 (40%) 391 419
8 (45%) 359 384

Table 7.5.3 Product Class 7, Side-by-side Refrigera tor-Freezers with Through-the-Door Ice Service: Average Annual Energy Use by Efficiency Level
Efficiency Level (percent less than baseline energy use) Proposed Test Field

kWh/year kWh/year

Baseline 756 1087
1 (10%) 680 979
2 (15%) 643 924
3 (20%) 605 870
4 (25%) 567 815
5 (30%) 529 761
6 (35%) 491 707
7 (40%) 454 652

7-40Table 7.5.4 Product Class 9, Upright Freezers: Average Annual Energy Use by Efficiency
Level
Efficiency Level (percent less than baseline energy use) Proposed Test Field

kWh/year kWh/year

Baseline 717 980

1 (10%) 646 882
2 (15%) 610 833

3 (20%) 574 784
4 (25%) 538 735
5 (30%) 502 686
6 (35%) 466 637
7 (40%) 430 588
8 (45%) 394 539

Table 7.5.5 Product Class 10, Chest Freezers: Average Annual Energy Use by Efficiency
Level
Efficiency Level (percent less than baseline energy use) Proposed Test Field

kWh/year kWh/year

Baseline 428 623
1 (10%) 385 561
2 (15%) 364 530
3 (20%) 342 498
4 (25%) 321 467
5 (30%) 300 436
6 (35%) 278 405
7 (40%) 257 374
8 (45%) 235 343

7-41Table 7.5.6 Compact Refrigerators and Freezers: Average Annual Energy Use by Efficiency Level

Efficiency Level (percent less than baseline energy use) Product Class
11: Compact refrigerators and refrigerator-freezers with manual defrost (kWh) 18: Compact chest freezers (kWh)

Baseline 325 313

10% 292 282

15% 276 266

20% 260 250

25% 244 235

30% 227 219

35% 211 203

40% 195 188

45% 179 172

7-42REFERENCES

1 U.S. Department of Energy–Ene rgy Information Administration. Residential Energy Consumption Survey, 2005 Public Use Data Files. 2009. U.S. Department of Energy: Washington, D.C. < www.eia.doe.gov/emeu/recs/recspubuse05/pubuse05.html >

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< www.energy.ca.gov/app liances/database/excel_based_files/Refrigeration/ > (Last accessed April 25, 2009.)

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10 Merriam R., Verone A., Feng H. EPA Refrigerator Analysis (ERA) Program: User's Manual
Version 1.0 , Cambridge, MA: Arthur D. Little Inc. March 1993.

7-4311 Meier, A. and M. Martinez. Energy Use of Icemaking in Domestic Refrigerators. ASHRAE Transactions: Symposia. 1996. AT-96-19-2.

12 Parker, D. and T. Stedman. Measured Electri city Savings of Refrigerator Replacement: Case Study and Analysis. ACEEE 1992 Summer Study on Energy Efficiency in Buildings, Proceedings—Commercial Performance: Analysis and Measurement Panel 3. 1992. American Council for an Energy-Efficient Economy.

13 U.S. Department of Energy–Office of Ener gy Efficiency and Renewable Energy. Energy Conservation Program for Consumer Pr oducts: Technical Suppor t Document: Energy Efficiency Standards for Consumer Products: Refrigerators, Refrigerator-Freezers, and Freezers. July 1995. Washington, D.C.

14 U.S. Department of Energy–Office of Ener gy Efficiency and Renewable Energy. Energy Conservation Program for Consumer Pr oducts: Technical Suppor t Document: Energy Efficiency Standards for Consumer Products : Refrigerators and Furnaces. November 1989. Washington, D.C.

15 U.S. Department of Energy–Office of Energy Efficiency and Renewable Energy. Consumer Products Efficiency Standards: Engineering Analysis Docume nt. March 1982. Washington,
D.C. DOE/CE-0030.

16 U.S. Department of Energy–Office of Energy Efficiency and Renewable Energy. Consumer Products Efficiency Standards: Engineeri ng Analysis. June 1980. Washington, D.C.
DOE/CE-0166.

17 Meier. A., A. Megowan, B. Litt, and B. Pon. The New York State Resi dential Refrigerator Electrical Energy Monito ring Project: Final Report . 1993. Lawrence Berkeley National Laboratory: Berkeley, CA. Report No. LBL-33708.

18 Miller, J.D. and R.G. Pratt. Estimates of Refrigerator Loads in Public Housing Based on Metered Consumption Data . 1998. Pacific Northwest National Laboratory. Report No.
PNNL-11991.

19 Meier, A.. and R. Jansky. Field Performance of Residential Refrigerators: A Comparison with the Laboratory Test . 1991. Lawrence Berkeley Laborat ory: Berkeley, CA. Report No.
LBL-31795.

20 Meier, A. “Refrigerator Energy Use in the Laboratory and in the Field.” Energy and Buildings. 1995. 22: pp. 233–243.

21 KEMA. 2004. 2003 EM&V RARP Study:Degradation and Market Potential Analysis

. Prepared for Southern California Edison, Rose mead, CA. Prepared by KEMA Inc., Madison,

7-44WI. December 23, 2004. CALMAC STUDY ID SCE0205 ma:projec t:scee0015 rarp 03 evaluation:report:title.

22 Peterson, J., D. Dohrmann, T. Alereza, S. Samiullah, S. Westberg, and J.H. Redd. Gross Savings Estimation for Appliance Recycling Programs: the Lab Versus in situ Measurement Imbroglio and Related Issues. Proceedings of the 2007 Intern ational Energy Performance Evaluation Conference (IEPEC). 2007. Chicago, IL. August. Report 653. 17 pp.

7-45APPENDIX 7-A. LITERATURE SURV EY OF ENERYG CONSUMPTION BY
RESIDENTIAL REFRIGE RATOR-FREEZERS

TABLE OF CONTENTS

7-A.1 INTRODUCTION .................................................................................................7-A-1
7-A.2 TEST PROCEDURE A ND FIELD STUDIES......................................................7-A-2
7A.2.1 DOE Test Procedure ..............................................................................................7-A-2
7A.2.2 Field Studies........................................................................................................... 7-A-3 7A.2.2.1 KEMA-Xenergy Findings....................................................................7-A-3
7-A.3 LITERATURE ANALYSIS ..................................................................................7-A-5
7-A.4 SUMMARY...........................................................................................................7-A-6
7-A.5 BIBLIOGRAPHY..................................................................................................7-A-6

LIST OF TABLES

Table 7-A.2.1 Refrigerator Energy Consumption Data by Year.......................................7-A-3 Table 7-A.2.2 Literature summary....................................................................................7-A-4

7A-iAPPENDIX 7-A. LITERATURE SURVEY OF ENERGY CONSUMPTION BY

RESIDENTIAL REFRIGERATOR-FREEZERS

7-A.1 INTRODUCTION

Efficient refrigerator-freezers reduce peak en ergy consumption as well as total household energy use. As a result, electric utilities regard replacement progr ams for these appliances as an attractive and effective way to reduce residential energy consump tion. To estimate the amount of electricity savings attributable to an energy-e fficient refrigerator-freezer program, utilities must evaluate the difference between the pre- and pos t-program energy consumption of the appliance stock. The challenge to accurately estimate the electricity savings of a refrigerator-freezer replacement program lies in estimating the real-life consumption of the original and replacement
units.

Estimation of appliance energy consumption may be undertaken in three ways, all of which are represented in the literature: A) The labeled energy consumption on a new appliance, based on the U.S. Department of Energy (DOE) test procedure underta ken on a sample of several identical appliances, and reported by the appliance manufacturer B) The DOE test procedure applied to a particul ar appliance (often not a new appliance),
and C) Measurement for some period of time in situ in a household. Most studies compare two of these measurements in order to evaluate energy use. For example, a study might compare the results of the DOE test procedure on an old refrigerator with the labeled energy consumption when new to isolate th e effect of appliance age, while eliminating possible effects due to user beha vior. This appendix refers to such a study as comparing (B) to (A).

Researchers have conducted studies that meas ure the field consumption of refrigeratorfreezers to compare in situ measurements to the DOE test results, represented either by the labeled results ((C) to (A)), or through direct testing under DOE conditio ns ((C) to (B)). When such field studies are evaluated, the lack of consistency among study conditions (such as geographic location, housing type, and the number a nd type of units), limited time of direct measurements, and the degradation of efficiency throughout the lifetime of a refrigerator-freezer
contribute to the challe nge of estimating potential energy c onsumption savings from new units.

This appendix summarizes available liter ature regarding the comparison of different measurement methods for refrigerat or-freezers in order to evaluate reasonable possible values for the ‘usage adjustment factor’ (UAF), which is an estimate of the ratio of (C) to (A). There are very few published measurements of freezers or compact appliances, so DOE addresses only refrigerator-freezers in this summary. Section 2 su mmarizes the DOE test procedure and lists and
characterizes the field studies wh ich DOE used in its analyses. S ection 3 discusses these studies and their implications for the UAF parameter used in Chapter 6, particularly regarding variation with season and climate, and effici ency degradation with unit age.

7-A-1