7-A.2 TEST PROCEDURE AND FIELD STUDIES
This section describes the DOE test proce dure, then lists field studies of energy consumption by refrigerator-freeze rs and distills their results.

7A.2.1 DOE Test Procedure
“The DOE test is a compromise between r ealism and minimizing the costs of performing a reliable, repeatable laboratory test” (Meier , 1993). The DOE procedure for evaluating the annual energy consumption of refr igerator-freezers comprises the following features (10 CFR, Chapter II, Part 430, Appendix A1).

• The standard test temperature for the fresh food compartment is 45°F.

• The standard test temperature fo r the freezer compartment is 5°F.

• The test is performed in a chamber that is ma intained at an ambient temperature of 90°F.

• The temperatures of the freezer and fresh food compartments are measured using three independent thermocouples, one for each compartment. Five thermocouples are used when the refrigerator height is over 40”.

• The appliance’s energy consump tion is calculated by interpolating test results that bracket the standard freezer temperature (5 °F). Interpolation is done around the 5°F temperature (freezer compartment) and the 45°F temperature (fresh food compartment).

• Ambient relative humidity is not specified.

• Doors are not opened during the test.

• The fresh food and freezer compartments are empty.

• Ice making capability, if present, is no t powered on or evaluated by the test.

The DOE test procedure is currently under going a rulemaking process which may change some of the above details. In pa rticular, changes have been proposed to the test temperatures for the refrigerator and freezer compartments.

The DOE test procedure does not measure the effects of door opening, cooling warm food, or ice making. However, this test procedure provides standardi zed results that can serve as the basis for comparing the performance of appl iances. Although the DOE test does not precisely mirror any single unit’s performance in situ , it serves as a fou ndation to which field measurements may be compared to develop estim ates that account for a range of real-life circumstances (KEMA, 2004).

A summary of new refriger ator-freezer unit energy cons umption values provided by manufacturers by year shows the annual variat ion of shipment-weighted refrigerator energy consumption from 1960s to the year 2006 (Table 2.1). These data are based on “nameplate” values. For the model years before the DOE energy standards (1989 a nd earlier), the test conditions are unknown in which energy consumpti on quantities were measured, although it is likely that manufacturers used the American Home Appliance Manufacturers (AHAM) test procedure or the test procedure prescribed by California state energy conservation standards.

7-A-2Table 7-A.2.1 Refrigerator Energy Consumption Data by Year

Model Year Shipment Weighted Average Use (kWh/yr) Model Year Shipment Weighted Average Use (kWh/yr) 2006 564 1990 988 2005 550 1989 1006 2004 559 1988 1049 2003 589 1987 1052 2002 576 1986 1165 2001 611 1985 1147 2000 779 1984 1139 1999 762 1983 1160 1998 738 1982 1191 1997 728 1981 1190 1996 708 1980 1278 1995 693 1975 – 1979 1530 †
1994 693 1970 – 1974 1730 †
1993 699 1965 – 1969 1540 †
1992 877 1961 – 1964 1150 †
1991 918 Source: AHAM Fact Books †: Approximate

7A.2.2 Field Studies

In situ conditions account for several importa nt factors including: ambient air temperature; the number and duration of door openi ngs; the temperature of food loaded into the unit; the placement of the unit in relation to walls , ovens, and stoves; the temperature setting in the field; and the ice maker setting in the field.

Since the early 1980s, utilities and government agencies have collected data on fieldmeasured refrigerator-freezer energy consumption in order to evaluate the effects of refrigerator “early replacement” programs. Th e collected data varies treme ndously by sample size, the type of refrigerator-freezer studi ed, the length of time each appl iance was monitored, and their operating conditions. The studies summarized in Table 2.2 describe the performance of refrigerator-freezers as measured in various ways.

7A.2.2.1 KEMA-Xenergy Findings
The private consulting firm KEMA-Xener gy in 2002 reviewed numerous reports of in situ performance studies for Sout hern California Edison. Several reports were summarized by KEMA-Xenergy but are not available to be revi ewed by DOE. These reports are indicated by a “#” in Table 2.2.

7-A-3Table 7-A.2.2Literature summaryAuthors(s)YearRatioAverageaRatio RangeComparisonTypeLocationRefrigeratorTypeAdjusted forclimate or seasonNo. ofRefrigeratorsArthur D. Little, Inc.#1982>1.2C to AFloridaunknownNounknownTopping & Vineyard19820.85 to 1.5bC to ANorfolk, VANewNoa47Meier & Jansky19930.85 is “typical”0.56 to 1.17C to ACold climates (many inPacific Northwest)Relatively newNo209Meier et al.1993B to A: 0.99,C to A: 0.87B to A: 0.89 to1.10B and C to ARochester, NYNew, “energyefficient”, frost-freeNo20Bos#1993“considerably” > 1B to ASacramento, CAAt replacementN/A79Quantum Consulting19940.87 for “highefficiency”, 1 for“super-efficiency”95% betweenroughly 0.7and 1.25C to ASouthern CA (SCE)1-3 years oldNo98Proctor Engineering(Dutt et al.)1994Between 0.86 and 0.9cC to ANorthern CA (PG&E)New, “energyefficient”Yesd256Goett#1995approx. 1UnknownCA (PG&E and SCE)NewNounknownBarakat & Chamberlin#1996“significantly more”than 1B to AUnknownAt replacementN/AunknownMiller & Pratt19981.10.72 to 1.2eC to ANew York City (multi­family public housing)Some new, someolderNo324Kinney & Belshe20010.96 (new);1.3 (mixture)C to ANew York City (multi­family public housing)220 old, 56 newNo276ICF Consulting2003approx. 0.5C to statisticalmodel of CCA (Bay Area)At replacementNo40Mowris#20031.06wide variationC to ANorthern CA (6 cities)At replacementunknown91KEMA20041.46 (median)0.85 to > 3B to ACaliforniaAt replacementN/A136Peterson et al.2007median 1.4, mean 1.5B to ACaliforniaAt replacementN/A193ADM, Athens, et al.20080.81 to 0.88,depending on weathermodelC to BCaliforniaAt replacementYes184aA value greater than 1 for this ratio for a C to A comparisonimplies that energy use in thefield (C) was greater than the labeled energy consumption (A).#KEMA-Xenergy (2004) is DOE’s only reference for the results of this study.bSeasonal variation for a single modelcRatio of average C to average A over sampledAdjusted for typical meteorological year (TMY) at locationeVariation in the mean of various types of refrigerators in various use environments7-A-47-A.3 LITERATURE ANALYSIS
DOE’s interest in surveying the refrigerator-fre ezer energy use literature is to evaluate the range of possible appropriate valu es for the ‘usage adjustment factor’, or UAF. The UAF is a “(C) to (A)”-type measurement, relating energy us e in situ to the DOE test result for a new appliance.

Studies of new appliances include Meier & Jansky (1993), Meier et al . (1993), Dutt et al. (1994), Quantum (1994), Goett (1995), Miller & Pratt (1998), and Kinney & Belshe (2001). The average (or typical) values of the ratio of (C) to (A) for th ese studies range from 0.85 to 1.1, and there is significant variation, w ith ratios ranging from 0.56 to 1.25. The majority of these studies are not adjusted for ambient temperature vari ations or climate (although several use year-long samples to eliminate seasonal effects). The only of th ese studies which is adjusted (Dutt et al.) is normalized to the climate of the particular locatio n of the measurements, rather than to a national average climate model. Taken collectively, these studies do not allow DOE to draw conclusions regarding possible national vari ation in new-refrigerator ener gy use, particularly due to variations in climate. They do indicate that the labeled energy consumption of a new appliance is likely to be accurate in situ to within 40%, as suggested by Meier (1995).

Studies of refrigerators at the time of re placement by utility progr ams show higher energy use relative to the labeled energy consumption than do new refrigerators. Fo r older refrigerators, studies predominantly take two form s: (B) to (A) or (C) to (A). (B) to (A) studies isolate the effects of age from any other effects (s uch as behavior or ambient temperature in situ ), while (C) to (A) studies give a direct in dication of the ‘UAF’ of old a ppliances. These studies are not necessarily representative of all older refrig erators, because they study only those units and households participating in utility refrigerator recycling programs.

Test-procedure-only compar ison studies include Bos ( 1993), Barakat & Chamberlin (1996), KEMA (2004) and Peterson et al. (2007). All four of these studies show significant energy use increase in the DOE test procedure; KEMA and Peterson both indicate an energy use increase of close to 50%, with wide variation. Only 7% of the refriger ators measured by KEMA used less than their labeled consumption. 25% of the refrigerators measured by Peterson et al. used more than 70% more that their labeled consumption.

Miller & Pratt (1998), Ki nney & Belshe (2001), and Mowris (2003) undertook direct evaluation of the ratio of in situ to labeled consumption for older refrigerators. The average ratio in all three studies was measured to be larger than one, although smaller than the test-procedurebased comparisons. Mowris indicated wide varia tion in energy use relative to the label, and Miller & Pratt’s sub-categories show a range of energy consump tions from 28% below the label to 20% above.

Only one study reviewed by DOE compared in situ energy use to the DOE test on the same appliance (ADM, Athens, et al., 2008), a (C ) to (B) comparison. Depending on the weather

7-A-5model used to adjust the in situ measurements, they found that on average the DOE test procedure overestimated the in situ use by 13 to 23%. This study does not include an indication of how the DOE test consumption comp ared with the labeled consumption.

Testing has confirmed that age, in combina tion with other refriger ator characteristics, accounts for the degradation of refrigerator en ergy efficiency (KEM A, 2004; Peterson, 2007). Therefore, energy efficiency degradation is a f actor in calculating the savings between new and replacement units. Energy use increases when barri ers to cabinet air and heat leakage degrade. For example, door seals no longer close tightl y, damaged walls allow air flow, and wet or degraded insulation no longer performs its function.

Two studies (KEMA, 2004 and Miller & Pratt, 1998) used regression analysis to measure the average effect of annual degradation on appliance energy use. KEMA determined an energy use growth rate of roughly 40 kWh/year, dependi ng on model characteristic s. Miller & Pratt’s regression model predicts a 1.37% increase in energy use each year. Smit (2006) reports that Athens (1998) calculated a degr adation rate of 0.6% per year.

7-A.4 SUMMARY
This appendix summarizes current literatur e pertaining to the di fference between DOEtest based measurements (when new or at re tirement) and field-based measurements of refrigerator-freezer energy consumption. In situ energy use was found to be close to labeled consumption for new refrigerators, but higher than labe led at the time of replacement. This appendix has examined the mean values and variab ility from the literature ; the variability across a national sample is likely much gr eater than the range addressed here.

Degradation of the refrigerator unit contribu tes to the discrepancy between the DOE test and field measured energy consumption data. Howe ver, the precise rate of efficiency decrease (and particularly its variability) cannot be determined from the literature.

7-A.5 BIBLIOGRAPHY
ADM Associates, Inc. 2004. Southern California Edison 1994 Residential Appliance Efficiency Incentive Program Ninth Year Retention Study . CEC Study ID #546A. Prepared for Southern California Edison Company. July 2004.

ADM Associates, Inc.; et al. 2008. Evaluation Study of the 2004-05 Statewide Residential Appliance Recycling Program; 2004-2005 Programs #1114, #1157, #1232 and #1348 Final Report and Appendices. Prepared by ADM Associates, Inc.; Athens Research; Hiner & Partners; and Innovologie LLC. Prepar ed for Southern California Edison. April, 2008.

7-A-6Athens Research, 1998. Refrigerator/Freezer UEC Estimation, 1996 ARCA/SCE Turn-In Program . In Support of Xenergy Inc’s Evalua tion of the 1996 Appliance Recycling Program.

Dohrmann, Donald R. et al. Net Savings Estimation in Applian ce Recycling Programs: A Review and Empirical Analysis with Recent California Data ADM Associates, Inc., Athens Research, Innovologie LLC for Southern California Edison.

Dutt, Guatam, et al., 1994. “Large Scale Resi dential Refrigerator Field Metering”, in 1994 ACEEE Summer Study in Energy Efficiency in Buildings , pp. 2.77.

ICF Consulting, 2003. Evaluation of the Energy and Enviro nmental Effects of the California Appliance Early Retirement and Recycling Program: Final Report. Prepared for: California Public Utilities Commission and Appliance Recycling Centers of America. May 12, 2003.

KEMA. 2004. 2003 EM&V RARP Study:Degradation and Market Potential Analysis . Prepared for Southern California Edison, Rosemead, CA. Prepared by KEMA Inc., Madison, WI. December 23, 2004. CALMAC STUDY ID SC E0205 ma:project:scee0015 rarp 03 evaluation:report:title.

KEMA, 2004. Final Report: Measurement and Evaluation Study of the 2002 Statewide Residential Appliance Recycling Program. February, 2004. Prepared for: Southern California Edison. February 13, 2004.

Kinney, Larry and Rana Belshe. 2001. Refrigerator Replacement in the Weatherization Program: Putting a Chill on Energy Waste: A special report for the Weatherization Assistance Program . E Source. September, 2001.

Market Transformation Programme. 2007. BNC11: Domestic Refriger ator Test Standard Vs Real-Use Energy Consumption . April 30, 2007. http://www.mtprog.com/SelectProductSt rategy.aspx?intSelec tion=1&intSector=1

Meier, Alan, 1995. “Refrigerator energy use in the laboratory and in the field,” Energy and Buildings , 22, pp. 233-243.

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.

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

7-A-7Meier. A., A. Megowan, B. Litt, and B. Pon. The New York State Residential Refrigerator Electrical Energy Monitoring Project: Final Report . 1993. Lawrence Berkeley National Laboratory: Berkeley, CA. Report No. LBL-33708.

Miller, J.D. and R.G. Pratt. Estimates of Refrigerator Loads in Public Housing Based on Metered Consumption Data . 1998. Pacific Northwest Nationa l Laboratory. Report No. PNNL11991.

Peterson, J., D. Dohrmann, T. Alereza, S. Sami ullah, S. Westberg, and J.H. Redd. Gross Savings Estimation for Appliance Recyc ling 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.

Quantum Consulting. 1994. 1991 Refrigerator Rebate Program Metering Study for Southern California Edison, Final Report . P646.070.

Smit, Kevin L. 2006. 2005 Refrigerator/Freezer Recycling Program Evaluation . Snohomish County Public Utility District No. 1. March.

Topping, Richard F. and Edward A. Vineyard. 1982. Field Test of a High-Efficiency, AutomaticDefrost Refrigerator Freezer . Prepared by AD Little and ORNL for the ASHRAE SemiAnnual Meeting, Toronto Canada. June 27-July 1, 1982.

7-A-8APPENDIX 7-B. DATA FOR ESTIMATING DISTRIBUTION OF REFRIGERATOR AND FREEZER SI ZE IN THE RECS SAMPLE

TABLE OF CONTENTS

7-B.1 INTRODUCTION ................................................................................................. 7-B-1 7-B.2 RESULTS .............................................................................................................. 7-B- 1

LIST OF FIGURE

Figure 7-B.2.1 Models of Top Mount Freezer without through-the-door ice (Product Class 3)....................................................................................................... 7-B-2 Figure 7-B.2.2 Models of Bottom Mount Freezer without th rough-the-door ice (Product Class 5)........................................................................................ 7-B-3 Figure 7-B.2.3 Models of Side Mount Freezer with through-th e-door ice (Product Class 7)....................................................................................................... 7-B-4 Figure 7-B.2.4 Models of Upright Freezer with automatic defrost (Product Class 9)....... 7-B-5 Figure 7-B.2.5 Models of Chest Freezers (Product Class 10)............................................ 7-B-6 Figure 7-B.2.6 Models of Comp act Refrigerator and Refrig erator-Freezer with manual defrost (Product Class 11).......................................................................... 7-B-7 Figure 7-B.2.7 Models of Compact Ch est Freezer (Product Class 18).............................. 7-B-8

7B-iAPPENDIX 7-B. DATA FOR ESTIMATING DISTRIBUTION OF REFRIGERATOR AND FREEZER SIZE IN THE RECS SAMPLE

7-B.1 INTRODUCTION
DOE used the California Energy Commission (CEC) appliance database 1 to determine the distribution of refrigerator and freezer volumes in the market. The Energy Information Administration’s (EIA) Residential Energy Consumption Surveys (RECS) 2 provides the volumes of household refrigerators only within bins (ran ges). In order to estimate the labeled energy consumption of a household’s standard-sized app liance, DOE selected a volume from within the appropriate RECS bin. DOE then selected a more precise volume randomly from the distribution of volumes within the RECS bin, basing the prob ability of selecting each volume on the number of models in the CEC database having that volume. The figures in this appendix show the volume distributions by number of models in the CEC database (n arrower, solid bars in figures) and the distributions of refrigerator volumes reported by RECS respondents (wider, empty bars in figures). For each standard-s ized refrigeration product DOE fi rst identified the appropriate RECS bin and product class, then chose a more pr ecise volume from the relevant part of the CEC distribution.

For compact products (product classes 11 and 18), for which DOE did not use a household sample, DOE used the distribution of vol umes from the CEC database to characterize the distribution of volumes sold in the market and determine the distribution of energy use.

7-B.2 RESULTS
Figures 7-B.2.1 through 7-B.2.7 de pict the volume di stributions on the nu mber of models in the CEC database and the distribution of re frigerator and freezer volumes reported in RECS.

7-B-1Frequency 700

600

500

400

300

200

100

0 CEC directory RECS bins

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Total Volume ( cu ft )

Figure 7-B.2.1 Models of Top Mount Freezer without through-the

door ice (Product Class 3)

7-B-2Frequency 160

140

120

100

80

60

40

20

0 CEC directory RECS bins

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Total Volume ( cu ft )

Figure 7-B.2.2 Models of Bottom Mount Freezer without through

the-door ice (Product Class 5)

7-B-30 100 200 300 400 500 600 700 800 900Frequency CEC directory RECS bins

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Total Volume ( cu ft )

Figure 7-B.2.3 Models of Side Mount Freezer with through-the

door ice (Product Class 7)

7-B-4Frequency 50

45

40

35

30

25

20

15

10

5

0 CEC directory RECS bins

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Total Volume ( cu ft )

Figure 7-B.2.4 Models of Upright Freezer with automatic defrost (Product Class 9)

7-B-5Frequency 70

60

50

40

30

20

10

0 CEC directory RECS bins

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Total Volume ( cu ft )

Figure 7-B.2.5 Models of Chest Freezers (Product Class 10)

7-B-6Frequency 70

60

50

40

30

20

10

0 CEC directory

1 2 3 4 5 6 7 8 9 10 Total Volume ( cu ft )

Figure 7-B.2.6 Models of Compact Refrigerator and RefrigeratorFreezer with manual defrost (Product Class 11)

7-B-7Frequency 30

25

20

15

10

5

0 CEC directory

1 2 3 4 5 6 7 8 9 10 Total Volume ( cu ft )

Figure 7-B.2.7 Models of Compact Chest Freezer (Product Class 18)

7-B-8REFERENCES

1 California Energy Commission. App liances Database—Refrigeration.

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

2 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 >

7-B-9CHAPTER 8. LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS

TABLE OF CONTENTS

8.1 INTRODUCTION ........................................................................................................... 8-1 8.1.1 Approach................................................................................................................. ......... 8-1 8.1.2 Summary of Inputs........................................................................................................ ... 8-2 8.2 INPUTS TO LIFE-CYCLE COST ANALYSIS ............................................................. 8-7 8.2.1 Inputs to Product Cost................................................................................................... ... 8-8 8.2.1.1 Baseline Retail Prices .................................................................................... 8-8 8.2.1.2 Increases in Manufactur er Selling Price ........................................................ 8-9 8.2.1.3 Markup and Sales Tax ................................................................................. 8-11 8.2.1.4 Installation Cost ........................................................................................... 8-11 8.2.1.5 Consumer Product Cost ............................................................................... 8-11 8.2.2 Inputs to Operating Cost ................................................................................................ 8 -13 8.2.2.1 Annual Energy Consumption....................................................................... 8-14 8.2.2.2 Energy Prices ............................................................................................... 8-15 8.2.2.3 Energy Price Trends.....................................................................................8-16 8.2.2.4 Repair and Maintenance Costs..................................................................... 8-17 8.2.3 Product Lifetimes........................................................................................................ ... 8-17 8.2.3.1 Estimated Survival Function........................................................................ 8-18 8.2.3.2 Conversion of First to Second Refrigerators ............................................... 8-23 8.2.3.3 Standard-Size Freezers................................................................................. 8-25 8.2.3.4 Compact Refrigeration Products.................................................................. 8-27 8.2.4 Discount Rates ........................................................................................................... .... 8-28 8.2.4.1 Discount Rates for Residential Consumers.................................................. 8-28 8.2.4.2 Assignment of Discount Rates to Sample Households................................ 8-31 8.2.4.3 Discount Rates for Commercial Purchasers ................................................ 8-31 8.2.5 Effective Date of Standard............................................................................................. 8-34 8.2.6 Base-Case Energy Efficiencies...................................................................................... 8-35 8.3 INPUTS TO PAYBACK PERIOD ANALYSIS........................................................... 8-37 8.4 RESULTS OF ANALYSES .......................................................................................... 8-38 8.4.1 Standard-Size Refrigerator-Freezers.............................................................................. 8-39 8.4.1.1 Summary of Results..................................................................................... 8-39 8.4.1.2 Distributions of Impacts............................................................................... 8-40 8.4.2 Standard-Size Freezers................................................................................................... 8-45 8.4.2.1 Summary of Results..................................................................................... 8-45 8.4.2.2 Distributions of Impacts............................................................................... 8-46 8.4.3 Compact Refrigeration Products.................................................................................... 8-50 8.4.3.1 Summary of Results..................................................................................... 8-51 8.4.3.2 Distributions of Impacts............................................................................... 8-52 8.5 REBUTTABLE PAYBACK PERIOD.......................................................................... 8-56 8.5.1 Metric................................................................................................................... .......... 8-56 8.5.2 Inputs to Rebuttable Payb ack Period Analysis .............................................................. 8-56

8-i8.5.3 Results of Analysis ...................................................................................................... .. 8-56

LIST OF TABLES

Table 8.1.1 Standard-Size Refrigerator-Freezers : Summary of Inputs to Calculations.......... 8-5 Table 8.1.2 Standard-Size Fr eezers: Summary of Input s to Calculations .............................. 8-6 Table 8.1.3 Compact Refrigeration Products: Summary of Inputs to Calculations................ 8-7 Table 8.2.1 Residential Refrigeration Produc ts: Average Baseline Retail Price.................... 8-9 Table 8.2.2 Standard-Size Refrigerator-Fr eezers: Increases in Manufacturer Selling Prices.................................................................................................................. 8-10 Table 8.2.3 Standard-Size Freezers: Increa ses in Manufacturer Selling Prices.................... 8-10 Table 8.2.4 Compact Refrigeration Products: Incr eases in Manufacturer Selling Prices..... 8-11 Table 8.2.5 Standard-Size Refrigerator-F reezers: Average Consumer Cost ........................ 8-12 Table 8.2.6 Standard-Size Freezers: Average Consumer Cost ............................................. 8-12 Table 8.2.7 Compact Refrigeration Pr oducts: Average Consumer Cost .............................. 8-13 Table 8.2.8 Standard-Size Refrigerato r-Freezers: Average Annual Energy Use by Efficiency Level................................................................................................. 8-14 Table 8.2.9 Standard-Size Freezers: Average Annual Energy Use by Efficiency Level...... 8-15 Table 8.2.10 Compact Refrigeration Pr oducts: Average Annual Energy Use by Efficiency Level................................................................................................. 8-15 Table 8.2.11 Average Electricity Prices in 2007 .................................................................... 8-16 Table 8.2.12 Standard-Size Refrigerato r-Freezers: Comparison of Survey and Shipments Data with Modeled Stock................................................................. 8-21 Table 8.2.13 Standard-Size Freezers: Compar ison of Survey and Shipments Stock to Modeled Stock ................................................................................................... 8-26 Table 8.2.14 Types of Household Debt and Equity by Percentage Shares............................. 8-29 Table 8.2.15 Average Nominal Interest Rates for Household Debt ....................................... 8-29 Table 8.2.16 Average Real Effective Inte rest Rates for Household Debt .............................. 8-30 Table 8.2.17 Average Nominal and Real Inte rest Rates for Household Equity ..................... 8-30 Table 8.2.18 Average Interest on Ho usehold Debt and Equity .............................................. 8-31 Table 8.2.19 Data for Calculating Weighted-A verage Cost of Capital for Commercial Sectors................................................................................................................ 8-33 Table 8.2.20 Weighted-Average Cost of Capital for Commercial Sectors............................. 8-34 Table 8.2.21 Discount Rates for Commercial Sectors............................................................ 8-34 Table 8.2.22 Standard-Size Refrigerator-Freezers : Base-Case Efficiency Distributions ....... 8-36 Table 8.2.23 Standard-Size Freezers: Base -Case Efficiency Distributions............................ 8-36 Table 8.2.24 Compact Refrigeration Products: Base-Case Efficiency Distributions ............. 8-37 Table 8.4.1 Product Class 3, Top-Mount Refriger ator-Freezers: Analy tical Results........... 8-39 Table 8.4.2 Product Class 5, Bottom-Mount Refrigerator-Freezers: Analytical Results ..... 8-40 Table 8.4.3 Product Class 7, Side-by-Side Refrigerator-Freezers with Through-theDoor Ice Service: Analytical Results................................................................. 8-40 Table 8.4.4 Product Class 9, Upright Fr eezers: Analytical Results...................................... 8-46 Table 8.4.5 Product Class 10, Chest Fr eezer: Analytical Results......................................... 8-46 Table 8.4.6 Product Class 11, Compact Refrig erators: Analytical Results .......................... 8-51

8-iiTable 8.4.7 Product Class 18, Compact Fr eezers: Analytical Results.................................. 8-51 Table 8.5.1 Standard-Size Refrigerator-F reezers: Rebuttable Payback Periods................... 8-57 Table 8.5.2 Standard-Size Freezers: Rebuttable Payback Periods........................................ 8-57 Table 8.5.3 Compact Refrigerators and Fr eezers: Rebuttable Payback Periods................... 8-58

LIST OF FIGURES

Figure 8.1.1 Flow Diagram of Inputs for Life-C ycle Cost and Payback Period Analyses ...... 8-4 Figure 8.2.1 Residential and Commercial Electricity Pr ice Trends (2007 = 1) ..................... 8-17 Figure 8.2.2 Comparison of Modeled Refriger ator Age Distribution with Data from Residential Energy Consumption Surveys......................................................... 8-22 Figure 8.2.3 Survival Function for Standa rd-Size Refrigerator-Freezers .............................. 8-22 Figure 8.2.4 Function for Conversion of Firs t to Second Refrigerator-Freezers ................... 8-25 Figure 8.2.5 Survival Function for Standard-Size Freezers ................................................... 8-27 Figure 8.4.1 Product Class 3, Top-Mount Refrig erator-Freezers: Dist ribution of LifeCycle Cost Impacts for Efficiency Level 5........................................................ 8-41 Figure 8.4.2 Product Class 3, Top-Mount Re frigerator-Freezers : Distribution of Payback Periods for Efficiency Level 5............................................................. 8-41 Figure 8.4.3 Product Class 3, Top-Mount Refrig erator-Freezers: Range of Life-Cycle Cost Savings by Efficiency Level...................................................................... 8-42 Figure 8.4.4 Product Class 5, Bottom-Mount Re frigerator-Freezers: Range of LifeCycle Cost Savings by E fficiency Level ........................................................... 8-43 Figure 8.4.5 Product Class 7, Side-by-Side Refrigerator-Freezers: Ra nge of Life-Cycle Cost Savings by Efficiency Level...................................................................... 8-43 Figure 8.4.6 Product Class 3, Top-Mount Refr igerator-Freezers: Range of Payback Periods by Efficiency Level............................................................................... 8-44 Figure 8.4.7 Product Class 5, Bottom-Mount Re frigerator-Freezers: Range of Payback Periods by Efficiency Level............................................................................... 8-44 Figure 8.4.8 Product Class 7, Side-by-Side Re frigerator-Freezers: Range of Payback Periods by Efficiency Level............................................................................... 8-45 Figure 8.4.9 Product Class 9, Upright Freezer s: Distribution of Life-Cycle Cost Impacts for Efficiency Level 5 .......................................................................... 8-47 Figure 8.4.10 Product Class 9, Upright Freezers: Distribution of Payback Periods for Efficiency Level 5.............................................................................................. 8-47 Figure 8.4.11 Product Class 9, Upright Freezers: Range of Life-Cycle Cost Savings by Efficiency Level................................................................................................. 8-48 Figure 8.4.12 Product Class 10, Chest Freezers: Range of Life-Cycle Cost Savings by Efficiency Level................................................................................................. 8-49 Figure 8.4.13 Product Class 9, Upright Freez ers: Range of Payback Periods by Efficiency Level................................................................................................. 8-50 Figure 8.4.14 Product Class 10, Chest Freezers: Ra nge of Payback Periods by Efficiency Level .................................................................................................................. 8-50 Figure 8.4.15 Product Class 11, Compact Refrigerat ors: Distribution of Life-Cycle Cost Impacts for Efficiency Level 5 .......................................................................... 8-52

8-iiiFigure 8.4.16 Product Class 11, Compact Refrigerators: Distribution of Payback Period for Efficiency Level 5 ........................................................................................ 8-53 Figure 8.4.17 Product Class 11, Compact Refrig erators: Range of Life-Cycle Cost Savings by Efficiency Level .............................................................................. 8-54 Figure 8.4.18 Product Class 18, Compact Freezers: Range of Life-Cycle Cost Savings by Efficiency Level............................................................................................ 8-54 Figure 8.4.19 Product Class 11, Compact Refrig erators: Range of Payback Periods by Efficiency Level................................................................................................. 8-55 Figure 8.4.20 Product Class 18, Compact Fre ezers: Range of Payback Periods by Efficiency Level................................................................................................. 8-55

8-ivCHAPTER 8. LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS

8.1 INTRODUCTION
This chapter describes the Department of Energy (DOE)’s method and metrics for analyzing the economic impact s on individual consumers of potential energy efficiency standards for refrigeration produc ts. The effects of standards on individual consumers include a change (usually a decrease) in ope rating cost and a change (usually an increase) in product cost. DOE analyzed the economic impacts related to potential new energy efficiency standards for standard-size refrigerator-freez ers (top-mount, bottom-mount, and side-by-side); standard-size freezers (upright and chest); and compact refrigeration products (r efrigerators and freezers), a total of 7 product classes. DOE examined the life-cycle cost, payback period, and rebuttable payback period of all potential efficiency standard s on all product classes. The terms used in this analysis are defined below.

• Life-cycle cost (LCC) is the total cost consumers in cur during the life of an appliance, including purchase and operating cost s (including energy expenditures). DOE discounts future operating costs to the tim e of purchase, and sums them over the lifetime of a product.

• Payback period (PBP) measures the amount of time it takes consumers to recover the assumed higher purchase cost of more energy efficient products through lower operating costs.

• Rebuttable payback period
, a special case of the payback period, is based on laboratory conditions (specifi cally, those that reflect th e DOE test procedure) for energy use. Its other inputs (including elec tricity prices) reflect representative realworld operating conditions.

Inputs to the LCC and the PBP are discussed in sections 8.2 and 8.3, respectively, of this chapter. Results of the LCC and PBP analyses ar e presented in section 8.4. The rebuttable PBP is discussed in section 8.5. Key vari ables and calculations are pres ented for each of the three metrics listed above. DOE performed the calculations discussed here using a series of Microsoft Excel spreadsheets that are accessible on the Internet ( www.eere.energy.gov/buildings/appliance_standards/ ). Details regarding and instructions for using the spreadsheets are di scussed in appendix 8-A.

8.1.1 Approach
Recognizing that several inputs to the anal ysis of consumer LCC and PBP are either variable or uncertain, DOE used Monte Carlo s imulation and probability distributions to model both the uncertainty and variabil ity of inputs. Appendix 8-B provi des a detailed explanation of Monte Carlo simulation and the use of probabil ity distributions. DOE developed LCC and PBP spreadsheet models that incorporate both Monte Carlo simulation and probability distributions

8-1by using Microsoft Excel ® spreadsheets combined with Crystal Ball ® , a commercially available add-in program.

In addition to using probability distributions to characterize severa l of the inputs to the calculation, DOE developed samples of indi vidual households that use standard-size refrigeration products. DOE performed the LCC and PBP calculations for each household in the sample to account for the variability in energy consumption and/or energy pr ice associated with a range of households.

As described in chapter 7, DOE used the DOE Energy Information Administration (EIA)’s 2005 Residential Energy Consumption Survey (RECS) to develop household samples for standard-size re frigeration products. 1 EIA constructed the 2005 RECS to represen t the range of households throughout the United States.

DOE used the 2005 RECS to establish the variability in the annual energy use of refrigeration products and in energy prices. DOE was able to assign a unique annual energy use and/or energy price to each household in the samp le. Because of the large sample of households considered in the LCC and PBP analyses, annual energy use and/or energy prices vary greatly. Thus, although the annual energy use and/or energy prices are known for any particular household, their variability across all households contributes to the rang e of LCCs and PBPs calculated for any particular possible standard.

DOE did not develop a household sample fo r compact refrigeration products, because many such products are used in lodging, dormitori es, and other commercial establishments. DOE estimated the fractions of shipments of compact re frigeration products used in the residential and commercial sectors, then used appr opriate inputs for those fractions.

DOE displays LCC and PBP results as dist ributions of impacts compared to baseline conditions. Results, presented in section 8.4, we re derived from 10,000 samples for each Monte Carlo simulation run. To illustrate the implicati ons of the analysis, DOE generated a frequency chart that depicts the variation in LCC and PBP for each standard level considered for refrigeration products.

8.1.2 Summary of Inputs
The LCC represents the total consumer cost during the life of a product, including purchase and operating costs (inc luding energy expenditures). DOE discounts future operating cost to the time of purchase, then sums them over the lifetime of each product. The PBP is the change in purchase cost due to an increased efficiency standard divided by the change in annual operating cost that results from the standard. The PBP represents the number of years it will take the customer to recover the increased purchas e cost through decreased operating cost.

DOE uses two types of inputs to the calculation of LCC and PBP: (1) inputs for establishing the purchase cost, otherwise known as the consumer product cost, and (2) inputs for determining the operating cost.

8-2The following are the primary inputs for establishing the consumer product cost.

• Baseline selling price : The price at which a manufactur er sells a product identified as a baseline-efficient model.

• Increases in manufacture r selling price (MSP) : The change in manufacturer selling price associated with producing a product that meets a particular efficiency level.

• Markups and sales tax : The costs associated with c onverting increases in the MSP into consumer product cost.

The following are the primary inputs for calculating the operating cost.

• Product energy consumption : The site energy use associ ated with operating a given product.

• Product efficiency : The energy consumption associat ed with a product that has an efficiency greater than that of the baseline product.

• Energy prices : The prices consumers paid for ener gy (electricity) in a recent year.

• Energy price trends . Energy prices forecasted into the future. DOE based these trends on the EIA’s Annual Energy Outlook (AEO) 2009. 2

• Repair and maintenance costs : Repair costs are associated with repairing or replacing components that fail. Maintenance costs are associated with main taining the operation of a product.

• Lifetime : The age at which a product is retired from service.

• Discount rate : The rate at which DOE discounted future expenditures to establish their present value.

Figure 8.1.1 graphically depicts the relationships among the i nputs for installed cost and operating cost used to calculate the LCC a nd PBP. The yellow boxes in Figure 8.1.1 indicate inputs; the green boxes indicate intermediate outputs; and the blue boxes indicate the final outputs of LCC and PBP.

8-3Baseline Manufacturer Selling Price

Std-Level Manufacturer Selling Price Retailer Markup

Sales Tax

Installation Cost Total Installed Cost

Energy Consumption Equipment Price

Lifetime Operating

Cost Annual Energy Cost

Product Lifetime Repair and Maintenance Cost

Discount Rate

Energy Price Trends Annual Operating

Cost Payback Period Life-Cycle Cost

Energy Prices

Figure 8.1.1 Flow Diagram of Inputs for Life-C ycle Cost and Payback Period Analyses

Tables 8.1.1 through 8.1.3 summarize the input values that DOE used to calculate the LCC and PBP for refrigeration products. The inpu ts for calculating total installed and operating costs included the product lifetim e, discount rate, and energy pri ce trends. DOE used single-point values to characterize all inputs to total cost, but used probability distributions to capture the uncertainty and/or variability of several inputs to operating cost . For those inputs characterized using probability distributions, the values in the following tables are average or typical values.

8-4Table 8.1.1 Standard-Size Refrigerator-Freezers: Summary of Inputs to Calculations Input Product Class Average or Typical Value Characterization

Baseline retail price Top-mount refrigeratorfreezer
Bottom-mount refrigerator-freezerSide-by-side refrigeratorfreezer with TTD* 550 2008$

1,615 2008$

1,332 2008$ Custom distribution

Custom distribution

Custom distribution

Increase in manufacturer selling price † All Varies by efficiency level Single-point value

Retailer markup All Baseline = 1.45 Incremental = 1.15 Single-point value

Sales tax All 7.1% Single-point value

Annual energy

use Top-mount refrigeratorfreezer
Bottom-mount refrigerator-freezerSide-by-side refrigeratorfreezer with TTD Baseline use = 657 kWh ‡

Baseline use = 699 kWh

Baseline use = 1,087 kWh Varies depending on usage

Varies depending on usage

Varies depending on usage
Energy prices All 11.4 cents per kWh Varies depending on region
Energy price trend All AEO 2009 reference case 2 Two additional scenarios: AEO high and low growth**

Lifetime All 16.2 years (median) Weibull distribution

Discount rate All 4.8% Custom distribution
* Through-the-door ice service. † Includes manufacturer markup. ‡ Kilowatt hours ** See section 8.2.2.3.

8-5Table 8.1.2 Standard-Size Freezers: Summary of Inputs to Calculations Input Product Class Average or Typical Value Characterization
Baseline retail price Upright
Chest 469 2008$
304 2008$ Custom distribution
Custom distribution
Increase in manufacturer selling price* All Varies by efficiency level Single-point value

Retailer markup All Baseline = 1.45 Incremental = 1.15 Single-point value

Sales tax All 6.59% Single-point value
Annual energy use Upright
Chest Baseline use = 980 kWh †
Baseline use = 623 kWh Varies depending on usage Varies depending on usage Energy prices All 11.4 cents per kWh Varies depending on region
Energy price trend All AEO 2009 reference case 2 Two additional scenarios: AEO high and low growth §

Lifetime All 21.7 years (median) Weibull distribution

Discount rate All 4.8% Custom distribution
* Includes manufacturer markup. † Kilowatt hours. § See section 8.2.2.3.

8-6Table 8.1.3 Compact Refrigeration Products: Summa ry of Inputs to Calculations Input Product Class Average or Typical Value Characterization
Baseline retail price Refrigerator
Freezer 153 2008$
193 2008$ Custom distribution
Custom distribution

Increase in manufacturer selling price* All Varies by efficiency level Single-point value

Retailer markup All Baseline = 1.45 Incremental = 1.15 Single-point value

Sales tax All 6.9% Single-point value
Annual energy use Refrigerator
Freezer Baseline use = 325 kWh †
Baseline use = 313 kWh Varies depending on usage Varies depending on usage Energy prices All 10.8 cents per kWh Varies depending on region
Energy price trend All AEO 2009 reference case 2 Two additional scenarios: AEO high- and low-growth §

Lifetime Refrigerator 5.6 years (mean) Weibull distribution

Freezer 7.5 years (mean) Weibull distribution

Energy prices All 4.8% (residential users) 6.2% (commercial users) Custom distribution

* Includes manufacturer markup † Killowatt hours. § See section 8.2.2.3.

8.2 INPUTS TO LIFE-CYCLE COST ANALYSIS
Life-cycle cost (LCC) is the total consumer co st during the life of an appliance, including purchase and operating costs (inc luding energy costs). DOE discounted future operating costs to the time of purchase, then summed them ove r the lifetime of the product. DOE used the following equation to define LCC.

LCC = PC + 

## ∑ N OC t

t 

## ( 1 + r 

## )
Where: t = 1

LCC = life-cycle cost in dollars; PC = consumer product cost in dollars; ∑ = sum over the lifetime, from year 1 to year N ; N

= lifetime of appliance in years; OC = operating cost in dollars;

8-7r = discount rate; and
t = year for which operating cost is being determined.
DOE expresses dollar values in 2008$ because it ga thered most of its data for the LCC and PBP analysis in 2008.

8.2.1 Inputs to Product Cost
DOE calculated the cost consumers pay for baseline products based on the following equation.

PC = ( RSP ) × ( TAX ) BASE BASE

Where:

PC BASE = consumer cost for baseline product, RSP BASE = retail selling price for baseline product, and TAX= sales tax.

DOE calculated the consumer cost for products having higher efficiency levels based on the following equation.

PC STD = PC BASE + ( Δ MSP STD × MU × TAX ) RETINCR

Where:

PC STD = consumer product cost for higher-efficiency products, PC BASE = consumer cost for baseline product Δ MSP STD = change in MSP for more efficient model, MU RET_INCR = incremental retailer markup, TAX= sales tax.

8.2.1.1 Baseline Retail Prices
DOE’s engineering analysis (see chapter 5) did not attempt to estimate the manufacturing sales price (MSP) for baseline models. Instead, it developed incremental increases in MSP associated with increases in efficiency level. This approach required DOE to estimate retail prices for the baseline mode l in each product class.

DOE drew upon proprietary retail pr ice data collected by The NPD Group. 3 These data reflect prices and sales at many retail outlets in the United States, representing more than 50 percent of retail sales nationw ide. The data include model number, refrigerated volume, configuration of doors and ice-making, and wh ether the unit is an ENERGY STAR product. Based on these data DOE developed a sales-we ighted price distribut ion for non-ENERGY STAR

8-8appliances in each product class. a For the LCC and PBP analyses of standard-sized products, DOE assigned a baseline price from that distri bution to each household sampled from the EIA’s 2005 Residential Energy Cons umption Survey (RECS). 1 For compact product classes, DOE assigned a baseline price from the distribution to each sampled product. Appendix 8-C presents the distribution histograms DOE developed for each product class. The average baseline retail prices before sales tax for each refrigerat ion product class are shown in Table 8.2.1.

Table 8.2.1 Residential Refrigeration Products: Average Baseline Retail Price Product Class Baseline Retail Price 2008$ Product class 3: Top-mount refrigerator-freezer 550 Product class 5: Bottom-mount refrigerator-freezer 1,615 Product class 7: Side-by-side refri gerator-freezer with TTD* 1,332 Product class 9: Upright freezer 469
Product class 10: Chest freezer 304 Product class 11: Compact refrigerator 153 Product class 18: Compact freezer 193
* Through-the-door ice service.

8.2.1.2 Increases in Manufacturer Selling Price

DOE used a combination of cost data s ubmitted by the Association of Home Appliance Manufacturers (AHAM) 4 and a reverse engineering anal ysis to estimate increases to manufacturing cost associated with increases in efficiency levels for re frigeration products. Refer to Chapter 5, Engineering Analysis, for deta ils. Adding the manufacturer markup described in chapter 6 yielded the MSP increases for each co nsidered efficiency level and product class shown in Tables 8.2.2 through 8.2.4.

a DOE assumed that prices for non-ENERGY STAR mode ls are a reasonable approximation of prices for the

baseline models.

8-9Table 8.2.2 Standard-Size Refrigerator-Freezers: In creases in Manufacturer Selling Prices

Efficiency Level

% less than baseline energy use Increase in MSP 2008$

Product Class 3: Top-Mount Refrigerator-Freezer Product Class 5: Bottom-Mount Refrigerator-Freezer Product Class 7: Side-by-Side Refrigerator-Freezer with TTD Ice Service
10 3.50 1.80 11.18
15 7.68 5.79 18.96
20 16.39 13.72 54.26
25 34.92 31.38 106.00
30 62.06 45.06 167.29
35 103.91 110.05 228.96
40 156.20 183.33 310.77
45 208.14 251.25
* Through-the-door.

Table 8.2.3 Standard-Size Freezers: Increases in Manufacturer Selling Prices Efficiency Level Increase in MSP 2008$

% less than baseline energy

use Product Class 9: Upright Freezer Product Class 10: Chest Freezer
10 6.41 2.35
15 11.45 6.05
20 13.57 24.08
25 27.51 29.26
30 46.58 34.84
35 76.82 74.35
40 124.06 77.12
45 196.78 136.90

8-10Table 8.2.4 Compact Refrigeration Products: Increase s in Manufacturer Selling Prices Efficiency Level

% less than baseline
energy use Increase in MSP 2008$
Product Class 11: Compact Refrigerator or

Refrigerator-Freezer Product Class 18: Compact Chest Freezer
10 3.36 6.05
15 6.32 9.65
20 8.85 34.03
25 20.56 42.62
30 21.63 60.19
35 26.77 63.00
40 39.24 75.22
45 57.49 89.70

8.2.1.3 Markup and Sales Tax

To derive the incremental increase in cons umer product cost for each efficiency level, DOE applied an incremental retail markup and sales tax to the MSP increases shown above. Refer to Chapter 6, Markups for Equipment Price Determination, for details. DOE also applied sales tax to the baseline retail prices.

8.2.1.4 Installation Cost

Because the cost to install re frigeration products does not change as efficiency increases, DOE did not incorporate insta llation costs in its analysis.

8.2.1.5 Consumer Product Cost
Tables 8.2.5 through 8.2.7 present the shipment -weighted consumer pr oduct cost at each considered efficiency standard level for the refr igeration product classes under consideration for new standards. These costs reflect the market e fficiency distributions discussed in section 8.2.6.

8-11Table 8.2.5 Standard-Size Refrigerator-Fre ezers: Average Consumer Cost Efficiency Level % less than baseline
energy use Product Class 3: Top-Mount 2008$ Product Class 5: Bottom-Mount 2008$ Product Class 7: Side-by-Side 2008$ Baseline 591 1,758 1,459
10 595 1,759 1,463
15 599 1,759 1,469
20 609 1,760 1,499
25 631 1,782 1,563
30 665 1,799 1,638
35 716 1,879 1,714
40 781 1,969 1,815
45 845 2,053

Table 8.2.6 Standard-Size Freezers: Average Consumer Cost

Efficiency Level % less than baseline energy use Product Class 9: Upright

2008$ Product Class 10: Chest 2008$
Baseline 505 325
10 511 328
15 517 332
20 520 355
25 537 361
30 561 368
35 598 416
40 656 420
45 745 493

8-12Table 8.2.7 Compact Refrigeration Products: Average Consumer Cost

Efficiency Level % less than baseline energy use Product Class 11: Compact Refrigerator 2008$ Product Class 18: Compact Freezer 2008$
Baseline 166 207
10 170 214
15 173 218
20 176 248
25 191 259
30 192 281
35 198 284
40 214 299
45 236 317

8.2.2 Inputs to Operating Cost
DOE defines operating cost ( OC ) by the following equation.

OC = EC + RC + MC Where:

EC = energy cost associated w ith operating the product, RC = repair cost associated with component failure, and MC = cost for maintain ing appliance operation.

DOE used the following equation to calcula te the annual operating cost for baseline products.

OC = ( AEC × PRICE ) + RC + MC BASE BASE ENERGY BASE BASE

Where:

OC BASE = operating cost for baseline product, AEC BASE = annual energy consumption for baseline product, PRICE ENERGY = energy price, RC BASE = repair costs associated with compone nt failure for baseline product, and MC BASE = maintenance costs for baseline product.

DOE used the following equation to calcu late the annual operating cost for higher efficiency products.

8-13OC = ( AEC × PRICE ) + RC + MC STD STD ENERGY STD STD

Where:

OC STD = operating cost of higher efficiency product, AEC STD = annual energy consumption of higher efficiency product, PRICE ENERGY = energy price in each year, RC STD = repair costs associated with compone nt failure for higher efficiency product, and MC STD = maintenance costs for higher efficiency product.

8.2.2.1 Annual Energy Consumption
As described in Chapter 7, Energy Use Determination, DOE developed samples of individual households that use each of the standard-sized re frigeration products considered herein. By developing the samples, DOE was able to calculate the LCC and PBP for each household to account for the variability in both en ergy use and energy price associated with that household.

Tables 8.2.8 through 8.2.10 are derived from the analysis described in chapter 7. The values shown for annual energy consumption are averages in the field. For compact products, DOE did not use the RECS sample, and the ener gy consumption is as measured using the DOE test procedure. DOE captured the variability in energy consumption by using a range of values in its LCC and PBP analyses.

Table 8.2.8 Standard-Size Refrigerator-Freezer s: Average Annual Energy Use by Efficiency Level Product Class 3:Top-Mount RefrigeratorFreezer Product Class 5:Bottom-Mount RefrigeratorFreezer Product Class 7:Side-by-Side RefrigeratorFreezer with TTD † Efficiency Level % less than baseline
energy use Energy Use kWh* Efficiency Level % less than baseline
energy use Energy Use kWh Efficiency Level % less than baseline
energy use Energy Use kWh Baseline 657 Baseline 699 Baseline 1,087 10 591 10 629 10 979 15 558 15 594 15 924 20 526 20 559 20 870 25 493 25 524 25 815 30 460 30 489 30 761 35 427 35 454 35 707 40 394 40 419 40 652 45 361 45 384

- - * Kilowatt hours. † Through-the-door ice service.

8-14Table 8.2.9 Standard-Size Freezers: Average Annual Energy Use by Efficiency Level Product Class 9: Upright Freezer Product Class 10: Chest Freezer Efficiency Level % less than baseline
energy use Energy Use kWh* Efficiency Level % less than baseline
energy use Energy Use kWh Baseline 980 Baseline 623 10 882 10 561 15 833 15 530 20 784 20 498 25 735 25 467 30 686 30 436 35 637 35 405 40 588 40 374 45 539 45 343 * Kilowatt hours.

Table 8.2.10 Compact Refrigeration Products: Average Annual Energy Use by Efficiency Level

Product Class 11: Compact Refrigerator Product Class 18: Compact Freezer Efficiency Level % less than baseline
energy use Energy Use kWh* Efficiency Level % less than baseline
energy use Energy Use kWh Baseline 325 Baseline 313 10 292 10 282 15 276 15 266 20 260 20 250 25 244 25 235 30 227 30 219 35 211 35 203 40 195 40 188 45 179 45 172 * Kilowatt hours.

8.2.2.2 Energy Prices
Using data from EIA Form 861 5 , DOE derived average energy prices for 13 geographic areas in the United States: the nine U.S. Census divisions, plus four la rge states (New York, Florida, Texas, and California) considered individually. For Cens us divisions containing one of those large states, DOE left out data for the larg e state when calculating average regional values.

8-15For example, the Pacific region average excludes California, and the West South Central region excludes Texas. Using the modified regional data , DOE assigned an appropriate energy price to each household in the sample.

DOE used data from EIA to estimate electric ity prices for residential consumers in each of the 13 geographic areas These data, which ar e published annually, include annual electricity sales in kilowatt hours (kWh), revenues from electricity sales, and number of consumers by sector for every utility that serv es final consumers. The calculation of an area-average residential or commercial electricity price proceeds in two steps.

1. For each utility, an average sector (residen tial or commercial) price is estimated by dividing sector revenue s by sector sales. 2. An average regional price is calculated, whereby each ut ility having customers in a region is weighted by the number of reside ntial consumers served in that region.

The calculation used the most recent EIA data av ailable at the time the analysis was conducted. Table 8.2.11 shows the average residential and commercial electricity price in 2007 for each Census division and large state.

Table 8.2.11 Average Electricity Prices in 2007

Geographic Area Average Residential Price 2008$/kWh Average Commercial Price 2008$/kWh New England 0.162 0.153
Middle Atlantic 0.127 0.111
East North Central 0.102 0.091
West North Central 0.088 0.075
South Atlantic 0.099 0.085
East South Central 0.087 0.086
West South Central 0.093 0.085
Mountain 0.097 0.084
Pacific 0.099 0.094
New York State 0.178 0.169
California 0.150 0.136
Texas 0.128 0.119
Florida 0.117 0.102 Source: U.S. Department of Energy–Energy Information Administration EIA Form 861.

8.2.2.3 Energy Price Trends
To estimate energy prices in future years, DOE multiplied the average prices listed in Table 8.2.11 by the forecast of annual aver age price changes in the EIA’s AEO 2009. 2 To estimate the trend after 2030, DOE followed guidelines that the EIA had provided to the Federal

8-16Energy Management Program, which called for using the average rate of ch ange for electricity during 2020–2030.

The Department calculated LCC and PBP for each class of refrigeration products using three separate projections from AEO 2009: reference, low, and high economic growth. Alternative assumptions regarding the future growth in energy markets reflects the uncertainty regarding economic conditions during the forecast period. Figure 8.2.1 shows the projected trends in residential and comme rcial electricity prices based on the AEO 2009 reference case. For the LCC results presented in this chapter, DOE used only the energy price forecasts from the AEO reference case.



### Electricity Price Trends
1.2

1.1

1.0

0.9

0.8 AEO 2009 Reference Res Elec

AEO 2009 Reference Com Elec



### 2000 2005 2010 2015 2020 2025 2030

Source: Energy Information Administration, Annual Energy Outlook. 2009

. Figure 8.2.1 Residential and Commercial Electricity Price Trends (2007 = 1)

8.2.2.4 Repair and Maintenance Costs
Because DOE found no evidence that repair or maintenance costs change as the efficiency of refrigeration pr oducts increases, it excluded th ose costs from its analysis.

8.2.3 Product Lifetimes

8-178.2.3.1 Estimated Survival Function
The Energy Information Agency (EIA)’s Residential Energy Consumption Survey (RECS) 1 of occupied primary housing units records the presence of various appliances in each household, and places the age of each appliance into bins comprising several years. Data from the U.S. Census’s American Housing Survey (AHS), 6 which surveys all housing including vacant and second homes, enabled DOE to adjust the RECS data to reflect some appliance use outside of primary residences. By combining the resu lts of both surveys with the known history of appliance shipments (collected from Appliance magazine or directly from manufacturer trade associations), DOE estimated the percentage of a ppliances of a given age still in operation. This survival function, which DOE assumed has the form of a cumulative Weibull distribution, provides an average and a median appliance lifetime.

The Weibull distribution is a probability distribution comm only used to measure failure
rates. b Its form is similar to an exponential distri bution, which models a fixed failure rate, except that a Weibull distribution allows for a failure rate that changes ove r time in a particular fashion. The cumulative Weibull distribution takes the form:

⎛ x

− θ ⎞ β

− ⎜ ⎟ 

### P ( x ) = 

# e ⎝ α ⎠ for x > θ and P(x) = 1 for x ≤ θ Where:

P(x) = probability that the applia nce is still in use at age x ;

x

= appliance age;

α = scale parameter, which would be the d ecay length in an exponential distribution; β

= shape parameter, which determines the wa y in which the failure rate changes through time; and θ

= delay parameter, which allows fo r a delay before any failures occur.

When β = 1, the failure rate is constant over tim e, giving the distribution the form of a cumulative exponential distribution. In the case of appliances, β commonly is greater than 1, reflecting an increasing failure rate as appliances age.

The RECS survey is DOE’s primary resource for appliance ages. For several appliances, including refrigerators and freezers, the survey asks respondents to identify the appliance’s age

as:

• less than 2 years old,

• 2 to 4 years old,

• 5 to 9 years old,

b For reference on the Weibull distribution, see sections 1.3.6.6.8 and 8.4.1.3 of the NIST/SEMATECH e-Handbook

of Statistical Methods , < www.itl.nist.gov/div898/handbook/ >.

8-18• 10 to19 years old, or

• more than 20 years old.

The RECS survey has been conducted every three or four years for the past several decades. For this analysis, DOE used the surveys conducted in 1990, 1993, 1997, 2001, and 2005. DOE used the AHS count of housing units that contain refrigerator s to scale the RECS data to better match the total installed stoc k. The U.S. Census AHS does not include data on freezers. DOE used the RECS micro-data to exclude from this analysis refrigerators that are both “half-height” and less than 10 cubic feet in capac ity, because such refriger ators are not standardsized. To determine overall refrigerator lifet ime, DOE included all appropriately sized refrigerators, whether the househol d’s first (primary) or second refr igerator. Households that did not know the age of their applia nce were allocated among the remaining age bins according to the distribution of respondents w ho did report the appliance age.

Refrigerator ownership exhibits complex c onsumer behavior, which is not adequately reflected in AHS. In particular, AHS records only whether a housing unit c ontains a refrigerator, not the number of refrigerators. In addition, AHS may record a unit as containing a refrigerator when it contains a compact, rather than standard-size, appliance. Therefore, DOE used AHS only to scale the number of first refrigerators record ed by RECS. The baseline number of refrigerators reported in each RECS age bin is the sum of th e AHS-scaled first refrigerators and the un-scaled, standard-size second refrigerators.

DOE adjusted the RECS survey data to accoun t for the fact that the RECS survey begins its reference year with July, whereas shipments data are provided for each calendar year. DOE adjusted the data by using the survival f unction to model the additional retirement and replacement of appliances that takes place in the latter half of a survey year (after a given respondent is surveyed).

DOE used the RECS data on appliance ages , combined with the history of appliance shipments, to develop survival functions for refrigeration products. For example, DOE summed the total shipments from 5 to 9 years before each RECS survey, then compared this number with the number of units still in use at the time of the survey to approximate the percentage of surviving appliances within that age bin. By comb ining the age bins from the five RECS surveys with shipments data, DOE had enough data to us e a least-squares method to build a fit to a Weibull distribution and find the parameters ( α , β

, θ ) that best approximate the number of surviving units. Because the first two (youngest) RECS bins tend to have a large scatter relative to the shipments in those years, DOE combined the RECS and shipments data in the first two bins. Refrigerators and freezers generally do not fa il during their first four years, so combining bins did not lower appreciably the accuracy of the distribu tion. DOE weighted each bin’s contribution to the sum of squares by the inverse of the variance in RECS survey results, which controls for the changes in sample size between bins and through time. c RECS has a complex

c See sections 4.1.4.3, 4.4.3.2, and 4.4.5.2 of NIST/SEMATECH e-Handbook of Statistical Methods
,

<www.itl.nist.gov/div898/handbook/>

.

8-19error model. DOE used only the e rror due to finite sample size to determine the variance for weighting the age bins. The equation for th e sum of squares that DOE minimized is: 

## ( RECS i − Surv i 

## ) 2 

## ∑

σ 2 ,

i i
, RECS Where:

i = the identifier for a bin from a single RECS; RECS i = the number of appliances reported by RECS in bin I ; Surv i = the number of surviving appliances in bin i predicted by the Weibull distribution applied to the number of applia nces shipped (a function of α , β , and θ ); and

σ i,RECS = the standard error (square root of the variance) of the RECS data point for bin i.

Table 8.2.13 shows the RECS data for refriger ators, the associated total shipments, and the best-fit Weibull calculation of stock by age bin. Figure 8.2.2 plot s the data from the third and fourth columns of Table 8.2.12 agai nst each other to show the quality of the fit. DOE allowed the delay parameter, θ , to vary only between 1 and 5 years, which corresponds to common warranty periods (see discussion below). For refrigerators and freezers, the best fit within this range is 5 years.

The Weibull distribution, shown in Fi gure 8.2.3, is characterized by the parameters α = 13.91, β = 1.68, and θ = 5.0. This distribution has a mean re frigerator lifetime of 17.43 years and a median lifetime of 16.18 years.

8-20Table 8.2.12 Standard-Size Refrigerator-Freezers: Comparison of Survey and Shipments Data with Modeled Stock RECS 2005 All Refrigerators Second Refrigerators Modeled Modeled Age Bin years Shipments RECS Stock Stock RECS Stock Stock 0 to 4 51,119,128 56,880,896 51,119,128 5,311,005 3,041,016 5 to 9 42,988,500 40,150,841 41,031,292 4,983,112 3,524,129 10 to 19 68,088,000 36,771,769 40,997,548 8,672,157 6,942,353 20 or more 165,800,000 10,337,608 12,039,872 4,139,841 4,628,220 RECS 2001 All Refrigerators Second Refrigerators Modeled Modeled Age Bin years Shipments RECS Stock Stock RECS Stock Stock 0 to 4 44,319,100 46,312,479 44,319,100 2,460,510 2,637,703 5 to 9 36,982,000 39,491,335 35,298,172 3,868,224 3,031,985 10 to 19 60,556,000 35,970,898 36,813,807 6,572,685 6,198,453 20 or more 144,325,000 11,301,203 11,920,574 3,955,496 4,580,842 RECS 1997 All Refrigerators Second Refrigerators Modeled Modeled Age Bin years Shipments RECS Stock Stock RECS Stock Stock 0 to 4 38,185,000 44,356,564 38,185,000 2,047,982 2,274,485 5 to 9 32,698,000 36,760,359 31,123,487 2,782,204 2,695,071 10 to 19 56,244,000 31,056,224 33,972,064 5,078,190 5,724,270 20 or more 122,660,000 10,989,427 11,832,244 3,879,197 4,475,841 RECS 1993 All Refrigerators Second Refrigerators Modeled Modeled Age Bin years Shipments RECS Stock Stock RECS Stock Stock 0 to 4 33,088,000 37,322,759 33,088,000 1,605,544 1,972,965 5 to 9 31,584,000 35,001,768 30,138,108 2,289,052 2,591,010 10 to 19 52,400,000 32,735,032 30,891,143 4,695,960 5,348,774 20 or more 101,577,000 13,119,858 11,723,329 5,708,862 4,296,210 RECS 1990 All Refrigerators Second Refrigerators Modeled Modeled Age Bin years Shipments RECS Stock Stock RECS Stock Stock 0 to 4 32,670,000 38,098,670 32,670,000 1,784,095 1,950,717 5 to 9 26,419,000 30,724,176 25,249,353 2,227,766 2,158,527 10 to 19 56,584,000 34,088,557 33,242,186 5,316,297 5,767,417 20 or more 82,797,000 12,571,836 10,159,632 4,869,236 3,737,018 Source: U.S. Department of Energy–Energy Information Agency. Residential Energy Consumption Survey. 1990, 1993, 1997, 2001, and 2005.

8-21Calculated number of refrigerators by bin 40000000

30000000

20000000

10000000

0 bins ideal

0 10000000 20000000 30000000 40000000 RECS reported number of refrigerators by bin

Figure 8.2.2 Comparison of Modeled Refrigerator Age Distribution with Data from Residential Energy Consumption Surveys

1.2

1.0Fraction surviving 0.8

0.6

0.4

0.2

0.0 16.18 17.43 Survival function Median lifetime Mean lifetime

0 5 10 15 20 25 30 35 40 45 Age (years)

Figure 8.2.3 Survival Function for Standard -Size Refrigerator-Freezers

8-22 50The method DOE used to calculate product lif etimes incorporates several assumptions:

• Appliance lifetime can be modeled by a surv ival function. In particular, a Weibull distribution is an approp riate survival function.

• The appliance survival functi on does not change through time.

• The survival function is independent of other household factors (such as household size or geographic region) as well as product class (within standard-size refrigerators or freezers).

• RECS respondents neither systematically overestimated nor underestimated the current age of their appliance.

• The historical shipment data are accurate.

• The shipped appliances are installed exclusiv ely (or almost exclusiv ely) in residences.

• The Weibull delay parameter, θ , is limited to between 1 and 5 years.
Three of these assumptions reflect analyt ical choices made by DOE. The first is the assumption that a Weibull distribu tion is the appropriate distributi on to use for rates of appliance retirement. This distribution is th e standard one used in lifetime analyses, but it is not guaranteed to reflect actual real-world experience. The s econd assumption is that consumer behavior and mechanical appliance lifetime have not change d over time. This assumption required DOE to treat equally all data from the several RECS su rveys. Using only recent surveys (which may better reflect recent consumer behavior and app liance lifetime) would provide only a few data points for attempting least-squares fits, producing large statistical uncertainty.

The third assumption concerns the Weibu ll delay parameter. DOE limited the delay parameter to between 1 and 5 years to reflect th e range of common applia nce warranties. A delay of less than 1 year would imply that some appliances fail or are replaced within their first year of use. A delay of more than 5 years would imply that no appliances are replaced for some time after the end of the longest standard warranty. Fits using θ > 5 also commonly show nonsensical behavior, with sharp changes in consumer beha vior or appliance surv ival immediately following the delay period.

8.2.3.2 Conversion of First to Second Refrigerators
When a household purchases a new refrigerator, sometimes it uses its original unit as a secondary appliance in the basement or ga rage. DOE modeled the process by which first refrigerators are converted to second refriger ators as a Weibull process having a cumulative distribution of the form: 

### ⎛ ⎜ ⎛ x

− θ ⎞ β 

### ⎞

− ⎟ 

### P ( x ) = δ + (1

− δ ) × ⎜ 1

− 

# e ⎝ α ⎠ 

### ⎟ for x > θ and 

### ⎜ ⎟ ⎝ ⎠ P(x) = δ for x ≤ θ

8-23Where:

P(x) = probability that the appliance has been converted at age x ;

x

= appliance age;

α = the scale parameter, which would be th e decay length in an e xponential distribution; β

= the shape parameter, which determines the way in which the conversion rate changes through time; δ = the percentage of shipme nts that are used immediately as second refrigerators; and θ

= the delay parameter, which allows for a delay before any conversions occur.

Rather than comparing second refrigerators to shipments, DOE compared them with the existing total installed base of refrigerators of a certain age, as measured by RECS. As with calculating appliance lifetime, the RECS data we re adjusted with AHS data. In essence, DOE constructed a Weibull distribution to model a conversion function ra ther than a survival function. In addition, the model allows for the direct purch ase of a new second refrigerator. A refrigerator bought to be a second refrigerator is modele d as being converted from first to second immediately at purchase; the offset parameter δ represents those units. Refrigerators commonly are bought to be second units, as indicated by the relatively large number of young second refrigerators reported by in RECS surveys.

DOE fit the conversion function usin g results from the 1990, 1993, 1997, 2001, and 2005 RECS. The RECS micro-data again enabled removi ng refrigerators that ar e not standard size, which has a significant effect give n that many compact refrigerators are used as second units. In Table 8.2.12 the fifth column shows the RECS-der ived stock of second refrigerators by age bin, and the sixth column shows the best fit from a Weibull distribution. Figure 8.2.4 shows the Weibull distribution. The best-fit Weibull parameters for the conversion function are α = 38.12, β = 2.03, and θ = 0.0, with an offset of 5.6 percent (meani ng that 5.6 percent of shipments are sold as new second refrigerators). Roughly 1.5 percent of surviving refrigerators are converted from first to second refrigerator status each year, a nd roughly 20 percent of surv iving refrigerators are converted to second refrigerators be fore they reach 15 years of age.

8-240.0 0.2 0.4 0.6 0.8 1.0Fraction converted to 2nd refrigerator Conversion function

0 1 0 2 0 3 0 4 0 5 0 Age (years)

Figure 8.2.4 Function for Conversion of First to Second Refrigerator-Freezers

8.2.3.3 Standard-Size Freezers
DOE assumed relatively simple consumer behavior related to freezers. DOE did not model the conversion from first to second freeze r for households having more than one freezer, but simply used all freezer data from RECS. St andard-sized freezers were assumed to have a capacity greater than 10 cubic feet . As with refrigerators, RECS bins were adjusted for units replaced in the second half of a year to synchr onize the RECS and shipments data. RECS did not collect freezer lifetime data in 1990, so DOE used results from only the 1993, 1997, 2001, and 2005 surveys. The U.S. Census AHS survey does notreport data on freezer s, so the RECS bins were not scaled by the AHS total as for refr igerators. Before 2005, RECS reported the age distribution only for a household’s first freezer, so DOE assumed that second and third freezers have the same age distribution as first freezers.

The best-fit Weibull parameters for freezer lifetime are α = 19.49, β = 2.40, and θ = 5.0. The resulting calculated mean fr eezer lifetime is 22.28 years; the median is 21.73 years. Table 8.2.13 lists the (adjusted) number of freezers repo rted in each RECS age bin, along with the modeled stock based on the best-fit Weibull surv ival function and the manufacturer-provided shipments history. Figure 8.2.5 shows the survival function used for standa rd-size freezers in the LCC and national impact analyses.

8-25Table 8.2.13 Standard-Size Freezers: Comparison of Survey and Shipments Stock to Modeled Stock RECS 2005 Age Bin years Shipments RECS Stock Modeled Stock 0–4 12,003,000 9,378,328 12,003,000 5–9 8,617,000 8,118,709 8,557,502 10–19 13,571,000 9,886,011 11,269,325 20 or more 47,672,000 7,607,227 6,973,305 RECS 2001 Age Bin years Shipments RECS Stock Modeled Stock 0–4 9,284,000 8,462,128 9,284,000 5–9 7,615,000 6,939,187 7,557,289 10–19 12,648,000 12,144,649 10,366,534 20 or more 42,528,000 7,494,606 7,817,703 RECS 1997 Age Bin years Shipments RECS Stock Modeled Stock 0–4 7,580,000 7,192,449 7,580,000 5–9 6,578,000 7,527,447 6,529,381 10–19 13,920,000 12,591,552 11,241,688 20 or more 36,203,000 6,561,157 8,045,004 RECS 1993 Age Bin years Shipments RECS Stock Modeled Stock 0–4 6,700,000 6,018,630 6,700,000 5–9 6,250,000 6,924,204 6,202,243 10–19 17,801,000 13,279,168 14,110,780 20 or more 27,388,000 8,277,900 6,374,921

8-2621.73

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 8.2.5 Survival Function for Standard-Size Freezers

8.2.3.4 Compact Refrigeration Products
As mentioned previously, compact refrigera tion products are used in the residential and commercial sectors. RECS micro-da ta identify households that have refrigerators that are “halfheight” and less than 10 cubic f eet in capacity. DOE considered those households as potentially using compact refrigerators. EIA’s Commercial Building Energy Consumption Survey (CBECS) survey of 2003 7 notes the presence of a residential-st yle refrigerator in an establishment. However, CBECS provides no further detail regard ing the size of the refrigerator. Thus, RECS and CBECS data together do not provide enough detail on compact refrigerators to develop a survival function similar to the ones developed for standard-sized refrigerator-freezers and freezers.

DOE assumed that a Weibull distribution re mains the appropriate functional form to represent retirement rates of compact refrig eration products. DOE initially used the average value of lifetime and historical shipments data from Appliance magazine to estimate Weibull parameters for compact refrigerators. When DOE applied the average lifetime of 10 years, given in Appliance magazine, to historical shipments, the model yielded a stock of compact refrigerators that was more than double th e stock indicated by RECS and CBECS. DOE

8-27therefore calibrated the average lif etime to match the stock of compact refrigerators as reported by the surveys.

The estimated Weibull parameters for compact refrigerator lifetime are α = 5.75 and β = 1.75. The resulting calculated mean lifetime is 5.62 years. For determining the lifetime of compact freezers, DOE used a scaling factor proportio nal to the ratio of the lifetimes of standardsized refrigerators and standard-sized freezers. Th e calculated mean lifetim e of a compact freezer is 7.46 years.

8.2.4 Discount Rates

The discount rate is the rate at which DOE discounts future expenditu res to establish their present value. DOE derived discount rates for the LCC and PBP analyses from estimates of the cost to finance the purchase of the considered products. Following financ ial theory, the financal cost of raising funds to purchase appliances can be inte rpreted as: (1) the fi nancial cost of any debt incurred to purchase a product, or (2) the opportunity cost of any equity used to purchase a product. In addition to estimating discount rate s for appliances bought directly by consumers, DOE also estimated discount rates for purchasers of compact refrigerator s and freezers in the commercial sector.

8.2.4.1 Discount Rates for Residential Consumers

Households use various methods to finan ce the purchase of major appliances. In principle, one could estimate the interest rates on the actual fina ncing vehicles used to purchase appliances. The frequency with which each financi ng vehicle is used to pur chase an appliance is unknown, however.

DOE’s approach involved identifying all possibl e debt or asset classes that might be used to purchase the considered appliances, includi ng household assets that might be affected indirectly. d DOE excluded debt from primary mortgage s and the equity of assets considered non-liquid (such as retirement accounts), because those are unlikely to be used to purchase appliances. DOE estimated the average percentage sh ares of the various types of debt and equity in the average U.S. household using da ta from the Federal Reserve Board’s Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. 8 Table 8.2.15 shows the average percentages of each considered type of debt or equity. DOE derived the mean percentages of each source of financ ing throughout the 7 years surveyed.

d An indirect effect would arise if a household sold assets in order to pay off a loan or credit card debt that might

have been used to finance the appliance purchase.

8-28Table 8.2.14 Types of Household Debt and Equity by Percentage Shares Type of Debt or Equity 1989 % 1992 % 1995 % 1998 % 2001 % 2004 % 2007 % Mean % Home equity loan 4.3 4.5 2.7 2.8 2.8 4.4 4.6 3.7
Credit card 1.6 2.1 2.6 2.2 1.7 2.0 2.4 2.1
Other installment loan 2.8 1.7 1.4 1.7 1.1 1.3 1.1 1.6
Other residential loan 4.4 6.9 5.2 4.3 3.1 5.8 7.1 5.3
Other line of credit 1.1 0.6 0.4 0.2 0.3 0.5 0.3 0.5 Checking account 5.8 4.7 4.9 3.9 3.6 4.2 3.4 4.4 Savings or money market
account 19.2 18.8 14.0 12.8 14.2 15.1 13.0 15.3
Certificate of deposit 14.5 11.7 9.4 7.0 5.4 5.9 6.5 8.6 Savings bond 2.2 1.7 2.2 1.1 1.2 0.9 0.7 1.4
Bonds 13.8 12.3 10.5 7.0 7.9 8.4 6.7 9.5
Stocks 22.4 24.0 25.9 36.9 37.5 28.0 28.6 29.0
Mutual funds 8.0 11.1 20.9 20.1 21.3 23.4 25.5 18.6
Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 2007.

DOE estimated interest or return rates associ ated with each type of equity and debt. The source for interest rates for loans, credit cards, and lines of credit was the Federal Reserve Board’s SCF for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. Table 8.2.16 shows the average nominal rates in each year and the inflation factor s used to calculate real rates. DOE calculated effective interest rates for home equity loans in a similar manner as for mortgage rates, because interest on both such loans is tax deductible. Table 8.2.17 shows the average effective real rates in each year and the mean rate across years. Beca use the interest rates for each type of household debt reflect economic conditions throughout num erous years, they are expected to be representative of rates that may be in effect in 2014.

Table 8.2.15 Average Nominal Interest Rates for Household Debt Type of Debt 1989 % 1992 % 1995 % 1998 % 2001 % 2004 % 2007 % Mean % Home equity loan 11.5 9.6 9.6 9.8 8.7 5.7 6.3 7.9
Credit card*

- - 14.2 14.5 14.2 11.7 7.9 9.0
Other installment loan 9.0 7.8 9.3 7.8 8.7 7.4 12.6 13.4
Other residential loan 8.8 7.6 7.7 7.7 7.5 6.0 10.4 8.6
Other line of credit 14.8 12.7 12.4 11.9 14.7 8.8 6.3 7.4
Inflation rate 4.82 3.01 2.83 1.56 2.85 2.66 2.85 Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. * No data on interest rates available for credit cards in 1989 or 1992.

8-29Table 8.2.16 Average Real Effective Interest Rates for Household Debt Type of Debt 1989 % 1992 % 1995 % 1998 % 2001 % 2004 % 2007 % Mean % Home equity loan 3.8 4.3 4.4 5.8 3.8 1.9 2.1 3.0
Credit card*

- - 11.0 12.7 11.1 9.1 3.3 3.9
Other installment loan 4.9 5.8 7.0 6.6 6.1 5.4 9.7 10.7
Other residential loan 4.0 4.7 4.8 6.0 4.6 3.3 5.8 6.0
Other line of credit 9.6 9.4 9.3 10.2 7.3 6.0 3.4 4.4
Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. * No data on interest rates available for credit cards in 1989 or 1992.

No similar rate data are available from the SCF for classes of assets, so the Department derived that information from national histori cal data. The interest rates associated with certificates of deposit, 9 savings bonds, 10 and bonds (AAA corporate bonds) 11 were collected from Federal Reserve Board time-series data for 1977–2008. DOE assumed rates on checking accounts to be zero. Rates on savings and money market accounts came from Cost of Savings Index data covering 1984–2008. 12 The rates for stocks are the annual returns on the Standard and Poor’s 500 for 1977–2008. 13 Rates for mutual funds are a weighted average of the stock rates (two-thirds weight) and the bond rates (one-third weight) in each year for 1977–2008. DOE adjusted the nominal rates to re al rates using the annual inflati on rate for each year. Average nominal and real interest rate s for the classes of household as sets are listed in Table 8.2.18. Because the interest and retu rn rates for each type of a sset reflect economic conditions throughout numerous years, they are expected to be representative of rates that may be in effect in 2014.

Table 8.2.17 Average Nominal and Real Interest Rates for Household Equity Type of Equity Average Nominal Rate % Average Real Rate % Checking account

- 0.0 Savings and money market accounts 5.4 2.2 Certificate of deposit 6.6 2.3 Savings bond 7.7 3.3
Bonds 8.5 4.1
Stocks 11.6 7.1
Mutual funds 10.3 5.8

Table 8.2.19 summarizes the mean real effectiv e rates of each type of equity or debt. DOE determined the average percentage of each type of debt and asset using SCF data for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. Each year of SCF da ta provides the percents of debts and assets for U.S. households. DOE averaged those percentages for the 7 years of survey data to arrive at the percentages show n in Table 8.2.19. The average rate across all types of household debt and equity, weighted by the per centages of each type, is 4.8 percent.

8-30Table 8.2.18 Average Interest on Household Debt and Equity

Type of Debt or Equity Average % of Household Debt plus Equity* Mean Effective Real Rate % ** Home equity loan 3.7 3.9
Credit card 2.1 10.7
Other installment loan 1.6 6.0
Other residential loan 5.3 4.4
Other line of credit 0.5 8.8 Checking account 4.4 0.0 Savings and money market account 15.3 2.2 Certificate of deposit 8.6 2.3 Savings bond 1.4 3.3
Bonds 9.5 4.1
Stocks 29.0 7.1
Mutual funds 18.6 5.8 Total/weighted-average discount rate 100.0 4.8
* Not including primary mortgage or retirement accounts. ** Adjusted for inflation and, for home equity loans, tax deduction of interest.

8.2.4.2 Assignment of Discount Rates to Sample Households
To account for variations among households, DOE assigned each sampled RECS household a rate from a distributi on of rates for each type of de bt and equity. DOE developed a probability distribution of interest rates ba sed on SCF data. Appendix 8-C presents the probability distribution of interest rates th at DOE used in the LCC and PBP analyses.

8.2.4.3 Discount Rates for Commercial Purchasers

DOE derived the discount rate for commercial owners of compact refrigeration products from the cost of capital of publicly traded firms in the sectors that purchase those products. The firms typically finance equipment purchases thro ugh debt and/or equity capital. DOE estimated the cost of the firms’ capital as the weighted aver age of the cost of equity financing and the cost of debt financing for each year between 2001 and 2008.

The costs of debt and equity financing us ually are publicly available for firms in the lodging and other commercial sectors e that may purchase compact refrigeration products.

DOE estimated the cost of equity usi ng the capital asset pricing model (CAPM). 14 The CAPM assumes that the cost of equity ( k e ) for a given company is proportional to the systematic risk faced by that company, whereby high risk is associated with a high cost of equity and low

e The “other commercial” sector includes financial ins titutions and all services other than lodging (SIC 6-8).

8-31risk is associated with a low cost of equity. Th e systematic risk facing a firm is determined by several variables: the risk coefficient of the firm ( β ), the expected return on risk-free assets ( R f ), and the equity risk premium ( ERP ). The risk coefficient of a firm describes the risk associated with that firm represented by standard deviations in the firm’s stock price. The expected return on risk-free assets is defined by the yield on long-term government bonds. The ERP represents the difference between the expected stock market return and the risk-free rate. To estimate the expected return on risk-free asse ts and the equity risk premiu m, DOE used stock and bond data from Damodaran Online, a widely used source of information about debt and equity financing for most types of firms. 15,16 The Damodaran Online data were adjusted for annual inflation using deflator data for the gross domestic product from the Bureau of Economic Analysis’ National Income and Product Accounts Tables

. 17

The cost of equity financing is estimated using the following equation:

k e = R f + 

## ( β × ERP 

## )

Where:

k e = cost of equity, R

f = inflation-adjusted expected return on risk-free assets, f β = risk coefficient of the firm, and ERP = equity risk premium.

The cost of debt financing ( k d ) is the interest rate paid on money a company borrows. The cost of debt is estimated by a dding a risk adjustment factor ( R a ) to the risk-free rate. This risk adjustment factor depends on the variability of stock returns represented by standard deviations in the firm’s stock price. Thus for firm i , the cost of debt financing is:

k = R + R

di f ai Where:

k

d = cost of debt financing for firm i
, R

f = expected return on risk-free assets, and R ai = risk adjustment factor to risk-free rate for firm i

. DOE estimates the weighted-average cost of capital using the following equation.

WACC = k × w + k × w e e d d Where:

WACC = weighted average cost of capital,

f Ibbotson Associates argues that the arithmetic mean equates the expected future value with the present value and should be used in calculating the risk-free rate and eq uity risk premium when using CAPM to estimate discount rates ( Stocks, Bonds, Bills, and Inflation 2009 Yearbook , Ibbotson Associates, p. 60).

8-32w e = proportion of equity financing, and

w d = proportion of debt financing.

The values of the parameters used in the calculations are shown in Table 8.2.20.

Table 8.2.19 Data for Calculating Weighted-Aver age Cost of Capital for Commercial Sectors

Sector Year β R f % ERP % R a % w e % w d %
2001 1.18 3.25 5.17 1.50 88 12
2002 1.27 3.55 3.66 1.50 89 11
2003 1.71 3.40 4.70 1.25 93 7
Lodging 2004 0.98 3.43 4.34 1.00 89 11
2005 1.45 3.36 4.08 1.25 93 7
2006 1.24 3.36 4.13 1.25 93 7
2007 1.25 3.54 4.33 1.00 96 4
2008 1.23 4.10 2.33 2.00 86 14
2001 0.87 3.25 5.17 3.50 77 23
2002 0.92 3.55 3.66 3.50 77 23
2003 0.87 3.40 4.70 1.50 81 19
Other Commercial 2004 0.90 3.43 4.34 1.25 84 16
2005 0.88 3.36 4.08 1.50 82 18
2006 0.91 3.36 4.13 2.00 84 16
2007 0.87 3.54 4.33 1.25 79 21
2008 0.93 4.10 2.33 3.00 68 32 Note: Parameters are defined on the preceding two pages.
Using the procedure described above and th e data in Table 8.2.20, DOE developed the real weighted-average cost of capital for th e two commercial sectors that purchase compact refrigeration products. Those cost s are listed in Table 8.2.21.

8-33Table 8.2.20 Weighted-Average Cost of Capital for Commercial Sectors
Year Lodging % Other Commercial %
2001 5.69 6.75
2002 5.11 6.21
2003 5.49 6.64
2004 5.82 6.62
2005 5.95 6.24
2006 6.04 6.46
2007 6.42 6.40
2008 5.74 5.60 Sector average 5.78 6.37

In calculating the discount rate for co mpanies that typically purchase compact refrigeration products, DOE generated a distribu tion of discount rates w ithin each sector. The standard deviation of the distribut ion for each sector is provided in Table 8.2.22. Weighting each sector’s discount rate by its share of compact refrigerator purchases, g DOE estimated that the average discount rate for companies that purchase co mpact refrigeration products is 6.20 percent.

Table 8.2.21 Discount Rates for Commercial Sectors

Sector Discount Rate % of Purchases Average % Max. % Min. % Standard Deviation % Lodging 5.78 11.98 2.35 1.26 29

Other commercial 6.37 15.65 2.48 1.72 71 Weighted average 6.20

- - - 100

To account for variations in discount rate s within each sector, DOE applied a normal probability distribution to the average values an d standard deviations in Table 8.2.22. DOE truncated the normal distributi on using the maximum and minimu m values presented in Table 8.2.22.

8.2.5 Effective Date of Standard
The effective date of a potential new standa rd is the future date when it would become operative. Based on DOE’s implementation report for energy conservatio n standards activities submitted pursuant to section 141 of the Energy Polic y Act of 2005, a final rule pertaining to the appliances being considered for this rulemaking is scheduled for December 2010. 18 The effective date of any new energy efficiency standards for the products is 3 years after the final rule is

g The approach for estimating the share of total purchases by each of the two commercial sectors is described in

chapter 9.

8-34published, or January 2014. The Department cal culated the life-cycle cost (LCC) for all consumers as if each would purchase a new appliance in the year the standard is to take effect.

8.2.6 Base-Case Energy Efficiencies
To estimate the percentage of consumers who would be affected by a standard at any of the potential efficiency levels, in its LCC analysis DOE considered the projected distribution of efficiencies for products that consumers purchase under the ba se case (the case without new energy efficiency standards). DOE refers to this distribution of product ener gy efficiencies as the base-case efficiency distribution. Using the proj ected distribution of effi ciencies for each product class, DOE randomly assigned a product efficien cy to each sample household. If a household was assigned a product efficiency that was greater than or equal to the efficiency of the standard level under consideratio n, the LCC calculation would show that this household would not be affected by that standard level.

DOE began with the energy efficiency di stribution (market shares) for refrigeration products in 2007 based on data provided by AHAM 19 . In 2007, efficiency level 2 for refrigerator-freezers corresponded to the efficiency required for EN ERGY STAR certification. In 2008, the criteria changed so that efficiency level 3 corresponded to the efficiency required for ENERGY STAR certification. If th e market shares of refrigerat ion products by efficiency were the same in 2008 as in 2007, the ENERGY STAR market share would be 0 percent for topmount refrigerators, 18 percent for bottom-mount refrigerators, and 2 percent for side-by-side refrigerators.

Efforts to promote ENERGY STAR products through various means, including consumer rebates, are expected to increase their market shares by 2014. Although it is difficult to predict appliance sales in 2014, it is reas onable to assume that the increase in market shares of ENERGY STAR products will follow the same pattern as they did between 2001 (the year in which the current DOE standards took effect and caused a shift in ENERGY STAR requirements) and 2007. The projected market shares of efficiency le vels are shown in Table 8.2.23. As shown, the assumed market share of ENERGY STAR models in 2014 (under current requirements) is equal to the market share of ENERGY STAR mode ls in 2007 (under the old requirements). For example, because 32 percent of side-by-side refrigerator-freezers qua lified for ENERGY STAR (efficiency level 2 and higher) under the pre-200 8 requirements, DOE assumed that 32 percent would meet ENERGY STAR require ments (efficiency level 3) in 2014. DOE also assumed that the market shares of lower-efficiency models ( i.e., baseline and 10 percent below baseline) would stay the same between 2007 and 2014.

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