PSE Ref Impact Final_WithERR

Residential Refrigerator Impact Evaluation

Contents:

• Residential Refrigerator Impact Evaluation by DNV KEMA

• Evaluation Report Response

This document contains both the final Residential Refrigerator Evaluation Report produced

by DNV KEMA, and the Puget Sound Energy Evaluation Report Response (ERR). PSE

program managers prepare an ERR upon completion of an evaluation of their program. The

ERR addresses and documents pertinent adjustments in program metrics or processes

subsequent to the evaluation.

This page is intentionally blank.

Evaluation Report Response

Program: PSE Refrigerator Programs – Refrigerator Replacement, Refrigerator Decommissioning, Energy Star

Refrigerator Rebate

Program Manager: Dennis Rominger, Sandy Sieg, Clint Stewart

Study Report Name: PSE Refrigerator Programs

Report Date: 05/14/2013

Evaluation Analyst: Bobbi Wilhelm

Date ERR Provided to Program Manager: 7/10/2013

Date of Program Manger Response: 7/30/2013, Revised 8/30/2013

Key Impact Evaluation Report Findings:

The KEMA PSE Refrigerator Programs report dated 5/14/2013 suggests the following:

The PSE deemed refrigerator replacement measure savings are too high that were based upon the 2005 California

Impact Evaluation. The report suggests the savings are too high due mostly to an HVAC interaction in

electrically-heated homes studied under this evaluation. It also suggests an anti-acceleration factor due to

customer survey responses, which indicate they would have purchased a new unit absent the PSE program. It also

suggests a tiered measure life by using RTF values on the estimated useful life divided by the remaining useful

life of units.

The RTF savings are too high for refrigerator decommissioning. The report suggests this is due mostly to

customer survey responses, which indicate absent the program they would have discarded the unit anyway. It also

suggests recent acquirers of a used unit would have acquired another similar used unit if the one they recently got

was not available.

The RTF savings are too high for CEE Tier 2 and CEE Tier 3 Energy Star refrigerator rebates. The report

suggests this is due mostly to customer survey responses, which indicate absent the program they would have

purchased an Energy Star refrigerator. It also suggests a tiered measure life due to an acceleration factor, also

determined by customer survey responses in regards to what the customer would have done.

1.1.1 Report Overview (Directly from the Evaluation Report):

Table 2-1summarizes the evaluated savings for the three PSE refrigerator programs. Gross and net savings are provided for the replacement and rebate programs. Savings for the decommissioning program are adjusted programmatic savings.

Table 0-1: Program Savings Summary

Program

Measure

Life Years

Annual

Savings

(kWh)

Annual Net

Savings

(kWh)

Decommissioning 11 150.4

Replacement

1-10 372.6 337.3

11-20 55.5 36.1

Rebate - Tier 2

1-14 67.1

49.5

15-20 15.4

Rebate - Tier 3

1-14 66.5

66.4

15-20 15.3

The decommissioning program savings represent the combination of both the direct removal of secondary units and the restriction of supply to the used unit market. The rebate and replacement program sections summarize the two-part life-time savings estimates produced for this evaluation. The replacement program generates gross savings at two distinct levels. For the first ten years of the measure life, the average remaining useful life (RUL) of the existing unit, savings are the difference between the average existing unit UEC and efficient program unit. The remainder of the new unit measure life generates savings for the difference between the efficient program unit and a standard efficiency baseline unit. Net savings reflect that some participants would have replaced their present unit without the program and some of those would have done so with an ENERGYSTAR® unit.

Rebate units produce gross savings at one level for the 20 year measure life. Net savings are reduced across the full twenty year measure life because a substantial percent of participants would have purchased ENERGYSTAR units without the program. In addition, though, a subset of participants say the program accelerated the purchase of a new unit. This increases savings during the remaining useful life of the existing unit. Savings logic and calculations are all discussed extensively in the report.

1.1.2 Discussion of Key Findings/Analysis:

The program team makes the following observations.

For refrigerator replacement:

HVAC Interaction: The HVAC interaction calculated for this report is based upon a high concentration of

electrically-heated homes studied under this particular evaluation. During the 2011-12 study years, this measure

marketed heavily to lower income customers that reside in rural areas of our service territory. This was for

efficiency purposes to align with our 2012 Rock-the-Bulb tour, which was also heavily rural focused. Rural

customers tend to be electrically-heated customers. This study population is not necessarily representative of the

future population that would participate in this program.

The net savings calculated for this report is based upon a question that asks customers if they would have

purchased an Energy-Star unit absent this program. This particular question may not be reliable to factor into net

savings as we know that Energy Star has 85% awareness amongst consumers, especially in association with

appliances. Absent relative cost information, it is more socially acceptable to say Energy Star when answering

this style of question. Again, with the assumption of a lower income participate, it is not a fair assessment to

assume that customers ―would have‖ bought an Energy Star unit. It is also not a fair assessment to assume that

they bought a new unit at all, but rather acquired a used unit of some type.

Measure life was calculated by using RTF values on the estimated useful life divided by the remaining useful life

of units. The report acknowledges that the determination of measure life was outside of the scope of this work. It

should be noted that the RTF methodology for measure life is based upon other refrigerator measures that attract a

wide range of participants. For those measures, the useful life for refrigerators often is whatever the participant

determines. The RTF doesn‘t assume a lower income customer that may not care about things like how the unit

looks or unit features, both of which change with the times. Both of these are common reasons for determining

the end of a refrigerators useful life and aren‘t reflective here.

For refrigerator decommissioning:

The realization rate from our evaluation is 17% of the potential to yield savings of 150 kWh. This is compared with a

realization rate of 41% to 62% on other evaluations conducted since 2002, including the most recent 2010 evaluation from

the Energy Trust of Oregon, which yielded a 50% realization rate. The difference in those evaluations versus KEMA‘s

evaluation, as stated on page 6-12, is primarily due to how this report has captured the market effect of removing units

from the secondary market. KEMA has chosen to:

“…develop a counterfactual scenario of what would have occurred in the market without the program. This approach recognizes

that shifting the supply curve in the secondhand market can have a variety of effects, including lowering the number secondhand

units purchased, altering the average UEC of secondary units on the market and/or motivating substitutions of new units in place

of the used unit. Each of these scenarios might generate savings. Only one scenario generates the full savings assigned to these

units by other evaluations – a person who would have purchased a secondhand unit for use as an additional, secondary unit who

decides as a result of the supply constraint not to purchase any unit.”

This scenario affects 61% of the units acquired under the program based upon hypothetical questions asked of participants

and an assessment of the used market. Although the survey questions give us an interesting presumption into the rationale

of past participants, it doesn‘t necessarily indicate real intention. To weigh so heavily into these questions does not seem

reliable and is a departure from all previous evaluations performed as standard industry practice.

Further analysis of the evaluation also makes several assumptions, that although lesser so, also factored into the savings

analysis. This includes, but is not limited to, the following:

29% of past participants indicated in hypothetical questions that they would have destroyed their unit absent the

program. We know from program research that units believed to be destroyed by recyclers and retailers are

actually stolen at the curb, stolen by pick-up drivers, or actually re-furbished by recyclers and continue to be kept

in use. A hypothetical question cannot properly assess the reality of what would have actually occurred.

The report suggests a lack of effect, by PSE‘s program, on the used market supply chain. This was determined by

interviewing second hand dealers via telephone while acting like a customer wanting to stock rental units. With

the setup of this scenario, an honest answer by a dealer wanting to make a sale is not likely. Additionally, most of

the second hand dealers are in the primary business of repairing units and are typically employed by

manufacturers whose units are still under warranty. These dealers may not notice effects on their used appliance

stock as it‘s actually their secondary business. In order to properly make any conclusions, we would need to visit

them and know how long these dealers have been in business. In order to be relevant, they would have to be in

business both before and after PSE‘s program started or survey and compare a market similar to PSE‘s that does

not have a decommissioning program. Also to consider, buying individual-to-individual is the typical method of

acquiring used units and this is mostly done on craigslist, which wasn‘t considered as part of this evaluation.

For refrigerator rebate:

The evaluation report assessed net savings based upon a question that asks customer what they would have

purchased absent this program. Customers that answered that they would have purchased another new Energy

Star unit are discounted savings and this was factored into the net savings calculations. This particular question

may not be reliable to factor into net savings as we know that Energy Star has 85% awareness amongst

consumers, especially in association with appliances. Absent relative cost information, it is more socially

acceptable to say Energy Star when answering a hypothetical question.

The report acknowledges that the determination of measure life was outside of the scope of this evaluation work.

For the purposes of the report, measure life was calculated by using RTF values on the estimated useful life

divided by the remaining useful life of units. The report acknowledges that remaining useful life was calculated

using the age distribution of matched existing units because unit age was not available in the tracking data. The

result is a tiered savings structure that does not fit well for PSE‘s cost-effectiveness calculator or the basic

understanding by individuals trying to understand the calculations.

1.1.3 Proposed Action Plan:

The program team proposes the following action to take effect on January 1, 2014:

For refrigerator replacement:

The program team will apply the findings within the report with some modifications. These are as follows:

An HVAC interaction rate of .86 will be used to align with other RTF measures that consider HVAC interaction.

Absent more knowledge on how lower income customers actually adjust their thermostat, this is more consistent

with other programs that reduce savings based upon HVAC interaction.

The annual gross savings will be used less the net effect that discounted savings based upon questions around

Energy Star.. Absent questions that pertain to relative cost information or the likelihood of acquiring a used unit,

the gross savings are the most precise.

The measure life will be adjusted to reflect 14-years. This is the estimated remaining useful life used within

section 5.4.2 for the refrigerator rebate program. Absent a thorough measure life analysis, based upon a lower

income population, this is a fair and reasonable belief.

The calculated savings for refrigerator replacement will be as follows:

Year 1-14

UEC for Existing Unit = 1136 kWh

Less UEC for program qualifying unit = 347 kWh

Subtotal = 789 kWh

Multiply by RTF HVAC Interaction Factor = .86

Measure Unit Savings = 578 kWh

Measure Life = 14 years, (year 1-14)

Year 15-20

UEC for Standard Efficiency New Unit = 464 kWh

Less UEC for program qualifying unit = 347 kWh

Subtotal = 117 kWh

Multiply by RTF HVAC Interaction Factor = .86

Measure Unit Savings = 101 kWh

Measure Life = 20 years, (year 15-20)

Measure will also be bundled with a single 1.50 gpm showerhead at 103 kWh and a 10-year measure life, and a single

CFL bulb at 16 kWh at a 5-year measure life.

For refrigerator decommissioning:

The program team will keep with the current RTF savings at 424 kWh at a 7-year measure life. When the RTF updates

measure savings, PSE will keep with policy and incorporate the new savings for the following calendar year.

For refrigerator rebate:

The program team will keep with the current RTF savings for Energy Star CEE Tier 2 & 3. Current RTF savings for an

Energy Star CEE Tier 2 is 46 kWh and for a CEE Tier 3 refrigerator is 85 kWh. Both measures have a 17-year measure

life. When the RTF updates measure savings, PSE will keep with policy and incorporate the new savings for the following

calendar year.

PSE Refrigerator Programs

Impact and Process Evaluation

Puget Sound Energy

Prepared by KEMA, Inc.

May 14, 2013

Table of Contents

KEMA, Inc. May 14, 2013 i

1. Executive Summary ........................................................................................................................... 2-1

1.1 Evaluation Overview ............................................................................................................... 2-1

1.2 Results Summary ..................................................................................................................... 2-1

1.3 Findings ................................................................................................................................... 2-2

1.3.1 Replacement Program Findings .................................................................................. 2-2

1.3.2 Rebate Program Findings ........................................................................................... 2-3

1.3.3 Decommissioning Program Findings ......................................................................... 2-3

2. Introduction ........................................................................................................................................ 3-1

2.1 Objectives ................................................................................................................................ 3-1

2.2 Overview of the Report ........................................................................................................... 3-1

3. Data Collection .................................................................................................................................. 4-1

3.1 Program Tracking Data ............................................................................................................ 4-2

3.2 California Energy Commission Label UEC Database ............................................................. 4-3

3.3 In situ Metering Data ............................................................................................................... 4-4

3.3.1 In situ Meter Data Collection ..................................................................................... 4-5

3.4 Weather Data ........................................................................................................................... 4-6

3.5 Standard Efficiency Data ......................................................................................................... 4-6

3.6 Expected Useful Life/Remaining Useful Life ......................................................................... 4-6

3.7 Survey Data ............................................................................................................................. 4-7

3.7.1 Participant Survey ....................................................................................................... 4-7

3.7.2 Non-Participant Survey Data ...................................................................................... 4-8

4. Replacement Program Impacts .......................................................................................................... 5-1

4.1 Replacement Program Description .......................................................................................... 5-1

4.2 Replacement Program Savings Logic ...................................................................................... 5-2

4.3 Replacement Program Savings Calculation Inputs .................................................................. 5-4

4.3.1 UECs ........................................................................................................................... 5-4

4.3.2 Estimated Useful Life/Remaining Useful Life Determination ................................... 5-6

4.3.3 HVAC Interaction Effect ............................................................................................ 5-7

4.4 Replacement Program Savings Estimates................................................................................ 5-7

4.4.1 Replacement Program Results Compared to Claimed Savings .................................. 5-9

5. Rebate Program Impacts .................................................................................................................... 6-1

5.1 Rebate Program Description .................................................................................................... 6-1

5.2 Rebate Program Savings Logic ............................................................................................... 6-1

5.3 Overview of Estimation Approach .......................................................................................... 6-3

5.4 Rebate Program Savings Calculation Inputs ........................................................................... 6-3

5.4.1 UECs ........................................................................................................................... 6-3

5.4.2 Estimated Useful Life / Remaining Useful Life Determination ................................. 6-4

Table of Contents

KEMA, Inc. May 14, 2013 ii

5.4.3 HVAC Interaction Effect ............................................................................................ 6-4

5.5 Rebate Program Savings Estimates ......................................................................................... 6-5

5.5.1 Replacement Program Results Compared to Claimed Savings .................................. 6-7

6. Decommissioning Program Impacts .................................................................................................. 7-1

6.1 Program Description ................................................................................................................ 7-1

6.2 Decommissioning Program Savings Logic.............................................................................. 7-2

6.3 Overview of Estimation Approach .......................................................................................... 7-3

6.4 Decommissioning Program Savings Calculation Inputs ......................................................... 7-6

6.4.1 UECs ........................................................................................................................... 7-6

6.4.2 Survey Responses ....................................................................................................... 7-7

6.5 Decommissioning Program Savings Estimation ...................................................................... 7-7

6.5.1 Results Compared to Other Evaluations ................................................................................ 7-11

7. Process Results and Market Characterization .................................................................................... 8-1

7.1 Program Satisfaction Results ................................................................................................... 8-1

7.2 Additional Participant Survey Results ..................................................................................... 8-1

7.2.1 Replacement ............................................................................................................... 8-1

7.2.2 Rebate ......................................................................................................................... 8-2

7.2.3 Decommissioning ....................................................................................................... 8-3

7.2.4 Comparative Participant Demographics ..................................................................... 8-4

7.3 Non-Participant Survey Results ............................................................................................... 8-4

7.3.1 Non-Participant Demographics .................................................................................. 8-4

7.3.2 Comparative Non-Participant Program Awareness .................................................... 8-5

7.3.3 Other Non-Participant Energy Attitudes .................................................................... 8-5

8. Results Summary and Findings ......................................................................................................... A-1

8.1 Results Summary .................................................................................................................... A-1

8.2 Findings .................................................................................................................................. A-2

8.2.1 Replacement Program Findings ................................................................................. A-2

8.2.2 Rebate Program Findings .......................................................................................... A-2

8.2.3 Decommissioning Program Findings ........................................................................ A-2

A. Replacement Program Savings ......................................................................................................... A-1

A.1 Savings Logic – Net Savings .................................................................................................. A-1

A.2 PSE Refrigerator Metering ..................................................................................................... A-3

A.3 Estimation of Label UEC ........................................................................................................ A-8

A.4 In situ Adjustment Calculation ............................................................................................... A-9

A.5 Determination of ―Standard‖ baseline UECs ........................................................................ A-11

A.6 HVAC Interaction Effect ...................................................................................................... A-12

A.7 Net Savings Calculations ...................................................................................................... A-13

Table of Contents

KEMA, Inc. May 14, 2013 iii

B. Rebate Program ................................................................................................................................. B-1

B.1 Estimation of Label UEC ........................................................................................................ B-1

B.2 Application of in situ Adjustment Factor ............................................................................... B-1

B.3 Determination of New ―Standard‖ UEC ................................................................................. B-2

B.4 Estimated Useful Life / Remaining Useful Life Determination ............................................. B-3

B.5 HVAC Interaction Effect ........................................................................................................ B-3

B.6 Rebate Program Net Savings .................................................................................................. B-3

C. Decommissioning .............................................................................................................................. C-1

C.1 Estimation of Label UEC ........................................................................................................ C-1

C.2 Application of in situ Adjustment Factor ............................................................................... C-1

C.3 Determination of New ―Standard‖ UEC ................................................................................. C-2

C.4 Determination of Resale Value UECs .................................................................................... C-3

C.5 Estimated Useful Life/Remaining Useful Life Determination ............................................... C-3

C.6 HVAC Interaction Effect ........................................................................................................ C-3

C.7 Decommissioning Program Survey Results ........................................................................... C-4

D. Used Unit Marked Characterization .................................................................................................. D-1

D.1 Market Characterization Data Gathering ................................................................................ D-1

D.2 Used Unit Market Characterization ........................................................................................ D-3

E. Additional Survey Data - Participant ................................................................................................ E-1

E.1 Total (Overall) Participant Respondent Profile ...................................................................... E-1

E.2 Participant Program Satisfaction ............................................................................................ E-2

E.3 Participant Energy Attitudes ................................................................................................... E-3

E.4 Participants: Awareness and Motivation ................................................................................ E-4

F. Survey Instruments............................................................................................................................. F-5

F.1 Non Participant CATI Refrigerator ......................................................................................... F-5

F.2 Participant CATI Refrigerator ............................................................................................... F-18

List of Exhibits

Table 1-1: Program Savings Summary ...................................................................................................... 2-2

Table 3-1: Number of Units in Tracking Database .................................................................................... 4-2

Table 3-2: Variables Used in Analysis That Were in the Tracking Data ................................................... 4-3

Table 3-3: Disposition of Replacement Program Metered Units Data ...................................................... 4-6

Table 3-4: PSE Refrigerator Programs: Participant CATI Dispositions .................................................... 4-8

Table 3-5: PSE Refrigerator Survey: Non-Participant CATI Dispositions ................................................ 4-9

Table 4-1: Replacement Program UECs .................................................................................................... 5-6

Table of Contents

KEMA, Inc. May 14, 2013 iv

Table 4-2: Remaining Useful Life/Program Unit Measure Life: Replacement Program .......................... 5-6

Table 4-3: Lifetime Savings Replacement Program .................................................................................. 5-9

Table 4-4: Key results from RTF report: Replacement Program ............................................................... 5-9

Table 5-1: In situ Adjusted Program UECs ............................................................................................... 6-4

Table 5-2: Market Baseline UECs for Rebate Program ............................................................................. 6-4

Table 5-3: Remaining Useful Life/Program Unit Measure Life: Rebate Program .................................... 6-4

Table 5-4: Lifetime Savings for Tier 2 and Tier 3 Rebate Programs ......................................................... 6-7

Table 5-5: Comparison of key results from RTF report: Rebate Program ................................................. 6-7

Table 6-1: Summary of Decommissioning Savings................................................................................. 7-10

Table 6-2: Programmatic Adjusted Decommissioning Program Savings ................................................ 7-10

Table 6-3: PSE Decommissioning Compared with Other Recycling Program Results ........................... 7-11

Table 8-1: Program Savings Summary ..................................................................................................... A-1

Appendix Table A-1: Label UEC Look-up, Matched and Imputed UEC: New Units in Replacement

Program ............................................................................................................................................. A-9

Appendix Table A-2: In situ Adjustments for the Replacement Program .............................................. A-10

Appendix Table A-3: Average Efficiency by Bins—Replacement Program ......................................... A-11

Appendix Table A-4: Replacement Program Standard Efficiency UEC ................................................ A-12

Appendix Table A-5: Heating and Cooling Share of PSE Year ............................................................. A-13

Appendix Table A-6: Share of Participants with Electric Heat/Air Conditioning: ................................. A-13

Appendix Table A-7: HVAC Interaction Factor Calculation: ................................................................ A-13

Appendix Table A-8: Recoded Survey Responses Used to Determine Acceleration Factor .................. A-14

Appendix Table A-9: Without the program, would you have purchased an ENERGY STAR refrigerator?

........................................................................................................................................................ A-14

Appendix Table B-1: Label UEC Look-up--Matched and Imputed UEC for Rebate Program ................ B-1

Appendix Table B-2: In situ Adjustments ................................................................................................ B-1

Appendix Table B-3: Average Efficiency by bins Rebate Program ......................................................... B-2

Appendix Table B-4: UECs for New Standard Efficiency Rebate Program Units ................................... B-2

Appendix Table B-5: Remaining Useful Life/Program Unit Measure Life: Rebate Program .................. B-3

Appendix Table B-6: HVAC Interaction Factor Calculation ................................................................... B-3

Appendix Table B-7: Survey responses used to determine acceleration factor ........................................ B-5

Appendix Table B-8: Without the program, would you have purchased an ............................................. B-6

Appendix Table C-1: Label UEC Look-up: Matched and Imputed UEC ................................................. C-1

Appendix Table C-2: In situ Adjustments ................................................................................................ C-2

Appendix Table C-3: UECs for Standard Efficiency ................................................................................ C-3

Appendix Table C-4: Estimated UEC ....................................................................................................... C-3

Appendix Table C-5: Remaining Useful Life/Program Unit Measure Life: Decommissioning Program C-3

Table of Contents

KEMA, Inc. May 14, 2013 v

Appendix Table C-6: Share of Participant unit With Electric Heat/Air Conditioning ............................. C-4

Appendix Table C-7: HVAC Interaction Factor Calculation ................................................................... C-4

Appendix Table C-8: What would you have done with the old refrigerator ............................................. C-4

Appendix Table C-9: I‘d like to talk to you about the refrigerator you disposed of. ................................ C-5

Appendix Table D-1: Sample - Used Refrigerator Retailer, Repair Service & Recycler ......................... D-1

Appendix Table D-2: Sources for additional research .............................................................................. D-2

Appendix Table D-3: Disposition Report from IDI contacts .................................................................... D-3

Appendix Table E-1: Participant Satisfaction on Program Processes ...................................................... E-2

Appendix Table E-2: Participant Level of Concern with Reducing Energy Use ...................................... E-3

Appendix Table E-3: Participant Reason for Concern with Reducing Energy Use .................................. E-4

Appendix Table E-4: Participant Source of Information about the Program? .......................................... E-4

Figure 4-1: Replacement Program Gross Savings Diagram ...................................................................... 5-3

Figure 4-2: Replacement Program Gross Savings Calculation .................................................................. 5-8

Figure 4-3: Replacement Program Lifetime Savings ................................................................................. 5-8

Figure 5-1: Rebate Program Gross Savings Diagram ................................................................................ 6-2

Figure 5-2: Rebate Program Gross Savings Calculation............................................................................ 6-5

Figure 5-3: Rebate Program Lifetime Savings for Tier 2 Units ................................................................. 6-6

Figure 5-4: Rebate Program Lifetime Savings for Tier 3 Units ................................................................. 6-6

Figure 6-1: Decommissioning Program Flowchart, Step One ................................................................... 7-4

Figure 6-2: Decommissioning Program Flowchart, Market Effects .......................................................... 7-5

Figure 6-3: Decommissioning Program Flowchart with Values, Step One ............................................... 7-8

Figure 6-4: Decommissioning Program Market Effects Flowchart with Values ....................................... 7-9

Appendix Figure A-1: Replacement Program Net Savings Diagram ....................................................... A-2

Appendix Figure-A-2: Example Meter Data Series ................................................................................. A-5

Appendix Figure A-3: In situ Metering by Date Existing Units ............................................................... A-7

Appendix Figure A-4: In situ Metering by Date—Program Qualifying Units ......................................... A-8

Appendix Figure A-5: In situ to Label UEC Ratio by Age ..................................................................... A-10

Appendix Figure A-6: Replacement Program Net Savings Calculation ................................................. A-15

Appendix Figure B-1: Rebate Program Net Savings Diagram ................................................................. B-4

Appendix Figure B-2: Rebate Program Net Savings Calculation, Tier 2 ................................................. B-7

Appendix Figure B-3: Rebate Program Net Savings Calculation, Tier 3 ................................................. B-8

Appendix Figure C-1: Decommissioning and Replacement Programs Unit Age Distribution ................ C-2

Appendix Figure E-1: When purchasing new appliances, do you look for ENERGY STAR labels? ...... E-3

Appendix Figure F-1: Non-participant Survey Questions ........................................................................ F-6

DNV KEMA Energy & Sustainability

KEMA, Inc. May 14, 2013 2-1

2. Executive Summary

2.1 Evaluation Overview

This report provides an evaluation of Puget Sound Energy‘s (PSE) refrigerator replacement, rebate and

decommissioning programs. The report provides full impact analyses for the three programs, as well as

parallel Appendix sections. Results from a process evaluation that covered all three programs are

discussed in a main body section and an Appendix section as well as throughout the impact sections.

A central goal of this evaluation is to carefully articulate the savings logic that drives these programs.

The impact evaluations carefully develop savings estimates using these structures. The evaluation derives

gross savings estimate for the replacement and rebate programs as well as adjusted programmatic savings

for the decommissioning program. Net savings are also calculated for the replacement and rebate

programs.

This evaluation also had the advantage of collecting a great deal of empirical data on which to base the

savings estimates. The evaluation completed metering of existing and replacement refrigerators in

replacement program households to inform the estimates of unit energy consumption (UEC) for all of the

programs‘ savings calculations. The evaluation also gathered survey data to inform form these

calculations. In particular, a large number used unit acquirers were surveyed about their activities on the

used unit market and how removal of used units would affect their activities.

Refrigerators have been a fruitful target of energy efficiency programs for many years. During that time,

appliance standards have changed the refrigerator market substantially. The results of this evaluation

reflect an area of program focus where savings are increasingly challenging to find. As the refrigerator

market continues to be transformed, refrigerator programs will have to be very focused regarding their

savings propositions.

2.2 Results Summary

Table 2-1summarizes the evaluated savings for the three PSE refrigerator programs. Gross and net

savings are provided for the replacement and rebate programs. Savings for the decommissioning program

are adjusted programmatic savings.


KEMA, Inc. May 14, 2013 2-2


Program

Measure Life

Years

Annual

Savings

(kWh)

Annual Net

Savings

(kWh)


Replacement

1-10 372.6 337.3

11-20 55.5 36.1

Rebate - Tier 2

1-14 67.1

49.5

15-20 15.4

Rebate - Tier 3

1-14 66.5

66.4

15-20 15.3

The decommissioning program savings represent the combination of both the direct removal of secondary

units and the restriction of supply to the used unit market. The rebate and replacement program sections

summarize the two-part life-time savings estimates produced for this evaluation. The replacement

program, generates gross savings at two distinct levels. For the first ten years of the measure life, the

remaining useful life of the existing unit, savings are the difference between the average existing unit

UEC and efficient program unit. The remainder of the new unit measure life generates savings for the

difference between the efficient program unit and a standard efficiency baseline unit. Net savings reflect

that some participants would have replaced their present unit without the program and some of those

would have done so with an ENERGYSTAR® unit.

Rebate units produce gross savings at one level for the 20 year measure life. Savings are reduced across

the full twenty year measure life because a substantial percent of participants would have purchased

ENERGYSTAR units without the program. In addition, though, a subset of participants say the program

accelerated the purchase of a new unit. This increases savings during the remaining useful life of the

existing unit. Savings logic and calculations are all discussed extensively in the report.

2.3 Findings

2.3.1 Replacement Program Findings

The replacement program appears to succeed in reaching its target market. The participant demographics

reveal a participant population with limited resources and education, modest housing and higher mobility.

They value energy efficiency highly because it saves money. Without the help of the program it is

unlikely they would update their refrigerator until the old unit broke and even then the replacement unit

might be a used unit.


KEMA, Inc. May 14, 2013 2-3

Though the savings estimate produced for this evaluation are well below the PSE claim savings levels, the

program savings are founded on sound principals. The pre-1993 year of manufacture requirement means

that existing unit UEC will remain relatively high though the program may have increasing trouble

finding eligible units and the remaining useful life will continue to drop. The primary challenge to the

savings of the replacement program is the high proportion of participant households with electric heat.

This prevalence of electric heated homes among this program‘s population means a substantial loss of

savings to HVAC interaction.

2.3.2 Rebate Program Findings

The rebate program is succeeding in giving point of purchase rebates to refrigerator purchasers. This

program delivery model is effective but faces high penetration levels of ENERGYSTAR appliances. The

PSE claimed savings appear to compensate for that fact and the evaluated savings for tier 2 are almost

identical to the claimed savings. Tier 3 evaluated savings are 78% of claimed savings because the lower

consumption magnitude counteracts the higher level of efficiency savings.

2.3.3 Decommissioning Program Findings

The primary goal of the decommissioning program is removing additional units in the household that

would otherwise remain on the grid. The relatively small percentage of recycled units that participants

indicated would have remained in use at the household in the absence of the program reveals that this

targeted group is a small proportion of decommissioning program population.

The decommissioning program started accepting non-secondary units in 2012. This reduced the

percentage of the targeted secondary of units. For a primary unit to receive credit, the participant would

have had to intend to keep it as an additional unit in the absence of the program. The program needs to

establish whether this is a sufficiently high probability event to justify the inclusion of these replaced,

mostly primary units.

The market effect savings reflect the limited savings opportunities that still exist in the used unit market

and the inefficiencies of supply-side efforts. Fifteen years ago, the majority of available used units pre-

dated the 1993 refrigerator appliance standard improvements. Motivating an upgrade to a post-1993 unit

offered substantial savings. In the present, the majority of available used units are post-1993 units. The

potential savings from an upgrade are more modest.

Upgrades do appear, however, to be the most likely source of savings in the used unit market because the

majority of persons acquiring units through formal and informal channels are getting a unit to use as a

primary unit. Rather than trying to decrease consumption by constraining the supply of units to the used

unit market why not directly target incentives for small, simple, low consumption units that will be used


KEMA, Inc. May 14, 2013 2-4

as primary units to used unit acquirers. This approach would combine aspects of the replacement and

rebate program to more effectively reduce consumption through the used unit market.


KEMA, Inc. May 14, 2013 3-1

3. Introduction

3.1 Objectives

The primary objectives for the refrigerator programs evaluation were:

Produce electric gross and net savings estimates for:

─ Refrigerator Replacement Program - targeted early refrigerator replacements –

─ Refrigerator Rebate Program - refrigerator upgrade via a direct rebate at the point of purchase

─ Refrigerator Decommissioning Program – secondary refrigerators removed from the home

and recycled

Analyze participant and non-participant data to better understand the refrigerator programs

populations.

Characterize the used unit market and its impact on energy savings.

Produce a comprehensive process evaluation for all three refrigerator programs

A secondary objective of the evaluation was the gathering of representative, local data on which to base

these savings estimates. PSE supported refrigerator metering for a large number of older, existing units as

well as new, replacement units. The results provide a much more clear picture of refrigerator

consumption than has been available for a Pacific Northwest appliance program. In addition, survey data

gathered for this evaluation describe in detail participant and non-participant activities in the new and

used refrigerator markets. These data support savings estimates founded on a solid savings logic

developed for each program.

3.2 Overview of the Report

The report is organized for the consideration of readers interested in the results for only one of the

programs. The three impact sections (Sections 4, 5 and 6) provide standalone discussions of the program

impact estimates for those programs. Those sections have parallel Appendix sections (Sections A, B and

C) that go further into detail and provide the net savings logic and calculations. The data used for all

three evaluations are introduced in the Data Collection section, Section 3. Process evaluation results are

presented in Section 7 and Appendices D and E.


KEMA, Inc. May 14, 2013 4-1

4. Data Collection

There is substantial overlap in the data required for the three different program evaluations performed

here. The purpose in combining the three evaluations was to leverage similarities across the data

acquisition process to bring efficiencies and improvements to each individual evaluation. This section

has two goals:

Summarize the data sources that were used for the three program evaluations.

Summarize the similarities and differences across programs, and how they affect the evaluation.

The first goal provides a summary of data sources that supports the subsequent separate impact sections.

The second goal deals with cross-program implications that are in part impact methodology specific but,

by necessity, come before the separate evaluation sections have explained those methodologies. We will

refer to these issues in a high level manner and reference the sections that will provide the larger context

necessary for full understanding.

For the purposes of our analysis, we required the following data:

Program population information on UECs

(existing, standard efficiency, market baseline and program qualifying units):

─ age

─ configuration

─ volume

─ defrost type

─ amps

─ label UEC

─ model number (for matching to CEC database)

─ estimated useful life/remaining useful life

participant behavior

─ free ridership and acceleration behavior

─ share of year participants kept units in use

─ counterfactual disposition of unit

non-participant behavior

─ share of disposers that transferred unit to second-hand market

─ counterfactual purchase decisions of second-hand unit acquirers

2012 unit meter data for the replacement program units

The sections below describe the sources and disposition of those data listed above.


KEMA, Inc. May 14, 2013 4-2

4.1 Program Tracking Data

The program evaluations were not organized around particular program years. Rather, we worked with

the best and/or most current tracking data available so as to make the results as relevant as possible going

forward for each program.

This section describes the disposition of the tracking data, focusing on the characteristics relevant to our

analysis. Table 4-1 summarizes the date ranges and counts from the tracking data used for the evaluation.

The decommissioning program data from 2012 was used as produced by the new program implementer,

JACO. The rebate program data changed composition in 2012 and provided less data useful for the

program evaluation. As a result we based our evaluation on tracking data from 2011. The evaluation

metered units from the replacement program through 2012. We used the tracking data for this period as

the replacement program population data.

Table 4-1: Number of Units in Tracking Database

Program Dates of Observations

Existing

Units/Program

Qualifying Units

Number of Unit level

observations

Decommissioning January 2012-October

2012 N/A 4,615

Rebate

April 2011-November

2011 Existing Units 540

February 2011-January

2012

Program Qualifying

Units-Tier 2 403

Program Qualifying

Units-Tier 3 1,176

Replacement December 2011-

September 2012

Existing Units 1,890

Program Qualifying

Units 1,890

The tracking data‘s coverage of the required information varied widely within and between program level

data. For example, in the tracking data for the decommissioning program, there was complete coverage of

all the key variables. However, for the rebate program, the only unit level data available was the model

number. Table 4-2 summarizes the data available from each of the refrigerator program tracking

databases that could be used for the evaluation. Particularly for existing units, it is optimal to have both

model numbers and configuration data.


KEMA, Inc. May 14, 2013 4-3

Table 4-2: Variables Used in Analysis That Were in the Tracking Data

Program

Unit/Existing

Unit Characteristic

Decommissioning

Program Rebate Program

Replacement

Program

Existing

Age X X

Configuration X X

Size X X

Defrost Type X X

Amps X X

Model Number X X

Program

Age

Configuration

Size

Defrost Type

Amps

Model Number X X

The full range of data (both model numbers and characteristics) is important to support UEC estimates

that reflect the full program population. We use a matching process based on tracking data model

numbers to get a preliminary (label) estimate of UEC. That matching process is generally not complete

for older units. The additional configuration data makes it possible to extrapolate from the matched subset

to the full population on a more informed basis.

4.2 California Energy Commission Label UEC Database

This evaluation bases UEC estimates on a combination of in situ metering and manufacturer-provided

―label‖ UECs. In situ (in the household) metering is challenging and expensive so it is performed on a

small subset of units. Label UECs, which provide estimated unit consumption when the unit was new,

are available for most units. In combination, the two measures of UEC provide estimates of UEC in the

home that reflect the whole population of units.

Label UEC refers to the annual consumption estimate that all refrigerators are assigned when they are

manufactured. These UECs are based on Department of Energy laboratory metering protocols and offer a

consistent way to compare energy consumption across new units. The California Energy Commission has


KEMA, Inc. May 14, 2013 4-4

collected these label UECs for units manufactured as long ago as the 1970s1. This dataset is commonly

used to look up label UECs. These ―as new‖ UECs take into account the major sources of variation

among units related to size, configuration and manufacturer. As a result, the average label UEC for the

whole program population contains important information on the consumption of the units for which a

label unit is located.

4.3 In situ Metering Data

DNV KEMA subcontracted with SBW to conduct in situ metering of a subsample of Refrigerator

Replacement Program participants. The in situ metering consisted of collecting a minimum of two weeks

of interval data on the existing unit that was going to be removed by the program and an additional two

weeks of interval data on the unit that was provided by the program. The metering scenario was

particularly informative because the units were metered in place in the house and in sequence. This

guaranteed that both the pre- and post-replacement period meter data reflected the same typical usage

characteristics at the house.

The annualized in situ meter data were used, in combination with their respective label UEC, to produce a

label to in situ UEC adjustment. The label UEC matching process produces an average UEC for each

program and unit type that is as closely matched to the full program population of units as possible. The

in situ adjustment then accounts for the average effects of household-specific usage characteristics and

age-related degradation relative to the label UEC. Using the adjustment based on replacement program in

situ metering for other program UEC estimates does assume that the household and degradation effects on

those primary units are sufficiently representative of the household and degradation effects on the units

from other programs.

The replacement program units should provide a good indication of unit degradation for the older units

recycled through the decommissioning program. The age distribution is slightly different than the

decommissioning program, but since all replacement program units are at least 20 years old, they should

provide informative degradation trends. The household characteristics will likely be somewhat different

across the two populations. The secondary units collected by the decommissioning program may be used

less and are likely not in the kitchen. In a hot climate where air conditioning is widespread, the location

difference could cause substantial differences in consumption. In PSE territory, the climate is mild and

air conditioning is neither widely adopted nor extensively used. In these populations and in this

geography, household related differences appear to be mixed and small compared to degradation which

only increases consumption and could so substantially.

1 http://www.appliances.energy.ca.gov/AdvancedSearch.aspx

http://www.appliances.energy.ca.gov/AdvancedSearch.aspx


KEMA, Inc. May 14, 2013 4-5

The evaluations also use a new unit in situ adjustment based on the new replacement unit in situ metering.

The label UECs are based on new units functioning under specific laboratory conditions. In this case, we

assume that the ratio of in situ to label UEC for replacement program units is informative for units from

the rebate program. That ratio should account for household-specific usage characteristics. We expect the

Label UEC to account for the substantial difference in the basic consumption distribution of the two

populations

These concerns, while important to consider and discuss, are secondary to the great advantages of having

done in situ metering at all. Many refrigerator evaluations do not perform any in situ metering of any

sort. As a result, they rely on arbitrary degradation rates to make label UECs applicable to older units.

New units are assigned label UECs despite the disconnect between laboratory conditions and on-site

conditions. The replacement program units offer the unique opportunity to meter new and used units that

have not been moved and are in typical use. In the absence of doing sufficient numbers of program

specific metering for all programs, the in situ adjustments based on the replacement program units

provide a useful adjustment for other program UECs.

4.3.1 In situ Meter Data Collection

Participants were recruited from a pool of qualified customers. Metering participants signed commitment

letters and SBW then visited participating households and collected information. SBW employees did the

following while at a participant‘s home:

1. Installed a logger on the existing refrigerator,

2. Tested and collected relevant data on the existing unit, such as refrigerator and freezer

temperature,

3. Interviewed customers, with a focus on collecting demographic and structural information.

Approximately four weeks after meter installation, SBW contacted each customer to schedule meter

removal and returned to the participant‘s home. During the second home visit, the SBW employee

recorded refrigerator and freezer temperatures were recorded, and removed the data logger. PSE

customers were awarded a VISA check card for their participation during this visit. For a complete

description of the meter data collection process, see Appendix A.2.

Table 4-3 below summarizes the disposition of the recruited participants in metering:


KEMA, Inc. May 14, 2013 4-6

Table 4-3: Disposition of Replacement Program Metered Units Data

Category Number

Recruited 179

Meters Installed 90

Logger data

submitted for

analysis

88

Remained after

inspection 83

4.4 Weather Data

Weather data was used to calculate HVAC interaction effects. Increasing the efficiency of, or removing,

a refrigerator from the conditioned part of a house will tend to increase the need for space heat and

decrease the need for cooling. In order to determine the share of days that required heating and cooling,

we required temperature data for the PSE service territory. These were provided by PSE and consisted of

hourly average temperature values for 2002 to 2012 from 10 localities in PSE‘s jurisdiction, as well as a

system-wide average.

4.5 Standard Efficiency Data

To determine the unit energy consumption of standard efficiency unit, we used the publicly available

database of ENERGY STAR qualifying units available from the ENERGY STAR Program 2. This

database contains information on the size, configuration, date of qualification, and model number for over

2,900 ENERGY STAR qualifying units.

4.6 Expected Useful Life/Remaining Useful Life

Measure life is essential to calculating lifetime savings for a measure. This evaluation was not tasked with

establishing new estimates of measure life. On the other hand, our savings calculations required estimates

of the remaining useful life for used units. This depends on the age of the unit which is dependent on the

program population. Regional technical forum (RTF) saving documentation provides an estimate of RUL

2 http://www.energystar.gov/index.cfm?fuseaction=find_a_product.showProductGroup&pgw_code=RF

http://www.energystar.gov/index.cfm?fuseaction=find_a_product.showProductGroup&pgw_code=RF


KEMA, Inc. May 14, 2013 4-7

as a function of age.3 To determine measure lives for the three programs, we used this look-up table

weighted to the specific population distribution.

4.7 Survey Data

DNV KEMA also surveyed PSE customers from all three programs as part of this program evaluation.

Participant surveys were primarily used to determine how the program affected their refrigerator-related

activities. This includes understanding what would have happened to a unit that was recycled if the

program has not been available. Survey responses also provided the basis for acceleration and free-

ridership calculations.

We also surveyed customers who did not opt to participate in the PSE Refrigerator programs, despite

changing out a refrigerator unit while the programming was available. Among other things, this survey

established how households dispose of refrigerators in general. It also looked at how people who bought

units on the used unit market would respond to market changes. This section briefly summarizes our

surveying methodology.

4.7.1 Participant Survey

PSE provided DNV KEMA with a population of its 2011 Refrigerator program participants. DNV KEMA

contracted with Discovery Research Group (DRG) to conduct computer-aided telephone interviews

(CATI) with a sample of program participants. Telephone numbers were not available from the PSE

tracking data, so DRG provided a telephone lookup for all program participants. DRG ultimately released

a total sample size of 1,739 participant customer records for surveying.

Our evaluation targeted 450 completed surveys with program participants of the refrigerator programs.

DRG completed 150 surveys with PSE rebate and replacement refrigerator program participants,

respectively. DRG additionally completed one-hundred fifty-two surveys among decommissioning

program participants. DRG completed all surveys with program participants in February and March,

2012, and had a final response rate of 28 percent. Table 4-4 below highlights the final participant survey

dispositions.

3 RTF FrigRecycle_FY10v2_3.Decision.6.2010..xls at rtf.nwcouncil.org


KEMA, Inc. May 14, 2013 4-8

Table 4-4: PSE Refrigerator Programs: Participant CATI Dispositions

Sample Description Number %

Sample Used (released) 1,739 N/A

Known Not Eligible 63 N/A

Estimated additional not eligible 33 N/A

Sample - Valid 1,643 N/A

Complete 452 28%

Refused 157 10%

Ineligible 35 2%

Not Completed - Eligible (terminated mid-

interview) 36 2%

Not Completed - Eligible, but over quota --

Not Completed - Estimated Eligible* 963 58%

*Indicates the number of households dialed but not reached (participant did not answer, DRG got

an answering machine or voice mail, etc) that were expected to be eligible.

4.7.2 Non-Participant Survey Data

PSE provided DNV KEMA with a population of its residential, non-participant customer records as of

July 2012 to use with its non-participant survey. Screener questions within the non-participant survey

instrument did not exclude a customer based on home ownership status – our non-participants could

either rent or own their homes. However, they qualified to take our survey only if they owned their

appliances. Further, customers were required to receive their get electric service from PSE in order to

qualify for the survey, either by being electric-only customers, or by receiving both gas and electricity

from PSE. Gas-only customers were not surveyed on the PSE Refrigerator programs. DNV KEMA again

worked with DRG to conduct computer-aided telephone interviews (CATI) of these non-participants.

DRG provided a telephone lookup for all sample records and released sample as needed to achieve our

completed surveying target.

The evaluation called for 400 total completed non-participant interviews. Our target was to survey 200

used refrigerator acquirers, and 200 customers who had disposed of a refrigerator unit in the past two

years. DRG surpassed those segment targets, completing interviews with 404 total non-participants in

August 2012. Table 4-5 highlights the non-participant survey dispositions.


KEMA, Inc. May 14, 2013 4-9

Table 4-5: PSE Refrigerator Survey: Non-Participant CATI Dispositions

Sample Description Number %

Sample Used (released) 12,000 N/A

Known Not Eligible 454 N/A

Estimated additional not eligible 1,359 N/A

Sample - Valid 10,187 N/A

Complete 404 4%

Refused 4,796 47%

Ineligible 1,847 18%

Not Completed - Eligible 44 0%

Not Completed - Eligible, but over quota 129 1%

Not Completed - Estimated Eligible* 2,967 29%

*Indicates the number of households dialed but not reached (participant did not answer,

DRG got an answering machine or voice mail, etc) that were expected to be eligible.


KEMA, Inc. May 14, 2013 5-1

5. Replacement Program Impacts

The PSE Refrigerator Replacement Program identifies older primary refrigerators (manufactured prior

to1993) in low income, rural and/or non-English speaking households and replaces them with a new,

ENERGYSTAR refrigerator. The primary driver of program gross savings is the difference in the

consumption levels of the existing unit, that would otherwise be expected to remain in the household, and

the new energy efficient replacement unit.

A core piece of this evaluation is the estimation of the average consumption levels for the existing and

replacement units for the program population. This evaluation uses in situ metering to establish these

consumption levels.

The fully developed savings logic requires additional considerations. Measure lives for both the existing

and replacement units are relevant. We also calculate net savings and this require further information on

free-ridership which comes from survey responses.

This section discusses the methodology and derivation of these savings estimates. The section is

organized as follows:

Program Description

Saving Logic

Required Data

Savings Calculations

5.1 Replacement Program Description

In June, 2011 PSE launched a program designed to replace old, primary refrigerators with new energy

efficient refrigerators. Prior to this, PSE only offered refrigerator replacement through the Low-Income

Weatherization Program. The replacement program expanded refrigerator replacement offerings to homes

not served by the current Low-Income Weatherization Program.

The Replacement Program does not have an income qualification requirement, but does target limited

income, rural, and non-English-speaking customers. Because of its targeted marketing, PSE does not

market this program through traditional communication channels; for example, program details do not

appear on the PSE website. PSE mails letters to limited customers inviting their participation; they also

distribute flyers through state agencies, non-profits (such as Goodwill), and other organizations or

businesses that may have contact with their target population. PSE staff confirmed in our interviews with


KEMA, Inc. May 14, 2013 5-2

them that the very limited marketing of this program results in questions about the program legitimacy

from PSE customers.

The Replacement refrigerator is offered to the customer at no cost. It is a basic unit (white, top freezer,

no ice maker, etc.) similar in size to the one replaced. To qualify for the program, the refrigerator to be

replaced must be:

Manufactured before 1993

In working/cooling condition and regularly used

For primary food storage in the kitchen

The kitchen outlet in which the customer‘s refrigerator is plugged must be properly grounded

(three-prong) to ensure safety

Customers schedule their replacement program appointment through the Appliance Recycling Centers of

America (ARCA). ARCA visits the participant‘s home to assure their unit qualifies for the program, and

collects basic unit information upon inspecting the current refrigerator. ARCA then schedules a return

visit to the home at a later date to pick up the existing unit, and replace it with a new, energy efficient

model.

5.2 Replacement Program Savings Logic

The goal of the replacement program is to replace refrigerators that would not otherwise be replaced at

that time. In this basic scenario, the immediate program gross savings are the difference between the

consumption of the existing unit and the efficient program unit. These initial savings reflect the existing-

to-program-efficiency differential that occurs until the existing unit would have reached the end of its

remaining useful life. The replacement unit is expected to remain in place for its whole measure life and

should produce savings at a lower level for the remaining years.

Figure 5-1 illustrates the gross savings scenario for the replacement program. The figure plots refrigerator

consumption (y-axis) over time (x-axis). Over the measure life of the replacement unit, the replacement

program will generate savings at two different levels. The replacement program unit (EULprog) reduces

consumption from the existing unit level to the program unit level for the measure life of the existing unit

(EULexist). After the existing unit would have stopped working ( ), the program unit may continue

to produce savings relative to the unit that would have replaced the existing unit. Because of the

difficulty of knowing what would happen after the existing unit measure life, including the likelihood of


KEMA, Inc. May 14, 2013 5-3

the purchase of used units, the consumption level of those units at that time, etc., the long term baseline

defaults to standard efficiency.4

Figure 5-1: Replacement Program Gross Savings Diagram

For the gross savings calculation,

Consumption levels are base on in situ metering.

EULs use measure life estimates based on the RTF lookup table, weighted to reflect the program

population 5.3.2).

The average per unit, life-time gross savings ( ) can be expressed as follows:

4 Themaximum possible savings would occur if all existing units were replaced with used unit constructed after

1992. In reality, the savings will fall somewhere between the reported savings and the possible savings depending

on the percentage of used units that would have been purchased and the average consumption of those units.

EULP

UECProg

UECstan

UECExist

kWh

Years

Saving from existing to program UEC for life of existing unit (EULE).

Savings from standard to program UEC for the rest of the measure life of the program unit (EULE - EULP).

EULE


KEMA, Inc. May 14, 2013 5-4

where

GSReplaced = Gross saving for replacement units

UECStand = Standard efficiency UEC

UECProg = Efficient program unit UEC

UECExist = Existing unit UEC

EULProg = Estimated useful life for the program unit

EULExist = Estimated useful life for the existing unit

HA = HVAC interaction adjustment

All components are discussed in the Figure 5-1 above except for HA. HA is a general HVAC interaction

adjustment that scales the savings to account for electric heating and cooling interaction. It is discussed in

section 5.3.3

This equation re-organizes the savings into standard-to-program savings for the program unit EUL and

existing-to-standard savings for the existing unit EUL. Multi-level savings can be difficult to characterize

in traditional program savings terms: First year savings with a measure life. The equation expresses

savings as two different first year savings with different measure lives.

For the replacement program, free-ridership affects the early replacement and efficiency portions of the

savings differently. When a replacement program participant indicates they would have purchased a new

unit in the absence of the program the high savings due to the standard-to-existing unit savings is reduced

regardless of the efficiency level of the unit they would have purchased. This is free-ridership with

regards to the replacement aspect of the program. We refer to this as anti-acceleration because it is

structurally the opposite of the typical acceleration which is captured in the rebate program net savings

calculation. In addition there is the possibility that the unit would have been ENERGYSTAR. This

represents free ridership with respect to the energy efficiency aspect of the program. This lowers the

savings by lowering the standard efficiency baseline for the lifetime of the new unit.

The derivation of both net and gross equations are discussed further in appendix A.1

5.3 Replacement Program Savings Calculation Inputs

5.3.1 UECs

The replacement program refrigerators provided a unique opportunity to meter the consumption of new

and old units in the same household. Participants were randomly recruited for the metering effort as they

joined the program. Recruitment lasted for just over a year. Engineers installed meters on the existing


KEMA, Inc. May 14, 2013 5-5

unit for at least two weeks. Then the replacement was installed and the same meter was installed for an

additional two weeks to measure consumption on the program replacement unit.

Savings calculations for the replacement program use the sample-based estimate of UEC directly from the

in situ metering. For the program replacement units, an additional step was possible to map the sample

estimate more closely with the program population. The additional step uses a ratio estimator approach

that takes advantage of informative data available for the program population to extrapolate sample

results to that population. The replacement unit model numbers are recorded in the replacement program

tracking data. This facilitates using a ratio approach between in situ UEC and the as-new UEC provided

on the refrigerator label. The steps of the process are as follows:

Estimate an average program ―label‖ UEC. Using model numbers from the program tracking

data, we look up label UECs for PSE program replacement unit population in the CEC label

dataset (section 4.2). This provides an average label UEC that appropriately accounts for the

variability across program units. For the replacement program, there is a limited range of new

units available (primarily different sizes), but this approach captures that variability.

Estimate an in situ ratio adjustment. The two other major sources of variation in refrigerator

consumption are age (or degradation) and household-specific usage characteristics. The sample-

based refrigerator metering performed for this evaluation allowed us to develop adjustments that

account for the difference between label UEC and in situ UEC for new and used units. The

adjustment is the ratio of in situ UECs and the label UECs.5 We developed separate ratios for

new and existing units as the effects of aging were hypothesized to affect the existing unit ratios.

Apply in situ ratio adjustment to label UEC estimate for the program population. This puts

the population-level estimate of label UEC back on an in situ basis. This provides the final in situ

UEC estimate for the evaluation. The adjustment factor estimated from the metered sample of

replacement participants is applied to the program-level label UECs for the rebate and

decommissioning.

Final estimates for the replacement program UECs are provided in Table 5-1

5 We first attempted to estimate the relationship between in situ ratio and unit age. There was not a statistically

significant relationship. Instead, we calculated the ratios for new and existing units. The ratio estimator approach is

the sum of in situ UECs divided by the sum of the label UECs. This is slightly different than calculating an average

of the individual ratios. The ratio estimator approach is weighted by the kWh.


KEMA, Inc. May 14, 2013 5-6

Table 5-1: Replacement Program UECs

Existing Unit/Program

Qualifying Unit

In situ Ratio

Adjusted UEC

90% Confidence

Interval

Program Qualifying 347 [310, 383]

Existing 1,160 [1058, 1262]

An extensive discussion of the process of estimating these UECs can be found in sections 7.4.1A.3

through A.5 below.

5.3.2 Estimated Useful Life/Remaining Useful Life Determination

An important part of the replacement program savings depends on the how long the existing unit would

have stayed in house if the program had not replaced it. Estimating empirical unit measure lives and

existing unit remaining useful lives was outside the scope of this evaluation. Our goal in establishing the

measure lives for this evaluation was to be consistent with existing RTF methodology, while reflecting

actual program population characteristics.6 To obtain program-level estimates of the remaining useful life

(RUL) of existing units, we mapped the EUL/RUL estimates provided by RTF to the tracking data,

obtaining an age-weighted average of RUL for each program. We used the standard PSE 20 year

estimated useful life (EUL) for new program qualifying units.

Table 5-2 below lists the measure life and remaining useful life results for the existing units of

replacement program participants. The existing unit RUL was calculated based on the age distribution of

the metered sub-sample because there was no existing unit age information in the replacement program

tracking data.

Table 5-2: Remaining Useful Life/Program Unit Measure Life: Replacement Program

Unit Type Life

Existing Units 9.9

Program Qualifying Units 20

6 RTF FrigRecycle_FY10v2_3.Decision.6.2010..xls : measure life


KEMA, Inc. May 14, 2013 5-7

5.3.3 HVAC Interaction Effect

Refrigerator energy consumption is transformed into waste heat. That waste heat contributes to ongoing

internal heat gains in the house if a refrigerator is inside the house thermal envelope. These internal heat

gains determine at what point the house‘s heating (and cooling) system must turn on to maintain the

thermostat setpoint. A reduction in refrigerator electricity consumption and the associated waste heat will

cause the heating system to activate at a higher outdoor temperature to make up for the lost waste heat.

The HVAC interaction effect for heating is calculated by combining the percent of the year the heating

system is active, the percent of households that are heated primarily with electric heat, and the percentage

of the removed or replaced refrigerators located inside the households‘ thermal envelope. The heat

interaction factor accounts for this effect in an aggregate manner, scaling average savings down to

account for the average heat interaction effect.

The HVAC effect works in the opposite direction in the summer. Air conditioning will not have to

counteract the lost waste heat and thus will come on at a higher outdoor temperature, lowering cooling

consumption. This beneficial cooling interactive effect is small in the Northwest where the percentage of

cooling days and the percentage of households with air conditioning are both very small.

A high proportion of replacement program units are in electrically heated space (73%). The portion of the

year when houses are in heating mode is also high (74%).7 These two factors combine to lower savings

by approximately 50%. The countervailing increase on the cooling side is comparatively small. Only

13% of the units are in areas with cooling and cooling only happen on approximately 10 days a year. The

combined HVAC interaction factor for this program is 47%, meaning the program gets credit for less than

half of the

5.4 Replacement Program Savings Estimates

Figure 5-2 provides the calculation of lifetime gross saving equation. It shows the combination of UEC

estimates, measure lives and HVAC interaction factor the replacement program gross savings.

7 This is the percentage of days when average daily outdoor temperature is at 60°F. or lower. The average setpoint

temperature is informed by extensive billing analysis work done for PSE.


KEMA, Inc. May 14, 2013 5-8

Figure 5-2: Replacement Program Gross Savings Calculation

The savings calculation above produces the savings estimates summarized in Figure 5-3 and Table 5-3.

The figure clearly illustrates the two-tiered nature of the lifetime savings for the replacement program.

Figure 5-3: Replacement Program Lifetime Savings

UEC For Existing

Unit-

UEC For Standard

Efficiency New UnitX

Heating Interaction

Factor=

Gross Unit

Savings

(Year 1-10)

1136 347 0.472 372.55

UEC For Standard

Efficiency New Unit-

UEC For Program

Qualifying New UnitX

Heating Interaction

Factor=

Gross Unit

Savings

(Year 11-20)

464 347 0.472 55.51

0

100

200

300

400

500

600

700

800

900

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

An

nu

al

Sa

vin

gs

(kW

h)

Measure Life Year

PSE Claimed

Savings

Gross Savings

Net Savings


KEMA, Inc. May 14, 2013 5-9

Table 5-3 provides the tabular results that underlie Table 5-3 above. The higher level savings are in place

for the first ten years, while the lower level saving last for the remaining ten years.

Table 5-3: Lifetime Savings, Replacement Program

Measure Life

Years

Annual Gross

Savings Annual Net Savings

1-10 372.6 337.3

11-20 55.5 36.1

5.4.1 Replacement Program Results Compared to Claimed Savings

PSE‘s claimed savings for the replacement program are said to be based on RTF savings calculations but

this cannot be verified. Table 5-4 compares PSE‘s savings and measure life with the results from this

evaluation. The HVAC interaction is from the standard RTF refrigerator standards.

Table 5-4: Comparison to Claimed Savings: Replacement Program

Result

PSE Claimed

Savings Evaluated Gross Savings

Savings per year 775 kWh 373 kWh (years 1-10)

56 kWh (years 11-20)

Measure Life

(Years) 15 years

10 years

(Existing Unit RUL)

20 years (Program

Qualifying Unit RUL)

HVAC Interaction

Adjustment 0.86 0.47

The lifetime realization rate is 37%. The low realization rate is explained by two factors. The HVAC

interaction adjustment of 0.47 is much lower than the standard RTF HVAC interaction assumption of

0.86 percent. The evaluated savings incorporates an HVAC interaction effect that reflects the high

percentage of the replacement program homes with electric heat. The more extreme HVAC interaction

effect explains almost half of the reduction in savings relative to the RTF estimate.

The reduction in savings is also likely explained by a different existing unit baseline. The RTF savings

documentation is unclear as to the basis for the RTF savings estimate. However, the RTF refrigerator

recycling documentation includes an estimate of a degraded, used refrigerator UEC of 1446 kWh. A

baseline UEC of this magnitude would explain the higher RTF replacement program savings estimate.


KEMA, Inc. May 14, 2013 5-10

The baseline of UEC of 1136 we used for this program was based on in situ metering of units from this

program. This different baseline would explain most of the remaining difference in the savings estimates.

Finally, the two-part, life-cycle savings approach used for this evaluation also produces a lower the

savings estimate. This approach means the program is only credited the full existing-to-program unit

savings for the 10 year remaining useful life of the existing unit. The additional savings in the second ten

years are only the presumed difference between the program unit and a standard efficiency unit. The RTF

savings, with a measure life of 15 years, award existing-to-standard efficiency savings for this longer

measure life.


KEMA, Inc. May 14, 2013 6-1

6. Rebate Program Impacts

6.1 Rebate Program Description

PSE launched this program in 2011 designed to provide a mail-in rebate to customers who replace their

primary refrigerator. The program offers a $75 incentive from PSE to purchase a Tier 2 or Tier 3

ENERGY STAR refrigeration unit. In addition to the PSE rebate, customers are expected to obtain

additional rebates through the refrigerator manufacturer and a discount from the retail provider. In order

to obtain a rebate, customers are required to apply for the mail-in rebate. At one point, the program

required proof that the existing unit had been recycled. This requirement was removed.

6.2 Rebate Program Savings Logic

The refrigerator rebate program is designed to motivate households purchasing a new refrigerator to

purchase an energy efficient refrigerator. The rebate program is designed as a point of sale promotion and

targets customers who are already in the market for a new refrigerator. For this scenario, program gross

savings are measured relative to a unit that would have been purchased without the program rebate -- the

market baseline UEC. The market baseline accounts for the percentage of energy efficient unit saturation

in the market place. We use a recent national saturation number that indicates thatENERGYSTAR units

represent 56%.8

Figure 6-1 below illustrates the gross savings scenario for the rebate program. The figure plots

refrigerator consumption (y-axis) over time (x-axis). Over the measure life of the rebate unit, the program

will generate gross savings at a single level as indicated by the shaded box.

8ENERGY STAR® Unit Shipment and Market Penetration Report Calendar Year 2011 Summary.

https://www.energystar.gov/ia/.../2011_USD_Summary_Report.pdf


KEMA, Inc. May 14, 2013 6-2

Figure 6-1: Rebate Program Gross Savings Diagram

The program unit (UECProg) reduces consumption in the house relative to the market baseline unit

consumption (UECMark) that would have been in the house for the full measure life of the program unit

( ) – the shaded, lower rectangle. For the rebate program gross savings, this would be the only

savings. The upper rectangle is not shaded because the rebate program gross saving logic assumes that the

existing unit would not have stayed in place in the absence of the program.

The average per unit, life-time gross savings calculation for the rebate program is

where

GSRebate = Gross saving for rebate program units

UECMark = Market efficiency UEC







KEMA, Inc. May 14, 2013 6-3

the term HA refers to the HVAC interaction adjustment factor. The population-specific adjustment

reflects the percentage of households with electric heat.

Net savings, for rebate program units, are somewhat more complicated. Despite the fact that the rebate is

a point of purchase rebate, some participants indicate that they may not have purchased a unit at all

without it. This increases saving because the existing unit would be the baseline for the savings

calculation until it was replaced. On the other hand, a higher percentage of program participants than the

market baseline percentage indicate that they would have purchased ENERGYSTAR in the absence of the

program. This effectively lowers the market baseline still lower. A discussion of the net savings logic

and calculation can be found in section

6.3 Overview of Estimation Approach

The rebate estimation approach uses an in situ estimate of the average program unit UEC. This UEC

accounts for the range of units purchased with a program rebate and applies the in situ adjustment for new

units that was developed based on new replacement program units.

A standard efficiency UEC is calculated by removing the ENERGYSTAR efficiency savings for

individual units based on whether they were tier 2 or tier 3. In aggregate, this produces an average

standard baseline UEC for the program population. The market baseline is a weighted average of the

standard and ENERGYSTAR UECs based on the average saturation of ENERGYSTAR units in the US.

The standard PSE refrigerator measure life of 20 years is assigned. The HVAC interaction adjustment is

calculated based on rebate program parameters and applied to the savings estimate.

Net savings details are found in Section B.6 .

6.4 Rebate Program Savings Calculation Inputs

6.4.1 UECs

The model numbers in the rebate program tracking database make it possible to develop a program

specific estimate of label UEC. This UEC estimate is adjusted by the replacement program in situ

adjustment so that it reflects realistic household conditions rather than the laboratory metering

environment. The adjustment indicates that new units use approximately 2% more energy in the

household than is indicated by the label. This increases both the baseline and program UECs, slightly

increasing the savings estimates. Table 6-1 provides the adjusted new UEC estimates.


KEMA, Inc. May 14, 2013 6-4

Table 6-1: Rebate Program UECs, Program Units

Program Qualifying Unit

In situ Ratio

Adjusted UEC

90% Confidence

Interval

Tier 2 513 [458, 567]

Tier 3 380 [339, 421]

The market baseline UEC is a weighted average between the standard efficiency UEC and the

ENERGYSTAR UEC using that national penetration rate of ENERGYSTAR units of 56%. Table 6-2

provides the final estimated market baseline UECs for the two tiers for the rebate program savings

calculation.

Table 6-2: Rebate Program UECs, Market Baseline Units


In situ Ratio

Adjusted UEC

90% Confidence

Interval

Tier 2 590 [529, 651]

Tier 3 457 [409, 504]

6.4.2 Estimated Useful Life / Remaining Useful Life Determination

The rebate program uses the standard PSE measure life of 20 years for program qualifying unit. The

acceleration portion of the net savings calculation requires an existing unit remaining useful life. The

general approach is described in section 5.3.2 above. Table 6-3 lists the remaining useful life results for

existing units for the rebate program. Remaining useful life was calculated using the age distribution of

matched existing units because unit age was not available in the tracking data.

Table 6-3: Remaining Useful Life/Program Unit Measure Life: Rebate Program

Existing Units/Program Qualifying Units Years

Remaining Useful Life for Existing Units 14.3

Program Unit Measure Life 20

6.4.3 HVAC Interaction Effect

We calculate a program specific HVAC interaction effect for the rebate program. The general approach

for calculating the HVAC interaction adjustment is described in section 5.3.3 above. The adjustment for


KEMA, Inc. May 14, 2013 6-5

the rebate program UECs is only 87%. This adjustment is a less extreme adjustment than the replacement

program adjustment because a smaller percentage of rebate program households heat with electric.

6.5 Rebate Program Savings Estimates

Figure 6-2 provides the gross savings calculation or the rebate program tier 2 and tier 3 units.

Figure 6-2: Rebate Program Gross Savings Calculations

Figure 6-3 and Figure 6-4 summarize the gross and net savings results in comparison to PSE claimed

savings. The bi-level net savings estimate is discussed in Section AppendixB.6.

UEC For Market

Efficiency New

Unit-

UEC For Program

Qualifying New

Unit

X XHeating

Interaction Factor

Gross Unit

Savings Tier 2

(Years 1-20)

590 513 0.87 67.15

UEC For Market

Efficiency New

Unit-

UEC For Program

Qualifying New

Unit

X XHeating

Interaction Factor

Gross Unit

Savings Tier 3

(Years 1-20)

457 380 0.87 66.55


KEMA, Inc. May 14, 2013 6-6

Figure 6-3: Rebate Program Lifetime Savings for Tier 2 Units

Figure 6-4: Rebate Program Lifetime Savings for Tier 3 Units

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

An

nu

al

Sa

vin

gs

(kW

h)

Measure Life Year

Gross Savings

PSE Claimed Savings

Net Savings

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

An

nu

al

Sa

vin

gs

(kW

h)

Measure Life Year

Gross Savings

PSE Claimed Savings

Net Savings


KEMA, Inc. May 14, 2013 6-7

Table 6-4 provides the tabular results that underlie the two figures above. Gross savings are constant at

just over 67 kWh for both tiers for the 20 year measure life. Net savings are two-tiered.

Table 6-4: Lifetime Savings for Tier 2 and Tier 3 Rebate Programs

Tier

Measure Life

Years

Annual Gross

Savings

Annual Net

Savings

Tier 2 1-14

67.1 49.5

15-20 15.4

Tier 3 1-14

66.5 66.4

15-20 15.3

Across all twenty years of the program unit measure life, free-ridership lowers both Tier savings levels to

just over 15 kWh per year. However, some participants say that they would not have purchased the new

unit at all without the rebate and, as a result, the acceleration factor produces additional net savings for the

14 years of the remaining useful life of the existing unit.

6.5.1 Replacement Program Results Compared to Claimed Savings

Table 6-5 compares the evaluated gross savings with PSE claimed savings obtained from RTF

documentation. Tier 2 gross savings are almost identical with PSE claimed savings. Tier 3 evaluated

gross savings are almost identical to tier 2 savings and 78% of PSE claimed savings for tier 3 units.

Table 6-5: Comparison to Claimed Savings: Rebate Program

Result

PSE Claimed

Savings

Evaluated Gross

Savings

Tier 2 Annual

Savings (kWh) 65 67.1

Tier 3 Annual

Savings (kWh) 86 66.5

Measure Life

(Years) 20 20

HVAC Interaction

Adjustment 0.86 0.87

The evaluation used the same measure life as that found in the RTF documentation. The evaluation

estimated a program-specific HVAC interaction adjustment and it proved to be almost identical the

assumptions found in the RTF documentation.

The only potential source of difference in the tier 3 savings estimates lies in the program-specific

calculation of UECs. The calculated average consumption of the program tier 3 units is smaller than the

tier 2 units. As a result, the savings are similar magnitude between the two tiers, despite the increased


KEMA, Inc. May 14, 2013 6-8

percentage savings for Tier 3. The RTF savings must have expected Tier 3 units to have consumption

closer to the consumption tier 2 units.


KEMA, Inc. May 14, 2013 7-1

7. Decommissioning Program Impacts

Decommissioning program savings are substantially different from other kinds of energy efficiency

program savings. There are two kinds of savings and neither is derived from increasing the efficiency of

program-related units. This section attempts to clearly lay out the savings logic for a decommissioning

program so that the derivation of savings used is transparent.

7.1 Program Description

The Refrigerator Decommissioning Program was originally designed to target secondary refrigeration

units for recycling. The program began also accepting primary units in 2012. Program staff report that

this has lessened customer confusion about what qualifies within the program.

DNV KEMA staff learned that there are three program delivery options within the current program design

during its interviews with program staff. They are:

Direct-to-Consumer: PSE markets the program directly to its customers, and appeal to them to

participate through those marketing messages. When a customer decides to participate, they call

the provided number and schedule a refrigerator pickup. PSE currently contracts with JACO

Environmental, who handles the bulk of the program implementation. JACO fields incoming

customer contact, schedules the appointment, and picks up and handles the refrigerator recycling

for the customers.

Quick Link: PSE has partnered with appliance retailers like Sears or Lowes, and sales staff at

these businesses alert customers about the Decommissioning program option when they are

making a new refrigerator purchase. Sales staff can schedule a home unit pick up directly in the

store during the sales transaction if the customer agrees to participate. This is a new program

element as of 2012.

Retailer Direct: PSE & JACO work with local retailers who accept refrigerators when delivering

a new unit to a home to assure that these units are collected and recycled. This was another

change to the program within 2012.

PSE staff indicates that most of their program participation comes from promoting the program directly to

its customers, and they promote the program through a variety of marketing channels. Staff at PSE report

communicating with their customers about the program through utility bill inserts, their web site

(PSE.COM), PSE‘s ENERGY WISE newsletter, and a modest amount of wider market advertising such

as radio, television, and billboards (i.e. ―ads in the Mariners field‖). Staff also notes that customers often


KEMA, Inc. May 14, 2013 7-2

report hearing about the program through word of mouth. Finally, community events and interaction are

also a priority within PSE‘s program promotion. PSE staff partner with representatives from public

relations firm Coolhour & Cohen (C&C) to work with local retailers and event organizers (i.e., farmers‘

markets, company events, home shows, etc) to increase their presence at these events. Their focus while

attending is to engage and educate PSE customers about energy efficiency options and programs.

Currently, the Program offers a $30 incentive and free removal to decommission the refrigerator. This is a

change compared to prior program years and promotions. PSE had a recent winter promotion within the

program where they offered a $50 incentive; in previous years, the program offered a $35 reward.

7.2 Decommissioning Program Savings Logic

The decommissioning program is primarily designed to motivate the removal of non-primary units, and to

prevent old, primary units from becoming additional units (secondary, tertiary, etc) in the house. The

incentive is provided to motivate the customer to decommission a unit that would otherwise remain

plugged in at the household. Full potential savings would be achieved if, in the absence of the program,

every unit that was decommissioned would have remained plugged in at the household as a secondary

unit. The per unit potential savings is the recycled unit population UEC adjusted as if the unit were in use

as a secondary unit. The UEC is also adjusted with an HVAC interactive effect that accounts for units

being removed from within the conditioned space of houses with electric heat.

The adjusted programmatic savings calculation for the decommissioning program assesses how many

units actually fit the description of a decommissioned unit in the program savings logic. The savings logic

specifically applies to units that have been additional and non-primary in the household prior to

participation in the program. Since this program accepts recent primary units that have just been displaced

by a new primary unit, the savings logic is extended to include any of those displaced units that would

have been kept at the household in the absence of the program9. In this case, the program is avoiding the

retention of the decommissioned unit‘s consumption on the system as a newly additional secondary unit.

We refer to both of these scenarios as direct savings. In each case, the program has caused the removal of

the consumption of the decommissioned unit, as a secondary unit, from the system.10

9 We refer to this additional unit as a secondary unit but it could be a tertiary unit or more. The import change is that

the household could increase its number of refrigerators. Adding a second unit is the most common scenario for

adding an additional unit at a household. In this scenario, the household only had one unit, buys a new primary unit

and the old primary unit becomes a secondary unit. If a household had two refrigerators and ―rotates stock‖ with the

purchase of a new unit by discarding the least desirable unit, there is no additional unit and no potential for savings. 10

To reiterate, it is essential to recognize that decommissioning programs are not designed to motivate the purchase

of the new unit that may make a unit available for decommissioning. There may be consumption reduction due to


KEMA, Inc. May 14, 2013 7-3

Decommissioning programs are also commonly assigned savings through a ―market effects‖ pathway. In

this scenario, the program decommissions a unit that might have otherwise returned to the grid at a

different household after being sold or given away as a used unit. These savings, referred to in this report

as ―would-be transfer‖ savings, occur only if a unit would not have been kept at the house or destroyed in

the absence of the program. The market effect savings quantify the effect on consumption of the removal

of ―would-be transfer‖ units from the used unit market.

If removing refrigerators from the second hand refrigerator market has an effect on that market, it should

have an effect akin to a leftward shift in the supply curve in a traditional supply and demand model. This

shift would tend to lower the number secondhand units sold and raise the price on those units that were

sold. In the face of this, some would-be purchasers of used units might instead purchase new units or

purchase no unit at all. These hypothesized market effects would lower overall system electric

consumption as a result of the actions of the decommissioning program. Alternatively, the used unit

market may be elastic or just too big relative to the program size, limiting the magnitude of the

consumption effect. It is even possible that, in response to lower supply and higher prices, the used unit

market might maintain supply by selling older units for which there would have been little demand

without the program, thus potentially having an increasing effect on overall consumption.

7.3 Overview of Estimation Approach

The estimation of decommissioning program savings has two parts: identifying the average per unit direct

savings for the removal of secondary units and assigning savings to the remaining units that would have

transferred to the used unit market.

Figure 7-1 provides an overview of the first step in the decommissioning program logic. In the absence

of the program, the participant has two options: keep the unit, or discard the unit. The calculation of direct

savings corresponds to the baseline scenario in which the participant would have kept the unit (the left-

hand branch of the figure). The calculation of market effects corresponds to all discarded units that would

have become viable, used units on the used unit market.

the replacement of an old refrigerator with a new refrigerator. That reduction is not related to any savings that

should be claimed by a decommissioning program

On occasion, billing analysis is used for decommissioning analysis. This approach is only valid if it estimates the

average energy consumption of the old units by effectively adding back in the replacement unit consumption into the

estimated pre-post difference in consumption.


KEMA, Inc. May 14, 2013 7-4

Figure 7-1: Decommissioning Program Flowchart, Step One

For those units that would have been discarded but not destroyed, there is the potential for producing

market effect savings. The potential market effect of the ―would-be transfer‖ units falls between zero

savings and full UEC savings for each transferred unit. The only way to produce full savings on the used

unit market is, similar to the direct savings, the avoidance of a secondary unit in a household. That is, if a

used unit acquirer was on the market for an additional unit but did not get one because of the effect of the

decommissioning program. At the opposite extreme, if the used unit acquirer was purchasing a unit for

use as a primary unit, savings could be zero. If the customer is seeking the least expensive form of

refrigeration available, they will be able to locate a used unit despite the decommissioning program, and

there will be no savings produced. 11

11

The effect of removing the decommissioning units from the larger used unit population is difficult to quantify.

Discussions with used unit retailers make it clear that almost all of the units they sell are less than 20 years old. As

over half of the decommissioning program population is over 20 years old, it is less likely they ever would have

been viable used units anyway. There is a further argument that indicates that the average UEC of units on the used

Participant Actions in the Absence of the Program

Keep Equipment

Keep in Use

Direct Savings = UEC

as secondary unit

Keep Unused

Direct Savings = 0, not plugged in

Discard Equipment

Transfer to another Customer (Sell to Dealer, Remove by dealer, Trade in for new

unit, Hire someone to remove, Give to charity, give to neighbor)

Market Effect (savings per

transferred unit)

Destroyed

No Market Effect


KEMA, Inc. May 14, 2013 7-5

Figure 7-2 provides a flowchart of how the market effect is calculated. To simulate the effect of

removing used units on those persons participating in the used unit market, we asked recent used unit

acquirers what they would have done if the specific unit they acquired had not been available. Three

responses were possible -- The acquirer might have purchased a similar unit, substituted a new unit, or

foregone a unit altogether. As the flowchart illustrates, the savings implications are quite different if the

unit was being purchased as a primary or secondary unit.

Figure 7-2: Decommissioning Program Flowchart, Market Effects

Acquirers of used units for use as a primary unit can only produce savings by upgrading the unit they

acquire to a new unit. The savings in that instance will be the difference between a typical used market

unit UEC and a standard efficiency new unit UEC. Those who would have found another used unit

would not have decreased the consumption of the unit they purchased. For those acquirers of a primary

unit who said they would have gone without, the market effect could actually be negative. This would be

the case if the program recycled a unit that would otherwise have been an upgrade in the house to which it

would have been transferred. Instead, we will consider that scenario to be a market effect of zero.

unit market could increase with the removal of decommissioning units. If the used unit dealers select a fixed

number of the best units for re-sale, then limiting the pool from which the market selects can only lower the quality

of the selected units.

Recent Acquirer of Used Unit

Acquired a Used Unit as a Primary Unit

Would Have acquired

similar used unit

Market Effect = 0

Would have acquired new

unit

Market Effect = viable used

primary UEC -New UEC

Would not have acquired

any unit

Market Effect = 0

Acquired a Used Unit as a Secondary Unit

Would Have acquired

similar used unit

Market Effect = 0


unit

Market Effect= viable

secondary used UEC -

New secondary UEC

Would not have acquired

any unit


UEC


KEMA, Inc. May 14, 2013 7-6

When a recent used unit acquirer acquires a unit for use as a secondary unit, there are two paths to

savings. They can upgrade the used unit to a new unit or they can opt to not purchase the unit at all. The

first option produces savings equal to the difference between a used unit and a new unit (as a secondary

unit). Unlike acquirers of primary units, secondary unit acquirers could decide to not get an additional

unit. This choice would avoid the full consumption of a secondary unit in that household. This scenario

would seem most likely to occur with units that changed hands by informal transfers, one option for

acquiring a unit. That is, rather than a neighbor‘s discarded unit going into the garage as a holiday/beer

fridge, it gets recycled.

7.4 Decommissioning Program Savings Calculation Inputs

As indicated by the flowcharts above, the decommissioning program savings estimation requires a

number of inputs.

Average program UEC, viable used unit UEC and typical new unit UEC.

Reduction of number of units at household.

─ Percentage of unit that would have been kept plugged in

─ Part-use factor for secondary unit UECs

Of those units that would not have been kept at the house, the percentage of units that would have

not been destroyed and would have been viable units.

Recent used unit acquirer stated preferences had their unit not been available.

This section provides an overview of those inputs. In addition Appendix has more specific information

on the derivation of these input values.

7.4.1 UECs

Multiple UECs are required for the calculation of decommissioning program savings.

The average decommissioning program unit UEC of 1,012 kWh is the basis for the direct savings

estimate. This UEC is lower than the replacement program existing unit UEC because many

decommissioning program units are lower consumption, post-1992 units. The direct savings are

awarded for the removal of a secondary unit so the UEC is adjusted down with a part-use factor

of 0.9 derived from the participant survey.

The average used unit UEC for the market effects calculation is derived from the same data but

only includes units no older than 20 years of life. Interviews in the used unit market indicated

that there is little demand for units greater than 20 years old. This UEC was 839 kWh.


KEMA, Inc. May 14, 2013 7-7

A standard efficiency new unit UEC is required as a plausible substitution for a used unit. We

use the same UEC as for the standard replacement unit for the replacement program. The UEC

was 464 kWh.

All used UEC estimates were based on the distribution of decommissioning program units. An estimate

of the program label UEC was developed and then adjusted with the in situ adjustment developed for the

replacement program evaluation. Addition explanation for the derivation of UEC estimates is found in

Sections C.1C.4.

7.4.2 Survey Responses

Survey responses provided key information for calculating decommissioning program savings. Program

participants were asked what they would have done without their unit if the program had not provided an

incentive to recycle it. Recent refrigerator discarders were assessed for unit disposal patterns. A sample

of recent used unit acquirers provided the responses necessary to calculate the market effect savings. The

specific results from these survey questions are provided in section C.7.

7.5 Decommissioning Program Savings Estimation

Figure 7-3 adds values to the overall program flowchart. The figure provides the percentage breakouts

for each step of the flowchart as well as the savings per unit that is produced for units in that pathway.

For direct savings, only just over 10% of units would have been kept in the absence of the program. Of

those, only 60% or about 6% of total program units, would have been kept plugged in. The estimate of

the UEC for those secondary units is 908 kWh. This must be adjusted downward to 790 kWh by the

HVAC interaction reflecting the percent of homes with electric heat and the units inside the conditioned

envelope.


KEMA, Inc. May 14, 2013 7-8

Figure 7-3: Decommissioning Program Flowchart with Values, Step One

For the market effects savings calculation, just over 61.0% of units (68% of 90%) had the potential of

producing savings on the used unit market. The used unit market savings were 166 kWh per unit.

Figure 7-4 provides further detail on how the used unit market effect savings were calculated. Surveys

with used unit acquirers indicated that the majority of used unit market acquisitions were for units that

would be used as primary units (85.6%). For these acquirers, 41.6% took the only path to savings which

is to upgrade the unit from the available used unit to a new unit.

Participant Actions in the Absence of the Program

Keep Equipment10.3%

Keep in Use60.6%

Direct Savings = UEC

as secondary unit

0.90 * 0.87 *

1012 kWh= 790 kWh

Keep Unused39.4%

Direct Savings = 0, not plugged in

Discard Equipment

89.7%

Transfer to another Customer (Sell to Dealer, Remove by dealer, Trade in for new

unit, Hire someone to remove, Give to charity, give to neighbor)

68.0%

Market Effect (savings per

transferred unit)

166 kWh

Destroyed32.0%

No Market Effect


KEMA, Inc. May 14, 2013 7-9

Figure 7-4: Decommissioning Program Market Effects Flowchart with Values

Only a small subset of recent used unit acquirers acquired a unit for use as a secondary unit. Overall, just

3% of the used unit acquirers who acquired a secondary unit (21% * 14%) would have upgraded to a new

unit or gone without altogether. The potential savings associated with these two paths are 336 and 752

kWh, respectively.

Table 7-1summarizes all the potential unit dispositions with the percentage of total units they represent,

savings for the pathway and the final weighted average savings per unit. This summary highlights that

there are ways to produce savings by removing secondary units and altering activity on the used unit

market. In total, though, only one of three units is producing savings through some pathway.

Recent Acquirer of Used Unit

Acquired a Used Unit as a Primary Unit

85.6%

Would Have acquired

similar used unit

55.2%

Market Effect = 0


unit41.6%

Market Effect = viable used primary UEC -

New UEC

839 kWh -464 kWh = 374 kWh

Would not have

acquired any unit3.2%

Market Effect = 0

Acquired a Used Unit as a Secondary Unit

14.4%

Would Have acquired

similar used unit

58.6%

Market Effect = 0


unit20.7%

Market Effect= viable

secondary used UEC -

New secondary

UEC

0.90 *(839 kWh -464 kWh) =

336 kWh

Would not have

acquired any unit

20.7%


UEC

0.90*839 kWh = 752 kWh


KEMA, Inc. May 14, 2013 7-10

Table 7-1: Summary of Decommissioning Savings

Disposition

Percent of Total

Units

Per Unit Savings

(kWh)

Kept Plugged in 6.24% 790.0

Un-

plugged 4.06% 0.0

Destroyed 28.70% 0.0

Transferred

Primary

Acquirer

No Change 28.82% 0.0

Upgrade 21.72% 374.5

Forego 1.67% 0.0

Secondary

Acquirer

No Change 5.15% 0.0

Upgrade 1.82% 335.9

Forego 1.82% 752.4

Per Unit Savings 100% 150.4

On the contrary, the summary shows that a large percent of units would have been destroyed regardless of

the program, producing no savings. Perhaps more importantly, a large percent of unit would have

transferred to used unit acquirers seeking a primary unit and willing to take whatever was available.

There may be more effective and efficient ways to motivate potential used unit acquirers to purchase new

efficient and smaller low consumption units than indirectly reducing supply of units to the used unit

market.

Table 7-2 summarizes the final estimate of programmatic adjusted savings for the decommissioning

program. The direct and market effect savings are the weighted totals of the savings paths illustrated in

the flowcharts above. The measure life is 11 years and was calculated based on the program population

using an RTF lookup table.

Table 7-2: Programmatic Adjusted Decommissioning Program Savings

Measure

Life

Direct

Savings

Market Effect

Savings

Total

Savings

11 49.3 101.1 150.4

The evaluation did a large number of used unit market interviews to characterize the market and support

this evaluation. Results from those surveys are found in section D. The qualitative results produced there


KEMA, Inc. May 14, 2013 7-11

support the quantitative results just presented. Most importantly, none of the used unit retailers reported

noticing any effects of the decommissioning program in their business.

7.5.1 Results Compared to Other Evaluations

Table 7-3 summarizes the results from this evaluation of the PSE decommissioning program in the

context of other decommissioning program results. The table illustrates that the key population

percentages, the percent kept in use and the percent transferred but not destroyed, are similar across all of

the evaluations. The PSE kept-in-use percentage is somewhat smaller than the earlier California studies

but closer to the more recent and geographically relevant ETO study. These are the units that generate full

potential savings. The transferred but not destroyed percentage represents the subset of units that would

have survived to move to the secondary unit market. For this percentage, the PSE result is also similar to

the other programs.

Table 7-3:

Comparison to Claimed Savings and Other Recycling Programs: PSE Decommissioning Program

Component

CA 2002

(KEMA )

CA 2004-5

(ADM)

CA 2006-8

(Cadmus)

ETO 2010

(Innov.)

RTF

2010

PSE 2013

(DNV

KEMA)

Kept in use 12% 12% 13% 8% 6%

Transfer, Not-destroyed 58% 47% 56% 60% 61%

Potential Savings kWH (UEC *

Part-use) 1,712 1,655 1,059 1,087 908

Realization Percent 41% 62% 55% 50% 17%

Adjusted Programmatic Savings 702 1,029 582 544 482 150

The estimated potential savings for these recycling programs illustrates the steep decline in average

consumption as a higher percentage of units were manufactured after 1993 when new Federal standards

came into effect. In addition, the two earliest evaluations used a laboratory meter approach that may have

produced relatively higher estimates of UEC than the now common in situ approach. The California

Statewide evaluation from 2006-2008 program years reported average in situ potential savings. The ETO

estimate is label-based and does not include an assumed degradation factor from CA that they


KEMA, Inc. May 14, 2013 7-12

considered.12

The PSE UEC is lower than the other most recent studies because no evidence of a

degradation effect was found in the in situ metering that was performed.

This evaluation‘s estimate of the realization percentage is substantially below those of prior evaluations.

This is understandable for all the evaluations except for the 2002 KEMA evaluation. The later evaluations

all give essentially full credit for non-destroyed, transferred units. As discussed in this report, that

approach does not capture the market effect of removing units from the secondary market in a realistic

way. As discussed in section 7.3, it is essential to develop a counterfactual scenario of what would have

occurred in the market without the program. This approach recognizes that shifting the supply curve in

the secondhand market can have a variety of effects, including lowering the number secondhand units

purchased, altering the average UEC of secondary units on the market and/or motivating substitutions of

new units in place of the used unit. Each of these scenarios might generate savings. Only one scenario

generates the full savings assigned to these units by other evaluations – a person who would have

purchased a secondhand unit for use as an additional, secondary unit who decides as a result of the supply

constraint not to purchase any unit. Our method identifies households that would have made this decision

and we give full credit for this subset of units and they represent a small percentage of used unit

purchasers on the secondary market (3%).

Perhaps more puzzling is why the current evaluation realization percentage (17%) is so much lower than

the 2002 California ARP evaluation result (35%) which used a similar market effects approach. A step-

by-step analysis of the two evaluation results shows that the PSE program generated lower savings at each

possible step.

Direct savings were lower. PSE customers reported keeping fewer units (two thirds) than did the

customers in the prior evaluation.

A larger percentage of PSE used unit acquirers said they would have simply located a similar

used unit in the absence of the unit they acquired. This scenario generates no savings, on average,

for this large share of the secondhand acquirers.

Similar percentages of PSE customers reported that they would substitute a new unit in place of

the used unit they purchased, however, substituting a new unit in 2012 generated less savings

than it did in 2002.

12

This makes the estimate more comparable to the PSE UEC estimate where effectively no degradation was

identified. It also does not include the part-use adjustment which would move it even closer to the PSE potential

savings estimate.


KEMA, Inc. May 14, 2013 7-13

Three times as many California used secondary unit acquirers said they would have gone without

a unit if the one they acquired was not available.

Each of these differences between the PSE results and the previous CA evaluation results explain a

portion of decrease in savings between the two evaluations. With this in mind, the final of per unit net

savings estimate of 150 kWh for the PSE decommissioning program is consistent with the 2002

evaluation results.


KEMA, Inc. May 14, 2013 8-1

8. Process Results and Market Characterization

8.1 Program Satisfaction Results

DNV KEMA surveyed PSE refrigerator program participants about their program satisfaction overall, and

about various program components individually. We asked participants to rate their satisfaction about

various parts of the program using a 5 point satisfaction where 1 meant ―Very dissatisfied‖ and 5 meant

―Very satisfied.

Participants across all three of the PSE Refrigerator programs reported high levels of satisfaction with the

program they participated in as a whole. Over 90% of each participant group we surveyed

(decommissioning, rebate, and replacement) rated their general program satisfaction at a ‗4‘ (satisfied) or

‗5‘ (very satisfied). While program participants offered low satisfaction ratings about program specifics

infrequently, when they did, they often attributed their dissatisfaction to the rebate payment process. Our

verbatim response groupings and analysis indicates that participants often cited the incentive dollar

amount (The rebate amount should have been larger) or the timeliness of the incentive payment (rebate

payment took too long to arrive) as leading sources of program dissatisfaction.

8.2 Additional Participant Survey Results

8.2.1 Replacement

The replacement program participants were much more likely to hear about the program through bill

inserts than any other form of marketing. Fully 52 percent of respondents referred to bill inserts as the

source of their information compared with 15 percent for the next most frequent source, other mail.

Participants confirmed that the program not only provided the household with a new, more efficient

refrigerator, but that new unit was, for many, smaller and with few energy consuming features. In fact,

nearly one-third of replacement program participants surveyed indicated that energy savings as a key

reason they participated in the program. Almost a third said the new unit was smaller than the unit that

was previous installed and ten percent gave up a unit with an ice maker through the door.

Participants indicated they were very concerned about energy efficiency. Their motivation was almost

entirely the cost of energy. Their interest in energy efficiency was further illustrated by the 88 percent

saying they looked for the ENERGY STAR label. The challenge of affording ENERGY STAR

refrigerators was shown in the answers of those who said they would have bought a new unit eventually

in the absence of the program. Three quarter said they would buy an ENERGY STAR model, while just

under three quarters said they would be likely to buy a used unit.


KEMA, Inc. May 14, 2013 8-2

The survey data make it clear that the replacement program provides an invaluable service to participating

households, helping them meet their energy conservation goals despite the challenging circumstances

they live in.

8.2.2 Rebate

Respondents DNV KEMA surveyed about their Rebate program experience most frequently report (61%)

hearing about the program through salespeople where they purchased their new refrigerator. Most other

Rebate program participants indicated that they got their initial program information from their utility bill

mailing.

Ninety-eight percent of the Rebate participants we surveyed claimed the unit they purchased and received

the rebate for replaced an existing unit. A large majority of this respondent group indicated their existing

unit was removed by the company that delivered the new unit; twenty respondents indicated that their

existing unit was not picked up when their new unit was delivered. Sixteen of those 20 respondents

confirmed they eventually called and arranged for a recycling pickup for the unit. One respondent overall

confirmed they kept and used both units after their new unit purchase. This is a incidence of this

outcome, but does represent a failure of the program process.

The Rebate program respondents are well-educated about ENERGY STAR; nine out of 10 respondents

confirmed they look for ENERGY STAR labels when appliance shopping. Slightly fewer (70%) of this

group reported they are ―very concerned‖ about reducing their home‘s energy use. When we asked those

who expressed some level of concern over their home‘s energy use to relay why, nearly all respondents

named the cost of energy, or reducing their bill, as their primary reason for concern.

Rebate program participants were split on the reasons they provided for purchasing an energy efficiency

refrigerator. Forty percent of the respondents indicated they purchased an energy efficiency refrigerator

because they needed a refrigerator. Another 37% reported they participated because they were looking for

energy savings. Cash incentive was the third most popular answer at 20%.

The survey data discussed in this section indicates the rebate program process works well. The

population the program serves and their reasons for interest in the program are consistent with

expectations. The bigger concern for the rebate program was reported in section B.6 in the discussion of

the net savings estimate. Over 90% of respondents said they would have purchased ENERGY STAR

without the program rebate. This number is likely higher than would actually be the case, but that does

not change the important conclusion to be drawn. ENERGY STAR is a well-known and desired brand.

Many refrigerator customers, perhaps even a majority, would purchase an ENERGY STAR unit in the


KEMA, Inc. May 14, 2013 8-3

absence of the program and that means PSE is not reducing consumption with those rebate dollars. After

all, ENERGY STAR refrigerators accounted for 50% of the new refrigerator sales as of 2010.13

With relatively high penetration of ENERGY STAR refrigerators, it‘s not clear how to avoid high free-

ridership rates. In their 2012 ACEEE paper, Frank, Peters and Canny point out that the barriers to

ENERGY STAR adoption are at the lower end of the refrigerator price spectrum. There are fewer options

available for units below $1000 and the efficiency-related price increment is a higher percentage of the

total cost. This analysis indicates that there may be an opportunity to promote ENERGY STAR at the

lower end of the price spectrum and increase adoption among those buying less expensive units. This

could be achieved by having rebate levels tied to consumption levels as well as efficiency tier. Rebates

structured in this way could have the additional effect of motivating customers to downsize or simplify

features on their unit, lowering consumption beyond the efficiency-related gains.

8.2.3 Decommissioning

Nearly half (47%) of the Decommissioning program participants reported hearing about the program

through their utility bill or a bill insert. Word of mouth was the second most popular way (16%)

Decommissioning respondents reported hearing about the program.

Easy disposal was the provided answer among roughly half of the participants to name why they chose to

participate in the program. About one-fifth of the program participants (21%) indicated they were

motivated to participation by the cash incentive.

Decommissioning program participants join other program participants we surveyed in being well-

informed on ENERGY STAR appliances. Ninety-two percent of this group confirmed they look for

ENERGY STAR labels when purchasing new appliances. Ninety-five percent expressed at least some

concern about their homes‘ energy use. / program motivation. Among those who expressed concern, the

leading explanation was the cost of energy and/or reducing their energy bill.

The decommissioning program is recognized as an easy way to dispose of a unit and get paid to do so.

The impact evaluation indicates that this is not an effective way to lower the number of secondary units or

lower consumption for used unit acquirers. Because recycling of refrigerators is required by regulations,

the environmental benefits are also likely low.

13

A Systematic Approach to Evidence-Based Appliance Program Design. Frank, Peters and Canny. Fueling Our

Future with Efficiency, ACEEE Conference Proceedings. 2012.


KEMA, Inc. May 14, 2013 8-4

8.2.4 Comparative Participant Demographics

Rebate and decommissioning programs serve quite similar populations. With respect to type of dwelling,

size, heating fuel, number in the house and education, the populations are remarkably similar. Rebate

households tend to be younger, in their house for a shorter time and make more money. All three of these

rebate program participant characteristics may reflect that the most common time to buy a new

refrigerator is when moving into a new house. Housing prices in the PSE service territory are relatively

high so we would expect newer home owners to have higher incomes.

The replacement program participants, as expected, represent a very different population group. For

example, almost half live in mobile homes. Consistent with this, the size of the homes is much smaller

than the home of the other programs‘ participants. Furthermore, 85% of households are heated with

electric heat.

The participants appear consistent with target low income and/or hard-to-reach population. Seventy

percent of the participants make less than 25 thousand dollars a year and 44 percent have only a high

school degree or less. Almost a third of replacement program participants have lived at their present home

for less than 5 years. Their average tenure in their present house is much less even than the rebate

program participants. They are also dramatically more likely to live alone, with 41 percent living alone

compared to only 11 percent for the other two programs.

8.3 Non-Participant Survey Results

8.3.1 Non-Participant Demographics

Roughly nine out of every 10 non-participant responders lived in a single family, detached home, and

own that home. Non-participant survey responders have lived in their home for over 14 years, on average,

and the mean square footage home size is 2,372. Non-participants overwhelmingly use natural gas as their

primary heat fuel (89%); electricity is the second most named heating fuel (9%). This group is slightly

more likely to use electricity to heat their hot water (13%), but natural gas is also the dominant fuel source

choice in this category.

The mean age of non-participants we surveyed was 53. A strong majority of total non-participants

surveyed indicated they live in their residence year-round (96%), and have a mean of 3.1 people living in

their home – including themselves and their children. Four out of five non-participant respondents had

participated in some level of post-secondary education (some college, an associate's degree, or higher).

The mean non-participant household income is just over $100,000 annually.


KEMA, Inc. May 14, 2013 8-5

8.3.2 Comparative Non-Participant Program Awareness

Awareness of the PSE Refrigerator programs was low among non-participants. Most of the non-

participants we surveyed (73%) had not heard of the PSE Refrigerator programs before taking the survey.

8.3.3 Other Non-Participant Energy Attitudes

Non-participants are less likely than program participants we surveyed to shop based on ENERGY STAR

program labeling. Eighty-five percent of non-participants indicated ENERGY STAR labels are a factor

when purchasing a new appliance, compared to 91% of participants who confirmed it was a factor.

Further, non-participants are less likely to rate their level of concerns with reducing their homes energy

use at ―very concerned‖ (55%) compared to participants (76%), respectively. Despite their different levels

of concern about reducing their homes‘ energy use, about three-fourths of both participants and non-

participants attributed their concern to ‗Cost of Energy / Reduce Energy Bill’.


KEMA, Inc. May 14, 2013 A-1

9. Results Summary and Findings

9.1 Results Summary

Table 9-1 summarizes the evaluated savings for the three PSE refrigerator programs. Gross and net

savings are provided for the replacement and rebate programs. Savings for the decommissioning program

are adjusted programmatic savings.


Program

Measure Life

Years

Annual

Savings

(kWh)

Annual Net

Savings

(kWh)


Replacement

1-10 372.6 337.3

11-20 55.5 36.1

Rebate - Tier 2

1-14 67.1

49.5

15-20 15.4

Rebate - Tier 3

1-14 66.5

66.4

15-20 15.3

The decommissioning program savings represent the combination of both the direct removal of secondary

units and the restriction of supply to the used unit market. The rebate and replacement program sections

summarize the two-part life-time savings estimates produced for this evaluation. The replacement

program, generates gross savings at two distinct levels. For the first ten years of the measure life, the

remaining useful life of the existing unit, savings are the difference between the average existing unit

UEC and efficient program unit. The remainder of the new unit measure life generates savings for the

difference between the efficient program unit and a standard efficiency baseline unit. Net savings reflect

that some participants would have replaced their present unit without the program and some of those

would have done so with an ENERGYSTAR® unit.

Rebate units produce gross savings at one level for the 20 year measure life. Savings are reduced across

the full twenty year measure life because a substantial percent of participants would have purchased

ENERGYSTAR units without the program. In addition, though, a subset of participants say the program

accelerated the purchase of a new unit. This increases savings during the remaining useful life of the

existing unit. Savings logic and calculations are all discussed extensively in the report.



9.2 Findings

9.2.1 Replacement Program Findings

The replacement program appears to succeed in reaching its target market. The participant demographics

reveal a participant population with limited resources and education, modest housing and higher mobility.

They value energy efficiency highly because it saves money. Without the help of the program it is

unlikely they would update their refrigerator until the old unit broke and even then the replacement unit

might be a used unit.

Though the savings estimate produced for this evaluation are well below the PSE claim savings levels, the

program savings are founded on sound principals. The pre-1993 year of manufacture requirement means

that existing unit UEC will remain relatively high though the program may have increasing trouble

finding eligible units and the remaining useful life will continue to drop. The primary challenge to the

savings of the replacement program is the high proportion of participant households with electric heat.

This prevalence of electric heated homes among this program‘s population means a substantial loss of

savings to HVAC interaction.

9.2.2 Rebate Program Findings

The rebate program is succeeding in giving point of purchase rebates to refrigerator purchasers. This

program delivery model is effective but faces high penetration levels of ENERGYSTAR appliances. The

PSE claimed savings appear to compensate for that fact and the evaluated savings for tier 2 are almost

identical to the claimed savings. Tier 3 evaluated savings are 78% of claimed savings because the lower

consumption magnitude counteracts the higher level of efficiency savings.

9.2.3 Decommissioning Program Findings

The primary goal of the decommissioning program is removing additional units in the household that

would otherwise remain on the grid. The relatively small percentage of recycled units that participants

indicated would have remained in use at the household in the absence of the program reveals that this

targeted group is a small proportion of decommissioning program population.

The decommissioning program started accepting non-secondary units in 2012. This reduced the

percentage of the targeted secondary of units. For a primary unit to receive credit, the participant would

have had to intend to keep it as an additional unit in the absence of the program. The program needs to

establish whether this is a sufficiently high probability event to justify the inclusion of these replaced,

mostly primary units.



The market effect savings reflect the limited savings opportunities that still exist in the used unit market

and the inefficiencies of supply-side efforts. Fifteen years ago, the majority of available used units pre-

dated the 1993 refrigerator appliance standard improvements. Motivating an upgrade to a post-1993 unit

offered substantial savings. In the present, the majority of available used units are post-1993 units. The

potential savings from an upgrade are more modest.

Upgrades do appear, however, to be the most likely source of savings in the used unit market because the

majority of persons acquiring units through formal and informal channels are getting a unit to use as a

primary unit. Rather than trying to decrease consumption by constraining the supply of units to the used

unit market why not directly target incentives for small, simple, low consumption units that will be used

as primary units to used unit acquirers. This approach would combine aspects of the replacement and

rebate program to more effectively reduce consumption through the used unit market.



A. Replacement Program Savings

This appendix provides more in depth discussion of the basis for replacement program savings

calculations in section 5.

A.1 Savings Logic – Net Savings

The gross savings logic is provided in section 5 above.

For the replacement program, free-ridership affects the early replacement and efficiency portions of the

savings differently. When a replacement program participant indicates they would have purchased a new

unit in the absence of the program the high savings due to the standard-to-existing unit savings is reduced

regardless of the efficiency level of the unit they would have purchased. This is free-ridership with

regards to the replacement aspect of the program. We refer to this as anti-acceleration because it is

structurally the opposite of the typical acceleration which is captured in the rebate program net savings

calculation. 14

In addition there is the possibility that the unit would have been ENERGYSTAR. This

represents free ridership with respect to the energy efficiency aspect of the program. This lowers the

savings by lowering the standard efficiency baseline for the lifetime of the new unit. Appendix Figure

A-1 provides a diagram of the replacement program net savings calculation.

14

Acceleration generally increases savings by increasing the amount of time an existing unit is the relevant baseline.

In this case, the opposite is occurring. The existing unit is the default baseline, and the possibility that a new unit

would have been purchased anyway reduces the amount of time the existing unit is the relevant baseline.



Appendix Figure A-1: Replacement Program Net Savings Diagram

Replacement program average per unit, life-time net savings ( ) can be expressed as follows:

Where

NSReplaced = Gross saving for rebate program units

UECStand = Standard efficiency UEC






ACC = Percentage ―accelerated‖ without program

In this equation, the two pieces comprising gross savings are scaled by an attribution factor ( ) and

an ―anti-acceleration‖ adjustment factor, respectively.

EULP

UECProg

UECStan

UECExist

kWh

Years

Anti Acceleration: Lost additional savings where participants would have purchased sooner than EULE

Free Ridership: Lost program to standard efficiency savings where participants would have purchased EE anyway

EULE



A.2 PSE Refrigerator Metering

This evaluation offered a unique opportunity to meter units, in situ, under realistic conditions in the

houses of program participants. Replacement program units were selected for metering because both the

existing and replacement units could be metered under the same conditions. Each unit was metered for at

least two weeks.

Metering the replacement program units guaranteed that the primary unit would be in place until the time

of program pick-up. This avoids issues that have occurred with the metering of recycling program units

where the metered unit has been moved and may only be plugged in for the metering process.

A.2.1 Preparation

Preparation for a site visit begins with the notification of a qualified customer. Once the customer has

been identified with a commitment letter, the preparation for the first site visit would be completed.

The site visit worksheet is prepared with the customer specific information including name, address and

phone number. For the first visit, a $25 gift card was drawn, and the serial number recorded on the

worksheet. In addition to the worksheet, a customer name tag was prepared with the last name and ID

number. The customer site packet consisted of the worksheet, $25 gift card and customer name tag.

The customer was contacted by phone to arrange a time for the visit.

Generally the night prior to the visit, the logger would be launched. Each logger was launched with a

setup script file. This assured that each installation had exactly the same setup. The logger was setup to

begin logging at the time of setup. While this had the effect of zero power logging for several hours prior

to the home visit, it had no impact on the overall performance.

A.2.2 Logger Installation

Upon arrival at the customer residence, the old refrigerator was inspected for accessibility and potential

risks to the surrounding area were noted. Some items were relocated to accommodate a safe move. The

refrigerator was moved to gain access to the power plug. The refrigerator was plugged into the logger

module and the logger module was plugged into the same wall receptacle as previously powered the

refrigerator.

The logger module enclosure was opened to expose the wires. A Fluke power meter (model 39) was

attached for a one-time power measurement. When the refrigerator was running, a power measurement

was taken and recorded on the worksheet. In most cases, the refrigerator was coaxed to run the

compressor, in order to take this measurement. The power meter was removed and the logger reconnected



and installation was inspected. The customer name tag was placed into the enclosure and it was closed.

The refrigerator with power module attached was rolled back into place.

The freezer and refrigerator compartment temperatures were taken and recorded. The temperatures were

measured with a GenTech Model 26451 Infrared thermometer. To minimize variation the temperature

was taken from a white object or package whenever possible. At least five different measurements were

taken of each area and the average entered on the worksheet. The thermostat settings were also observed

and positions entered on the worksheet.

An interview with the customer provided demographic and structural information which was then entered

on the worksheet. Questions about what would they have done without the existence of this program

resulted in a very consistent set of answers. With all but one site, they would have replaced the

refrigerator when it failed and had the old unit recycled or hauled off to the trash. Most would have

looked for a new unit similar to their old one, but newer. About half of the customers indicated they most

likely could not afford a new refrigerator.

The refrigerator manufacturer and model number was recorded on the worksheet.

Upon leaving, the customer was given the gift card and thanked for their participation in the evaluation

program.

A.2.3 Logger Removal

Approximately four weeks after the meter was installed, the customer was contacted to schedule the meter

removal. Prior to the site visit a $50 gift card was drawn and the associated number(s) entered onto the

worksheet.

The logger module enclosure was opened to expose the wires. A Fluke power meter (model 39) was

attached for a one-time power measurement. When the refrigerator was running, a power measurement

was taken and recorded on the worksheet. In some cases, the refrigerator was coaxed to run the

compressor, in order to take this measurement.

The freezer and refrigerator compartment temperatures were taken and recorded. The temperatures were

measured with a GenTech Model 26451 Infrared thermometer. To minimize variation the temperature

was taken from a white object or package whenever possible. At least five different measurements were

taken of each area and the average entered on the worksheet. The thermostat settings were also observed

and positions entered on the worksheet.



The logger module was removed from the refrigerator and the latter plugged into the wall. The logger

module with customer tag inside was secured and returned to SBW Consulting offices.

The refrigerator manufacturer and model number was recorded on the worksheet.

Upon leaving, the customer was given the $50 gift card and thanked for their participation in the

evaluation program.

A.2.4 Logger Data Transfer

After returning to the SBW Consulting offices, the logger data was downloaded from the logger and

saved locally as two files named with the customer ID only. One saved file is the raw download the other

is the .CSV file.

The data .CSV file was uploaded to the KEMA SharePoint site and the collected worksheet data was

entered into the KEMA spreadsheet.

The logger was disabled and inspected for redeployment.

A.2.5 Data Preparation

This section describes the process by which we readied the data for analysis. For our purposes, we

required daily consumption data. The loggers recorded hourly data and these data required cleaning and

preparation of the hourly data to make them suitable for aggregation to the day. Given the relatively small

number of meter data series, we produced a wide range of plots of unit demand to confirm that the raw

data informing the in situ UEC estimates were sound. Appendix Figure-A-2 provides an example meter

data series that already has preceding and following zeroes removed. The changeover period, outlined in

red, also had to be trimmed.

Appendix Figure-A-2: Example Meter Data Series



A full outline of the steps involved includes:

Prep of hourly logger data:

─ Check and correct obvious errors in the meter data (e.g. sign flips)

─ Plot data

─ Flag extremely high demand (did not delete)

─ Flag and drop leading and trailing zeros at the hourly level

─ Use tracking data to identify hours for which existing and program qualifying units were

metered, as well as black out period.

─ Compare meter data series levels to spot kW checks performed with independent meter at

drop-off and pick up (this process identified two faulty meters).

Prep of data aggregated to the daily level

─ Plot data and use visual inspection to correct errors in the switchout date found in the meter

tracking data

─ Drop meters that were either flagged as faulty in the tracking data, or did not pass visual

inspection of plots

─ Trim series by dropping partial first and last day from all meters

A.2.6 Annualization of Meter Data

A challenge of short term metering is expanding the meter results to an annual estimate of consumption.

Refrigerator energy consumption varies over the year with internal household temperature. Internal

household temperature will vary across households due to outdoor temperature and household heating and

cooling characteristics. Short term metering results will reflect the consumption level given the weather

and household characteristics at the time of the metering. If all metering takes place during a limited

timeframe, it is essential to annualize the metering results or the estimate of consumption will reflect the

consumption characteristics of the time of year of the metering.

For this evaluation, the metering effort took place across a full calendar year. This made it possible to

annualize assuming a flat load shape and allow the averaging across units metered at different points in

the year to account for seasonal effects. Because the metering was not uniformly distributed across the

year, we calculated a weighted averaging assuring the winter and summer metering results carried the

appropriate weight.



A.2.7 In situ UEC results

Appendix Figure A-3 plots all of the in situ metering data that was collected for existing units. The plot

illustrates that units were metered for at least two weeks and that individual metering took place within a

12 month timeframe. The separate unit series illustrate the variation both within and between units.

Appendix Figure A-3: In situ Metering Series by Date, Existing Units

Appendix Figure A-4 below plots the meter data for the replacement program qualifying units. The plot

is on the same scale as the plot above of existing unit data. The overall reduction in consumption is

clearly evident.



Appendix Figure A-4: In situ Metering Series by Date, Program Qualifying Units

These meter data inform all of the UECs estimated for this evaluation. For the replacement program

existing units, the UEC is estimated directly from the annualized meter sample UECs. For all other UECs

for all three evaluations, this metering effort informs the in situ adjustment factor. This factor captures

the average ratio relationship between the metered units and their associated label UEC. This factor is

applied to a population-based estimate of label UEC for a set of units to combine the representativeness of

the label UEC and the empirically-based evidence of in situ consumption dynamics.

A.3 Estimation of Label UEC

To determine label UEC, we matched model numbers from the tracking databases to a look-up table

available from the California Energy Commission (CEC) that contained UECs for different model

numbers. The CEC database is extensive and now encompasses the vast majority of units that are still on

the grid today. We use statistical algorithms to match program unit model numbers to the CEC data.

For the new, replacement units, the match rate was 100 percent. Appendix Table A-1 summarizes label

UEC look up process. The table provides the count of units from the replacement program for which a

match was attempted, the match rate, and the resulting label UECs.



Appendix Table A-1: Label UEC Look-up, Matched and Imputed UEC: New Units in Replacement

Program

Existing

Unit/Program

Qualifying Unit

Number

of Units Match Rate

Matched

Label UEC

(kWh)

Imputed Full

Population Label

UEC (kWh)

Program Qualifying 1,890 100% 355 355

The available data population data for replacement program existing units was limited. In particular, the

tracking data did not provide model numbers for any existing units. This meant there was no way to

improve the representativeness of the metering sample by using label UEC. As a result, estimates of

existing unit UEC are produced directly from the metering sample.

We did, however, collect model numbers for the metering sample and match them for the purpose of

creating the in situ ratio adjustment. For these units, the match rate was approximately 70%. For older

units, model numbers can be difficult to capture even for trained personnel visiting the site. Model

numbers may no longer exist on the unit, no longer be legible or may be difficult to find. For those units

without a direct match, we used a regression model to impute label UECs from those units with a direct

match.

A.4 In situ Adjustment Calculation

The primary purpose of the metering was to develop an in situ to label adjustment. This adjustment

accounts for the difference between the conditions under which label UEC is determined and those under

which units are actually used. It also accounts for any age related degradation of the unit.

Using estimates of annualized UEC from the metered sample, and label UECs obtained by matching those

units‘ model numbers to the CEC database, we are able to estimate an in situ ratio. We are interested in

the determining the in situ factor, , given by the following value:

Appendix Figure A-5 provides the in situ ratios for both new and used units plotted by age. The new

replacement units are all plotted at year one. The existing units are plotted at their age. The plot

illustrates a two related, unexpected findings. First, there was similar or greater variation in new unit

UECs than existing unit UECs. For new units, the in situ ratio is expected to capture the difference

between laboratory and household usage characteristics. This is true for older units with the additional


KEMA, Inc. May 14, 2013 A-10

variability of unit degradation over the age of the unit. Given this, the existing unit variation would be

expected to be greater than the new units.

Appendix Figure A-5: In situ to Label UEC Ratio by Age

In addition, the existing units (age greater or equal to 20 years) lack a discernible age-dependent trend.

This indicates no apparent evidence of an age-related degradation effect. We tested many specifications

of the degradation models including a range of age transformations. There was no indication of an age-

related trend. No other characteristics were statistically significant either.

For the purposes of this evaluation, we calculated the in situ adjustment as ratio estimator of the new units

and existing units. This is calculated as the sum of in situ UECs divided by the sum of label UECs.

Appendix Table A-2 provides the estimated label and in situ UEC for the replacement program units and

the in situ adjustment.

Appendix Table A-2: In situ Adjustments for the Replacement Program

Units

In Situ

Adjustment

Factor

90%

Confidence

Interval

Program Qualifying

Units 0.98 [0.87, 1.08]

Existing Units 1.02 [0.93, 1.11]

The in situ adjustments from replacement program metered units are applied to all of the label UEC

estimates generated from the tracking. Because there is little evidence of a pronounced degradation effect,

possible distinction between programs becomes less important. The Decommissioning and replacement


KEMA, Inc. May 14, 2013 A-11

program units are somewhat similar in age distribution so they would likely have similar degradation ratio

regardless.

A.5 Determination of ―Standard‖ baseline UECs

The development of a standard efficiency UEC for the new replacement units was essential for the

replacement program baseline scenario. For this savings calculation input, we assume that, in the absence

of the program, the household would have replaced their existing unit at the end of its remaining useful

life with a standard efficiency unit similar to the ENERGY STAR unit installed by the program. This

assumption of standard efficiency is the typical approach to setting future baseline scenarios like this. We

used the following approach to produce an average standard replacement unit UEC:

Bin actual replacement program units according to size and configuration

Calculate average efficiency increase by bin in the ENERGY STAR database

Adjust the efficient unit label UEC to generate an equivalent new standard UEC

Calculate the average UEC for these standard efficiency versions of the replacement units

From the replacement program tracking data, we obtained size and configuration combinations for model

numbers matched to CEC. The size/configuration combinations for the replacement program are listed in

Appendix Table A-3 below:

Appendix Table A-3: Average Efficiency by Bins—Replacement Program

Configuration Size* Frequency Efficiency

Top Freezer

large 287 20%

medium 188 20%

999 30%

small 416 20%

* large: > 21 cubic feet; medium: 18-21 cubic feet; small < 18 cubic feet

The efficiency level reported in the table above is the percent below the federal standard for annual

consumption for refrigerators. Appendix Table A-4 below summarizes the UEC for a standard efficiency

unit for the replacement program.


KEMA, Inc. May 14, 2013 A-12

Appendix Table A-4: Replacement Program UEC, Standard Efficiency

Label UEC

Estimate

In situ Ratio

Adjusted UEC

90% Confidence

Interval (In situ

Adjusted UEC)

475 464 [434, 494]

A.6 HVAC Interaction Effect

The theory behind the HVAC interaction effect is discussed in section 5.3.3. This section provides the

calculations and the inputs.

A.6.1 Calculating HVAC-Adjusted UEC

The HVAC interaction effect is calculated as

where

H = % of year that a given home requires heating

EH = % of units within the envelope of electrically heated homes.

C = % of year that a given home requires cooling

AC = % of homes that use air conditioning

As written above, corresponds to a HVAC realization rate, the share of gross savings realized after

interaction with the home‘s HVAC system has been taken into account.

A.6.2 Summary of Input Values

Appendix Table A-5 provides the share of year requiring heating and cooling. Base temp is the average

outdoor daily temperature below or above which a day is considered a heating or cooling day,

respectively. Daily average temperatures provide an approximate picture of the activity during that day.

The choice of base temp was designed to account for partial heating and cooling days on the margin.

Degree day bases were chosen based on previous billing analysis work done for PSE.


KEMA, Inc. May 14, 2013 A-13

Appendix Table A-5: Heating and Cooling Share of PSE Year

HVAC Share Base Temp % of year

Heating 60 73.6%

Cooling 72 2.4%

Appendix Table A-6 provides the participant survey data indicating the percent of units that are in

electrically heated or cooled space.

Appendix Table A-6: Share of Participants with Electric Heat/Air Conditioning:

Replacement Program

Category

Share of

Population

Electric Heat 72.5%

Air Conditioning 13.3%

Appendix Table A-7 provides the calculations and the HVAC factor.

Appendix Table A-7: HVAC Interaction Factor Calculation:

0.736 0.725 0.467 0.024 0.133 0.003 0.470

A.7 Net Savings Calculations

The net savings calculations require additional information regarding what they participant would have

done in the absence of the program. We obtained these parameters from our survey of replacement

program participants. The tables below summarize the survey responses that were used to generate these

parameters.

We recoded these responses to reflect the functional effect of these responses. In particular, only when the

respondent affirmatively indicated that they had a concrete plan to purchase a refrigerator within a year in

the absence of the program, they were given an acceleration value of between 0.90 and 1.00. Appendix

Table A-8 below shows how we recoded the survey responses in order to arrive at relevant categories for

an acceleration factor calculation.


KEMA, Inc. May 14, 2013 A-14

Appendix Table A-8: Recoded Survey Responses Used to Determine Acceleration Factor

Survey Response Interpretation for Acceleration Factor Percent

Anti-

Acceleration

Factor (as % of

RUL)

Sooner than I did Would Have Purchased at Same Time 2.7 1.00

Same time

Within month Would Have Purchased in One Month 2.0 0.99

Within the next year Would Have Purchased in One Year 8.0 0.90

More than 1 year later than I did

Would Have Purchased When the Unit Broke 87.3 0.00 When it broke

Would not have purchased

Don‘t know

To arrive at a single population-wide acceleration factor, we first weight each of the recoded responses

above by factor corresponding to each responses share of remaining useful life for a typical unit. Using an

RUL of 9.9 years for the replacement program, we obtain an estimated anti-acceleration factor of 0.12.

We apply one minus the anti-acceleration factor to the existing to standard portion of the gross savings

estimate as part of our net-to-gross adjustment.

In addition to the anti-acceleration adjustment, we apply an attribution factor, based on the percentage of

participants that indicated that in the absence of the program they would have purchased an ENERGY

STAR Unit. Appendix Table A-9 below summarizes the responses to the relevant survey question. Only

those who said they would have considered purchasing a unit in the absence of the program were asked.

Appendix Table A-9: Without the program, would you have purchased an ENERGY STAR

refrigerator?

Response %

Yes 34.7

No 10.7

Don‘t Know 8.7

Not Asked 46.0


KEMA, Inc. May 14, 2013 A-15

For the purposes of determining attribution, we recoded the survey responses so that only those

participants who affirmatively indicated that they would have purchased an ENERGY STAR Unit were

considered free riders. This produces a free-ridership estimate of 34.7 percent. The final net savings result

is the gross saving estimate net of free ridership and decreased by lost anti- acceleration savings. The two

figures below summarize how the components of our analysis combine to generate estimates of net

savings. Appendix Figure A-6 present estimates the life-time savings for the two parts of the calculation

along with the relevant measure life.

Appendix Figure A-6: Replacement Program Net Savings Calculation

UEC For Existing Unit -UEC For Standard


Heating Interaction

FactorX 1-(Anti-Acceleration)

1136 464 0.472 0.95

=

337.27

UEC For Existing Unit -UEC For Standard


Heating Interaction

FactorX Attribution Factor

464 347 0.472 0.65

UEC For Standard

Efficiency New Unit-

UEC For Program

Qualifying New UnitX

Heating Interaction

FactorX Attribution Factor =

Total Net Unit

Savings (Year 11-

20)

464 347 0.472 0.65 36.08

Total Net Unit

Savings (Year 1-10)


KEMA, Inc. May 14, 2013 B-1

B. Rebate Program

B.1 Estimation of Label UEC

The general approach to the estimation of label UEC is described in the detail in Section A.3 above.

Appendix Table B-1 summarizes the label UEC look up process for rebate program. The table provides

the count of units from each program for which a match was attempted, the match rate, and the resulting

label UECs.

Appendix Table B-1: Label UEC Look-up--Matched and Imputed UEC for Rebate Program


Qualifying Unit

Number

of Units

Match Rate

(%)

Matched

Label

UEC

(kWh)

Imputed Full

Population

Label UEC

(kWh)

90% Confidence

Interval

Program Qualifying (Tier 3) 1,176 100% 389 389 [385, 393]

Program Qualifying (Tier 2) 403 100% 525 525 [524, 526]

Existing 540 68% 841 * [812, 870]

*The rebate program tracking data did not provide additional characteristic data for old units.

For the rebate program, we used the tracking database model numbers to perform the matching with the

CEC database. The rebate program tracking database collected model numbers for the replaced unit but

not additional unit characteristics. This meant we could not impute label UEC values for unmatched

existing units. As a result, we used the UEC for the matched subset of existing units. This value is only

used for the acceleration portion of the net savings estimate.

B.2 Application of in situ Adjustment Factor

The metering of replacement program units provide in situ adjustments for the rebate program ENERGY

STAR units and existing units. The in situ adjustments are designed to adjust label UEC, which is

measured in laboratory conditions, to in situ UECs that reflect household usage characteristics. Contrary

to previous evaluations, the adjustment for both new and older units were small (Section A.4). Appendix

Table B-2 provides the adjusted UEC estimates.

Appendix Table B-2: Rebate Program UECs


Qualifying Unit

In Situ Ratio

Adjusted UEC

90% Confidence

Interval

Program Qualifying (Tier 2) 513 [458, 567]

Program Qualifying (Tier 3) 380 [339, 421]

Existing 857 [783, 931]



B.3 Determination of New ―Standard‖ UEC

The rebate program saving estimate requires a standard efficiency unit UEC consistent with the

population characteristics of the rebate program qualifying unit. The general approach is described in

section A.5 above. The size/configuration combinations for the rebate program are listed in Appendix

Table B-3.

Appendix Table B-3: Average Efficiency by bins Rebate Program

Configuration Size* Frequency Tier Average Efficiency (%)

Bottom Freezer

large 339 2 25.6

329 3 30.0

medium 30 3 30.0

small 2 2 25.0

Side-By-Side large 59 2 25.0

248 3 30.9

Top Freezer

large 2 2 25.0

103 3 30.0

medium 1 2 25.0

298 3 32.8

small 168 3 35.0

* large: > 21 cubic feet; medium: 18-21 cubic feet; small < 18 cubic feet

Appendix Table B-4 provides the final estimated baseline UECs for the two tiers for the rebate program

savings calculation.

Appendix Table B-4: Rebate Program UECs, Standard Efficiency Units


In Situ Ratio

Adjusted Std

Efficiency

90% Confidence

Interval

Tier 2 689 [687, 690]

Tier 3 554 [549, 559]

The market baseline used for the rebate program savings calculations in a weighted combination of the

ENERGYSTAR UECs and the standard efficiency UEC here based on the national penetration of

ENERGYSTAR units.



B.4 Estimated Useful Life / Remaining Useful Life Determination

The rebate program uses the standard RTF measure life of 20 years for program qualifying unit. The

acceleration part of the net savings calculation requires an existing unit remaining useful life. The general

approach is described in section 5.3.2 above. Appendix Table B-5 lists the remaining useful life results

for existing units for the rebate program. Remaining useful life was calculated using the age distribution

of matched existing units because unit age was not available in the tracking data.

Appendix Table B-5: Remaining Useful Life/Program Unit Measure Life: Rebate Program

Existing Units/Program Qualifying Units Years

Remaining Useful Life for Existing Units 14.3

Program Unit Measure Life 20

B.5 HVAC Interaction Effect

We calculate a program specific HVAC for the rebate program. The general approach is described in

section A.6 above. Appendix Table B-6 provides the calculations and the HVAC factor for the rebate

program.

Appendix Table B-6: HVAC Interaction Factor Calculation

0.736 0.186 0.863 0.024 0.197 0.005 0.868

B.6 Rebate Program Net Savings

The rebate program Net Savings logic recognizes that some participants would have purchased an energy

efficient refrigerator even in the absence of the program. It also recognizes that, for some participants, the

rebate may have actually motivated the purchase of a new unit even though that was not its intent. As a

result, the rebate program Net Savings calculation combines a reduction in savings due to free-ridership

with an increase in savings due to revised baseline consumption for some households. These changes are

captured in Appendix Figure B-1.



Appendix Figure B-1: Rebate Program Net Savings Diagram

The following equation provides the calculation for rebate program average per unit, life-time net savings.

Where

NSRebate = Net saving for rebate program units

UECMark = Market efficiency UEC






ACC = Percentage accelerated without program

Free-ridership (FR) is the percentage of rebate program participants, above national penetration rates, that

indicate they would have purchased an energy efficient unit if the program rebate was not available. Any

additional indication of a counterfactual purchase of energy efficient units beyond the national penetration

levels effectively lowers the baseline consumption as the baseline unit becomes a combination of the

EULP

UECProg

UECMark

UECExist

kWh

Years

EULE

Free Ridership: Lost program to market efficiency savings where participants would have purchased EE anyway

Acceleration: Additional savings where participants purchased sooner because of the program



market efficiency baseline and energy efficient units that would have been purchased in the absence of the

program. This results in a decreased difference between the market efficiency line and the program

alternative.

Acceleration counteracts free-ridership. It is a combination of the percentage of participants that

indicated they would not have purchased a new unit in the absence of the program and how long they

think it would have taken them to make that purchase. The longest it could take to get a new unit is the

EUL of that existing unit. To simplify the already complicated life-time savings structure, the acceleration

calculation assigns additional acceleration-related savings in terms of the average unit savings through

existing unit EUL.15

Both the values for the acceleration factor and free-ridership were obtained from the survey of rebate

program participants. The tables below summarize the survey responses that were used to generate these

parameters.

Appendix Table B-7 presents the question and response that we used to determine the acceleration rate.

Responses are to the question ―When would you have purchased a unit in the absence of the program‖.

Appendix Table B-7: Survey responses used to determine acceleration factor

Response Interpretation for Acceleration Factor %

Sooner than I did Would Have Purchased at Same Time 80.0

Same time

Within month Would Have Purchased in One Month 2.0

Within the next year Would Have Purchased in One Year 3.3

More than 1 year later than I did

Would Have Purchased When the Unit Broke 14.7 When it broke

Would not have purchased

Don‘t know

Appendix Table B-8 below presents the survey responses that were used to generate our free-ridership

estimate. ―Don‘t know‖ and ―refused‖ and answers were consider a ―No‖ answer.

15

In reality, the acceleration savings could be different for each year of the existing unit EUL because participants

vary as to how long it would take to get the new unit in the absence of the program. This calculation represents the

same amount of savings but put in terms of units that would not have been replaced until existing unit measure life.



Appendix Table B-8: Without the program, would you have purchased an

ENERGY STAR refrigerator?

Response %

Yes 82.1

No 6.4

Don‘t Know 10.7

Refused 0.7

The final net savings result is the gross saving estimate net of free ridership and increased with

acceleration savings. The three figures below summarize how the components of our analysis combine to

generate our estimates of net savings.

Appendix Figure B-2 applies the acceleration factor and attribution factor (1-Freeridership) to the gross

savings estimate for the Tier 2 rebate program.



Appendix Figure B-2: Rebate Program Net Savings Calculation, Tier 2

Appendix Figure B-3 applies the acceleration factor and attribution factor (1-Freeridership) to the gross

savings estimate for the Tier 3 rebate program.

UEC For Market

Efficiency New

Unit-

UEC For Program

Qualifying New

Unit

XHeating

Interaction FactorX

Acceleration

Factor

857 590 0.87 0.15

=

49.50

UEC For Existing

Unit -UEC For Market

Efficiency New

Unit

XHeating

Interaction FactorX Attribution Factor

590 513 0.87 0.23

UEC For Existing


Efficiency New

Unit

XHeating

Interaction FactorX Attribution Factor =

Net Unit

Savings (Year

15-20)

590 513 0.87 0.23 15.44

Total Net Unit

Savings (Year

1-14)



Appendix Figure B-3: Rebate Program Net Savings Calculation, Tier 3

UEC For Market

Efficiency New

Unit-

UEC For Program

Qualifying New

Unit

XHeating

Interaction FactorX

Acceleration

Factor

857 457 0.87 0.15

=

66.39

UEC For Existing


Efficiency New

Unit

XHeating

Interaction FactorX Attribution Factor

457 380 0.87 0.23

UEC For Existing


Efficiency New

Unit

XHeating

Interaction FactorX Attribution Factor =

Net Unit

Savings (Year

15-20)

457 380 0.87 0.23 15.31

Total Net Unit

Savings (Year

1-14)


KEMA, Inc. May 14, 2013 C-1

C. Decommissioning

C.1 Estimation of Label UEC

Appendix Table C-1 summarizes label UEC look up results for the decommissioning program. Unlike the

rebate and replacement programs, there are no program qualifying units to match, as the sole purpose of

the decommissioning program is the removal of existing units. The table provides the count of units for

which a match was attempted, the match rate, and the resulting label UECs.

Appendix Table C-1: Label UEC Look-up: Matched and Imputed UEC

Number of

Units

Match Rate

(%)

Matched Label

UEC (kWh)

Imputed Full Population

Label UEC (kWh)

90% Confidence

Interval

4,615 70% 974 993 [989, 998]

We used a regression model to impute missing label UEC values. In particular, we used a model

specification that included characteristics that are known to impact the performance of the unit, including

age, amps, configuration, and defrost type as well as a categorical variable corresponding to the program.

This model made use of all of the data to guide imputation but accounted for any additional differences

between the types of units found in the decommissioning program and the replacement program

C.2 Application of in situ Adjustment Factor

The in situ adjustments from replacement program metered units are applied to the decommissioning

label UEC estimate generated from the tracking data. Because there is little evidence of a pronounced

degradation effect beyond 30 years, possible distinctions between programs become less important. The

decommissioning and replacement program existing units have a quite different age distribution but their

average ages are almost identical at 26.6 and 25.9 years, respectively. Appendix Figure C-1 shows the

two distributions. The decommissioning program has units that are both younger and older than the

replacement program units.



Appendix Figure C-1: Decommissioning and Replacement Programs Unit Age Distribution

Appendix Table C-2 provides the adjusted UEC estimate. Although applying the in situ adjustment factor

does not alter the point estimate, it does increase the variation in the estimate, which is reflected in the

wider confidence interval.

Appendix Table C-2: Decommissioning Program UEC

In Situ Ratio

Adjusted UEC

90% Confidence

Interval

1,012 [925, 1099]

C.3 Determination of New ―Standard‖ UEC

A standard efficiency unit UEC that is required for the decommissioning program market effects savings

calculation. The general approach is described in section A.5 above. Appendix Table C-3 provides the

standard efficiency unit UEC. We are assuming that the demand for units in the second-hand market has a

similar size and configuration profile as units replaced by the replacement program.

0

5

10

15

20

25

30

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50

%

Age

Replacement

Decommissioning



Appendix Table C-3: Decommissioning Program, Standard Efficiency

Used Unit Alternative UEC

In Situ Ratio

Adjusted UEC

90% Confidence

Interval

464 [434, 494]

C.4 Determination of Resale Value UECs

The calculation of market effects requires the estimation of UECs for those units that would have found

their way into the secondary market. For this study we assumed that only those units aged 20 years or less

had resale value. One would expect that the subset of decommissioned units that have resale value would

have lower UECs than the full sample. We found this to be the case. Appendix Table C-4 below

summarizes the estimated UEC for this subset of decommissioned units:

Appendix Table C-4: Decommissioning Program, Decommissioned Units with Resale Value

In Situ Ratio

Adjusted UEC

90% Confidence

Interval

839 [608, 1069]

C.5 Estimated Useful Life/Remaining Useful Life Determination

The general approach is described in section 5.3.2 above. Appendix Table C-5 below lists the remaining

useful life results for existing units for the rebate program. Remaining useful life was calculated using the

age distribution of the recycled units in the tracking data.

Appendix Table C-5: Remaining Useful Life/Program Unit Measure Life: Decommissioning

Program

Remaining Useful Life for

Existing Units (Measure Life)

10.7

C.6 HVAC Interaction Effect

The general approach is described in section A.6 above. Appendix Table C-6 provides the participant

survey data indicating the percentage of units that are in electrically heated or cooled space.



Appendix Table C-6: Share of Participant unit With Electric Heat/Air Conditioning

Category % 90% CI

Electric Heat 17.8 [15.8, 19.8]

Air Conditioner 9.2 [8.1, 10.3]

Based on these values, and based on the assumptions made so far, the HVAC factors for each program

can be estimated. Appendix Table C-7 provides the calculations and the HVAC factors.

Appendix Table C-7: HVAC Interaction Factor Calculation

0.736 0.180 0.868 0.024 0.092 0.002 0.870

C.7 Decommissioning Program Survey Results

In addition to the part-use factor, we adjust the savings estimate further by multiplying the part-use

adjusted savings by the percentage of participants that indicated that they would have kept and used their

unit.

Appendix Table C-8: What would you have done with the old refrigerator

if you had not participated in the decommissioning program?/ If you had kept the refrigerator,

would you have used it or stored it unplugged?

What would you have done? %

Gotten rid of it 89.7%

Kept it 10.3%

used 60.6%

stored unplugged 39.4%

100.0% 100.0%

From these survey questions we are able to assign a % kept in use adjustment factor of 6.0%. This

number does not include those kept but stored unplugged. It does include those who would have kept the

unit but did not know if they would have kept it plugged in or not.



C.7.1 Market Effect, Would-be Transfer Units

The non-participant unit discarder survey provides us with the information required to estimate the share

of units that would have found themselves into the secondary market. Appendix Table C-9 below

summarizes the responses for the relevant survey question, as well as how we recoded them for the

purpose of this analysis.

Appendix Table C-9: I‘d like to talk to you about the refrigerator you disposed of.

What did you do with that refrigerator?

Survey Response

Disposal

Path Percent

Threw away / Took to Landfill Destroyed 31.0

Took to recycling center

Donated to charity

Transferred 66.0

Taken by installer of new one

Sold to used appliance dealer

Sold to private individual

Gave to friend/relative/private individual

Set it out on the curb for someone to take

Other

Omitted 3.0 Don‘t know

Refused;

The proportion of units that would have been transferred weight the difference between the baseline

transfer UEC and the program alternative transfer UEC. Each of these in turn consists of a weighted

average of full use UEC estimates of units with resale value (baseline) and the program alternative full

year UEC, where the weights are the part-use adjustment factor calculated as described above.


KEMA, Inc. May 14, 2013 D-1

D. Used Unit Marked Characterization

D.1 Market Characterization Data Gathering

D.1.1 Approach

DNV KEMA recognized that the information sought about the used refrigerator market is difficult to

obtain from key actors using a direct survey. Instead we used a Mystery Shopper Approach as a means of

obtaining objective, representative data and to increase participation in our research effort. Mystery

Shopping involves the use of agents posing as customers in order to gather information on a (potential)

retail transaction.

D.1.2 Sample

Multiple sources such as Craigslist, Yelp, Google listings, Yellow Pages, and InfoUSA databases were

used to develop the sample of used refrigerator retailers for this qualitative research. SIC/NAICS codes

combined with geography of interest was used to filter the InfoUSA database and simple search terms

such as ―Used Appliance‖, ―Used Refrigerator‖, ―Used Fridge‖ etc. were used to develop the sample from

all other sources listed.

Appendix Table D-1: Sample - Used Refrigerator Retailer, Repair Service & Recycler

Source

Sample

Size Category Geography

InfoUSA 31

Used Appliance Retailers &

Repair Service

PSE Electricity and PSE

Gas & Electricity

service area 9 Scrap Metal Recyclers

Craigslist 1 Used Appliance Retailer Seattle-Tacoma Area

Yelp 2 Used Appliance Retailers Seattle-Tacoma Area

Google 3 Used Appliance Retailers Seattle-Tacoma Area

Desktop research was done to augment information on related factors such as peer-to-peer

exchanges/sales, donations, recycling programs (free or fee based) etc. Additional interviews were

conducted with municipalities and supplemental market actors such as thrift stores.



Appendix Table D-2: Sources for additional research

Category Geography

Municipality Thurston County,

Olympia, Bellevue

Peer-to-Peer 2Good2Toss,

Freecycle

Thrift Store Salvation Army,

Western Territory HQ

D.1.3 Interview Protocol

In order to prevent exhausting the sample in the PSE territory, a few preliminary calls were made to

retailers in the San Francisco Bay Area to help develop the interview protocol and understand better the

parameters we seek definition on.

Retailers were approached under the premise that we were looking to stock a rental unit (mystery

shopper) and were hence interested in learning more about the used refrigerator options available in the

market. Retailers were asked questions on availability of basic 18 cubic feet models and then probed

further regarding age and price of older/newer, bigger/smaller and frost-free versus manual defrost

models. Flexibility was indicated on specifications such as single versus double door, freezer placement,

color etc. and more interest was indicated in the price, age and provenance of their stock.

Toward the end of calls to retailers in the PSE area we included questions on the impact of the recycling

program on the used refrigerator market (ability to acquire stock, changes in stock composition etc.).

Questions related to the recycling program were introduced casually and positioned as driven by

individual/shopper curiosity. PSE was not revealed (either explicitly or implicitly) as the sponsor of the

research.

D.1.4 Disposition

The summary disposition report below indicates that we had a response/completion rate of around 20%

for our research.



Appendix Table D-3: Disposition Report from IDI contacts

Category Count

Completes - Used refrigerator retailers 8

Completes - Recyclers 4

Repair/Service only, no sale, not

refrigerators, parts only etc. 26

No response/voice-mail 8

D.2 Used Unit Market Characterization

This section summarizes primary research conducted to characterize the second hand refrigerator market

with the intent of better understanding the effect of recycling/decommissioning older refrigerators. A

major portion of the research was comprised of in-depth interviews with retailers that helped to determine

the kind of units that are likely to become available as secondary units. This informed the impact

evaluation savings estimation.

Experience with prior refrigerator market characterization work illustrates the challenges of research in

this area. Market actors are difficult to identify, reach, and engage in a useful discussion. The results are

ultimately anecdotal and may not represent the full range of second hand market actors and their roles.

Recognizing these limitations, DNV KEMA focused this research effort on those actively selling second

hand units at the present time and took an approach that would maximize response rate.

D.2.1 Findings from Used Refrigerator Retailers

Age – Responses regarding age were vague, both in general about their entire stock and specifically as

well. While a couple of retailers did have 15-20 year models (manual defrost), most of them gave the

indication that they received and sold refrigerators under/around 10 years old. One respondent specified

that 30% of their stock is over 10 years old. Many noted that the age is not specified on the unit and that

their focus was not the age, but whether it worked.

Unsold stock: End-of-life – Retailers noted that they only refurbished what they thought they could sell

else disposed the units with the recycler. A used appliance retailer we spoke to noted that of the used

refrigerators they acquired each week they sold one on average and sent 4-5 to the recycler. When probed

if the recycler could put it back through a ―3rd

hand‖ seller of appliances, retailers were doubtful about

that possibility and stated that the more likely outcome was that the recycler would sell the unit to the

scrap metal dealer.



Channels of acquisition – The main acquisition channel for retailers that sell both new and used

refrigerators were trade-ins from their own customers. A specific respondent noted that they were not in

the used appliance business and did not work with distributors or other second-hand sources. Some

retailers noted that they acquire their stock from ―all over‖ – individuals, institutions, hotels etc. Retailers

indicated that there was no additional layer, such as a distributor network for used appliances. All

transactions were conducted directly with the user/owner of the used refrigerators.

Impact of PSE program on their stock – Retailers indicated that they did not see a change in

composition or size of their stock of used refrigerators due to this program.

D.2.2 Findings from Supplemental Market Actors

Recyclers – We spoke to scrap metal recyclers in the PSE service area in order to get a more complete

picture of how used refrigerators travel through market. One recycler did not accept refrigerators. The

two recyclers that handled refrigerators did so for a fee which ranged from $20 for drop-offs to a higher

$50-$75 for pickup. The fee included the work required in the removal and safe disposal of the

compressor.

One of the recyclers said that they did (re)sell some market-worthy refrigerators they received to a

specific used appliance retailer in the area. This indicates that all refrigerators indicated as recycled by

non-participants may not have been ultimately disposed of.

Donations to charities (e.g. Salvation Army) – Some previous used unit market research has raised

questions as to whether charities continued to accept refrigerators as donations. Our research included

speaking with the supervisor at Salvation Army, in Seattle to understand how residential donations flowed

through the market. The Salvation Army estimated that while they sold 80% of the donated refrigerators

after refurbishing them, they disposed the remaining unsellable 20% for a fee by weight of the

refrigerators. They noted that the majority of their refrigerators were 5-15 years old and they received

about 30 in a month. This amounts to approximately 300 used refrigerators sold per annum through

Salvation Army. There are other such charities such as Goodwill that do accept refrigerators.

Municipalities – Our research included interviews with some municipalities in the PSE service area.

Thurston County has a program that residents could pay $36 to have the city dispose off their used

refrigerators. Olympia does not take refrigerators but does help residents identify businesses that might

take those materials such as private recyclers. Bellevue runs one off recycling events that take in

refrigerators for disposal for a fee of $25. Both officials at Thurston County and Olympia referenced the

PSE recycling program, unprompted.



D.2.3 Market Characterization Summary

The survey of the used unit market supports many aspects of impact evaluation. Dealers indicated that the

used units they sold tended to be units less than 15 years old. Dealers indicated also that most of their

stock came through direct trade-ins rather than through distributors. This implies the dealer pay more for

the used units they collect than the decommissioning incentive and that those units continue to have value

on the secondary unit market. Finally, none of the dealers indicated that their supply of used units had

been affected by the PSE decommissioning program. The Salvation Army store, though just outside of the

PSE territory, reported similar findings.

The market surveys also confirmed that other options for recycling a refrigerator exist in the area, though

there most charge a fee. This indicates that the decommissioning program may provide a valuable service,

from an environmental perspective, and that value could be captured in the program benefits.


KEMA, Inc. May 14, 2013 E-1

E. Additional Survey Data - Participant

E.1 Total (Overall) Participant Respondent Profile

Respondent

Characteristics

Total

Participant

N

Total

Participant

%

Gender

Men 194 43%

Women 258 57%

Income

Less than $25k 118 26%

$25,000 to $49,999 57 13%

$50,000 to $74,999 47 10%

$75,000 to $99,999 35 8%

$100,000 or more 46 10%

Don't know / Ref 149 33%

Highest Education

High school or less 116 26%

Some college or an

Associate's degree 164 36%

Bachelor's degree 74 16%

More than four-year

degree 70 15%

Don't know / Ref 28 6%

Home Characteristics

Total

Participants N

Total

Participants %

Own or Rent?

Own 374 83%

Rent 70 15%

DK / ref 8 2%

What year was your

home built? (mean) 1975 --

Finished square footage

of your home? (mean) 1,721 --

Number of residents / at

least six months of the

year? 2.51 --

Single family,

detached, 67%

Single family,

attached, 5%

Mobile home, 20%

Apartment, 6%

DK / ref, 2%

Home Type

The following is a PSE Participant profile, according to the collected survey data. A majority of PSE

participants we surveyed have the following characteristics:

Own, and live in, single-family, detached homes (67%). Another twenty percent live in mobile

homes.

Are likely to heat their water in their homes with electricity (59%). Nearly half (47%) heat

their homes with electricity.

Have modestly-sized homes, most commonly built in the 1970‘s.

Have more than two people living in their households year-round, suggesting that families

often take advantage of these programs as a whole.

More than half of the participants (52%) had an education level below a bachelor‘s degree. While more

than one-third of the surveyed participants refused to name their income range, those that did most

frequently have an income below $50,000. Demographic data for the surveyed participants appear in

the following tables and figures.



E.2 Participant Program Satisfaction

Program participants were largely satisfied with the PSE refrigerator programs overall. We asked

participants to rate their satisfaction on a ‗1‘ to ‗5‘ scale, where 1 was ‗extremely dissatisfied‘, and ‗5‘

equaled ‗extremely satisfied‘. The results in Appendix Table E-1 indicate the mean satisfaction scores, by

program, across the various program elements we asked participants to assess.

Decommissioning participants rated the actual pickup of the old refrigerator with the highest satisfaction

marks; Replacement participants were most satisfied with the refrigerator removal scheduling process.

Rebate participants had fewer program elements which applied to their experience; among their options,

they scored the program as a whole with their highest satisfaction. The mean score across all participants

for the program as a whole was a 4.7 out of a possible 5, representing high satisfaction levels.

Appendix Table E-1: Participant Satisfaction on Program Processes

Participant Group N

Elapsed time

between

appointment

scheduling & old

refrigerator pick up

date

Refrigerator

removal

scheduling

process

Actual pickup

of the old

refrigerator

Dollar

amount of

the incentive

Timeliness of

the incentive

payment

The

program as

a whole

Decommissioning 152 4.61 4.72 4.85 4.66 4.58 4.72

Rebate 150 NA NA NA 4.52 4.42 4.64

Replacement 150 4.5 5 4.33 NA NA 4.69

Total 452* 4.6 4.9 4.6 4.6 4.5 4.7

Electricity, 47%

Natural Gas, 39%

Wood , 6%

Propane, 5%

Other / DK / REF, 4%

Home Heating Fuel

Electricity, 59%

Natural Gas, 35%

Propane, 4%

Other / DK / REF, 2%

Home Water Heating Fuel



E.3 Participant Energy Attitudes

Most PSE Refrigerator program participants report looking for ENERGY STAR labels when shopping for

new appliances. Ninety percent of all participants surveyed in this evaluation indicated appliance

shopping includes looking for ENERGY STAR labels. The data were similar for rebate program

participants alone.

Appendix Figure E-1: When purchasing new appliances, do you look for ENERGY STAR labels?

Total Participants, N=452

To further assess PSE program participants‘ energy awareness, we asked them how concerned they are

with reducing their home‘s energy use. Appendix Table E-2 provides the results. Nearly all PSE program

participants, regardless of what program(s) they took part in, categorized themselves as ―somewhat‖ or

―very‖ concerned. Replacement program participants were most likely to categorize themselves as ―very

concerned‖ about their homes‘ energy use compared to other program participant groups. Only a few

participants in each program reported not being concerned.

Appendix Table E-2: Participant Level of Concern with Reducing Energy Use

Yes, 90%

No, 7%

Don't know, 3%

Response

Total Part

N

Total Part

%

Decommissioning

Part N

Decommissioning

Part %

Replacement

N

Replacement

Part % Rebate N

Rebate Part

%

1 - Not at all concerned 12 3% 6 4% 4 3% 2 1%

2 - Somewhat concerned 91 20% 40 26% 10 7% 41 27%

3 - Very concerned 343 76% 104 68% 134 89% 105 70%

Don't know 5 1% 2 1% 2 1% 1 1%

Refused 1 1% 0 0% 0 0% 1 1%

Total 452 152 150 150

How concerned are you with reducing your home's energy use? Would you say. . .



Participants who indicated they were concerned about their home energy use often provided multiple

reasons for their concern; however, the most frequently mentioned cause for concern was the cost of

energy or a goal of lowering their energy bill. Concern for the environment and/or global warming was

the second most frequently mentioned response.

Appendix Table E-3: Participant Reason for Concern with Reducing Energy Use

E.4 Participants: Awareness and Motivation

Program information sources were reported differently among our program participants, as shown in

Appendix Table E-4. Nearly half of both the Decommissioning and the Replacement program participants

reported hearing about the program from information within their utility bill, suggesting that PSE is

making good marketing use of their monthly mail contact with their customers. Rebate participants were

more likely to first hear about the program from someone where they were purchasing their refrigerator,

suggesting that the program partners and retailers are creating an impression with PSE customers while

shopping for energy efficient appliances.

Appendix Table E-4: Participant Source of Information about the Program?

Response

Total Part

N

Total Part

%

Decommissioning

Part N

Decommissioning

Part %

Replacement

N

Replacement

Part % Rebate N

Rebate Part

%

Cost of energy / reduce

energy bill 391 87% 125 82% 137 91% 129 86%

Environment / global

warming 97 21% 43 28% 15 10% 39 26%

Power availability /

reliability 15 3% 8 5% 3 2% 4 3%

Dependence on foreign oil 4 1% 2 1% 1 1% 1 1%

Other 4 1% 2 1% 1 1% 1 1%

Don't know 6 1% 3 2% 3 2% 0 0%

Refused 1 1% 0 0% 0 0% 1 1%

Total 518 183 160 175

Why are you concerned with reducing your home's energy use? (among those indicating concern )

Response

Decommissioning

Part N

Decommissioning

Part %

Replacement

Part N

Replacement

Part %

Rebate Part

N

Rebate Part

%

Contractor / Salesperson where

equipment purchased 8 5% 4 3% 93 62%

Utility bill insert / information with utility

bill 72 47% 78 52% 29 19%

Utility website 6 4% 0 0% 9 6%

Internet (other than utility site) 10 7% 2 1% 2 1%

Newspaper - Local, State, or Nat. 6 4% 2 1% 1 1%

TV, radio 1 1% 2 1% 1 1%

Friends, relatives, or neighbors 24 16% 19 13% 4 3%

Community center / events / schools 2 1% 8 5% 4 3%

Mail 0 23 15%

Other 3 2% 5 3% 2 1%

Don't know 21 14% 9 6% 7 5%

Total 153 101% 152 101% 152 101%


KEMA, Inc. May 14, 2013 F-5

F. Survey Instruments

F.1 Non Participant CATI Refrigerator


Non-Participant Residential CATI Survey

SURVEY HOUSE INSTRUCTIONS

1. Text in bold should be read.

2. Text in brackets [ ] are instructions for interviewer, minor programming such as skips, or answer

choices and should NOT be read.

3. Text in carrots < > are database variables that should be filled in on a case-by-case basis.

4. Text in double-carrots << >> are larger blocks of text that will change on a case-by-case basis

depending on database variables.

5. Text in gray boxes is major programming instruction.

6. Unless specifically noted, do NOT read answer choices. [Don‘t know] and [Refused] should NEVER

be read.

PROGRAMMING NOTES

Code multiple response questions as a series of variables that have a 0 or 1 value. One variable for

each answer option. For example, R5_1 = 1 if the respondent answers ―internet‖ to R5. R5_1 = 0 if

the respondent does not answer ―internet. Make separate 0/1 variables for the [Don‘t know] and

[Refused] options as well.

DATABASE VARIABLES

Variable Definition

(Unless otherwise noted, the database can contain more than one of each

variable per respondent)

program Name of the refrigerator program the customer participated in. One per

customer.

Address Address where equipment was picked up / recycled

ref_qty # of refrigerators recycled according to records

NUM REF # of refrigerators recycled according to customer

new_config Configuration of new refrigerator (top-mounted freezer, etc) from records

new_brand Brand of new refrigerator (Maytag, Whirlpool, etc) from records

qPAwording IF <program> = rebate then ―the rebate for‖ else ―‖



Appendix Figure F-1: Non-participant Survey Questions

Tasks /Selected Topics to be

Covered Purpose

Nonparticipant Survey: customers

who disposed of refrigerator in past 2

years.

n = 200 screened customers who discarded

refrigerators 2010 - 2011. Frame: PSE population

How appliances taken out of service

were disposed of

Percentage of disposed of units that went into

channels where they would be destroyed. Key step

to determining whether participant units would have

been destroyed even without program

Awareness of the programs and sources

of information General process and Spillover set-up

Knowledge of the benefits of appliance

recycling General process and Spillover set-up

Influence of the program on disposal

decision and channels Spillover

Reasons for selecting disposition

method Spillover

Most recent refrigerator acquired? New

unit? Used unit purchased from dealer?

Used unit acquired (purchased, given,

traded) through informal channels

(neighbor/friend, classified ads,

Craigslist)

Effect of recycling/decommissioning on second-

hand unit acquirer.



Intro and Screening

REF_Intro4. Do you own the appliances, including the refrigerator, in your home or is that the property

of the landlord?

1 Tenant Owns

[IF REF_Intro 2=1 Skip to

REF_Intro6; If REF_Intro 3=1 skip

to REF_Intro5]

2 Landlord Owns [THANK AND TERMINATE]

-97 [Don‘t know] [THANK AND TERMINATE]

-98 [Refused] [THANK AND TERMINATE]

REF_Intro5. Did you participate in a refrigerator rebate or refrigerator recycling program offered by

PSE at that time?

1 [Yes] [THANK AND TERMINATE]

2 [No] REF_Intro6


-98 [Refused]

REF_Intro6. For verification purposes, can I please get your first and last name?

[RECORD FIRST and LAST NAME] If REF_Intro2=1 Goto S0, else goto A0d

-98 [Refused] [THANK AND TERMINATE]




USED UNIT PURCHASE

S0. Thinking about the used unit you brought into your house, where did you get that unit?

1 [used Appliance Dealer]

S1

2 [Friend]

3 [Off street]

4 [Craigslist internet]

etc

-97 [Don‘t know]

-98 [Refused]

S1 Approximately, how much did you pay for that unit? 1 0 Free

S2

2 <=$100

3 $100< <=$200

4 >$200

-97 [Don‘t know]

-98 [Refused]

S2 When you got that unit did it become your only refrigerator? 1 Yes (It is the only refrigerator in home) S3

2 No (There are multiple refrigerators in the home) S2a

-97 [Don‘t know] S3

-98 [Refused]

S2a Is it your primary refrigerator? 1 Yes S2f

2 No S2b

-97 [Don‘t know] S2b

-98 [Refused]

S2b Where in the house is this refrigerator located?

1 [Kitchen]

S2c

2 [Basement]

3 [Garage]

4 [Porch]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

S2c Is that refrigerator plugged in and used all year?

1 [Yes] S2f

2 [No]

S2d -97 [Don‘t know]

-98 [Refused]



S2d How many months is the fridge plugged in and running?

[RECORD VERBATIM]

(If answer=zero skip to S2f); else S2e -97 [Don‘t know]

-98 [Refused]

S2e What months?

[RECORD VERBATIM]

S2f -97 [Don‘t know]

-98 [Refused]

S2f. How many refrigerators do you use? 1 [Record number _______________________]

S3 -97 [Don‘t know]

-98 [Refused]

S3 Thinking back to when you got that used refrigerator, what would you have done if the specific used

refrigerator you acquired had not been available? Would you have . . 1 Found another similar used unit,

S4 2 Bought a new unit.

3 Stayed with the unit you already had/not replaced

4 Not acquired one R11

5 Other [Record:____________________________] S4

-97 [Don‘t know]

-98 [Refused]

S4 To confirm, then, in place of the used unit you got within the last four years you would probably have

had a unit that was … 1 Similar

R11

2 Better

3 Worse

-97 [Don‘t know]

-98 [Refused]

R11 What features were important to you? [Do not read options. Circle all that apply]

1 Configuration

R12

2 Size

3 Icemaker

4 Color

5 Energy Use

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

R12 On a scale of 1 to 5, with 1 being ‗Not Important at all‘ and 5 being ‗very important‘ how important

was Energy Efficiency for you in selecting a refrigerator?


KEMA, Inc. May 14, 2013 F-10

1 Not important at all

R13

2

3

4

5 Very important

-97 [Don‘t know]

-98 [Refused]

R13 Have you disposed of a full-sized refrigerator in the last two years?

1 [Yes] USED_REF_Intro5

2 [No] P0

-97 [Don‘t know]

-98 [Refused]

USED_REF_Intro5. Did you participate in a refrigerator rebate or refrigerator recycling program

offered by PSE at that time?

1 [Yes] [SKIP TO D1

2 [No] A0d

-97 [Don‘t know] [SKIP TO PO]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-11

DISCARD QUESTIONS

A0d. I‘d like to talk to you about the refrigerator you disposed of. What did you do with that

refrigerator?

1 [Threw away / Took to Landfill]

A0e

2 [Recycled – taken or picked up]

3 [Donated to charity]

4 [Taken by installer of new one]

5 [Sold to used appliance dealer]

6 [Sold to private individual]

7 [Gave to friend/relative/private individual]

8 [Set it out on the curb for someone to take]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

A0e. Why did you choose that option?

1 Least expensive option

A4a

2 Easiest option

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

A4a. Thinking about the unit you discarded, where was the freezer located on the refrigerator?

1 [Top Mounted Freezer]

A4b

2 [Side by Side]

3 [Bottom Freezer]

4 [Internal Freezer]

5 [Refrigerator Only – no freezer]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

A4b What was the size of the old refrigerator?

1 [Less than 10 cubic feet]

A4c

2 [10.1 to 15 cubic feet]



5 [greater than 25 cubic feet]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

A4c. Did the old refrigerator have an ice maker in the door?


KEMA, Inc. May 14, 2013 F-12

1 [Yes]

A5 2 [No]

-97 [Don‘t know]

-98 [Refused]

A5. Approximately how old was the refrigerator?

1 [0-5 years]

A5a

2 [6-10 years]

3 [11-15 years]

4 [16-20 years]

5 [21-25 years]

6 [Older than 25 years]

-97 [Don‘t know]

-98 [Refused]

A5a. What would you say was its overall condition?

1 It worked and was in good physical condition

A5b

2 It worked but needed minor repairs (like a door seal or handle)

3 It worked but had some problems (like it wouldn't defrost)

4 Or, it didn't work

-97 [Don‘t know]

-98 [Refused]

A5b Was it your primary refrigerator? 1 Yes A6

2 No A5c

-97 [Don‘t know]

-98 [Refused]

A5c Where in the house was this refrigerator located?

1 [Kitchen]

A5d

2 [Basement]

3 [Garage]

4 [Porch]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

A5d Is that refrigerator plugged in and used all year?


KEMA, Inc. May 14, 2013 F-13

1 [Yes] A6

2 [No]

A5e -97 [Don‘t know]

-98 [Refused]

A5e How many months is the fridge plugged in and running?

[RECORD VERBATIM]

(If answer=zero skip to A6); else A5f -97 [Don‘t know]

-98 [Refused]

A5f What months?

[RECORD VERBATIM]

A6 -97 [Don‘t know]

-98 [Refused]

A6 Did you replace the refrigerator you discarded with another refrigerator?

1 [Yes] P0

2 [No] A7

-97 [Don‘t know]

-98 [Refused]

A7 So, after discarding this unit you had one less refrigerator in the house?

1 [Yes] P0

2 [No]

-97 [Don‘t know]

-98 [Refused]

PROGRAM AWARENESS

P0. I‘d like to ask about your awareness of the PSE refrigerator programs. Before today, had you heard

of the PSE Refrigerator Rebate or Refrigerator Recycling programs? 1 [Yes] Both

P1 2 [Yes] Rebate

3 [Yes] Recycling

4 [No]

P4 -97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-14

P1. Where did you first hear about the program?

[ALLOW MULTIPLE RESPONSES. DO NOT READ RESPONSES] 1 [Contractor / Salesperson where equip purchased]

If

REF_Intro2=1

AND

R13<>1, goto

EA1

2 [Utility bill insert/information with utility bill]

3 [Utility website]

4 [the Internet other than utility‘s website]

5 [Local newspaper]

6 [A state or national newspaper]

7 [TV, radio]

8 [Friends, Relatives, or Neighbors]

9 [Community Events or Local Schools]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

P2. Were you aware of these programs when you disposed of your refrigerator?

1 [Yes] P3

2 [No]

P4 -97 [Don‘t know]

-98 [Refused]

P3. Why didn‘t you participate in the program?

1 [Costs too much even with rebate]

P4

2 [Too much of a hassle to go through rebate process]

3 [Other] [RECORD RESPONSE]

-97 [Don‘t know]

-98 [Refused]

P4. Why did you dispose of the refrigerator?

1 [It was not functioning at all]

EA1

2 [It was still functioning but with significant performance or

maintenance problems]

3 [It was too expensive to operate/Not energy efficient]

4 [Contractor recommended]

5 [Remodeling]

6 [Other] [RECORD RESPONSE]

-97 [Don‘t know]

-98 [Refused]

ENERGY ATTITUDES

EA1 When purchasing new appliances, do you look for Energy Star labels?

1 [Yes]

EA2 2 [No]

97 [Don‘t know]

98 [Refused]

EA2. How concerned are you with reducing your home‘s energy use? Would you say...

[READ UNBRACKETED OPTIONS.]


KEMA, Inc. May 14, 2013 F-15

1 Not at all concerned D1

2 Somewhat concerned EA3

3 or Very concerned?

97 [Don‘t know] D1

98 [Refused]

EA3. Why are you concerned with reducing your home‘s energy use?

[DO NOT READ. ACCEPT MULTIPLE ANSWERS] 1 [Cost of energy / Reduce energy bill]

D1

2 [Environment / Global warming]

3 [Power availability / reliability]

4 [Dependence on foreign oil]

-77 [Other, specify______________]

97 [Don‘t know]

98 [Refused]

DEMOGRAPHICS

For all following questions, 97 = Don‘t Know, 98 = Refused

D1. Which of the following best describes the type of home you live in? Is it a… [READ]

01 Single family, detached,

02 Single family attached, such as town house or row house,

03 Apartment in multi-unit structure of 2–4 units,

04 Apartment in multi-unit structure of 5 or more units, or

05 Mobile Home?

D1a. How many years have you lived in your current home?

01___ years [IF <1 YEAR, RECORD 0]

D3. Approximately what year was your home built? [DO NOT READ]

01 2006 OR LATER – Specify year :___________

02 2000 TO 2005– Specify year :___________

03 1990 TO 1999

04 1980 TO 1989

05 1970 TO 1979

06 1950 TO 1969

07 EARLIER THAN 1950

D4. What is the approximate finished square footage of your home? Your best estimate is fine. [DO NOT

READ]

01 LESS THAN 1,2000 SQUARE FEET

02 1,200 TO LESS THAN 1,800 SQUARE FEET




KEMA, Inc. May 14, 2013 F-16

05 3,000 SQUARE FEET OR MORE

D5. What is the primary fuel used to heat your home? [DO NOT READ]

01 NATURAL GAS

02 ELECTRICITY

03 PROPANE

04 OIL

05 WOOD

06 SOLAR

D6. What is the primary fuel used to heat your hot water (water heater)? [DO NOT READ]

01 NATURAL GAS

02 ELECTRICITY

03 PROPANE

04 OIL

05 WOOD

06 SOLAR

D6a. How many months per year is your home occupied?

[RECORD #]

[D6b]

-97 [Don‘t know]

-98 [Refused]

D6b. Including yourself, how many people live in your home at least six months of the

year?

01___ RECORD NUMBER OF PEOPLE

[IF D6b = 97/98/1 PERSON, SKIP TO D7, ELSE ASK D6c]

D6c. How many people in your household are under 5 years of age?

01 ___ RECORD NUMBER OF PEOPLE

D6d. How many in your household are 5 to 17 years of age?


D6e. How many people in your household are 18 to 64 years of age?


D6f. How many people in your household are 65-79 years of age?


D6g. How many people in your household are 80 years of age or older?


[CHECK THAT D6b = D6c-D6g MINUS 1]

[IF THEY DON‘T ADD UP, VERIFY RESPONSES TO D6c THROUGH

D6g UNTIL THEY DO]


KEMA, Inc. May 14, 2013 F-17

D7 Next, for statistical purposes only, what is the highest level of education you have obtained? [READ

LIST]

1 Some high school,

2 High school graduate, including GED,

3 Some college or an Associate‘s degree,

4 Bachelor‘s degree,

5 Some graduate school,

6 Graduate or professional degree.

D8. Again, for statistical purposes only, I‘d like to know your household‘s total 2011 annual income

before taxes. Please stop me when I reach the category that best describes your household‘s income.

[READ IF NECESSARY: This information is confidential and will only be used for characterizing

respondents to this study.] [READ LIST]

1 Less than $25,000,

2 $25,000 to $49,999,

3 $50,000 to $74,999,

4 $75,000 to $99,000, or

5 $100,000 or more?

D8a. What is your age?

01 ___ RECORD AGE

W WRAP UP – ASK ALL

[READ]: Those are all the questions I have for you. Is there anything that you want me to pass on to PSE? Thank

you very much for your time and opinions.

IF YES, RECORD:_____________

D9. RECORD GENDER

1 MALE

2 FEMALE

97 CAN‘T DETERMINE


KEMA, Inc. May 14, 2013 F-18

F.2 Participant CATI Refrigerator


Residential CATI Survey

SURVEY HOUSE INSTRUCTIONS

1. Text in bold should be read.

2. Text in brackets [ ] are instructions for interviewer, minor programming such as skips, or answer

choices and should NOT be read.

3. Text in carrots < > are database variables that should be filled in on a case-by-case basis.

4. Text in double-carrots << >> are larger blocks of text that will change on a case-by-case basis

depending on database variables.

5. Text in gray boxes is major programming instruction.

6. Unless specifically noted, do NOT read answer choices. [Don‘t know] and [Refused] should NEVER

be read.

PROGRAMMING NOTES

1. Code multiple response questions as a series of variables that have a 0 or 1 value. One variable for

each answer option. For example, R5_1 = 1 if the respondent answers ―internet‖ to R5. R5_1 = 0 if

the respondent does not answer ―internet. Make separate 0/1 variables for the [Don‘t know] and

[Refused] options as well.

Database variables

Variable Definition

(Unless otherwise noted, the database can contain more than one of each

variable per respondent)

name Contact name(s).

old_brand Brand of old refrigerator (Maytag, Whirlpool, etc) from records

old_config Configuration of old refrigerator (top-mounted freezer, etc) from records

program Name of the refrigerator program the customer participated in. One per

customer.

Address Address where equipment was picked up / recycled

ref_qty # of refrigerators recycled according to records

NUM REF # of refrigerators recycled according to customer

new_config Configuration of new refrigerator (top-mounted freezer, etc) from records

new_brand Brand of new refrigerator (Maytag, Whirlpool, etc) from records

qPAwording IF <program> = rebate then ―the rebate for‖ else ―‖

Wording1 If <program> = rebate then ―purchased and received a rebate for‖

If <program> = decommissioning then ―had removed‖

If <program> = replacement then ―received‖


KEMA, Inc. May 14, 2013 F-19

Was_is If <program>=rebate AND A0b=2 OR 3 ―is‖ ELSE ―was‖

Source Where the refrigerator was purchased/acquired from records


KEMA, Inc. May 14, 2013 F-20

INTRODUCTION

Intro1. Hello, my name is __________, and I‘m calling on behalf of Puget Sound Energy about the

refrigerator you recently <wording1>. Can I please speak with <name>?

[IF NECESARRY: I'm not selling anything; I'd just like to ask your opinions. Your responses will be

kept confidential and your individual responses will not be revealed to anyone.]

1 [Yes] If program = Rebate GOTO Intro2a.

If program = Replacement GOTO Intro2b.

If program = Decommissioning GOTO Intro2c.

2 [Not available right now]

3 [No]

-97 [Don‘t know] Arrange callback

-98 [Refused] TERMINATE

Intro2a. Our records show that your household received a rebate for the purchase of a new refrigerator. Is

this correct?

1 [Yes] INTRO4

2 [No] TERMINATE

-97 [Don‘t know] INTRO4


Intro2b. Our records show that your household participated in the PSE refrigerator replacement program

where you received a new energy efficient refrigerator. Is this correct?

1 [Yes] INTRO4

2 [No] TERMINATE



Intro2c. Our records show that your household participated in the PSE refrigerator decommissioning

program and had a refrigerator removed. Is this correct?

1 [Yes] INTRO4

2 [No] TERMINATE



Intro 4. Are you responsible for making decisions about appliances in your home?

1 [Yes]

(if Intro 2c=Don‘t know terminate If Intro

2b=‘don‘t know‘ terminate; If intro 2a=‘don‘t

know‘ terminate )

Else go to Intro 6

2 [No]

INTRO5 -97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-21

Intro5. May I please speak with someone who was involved in making decisions about your appliances in

your home, and might know if your home was involved with the program?

1 [Yes] INTRO1

2 [Not available right now] Arrange callback

3 [No] TERMINATE

-97 [Don‘t know] Arrange callback


Intro6. For verification purposes, can I please get your first and last name?

[RECORD FIRST and LAST NAME]

P0 -98 [Refused]

-97 [Don‘t know]

PROGRAM AWARENESS

P0. I‘d like to start by asking you about your awareness of the <program> program.

P1. Where did you first hear about the < program > program?

[ALLOW MULTIPLE RESPONSES. DO NOT READ LIST; QUESTION MUST BE UNAIDED.] 1 [Contractor / Salesperson where equip purchased]

If <program> = Rebate GOTO P2a.

Else GOTO P2

2 [Utility bill insert/information with utility bill]

3 [Utility website]

4 [the Internet other than utility‘s website]

5 [Local newspaper]

6 [A state or national newspaper]

7 [TV, radio]

8 [Friends, Relatives, or Neighbors]

9 [Community center/ Events or Local Schools]

10 [Mail]

77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

P2 Why did you choose to participate in the < program > program ?

[ALLOW MULTIPLE RESPONSES. DO NOT READ RESPONSES] 1 Cash Incentive

P3

2 Needed a new refrigerator

3 Environment

4 Energy savings

5 Easy disposal

6 Offered / suggested

7 Had extra refrigerator

77 Other

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

P2a. Why did you choose to purchase an Energy Efficient Refrigerator?


KEMA, Inc. May 14, 2013 F-22

1 Cash Incentive

P3a

2 Needed a new refrigerator

3 Environment

4 Energy savings

5 Easy disposal

6 Common sense

7 What was available

77 Other

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

P3. PSE has three refrigerator programs: In addition to the <program> program, have you participated in

the others?

1 [Yes] P4

2 [No] If <program> = Rebate GOTO A0a.

If <program> = Replacement GOTO A0b.

If <program> = Decommissioning GOTO A1.

-97 [Don‘t know]

-98 [Refused]

P3a. PSE has three refrigerator programs:. In addition to receiving a rebate for your new refrigerator, did you

participate in any of the other refrigerator programs?

1 [Yes] P4

2 [No] If <program> = Rebate GOTO A0a.



-97 [Don‘t know]

-98 [Refused]

P4. Which of the other refrigerator programs did you participate in? [Allow multiple responses]

1 Rebate If <program> = Rebate GOTO A0a.



2 Replacement

3 Decommissioning

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

VERIFY GROSS INSTALLATION

A0a. Did the refrigerator you received a rebate for replace an existing refrigerator?

1 Yes A0b

2 No R0

-97 [Don‘t know] R0

-98 [Refused]

A0b. Was the existing refrigerator removed by the company that delivered your new unit?

1 Yes [If <old_brand> is populated GOTO A3a.

Else A3b]

2 No A0c

-97 [Don‘t know] A0c

-98 [Refused]

A0C.


KEMA, Inc. May 14, 2013 F-23

Did you make arrangements with a refrigerator recycling company to remove and recycle your old

unit?

1 Yes [If <old_brand> is populated GOTO A3a.

Else A3b]

2 No A0d

-97 [Don‘t know] A0d

-98 [Refused]

A0d. What did you do with the old refrigerator ?

1 [Kept and used] A3b

2 [Kept unplugged]


A3b


5 [Recycled – taken or picked up]






-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

A1. I have some questions about the refrigerator that was removed because of the decommissioning

program. Our records show you had <ref_qty> refrigerator(s) removed. Is that correct?

1 [Yes]

<NUM REF> = <ref_qty>

IF<NUM_REF> is greater than 1, GOTO (A2)

ElseIf <old_brand> is populated GOTO A3a.

Else A3b

2 [No] A1a

-97 [Don‘t know] IF< <ref_qty> is greater than 1, GOTO A2.


Else A3b -98 [Refused]

A1a. How many refrigerators were removed?

[RECORD VERBATIM]

<NUM_REF> = answer

IF<NUM_REF> is greater than 1, GOTO A2.


Else A3b

-97 [Don‘t know] IF< <ref_qty> is greater than 1, GOTO A2.


Else A3b -98 [Refused]

A2. Were the refrigerators removed at the same time?


KEMA, Inc. May 14, 2013 F-24

1 [Yes] A2b

2 [No] A2a

-97 [Don‘t know] A2b

-98 [Refused]

A2a. I would like to talk to you about the more recently removed refrigerator.

[If <old_brand> is populated GOTO A3a. Else A3b]

A2b Was one of the refrigerators used as a primary kitchen refrigerator?

1 [Yes] A2c

2 [No] A2d

-97 [Don‘t know] A2d

-98 [Refused]

A2c I would like to talk to you only about the unit that was your primary kitchen refrigerator.


A2d. I would like to talk about the removed unit that you used most frequently.


A3a. Was the refrigerator that was removed a <brand>?

1 [Yes]

If <configuration> is populated GOTO A4.

Else A4a

2 [No] A3b

-97 [Don‘t know] If <configuration> is populated GOTO A4.

Else A4a

-98 [Refused]

A3b. What was the brand of that old refrigerator?

[RECORD VERBATIM]

If <configuration> is populated GOTO A4.

Else A4a

-97 [Don‘t know]

-98 [Refused]

1 Admiral

2 Amana

3 Frigidaire

4 GE / General Electric

5 Kenmore

6 Maytag

7 Sears

8 Westinghouse

9 Whirlpool

77 Other


KEMA, Inc. May 14, 2013 F-25

A4. Was that refrigerator a <old_config> ?

1 [Yes] A4b

2 [No]

A4a -97 [Don‘t know]

-98 [Refused]

A4a. Where was the freezer located on that old refrigerator?


A4b

2 [Side by Side]

3 [Bottom Freezer]



6 Freezer Only

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

A4b What was the size of that old refrigerator?


A4c





6 Same as the new refrigerator

7 Bigger than the new refrigerator

8 Smaller than the new refrigerator

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

A4c. Did that old refrigerator have an ice maker in the door?

1 [Yes]

A5 2 [No]

-97 [Don‘t know]

-98 [Refused]

A5. Approximately how old was that refrigerator?

1 [0-5 years]

A5a

2 [5-10 years]

3 [10-15 years]

4 [15-20 years]

5 [20-25 years]

6 [Older than 25 years]

-97 [Don‘t know]

-98 [Refused]

A5a. What would you say was its overall condition? Would you say. . . [If necessary, read options…]


KEMA, Inc. May 14, 2013 F-26

1 It worked and was in good physical condition

IF A2b=1 GOTO A9

If A2b=2 skip to A7

ELSE GOTO A6

2 It worked but needed minor repairs (like a door seal or handle)

3 It worked but had some problems (like it wouldn't defrost)

4 Or, it didn't work

-97 [Don‘t know]

-98 [Refused]

A6. Was that old refrigerator your primary kitchen refrigerator?

1 [Yes] A9

2 [No]


-98 [Refused]

A7. Was that refrigerator plugged in and used all year?

1 [Yes] A8

2 [No]

A7a -97 [Don‘t know]

-98 [Refused]

A7a. How many months was the fridge plugged in and running?

[RECORD VERBATIM]

(If answer=zero skip to R8); else A7b -97 [Don‘t know]

-98 [Refused]

A7b. What months?

[RECORD VERBATIM]


-98 [Refused]

A8. Where in the house was this refrigerator located?

1 [Kitchen]

A9

2 [Basement]

3 [Garage]

4 [Porch]

5 Utility area (Laundry Room, Shop, Utility Room)

77 Other

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-27

A9. How, if at all, is that <insert space name if possible> space heated?

1 [Not heated]

A10

2 [Gas]

3 [Electric]

4 Wood

5 Heat Pump (Air, Ground, Geo)

6 Propane

7 Oil

77 Other

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

A10. Is that an air conditioned space?

1 [Yes] Central Air Conditioner

If program =Decommissioning, GOTO PA0

ELSE GOTO R0

2 [Yes] Room Air Conditioner

3 [No]

-97 [Don‘t know]

-98 [Refused]

REPLACEMENT REFRIGERATOR

R0. Now let‘s talk about the new refrigerator you received <qPAwording> from the <program> program.

IF program= REPLACMENT go to R3.

IF <new_config> AND <new_brand> are populated GOTO R2. ELSE GOTO R2a.

R2. Is the new fridge a <new_config> <new_brand>?

1 [Yes] R3

2 [No]

R2a -97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-28

R2a. What brand is the new fridge?

[RECORD VERBATIM]

R2b

-97 [Don‘t know]

-98 [Refused]

1 Admiral

2 Amana

3 Frigidaire

4 GE / General Electric

5 Kenmore

6 Maytag

7 Sears

8 Westinghouse

9 Whirlpool

77 Other

R2b. Where is the freezer located on the new refrigerator?


R2c

2 [Side by Side]

3 [Bottom Freezer]



-97 [Don‘t know]

-98 [Refused]

R2c. What size is the new refrigerator?


R3





-97 [Don‘t know]

-98 [Refused]

R3. Is this new unit your primary kitchen refrigerator?

1 [Yes]

IF A6=1 GOTO PA0

ELSE R6

2 [No]

R4

-97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-29

R4. Is it plugged in and used all year?

1 [Yes] R5

2 [No]

R4a -97 [Don‘t know]

-98 [Refused]

R4a. How many months is the fridge plugged in and running?

[RECORD VERBATIM] R4b

If Answer=0, skip to R5 -97 [Don‘t know]

-98 [Refused]

R4b. What months?

[RECORD VERBATIM]

R5 -97 [Don‘t know]

-98 [Refused]

R5. Where is the unit located?

1 [Kitchen]

IF R5=A8 GOTO PA0

ELSE R6

2 [Basement]

3 [Garage]

4 [Porch]

77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

R6 How, if at all, is that space heated?

1 [Not heated]

R10

2 [Gas]

3 [Electric]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

R10. Is that an air conditioned space?

1 [Yes] Central Air Conditioner

PA0

2 [Yes] Room Air Conditioner

3 [No]

-97 [Don‘t know]

-98 [Refused]

PROGRAM ATTRIBUTION

PA0. Now I‘d like to ask you some questions about what you would have done if you hadn‘t taken part in

the PSE program.

If program =Decommissioning GOTO PA8


KEMA, Inc. May 14, 2013 F-30

PA1. If you had not received < qPAwording > ‗a new refrigerator‘ when would you have purchased a

refrigerator ?

1 [Sooner than I did]

PA3

2 [Same time]

3 [Within month]

4 [Within the next year]

5 [More than 1 year later than I did]

6 [When it broke]

7 [Would not have purchased]

If A0a=2, -97, or -98 And ‗Replacement‘ Go to S5

If A0a=2, -97, or -98 And ‗Rebate‘ go to S3

If R3=1 or R6=1 Skip to PA9a

Else go to PA8

-97 [Don‘t know]

-98 [Refused]

PA3. Would you have purchased a new or used refrigerator?

1 [New} PA5

2 [Used] PA4

3 [None] PA8

-97 [Don‘t know] PA5

-98 [Refused]

PA4. Where would you have purchased or acquired it?

1 [Appliance Store]

PA5 2 [Craigslist/classifieds]

3 [Second-hand store (Goodwill, etc)]

4 [Friend/Relative]

77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

PA5. Without the <program> program, would you have purchased or acquired a refrigerator that was

larger than, smaller than or the same size as your new refrigerator?

1 [Larger]

PA6

2 [Same]

3 [Smaller]

-97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-31

PA6. Without the < program> program, would you have purchased or acquired a refrigerator with a

different configuration?

1 [Yes] PA6a

2 [No] PA7

-97 [Don‘t know] PA6a

-98 [Refused]

PA6a. What configuration?


PA7

2 [Side by Side]

3 [Bottom Freezer]



6 [With Icemaker]

7 [Without Icemaker]

77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

PA7. Without the program, would you have purchased an Energy Star refrigerator?

1 [Yes] If A0a=2 and ‗Rebate‘ skip to S3

IF A0a=2 and ‗replacement‘ skip to S5

If A0c=2 And ‗rebate‘ skip to S3

If A0c=2 and ‗Replacement‘ skip to S5

Else GOTO PA8

2 [No]

-97 [Don‘t know]

-98 [Refused]

PA8 What would you have done with the old refrigerator if you had not participated in the <program>

program?

1 [Gotten rid of it] PA10

2 [Kept it] PA9


-98 [Refused] S0

PA9. If you had kept the refrigerator, would you have used it or stored it unplugged?

1 [Used] PA9a

2 [Stored unplugged] S0

3 [Both] PA9a


-98 [Refused] S0


KEMA, Inc. May 14, 2013 F-32

PA9a. For how many years might it have kept your old unit running?

1 Less than one year

IF Rebate Skip to S3

If Replacement Skip to S5

If Decommissioning skip to SO.

2 1 to 3 years

3 4 to 6 years

4 7 to 9 years

5 10 or more years

6 [Until it broke]

-97 [Don‘t know]

-98 [Refused]

PA10. How would you have disposed of the unit?


PA10a

2 [Took to recycling center]







77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

PA10a When would you have done this?

1 [Sooner later than I did]

If Decommissioning: S0

If Rebate skip to S3

If replacement skip to S5

2 [Same time as it was done]

3 [Within month]

4 [1-3 months later than I did]




8 [More than 1 year later than I did]

9 [Same time as the new refrigerator was received]

-97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-33

SATISFACTION

S0. How much time elapsed between when you scheduled the appointment and the date the old refrigerator was

picked up?

1 Less than a week

S1

2 One week

3 Two weeks

4 Three weeks

5 Four weeks

6 Five weeks

7 Six weeks

8 More than six weeks

-97 [Don‘t know]

-98 [Refused]

S1. Now I have some questions about your satisfaction with the <program>. Please use a 5 point scale where

1 means ―Very dissatisfied‖ and 5 means ―Very satisfied‖ to rate your satisfaction.

S1b. How satisfied were you with how much time elapsed between when you scheduled the appointment

and the date the old refrigerator was picked up? 1 Very dissatisfied

S1c

2

3

4

5 Very satisfied

-97 [Don‘t know]

-98 [Refused]

S1c. How satisfied are you with the process of scheduling your refrigerator removal?

[IF NECESSARY- Please use the same 5 point scale where 1 means ―Very dissatisfied‖ and 5 means

―Very satisfied‖.]

1 Very dissatisfied

S1d 2

3

4

S2 5 Very satisfied

-97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-34

S1d. Why do you say that?

[ALLOW MULTIPLE RESPONSES]

1 [The rebate application form was too long / the paperwork was too much]

S2 2 [They could not tell me a definite time when they would pick it up]

3 [They could not schedule a convenient time for pickup]

77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

S2. How satisfied are you with the actual pickup of the old refrigerator?

[IF NECESSARY- Please use the same 5 point scale where 1 means ―Very dissatisfied‖ and 5 means

―Very satisfied‖.] 1 Very dissatisfied

S2b 2

3

4 If program = Rebate GOTO S3. (rebate shouldn‘t go here)

If program = Replacement GOTO S5. (replacement should

not go here)

If program = Decommissioning GOTO S3

5 Very satisfied

-97 [Don‘t know]

-98 [Refused]

S2b. Why do you say that?

[DO NOT PROMPT. ACCEPT MULTIPLE RESPONSES. WHEN RESPONDENT SEEMS FINISHED,

PROMPT W/ ―ANY OTHER REASON?‖ BEFORE PROCEEDING]

1 [Damaged my home while removing appliance]

If program = Rebate GOTO S3.

If program = Replacement GOTO S5.

If program = Decommissioning GOTO S3

2 [Didn‘t check that the unit was working]

3 [Did not come on the scheduled date]

4 [Did not come on time]

5 [Not courteous / un-professional staff]

6 [Didn‘t leave check where instructed]

7 [Too much paperwork]

77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

S3. How satisfied were you with the dollar amount of the incentive? [REPEAT SCALE IF NECESSARY-

Please use a 5 point scale where 5 means ―Very satisfied‖ and 1 means ―Very dissatisfied‖]

1 Very dissatisfied

S3b 2

3

4

S4 5 Very satisfied

-97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-35


1 [The rebate amount should have been larger] S4

77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

S4. How satisfied were you with the timeliness of the incentive payment?

[REPEAT SCALE IF NECESSARY]

1 Very dissatisfied

S4b 2

3

4

S5 5 Very satisfied

-97 [Don‘t know]

-98 [Refused]


1 [Rebate payment took too long to arrive] S5

2 [Still haven‘t received rebate]

77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

S5. How satisfied were you with the program as a whole?

[REPEAT SCALE IF NECESSARY]

1 Very dissatisfied

S5b 2

3

4

EA1 5 Very satisfied

-97 [Don‘t know]

-98 [Refused]


KEMA, Inc. May 14, 2013 F-36


1 [The rebate amount was not large enough]

EA1

2 [I haven‘t received the rebate check yet]

3 [The rebate check took too long to arrive]

4 [Damaged my home while removing appliance]

5 [Didn‘t check that the unit was working]

6 [Did not come on the scheduled date]

7 [Did not come on time]

77 [Other]

-77 [Other, specify______________]

-97 [Don‘t know]

-98 [Refused]

ENERGY ATTITUDES

EA1 When purchasing new appliances, do you look for Energy Star labels?

1 [Yes]

EA2 2 [No]

97 [Don‘t know]

98 [Refused]

EA2. How concerned are you with reducing your home‘s energy use? Would you say...

[READ UNBRACKETED OPTIONS.] 1 Not at all concerned D1

2 Somewhat concerned EA3

3 or Very concerned?

97 [Don‘t know] D1

98 [Refused]

EA3. Why are you concerned with reducing your home‘s energy use?

[DO NOT READ. ACCEPT MULTIPLE ANSWERS] 1 [Cost of energy / Reduce energy bill]

D1

2 [Environment / Global warming]

3 [Power availability / reliability]

4 [Dependence on foreign oil]

77 [Other]

-77 [Other, specify______________]

97 [Don‘t know]

98 [Refused]

DEMOGRAPHICS

D1. Which of the following best describes the type of home you live in? Is it a… [READ]

06 Single family, detached,

07 Single family attached, such as town house or row house,

08 Apartment in multi-unit structure of 2–4 units,

09 Apartment in multi-unit structure of 5 or more units, or


KEMA, Inc. May 14, 2013 F-37

10 Mobile Home?

97 DON‘T KNOW

98 REFUSED

D2 Do you own or rent your home?

1 OWN

2 RENT

97 DON‘T KNOW

98 REFUSED

D3. How many years have you lived in your current home?

01___ years [IF <1 YEAR, RECORD 0]

97 DON‘T KNOW

98 REFUSED

D4. Approximately what year was your home built? [DO NOT READ]

08 2006 OR LATER

09 2000 TO 2005

10 1990 TO 1999

11 1980 TO 1989

12 1970 TO 1979

13 1950 TO 1969

14 EARLIER THAN 1950

97 DON‘T KNOW

98 REFUSED

D5. What is the approximate finished square footage of your home? Your best estimate is fine. [DO NOT

READ]

06 LESS THAN 1,2000 SQUARE FEET




10 3,000 SQUARE FEET OR MORE

97 DON‘T KNOW

98 REFUSED

D6. What is the primary fuel used to heat your home? [DO NOT READ]

01 NATURAL GAS

02 ELECTRICITY

03 PROPANE

04 OIL

05 WOOD

06 SOLAR

97 DON‘T KNOW

98 REFUSED


KEMA, Inc. May 14, 2013 F-38

D7. What is the primary fuel used to heat your hot water (water heater)? [DO NOT READ]

01 NATURAL GAS

02 ELECTRICITY

03 PROPANE

04 OIL

05 WOOD

06 SOLAR

97 DON‘T KNOW

98 REFUSED

D9. Including yourself and children, how many people live in your home at least six

months of the year?

01___ RECORD NUMBER OF PEOPLE

97 DON‘T KNOW

98 REFUSED

[IF D9 = 97/98/1 PERSON, SKIP TO D15, ELSE ASK D10]

D10. How many people in your household are under 5 years of age?


97 DON‘T KNOW

98 REFUSED

D11. How many in your household are 5 to 17 years of age?


97 DON‘T KNOW

98 REFUSED

D12. How many people in your household are 18 to 64 years of age?


97 DON‘T KNOW

98 REFUSED

D13. How many people in your household are 65-79 years of age?


97 DON‘T KNOW

98 REFUSED

D14. How many people in your household are 80 years of age or older?


97 DON‘T KNOW

98 REFUSED

[CHECK THAT D9 = D10-D14 MINUS 1]

[IF THEY DON‘T ADD UP, VERIFY RESPONSES TO D10 THROUGH D14 UNTIL

THEY DO]

D15 What is your age?

02 ___ RECORD AGE

97 DON‘T KNOW

98 REFUSED


KEMA, Inc. May 14, 2013 F-39

D16 What is the highest level of education you have obtained? [READ LIST]

1 Some high school,

2 High school graduate, including GED,

3 Some college or an Associate‘s degree,

4 Bachelor‘s degree,

5 Some graduate school,

6 Graduate or professional degree,

97 DON‘T KNOW

98 REFUSED

D17 Next, for statistical purposes only, I‘d like to know your household‘s total 2011 annual income before

taxes. Please stop me when I reach the category that best describes your household‘s income. [READ IF

NECESSARY: This information is confidential and will only be used for characterizing respondents to

this study.] [READ LIST]

1 Less than $25,000,

2 $25,000 to $49,999,

3 $50,000 to $74,999,

4 $75,000 to $99,000, or

5 $100,000 or more?

97 DON‘T KNOW

98 REFUSED

W WRAP UP – ASK ALL

[READ]: Those are all the questions I have for you. Is there anything that you want me to pass on to PSE? Thank

you very much for your time and opinions.

IF YES, RECORD:_____________

RECORD GENDER

3 MALE

4 FEMALE

97 CAN‘T DETERMINE

PSE Ref Impact Final_WithERR

Documents

Transcript of PSE Ref Impact Final_WithERR