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# EPRi lectric Power esearch Institute Topics: Residential energy use End-use consumption Appliances Load research EPRI CU-6952 Project 2863-3 Interim Report October 1990

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Residential Energy Usage Comparison Project:An Overview

Prepared by Quantum Consulting Inc. Berkeley, California

## R'E P O R T S U M M A R
Demand-side planning / Market assessment / Lighting and appliances Residential energy use Appliances End-use consumption Load research DSM and marketing managers / Market and load researchers



## Residential Energy Usage Comparison Project:An Overview An integrated load and market research project hascompared the load-shapeandenergy consumption patterns ofmajor residential electricand gas appliancesand hasyielded new insights into customerpreferences forfuel andappliancetypes.The metered energyconsumption data provide an importantbenchmark for comparingthe costs ofalternative end-usetechnologies.

BACKGROUND

OBJECTIVES

APPROACH Traditional studies of the relative energy consumption of electric and gas household appliances have relied on laboratory analyses and computer simulations. EPRI and the Southern California Edison Company (SCE) jointly sponsored the residential energy usage comparison project to study the appliance energy consumption patterns of actual households. To measure and compare typical energy consumption patterns of comparably efficient residential electric and gas appliances; to determine customer satisfaction with electrical technologies and other factors determining customer appliance choices. The project team identified.92 households in Orange County,California, southeast of Los Angeles, to serve as the scientifically designed study sample. The households were owner-occupied, single-family homes in a highgrowth area, thus representing typical newer homes in the SCE service area. New space-conditioning, water-heating, cooking, and clothes-drying appliances were installed in customers' homes. Half ofthe households received electric equipment and the other half, gas equipment. All of the appliances were metered, and data were collected regularly. The team surveyed the participating households to obtain information on their energy needs and the acceptance of the appliances. RESULTS Appliance energy data gathered from February 1988 to January 1989 revealed the following: *Energy requirements for the electric heat pumps were less than 40% of the energy required by the gas space-conditioning systems during the winter months. Electric heat pump water heaters consumed only 40% of the energy used by the gas water heaters. Electric ranges consumed 38% of SUBJECTS TOPICS
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EPRI CU-6952s - Electric Power Research Institutethe energy of gas ranges, and electric clothes dryers used 80% of thr energy of gas dryers.

The winter-weekday space-conditioning peak load was much smaller for households with an electric heat pump: 1 kW (about 3 kBtulh), cot pared with about 11 kBtu/h for gas furnaces. In addition, analysis of the customer survey data indicated that many customers have a very short required payback period for appliance pu chases. About 40%/require payback on energy efficiency investments in less than two years (through operating cost savings), and 30% require payback in two to five years. EPRI PERSPECTIVE The energy-usage and consumer behavior data developed in this proj ect provide important new information for utility market planners. As a result of the project, SCE and the utility industry have gained new insights into the relative energy consumption patterns of comparable electric and gas household appliances as they are operated in consumers' homes. Utilities can use this information to compare the cost-effectiveness of these options for their customers as part of a demand-side management or market-planning process. In addition, the project clarified consumer fuel-type images and attitudes toward the new appliances. Finally, the project provides an example of calculating load-shape data.for alternative market segments, including energyneeds-based segments determined by EPRI's CLASSIFY computer code (report EM-5908), which can help utilities assess the likely load impacts of attracting particular types of customers through targeted marketing programs. PROJECT RP2863-3 EPRI Project Manager: Steven D. Braithwait Customer Systems Division

For further information on EPRI research programs, call EPRI Technical Information Specialists (415) 855-2411. 

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### Residential Energy Usage Comparison Project: An any Overview

. PU_ ?ntsreCU-6952 Research Project 2863-3 ~roj. s a .Interim Report, October 1990in1-

the Prepared by ting QUANTUM CONSULTING INC. 2030 Addison Street Berkeley, California 94704 id Principal Investigators B.A. Smith R. T.Uhlaner T. N. Cason

Prepared for Southern California Edison Company Project Manager P.Delaney and Electric Power Research Institute 3412 Hillview Avenue Palo Alto, California 94304

EPRI Project Manager S. D.Braithwait Market Assessment Program Customer Systems DivisionORDERING INFORMATION Requests for copies of this report should be directed to Research Reports Center (RRC), Box 50490, Palo Alto, CA 94303, (415) 965-4081. There is no charge for reports requested by EPRI member utilities and affiliates, U.S. utility associations, U.S. government agencies (federal, state, and local), media, and foreign organizations with which EPRI has an information exchange agreement. On request, RRC will send a catalog of EPRI reports.

Electric Power Research Institute and EPRI are registered service marks of Electric Power Research Institute. Inc Copyright © 1990 Electric Power Research Institute, Inc All rights reserved. NOTICE This report was prepared by the organization(s) named below as an account of work sponsored in pan by the Electric Power Research Institute. Inc. (EPRI). Neither EPRI.'members of EPRI. the organization(s) named below. nor any person acting on behalf of anyof them: (a) makes any warranty, express or implied, with respect to the use of any information, apparatus, method, or process disclosed in this report or that such use may not infringe privately owned rights: or (b)assumes any liabilities with respect to the use of. or for damages resulting from the use of. any information, apparatus, method, or process disclosed inthis report. Prepared by Quantum Consulting Inc. Berkeley. California ---- I IIABSTRACT This report provides an overview of the residential energy usage comparison project, an integrated load and market research project sponsored by EPRI and the Southern California Edison Company. Traditional studies of the relative energy consumption of electric and gas household appliances have reliedon laboratoryanalysesandcomputersimulations. Thisproject was designed to study the appliance energy consumption patterns of actual households. Ninety-two households in Orange County, California,southeast ofLos Angeles, served as the studysample. Halfofthe householdsreceived newelectricspace-conditioning,water-heating, cooking,and clothes-drying equipment; the other halfreceived gas equipment.The electric space-conditioning and water-heating appliances were heat pump technologies.All of the appliances were meteredtocollect load-shapeandenergy consumption data.The households werealsosurveyed periodicallytoobtain information ontheirenergy needsand theiracceptance of the appliances. The metered energy consumption data provide an important benchmark for comparing the energy consumption and costsofalternative end-usetechnologies.Thecustomer research results provide new insights into customer preferences for fuel and appliance types.

iii 

## UivEPRI FOREWORD The residential energy usagecomparison (REUC) project has been ajoint effort by EPRI and the Souther California Edison Company to measure andcomparetypical energy consumption patternsofcomparableefficient residential electricand gasappliances.This innovativedemandside project has produced valuable information about how actual households use electricity andgas forspaceconditioning,waterheating,cooking,andclothesdrying.This report provides asynopsisofthe research activitiesand resultsfromthe REUC project. A more comprehensive presentation ofthe project results will be provided in the forthcoming final project report. Steven D. Braithwait, Project Manager Customer Systems Division

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vviviiiCONTENTS
Section Page 1 INTRODUCTION -1-1 Overview ofthe.REUC Project 1-1 EPRI Involvement in the REUC Project 1-5 Report Organization 1-6 2 REUC PROJECT DESIGN 2-1 Introduction 2-1 REUC Project Scope 2-1 Historyof REUC Data Collection 2-4 REUC Sample Design 2-5 Demographic Description ofthe REUC Sample 2-6 3 REUC APPLIANCE ENERGY USAGE 3-1 Introduction 3-1 Load Data Collection and Analysis 3-1 Average Annual and Seasonal Usage 3-2 4 REUC APPLIANCE LOAD PROFILES 4-1 Introduction 4-1 Load Profiles 4-1 5 REUC INTEGRATED MARKET RESEARCH 5-1 Introduction 5-1 Participants' Image ofElectricity and Gas 5-1 Load Profiles by Customer Segment 5-2 Appliance Life-Cycle Costs 5-7

ixxFIGURES Figure Page 1-1 REUC Project Milestones 1-3 2-1 REUC Orange County Survey and Load Data Collection 2-4 History 3-1 Annual Average Energy Usage
- Space Conditioning and 3-3 Water Heating 3-2 Annual Average Energy Usage
- Clothes Dryingand Cooking 3-4 3-3 Difference in Annual Energy Consumption between Gas 3-6 Appliances and Electric Appliances 4-1 SCE REUC: Average Load Profiles
- Winter Weekday Space 4-2 Conditioning 4-2 SCE REUC: Average Load Profiles
- Winter Weekday Water 4-2 Heating 4-3 SCE. REUC: Average Load Profiles
- Winter Weekday Cooking 4-3 5-1 REUC Participant Images of Electric vs. Gas 5-2 5-2 SCE REUC: CP&B Needs-Based Segments

- Summer Weekday 5-4 Electric Space Conditioning 5-3 SCE REUC: Value Factor Segments

- Summer Weekday Electric 5-5 Space Conditioning 5-4 SCE REUC: Quality Factor Segments

- Winter Weekday Heat 5-6 Pump Water Heater 5-5 SCE REUC: Income-by-Square-Feet Segments

- Winter 5-7 Weekday Heat Pump Water Heater 5-6 REUC Participants' Required Payback Periods 5-9 5-7 REUC Space Conditioning Fuel Choice Preference Regions 5-10

xixiiTABLES Table Page 2-1 REUC Participant Demographics
- Sample Design 2-7 Stratification Variables 2-2 FEUC Participant Demographics
- Highest Completed 2-8 Education Level Among Key Household Members 3-1 Average Annual and Seasonal Energy Usage for Orange 3-5 County Sample Households

xiiiSUMMARY This report presents a synopsis of the research activities and results from the Residential Energy Usage Comparison (REUC) project, ajoint effort by Southern California Edison Company (SCE) and the Electric Power Research Institute (EPRI). The REUC project isan innovative demand-side project designed to measure and compare typical energy consumption patterns ofcomparably efficient residential electric: and gas appliances. The results presented in this report pertain to a sample of 92 households in Orange County, southeast of LosAngeles. The REUC Orange County participant sample was designed to represent an important segment of SCE's residential customers, namely owner-occupied, new single-family homes. Overthe past decade, Orange County has experienced significant residential and commercial growth. REUC PROJECT OVERVIEW The REUC project has been designed to assess the energy performance and customer acceptance of new electric and gas appliances. Traditionally, studies that have examined the relative energy efficiencies of electric and gas end-use technologies have relied on laboratory settings or computer simulation models. The nature of the REUC project isto move away from the laboratory setting by relying on the energy demands and customer behavior of actual households. instead of simulated "test bench" usage patterns. The REUC project results have thus accounted for many of the subtle but important determinants of appliance usage, including household characteristics, that are not captured in engineering models. The results presented in this report illustrate thevalue oftwo unique facets ofthe project's design: first, end-use (appliance) load data have been collected for both electric and gas appliances; and, second, both customer survey-data and end-use data have been collected from the participants. End-use data collection began in late 1986 for aportion of the Orange County participants; survey research data collection began in mid-1987. Both end-use data and survey research data

S-1collection concluded in December 1989. The REUC project Final Report will present analysis results usingall the availabledata.
A summary ofthe results presented in this report isprovided below.
ELECTRIC AND GAS APPLIANCE ENERGY CONSUMPTION A principal objective of the REUC project has been to measure electric and gas appliance energy consumption, at point of use. Southern California Edison identified four residential energy uses to be considered in the project: space conditioning, water heating, cooking and clothes drying. These four end-uses were selected because of the direct competition between electricity and natural gas and the development of new, high-efficiency electric technologies. Figure S-1 illustrates the point of use annual average energy consumption (in millions of BTUs forcomparison) for the REUC space conditioning appliances (electric heat pumps relative to gas furnaces/electric air conditioners) and water heating appliances (electric heat pump water heaters and gas water heaters). These results are based on appliance energy data gathered over a one-year period, from February 1988 through January 1989, for the Orange County households. The figure shows that on an annual basis the electric heat pumps consume less than 45 percent as much energy as the gas furnace/electric air conditioner space conditioning systems. As reported in Section 3, electric heat pumps consume less than 40 percent of the energy of the gas systems during the winter season. Inaddition, electric heat pump water heaters consume only 40 percent as much energy as gas water heaters.
Additional results for the REUC project electric and gas appliances' energy consumption are presented in Section 3.

S-2Annual Average Energy Usage Space Conditioningand Water Heating

22.6 SpaceConditioning 10.1

23.7 Water Heating 9.4

MBTU 0 10 20 30 aAt Pointof Use El GasSample

. | Electric Sample | FigureS-1

ELECTRIC AND GAS APPLIANCE LOAD PROFILES An uncommon facet ofthe REUC project has been the collection of both electric and gas appliance load data. The unique pairing of electric and gas end-uses affords an opportunity to carefully compare the daily usage patterns ofappliances with different energy sources. Figure S-2 illustrates the average winter weekday load profiles for both gas and electric space conditioning appliances (electric heat pumps and gas furnaces). Again, these load profiles are based on appliance energy data gathered over a one-year period, from February 1988 through Jariuary 1989, ror the 92 household Orange County sample. As the figure indicates, gasfurnaces have amuch higher

S-3 I II~morning peak (about 11 kBTU per hour) than electric heat pumps. Electric heat pumps, on the other hand, have a lower diversified load (about 3 kBTU per hour or 1 kW) and draw smaller amounts ofenergy over longer periods of time during the day. SCE REUC: Average Load Profiles Winter Weekday Space Conditioning

6 9 12 15 18 21 24 ime of Day (in Hours PST) FigureS-2
Additional REUC appliance load presented in Section 4. profiles developed from end-use data are

CUSTOMER ACCEPTANCE OF APPLIANCES Measuring customer acceptance of the appliances was another objective of the project. The REUC project included the administration of surveys designed to measure the level of new appliance acceptance among REUC participants. Acceptance was measured by allowing the participants to rate their new
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r A:Oppliances among various attributes including reliability,operating cost, response ime and maintenance.
-INTEGRATED MARKET RESEARCH

The collection of both end-use load data and participant survey data isyet another distinctivefeature of the REUC project. Integrated market research isthe creative synthesis of load research information with market research/survey information to provide insight about customers' energy usage behavior patterns. The REUC project surveys included questions designed to estimate participants' appliance investment payback requirements based on their implied discount rates. The higher an individual customer's discount rate for an appliance investment, the shorter the required payback period for such investments. As illustrated by Figure S-3, the REUC participants' required payback periods are generallyquite short, with the vast majority clustered between 0 and 5years. REUC Participants' Required Payback Periods
Percentof 50 Participants
.40
-

30-

20 -

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0 <2 2-5 6-12 13-20 Payback Period (Yrs.) Figure S-3

S-5The REUC project surveys also included questions designed to elicit participants' images of electricity and gas. Figure S-4 portrays the REUC participants' fuel images for electricity and gas. Fuel images were found to be useful for defining customer segments. Factor analysis ofthe REUC participants' fuel images resulted in the derivation of a Qualityfactor (a composite of the Safety, Convenience, Service and Reliability images) and a Valuefactor (acomposite ofthe Appliance Cost, General Expense and Monthly Utility Bill images).

REUC Participant Images of Electric vs. Gas
Dirty Dangerous
Hard to Hookup
Inconvenient Poor Service from Utility
Unreliable Sluggish Heat High Cost Appliances Expensive High Monthly Utility Bills Electricity Image , Gas Image. Clean T Safe EasytoHookup
Convenient Good Service

from Utility Reliable
Fast HeatLow Cost Appliances Inexpensive Low Monthly

Utility BillsFigure S-4

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### _-Figure S-5 illustratesthe use ofthe Qualityfactor for customer segmentation. The figure presents average winter weekday load profiles for participants' heat pumps segmented with the electric and gas Qualityfactors. This figure shows the distinct load shapes for these customer segments.

Figure S-5 The EPRI Customer Preference and Behavior (CP&B) CLASSIFYTM survey was administered to the REUC participants and was also found to be auseful instrument for customer segmentation. Figure S-6 presents average winter weekday load profiles for heat pumps segmented by Appearance Conscious and Value Seekers needs-based segments.

S-7 SCE REUC: Quality Factor Segments Winter Weekday Heat Pump Load

in kW

0 3 6 9 12 15 18 21 24 Time ofDay (in Hours PST)Additional integrated market research results of the REUC project are presented in Section 5.

FigureS-6

S-8 SCE REUC: CP&B Needs-Based Seements WinterWeekday Heat PumD Load 1.2

in kW

0 .3 6 9 12 15 18 21 24 TimeofDay (in HoursPST) v .

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### __ ·Section 1 INTRODUCTION This report presents a synopsis of the research activities and results from the Residential Energy Usage Comparison (REUC) project, ajoint effort by Southern California Edison Company (SCE) and the Electric Power Research Institute (EPRI). The REUC project isan innovative demand-side project designed to measure and compare typical energy consumption patterns ofcomparably efficient residential electric and gasappliances.

OVERVIEW OF THE REUC PROJECT The REUC project has been designed to provide information necessary for assessing the energy performance, the relative cost-effectiveness and the customer acceptance ofnew electric and gas appliances. Southern California Edison has recognized that evaluating key residential end-uses such as space conditioning, water heating, cooking and clothes drying can provide much needed insight intothe energy efficiencies ofthese technologies for the benefit ofits customers. Traditionally, studies that have examined the relative energy efficiencies of gas and electric technologies have relied on laboratory settings or computer simulation approaches in order toassessthese end-usetechnologies' performance. The nature ofthe REUC project isto move away from the laboratory setting by substituting the energy demands of actual households in place of simulated usage patterns. The advantage of this approach isthat itaccounts for many ofthe subtle but important determinants of appliance usage not captured in engineering models, including unobservable household characteristics. The advantages of conducting a "field" experiment are reflected in the value of more comprehensive, realistic assessments of actual customers' usage and response to new electrotechnologies. These advantages offset the reduction in "control" afforded by a laboratory simulationstudy.

1-1

- I II·· · · tSCE Needs The REUC project has been undertaken in part to meet several ofSCE's needs for assessing new electrotechnologies available to residential customers. These needs include: * real-world comparison of electric and gas appliance energy usage; * development of engineering and customer data for energy efficiencyassessmentanalyses; and * evaluation of customer acceptance of electric and gas enduse technologies.
Proiiect Objectives The REUC project was designed to meet these needs by satisfying several objectives: * measure energy usage of electric and gas residential appliances; * compare usage patterns ofsimilar electric and gas appliances;

· * assess customer acceptance of new end-use technologies; and

· generalize results to other residential customers. Project Milestones Since 1985, when the project was firstsuggested by SCE and the California Public Utilities Commission, the REUC has involved three phases: Phase I,from early 1986 through late 1987, included the experimental design, analysis plan and instrumentation installations; Phase II, which consisted of initial data collection and analysis, ran through early 1989. Phase III has consisted ofsubsequent data collection and analysis and ison-going. The major REUC project milestones are illustrated in Figure 1-1

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# REUC Project Milestones 1985 1986 1987 1988 1989 1990

1985
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- Discussions with EPRI Summer 1986
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- Winter 1986
- Irvine Installations Complete Fall 1987
- ProjectAnalysis Plan

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- MissionViejo Installations Complete 

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- Second REUC Survey
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Summer 1989
- Third REUC Survey; Winter 1989
- Final REUC Survey; Equipment Removal

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IEPRI INVOLVEMENT IN THE REUC PROJECT EPRI has contributed to the'REUC project inthree principal areas: projectdesign and planning; 4, projectanalysis; and it project management. Proiect Design EPRI first became involved with the REUC project during its experimental design and planning activities. EPRI project staff emphasized the need to focus on a clear set of objectives of the project, and then to carefully and systematically design the REUC household sample accordingly. The participants would need to accurately represent important segments of SCE's residential customer population. In addition, the REUC experimental design needed to determine how much and what type ofcustomer data should be collected in order to ensure the precision ofsubsequent REUC analyses. Finally, the design needed to include a comprehensive REUC data analysis plan, so that the collected data would be applied to best effect. The REUC experimental design activities took advantage of previous EPRIsponsored research results, including the design'of the Athens Automation and Control Experiment (EPRI EM-4628), and the model-based sample design techniques in EPRI EA-3286. Project Analysis The REUC project has pioneered the integration of load research/load shape analysis with market' research/customer behavior analysis. The project team has developed "integrated market research" techniques and "behavioral engineering statistical techniques (BEST)" to meet the project objectives. These techniques have leveraged upon research results from several other EPRI projects, including the Customer Preference and Behavior (CP&B) Project (RP2671) and the Load Data Analysis Workstation Project (RP2342).

1-5Proiect Management EPRI has assisted SCE staff by offering primary management ofthe REUC project design anddataanalysestasks. SCE staff provided effective' management of the customer contact, equipment installation, and data collection efforts. Members ofthe project team, from EPRI, SCE and the Contractor, have presented preliminary results from the REUC project at numerous industry conferences and meetings. REPORT ORGANIZATION The remainder of this report isorganized as.follows: Section 2, REUC Project Design, describes the design of the REUC project. Section 3, REUC Appliance Energy Usage, presents results from the analysis of twelve months of appliance energy data. Section 4, REUC Appliance Load Profiles, provides examples of appliance load profilesfor the REUC electricand gas appliances. 'Section 5,REUC Integrated Market Research, presents results of integrated market research analyses,suchas participants' fuel imagesand load profiles bycustomer segment.

1-6

II ISection 2 REUC PROJECT DESIGN
INTRODUCTION The REUC customer sample consists of 100 households. These 100 households are comprised of two distinct groupings: eight homes where load monitoring equipment was initially tested, the "equipment test sample"; and 92 homes located in Irvine and Mission Viejo, the "Orange County sample." This report focuses only on data from the REUC's Orange County sample. Irvine and Mission Viejo are located in Orange County along a high-growth corridor between San Diego and Los Angeles. Over the past 20 years, this area has undergone atransition from alightly populated agriculturally based economy to a metropolitan area consisting of high-technology research and manufacturing industries. The population is largely new to the area and represents a diverse cross-section ofother parts ofthe SCE service area and ofthe country. We first describe the design of the Orange County portion of the REUC project and then provide an overview of the project. The history of the REUC data collection follows, and then the sample design procedures and criteria are discussed. Finally, we present the resulting demographic characteristics of the REUC Orange County sample.
REUC PROJECT SCOPE Southern California Edison identifiedfour residential energy usesto be considered in the REUC project
- space conditioning, water heating, cooking, and clothes drying. They were selected because these end-uses represent a majority of residential energy consumption and the development of new, efficient electric technologies. Because the project has been designed to provide direct comparisons between similar gas and electric appliances that might be installed in new homes, new space conditioning, water heating, and clothes drying appliances were installed in both gas and electric homes. Inthe Electric Sample, households were retrofitted with heat pumps for both space conditioning and water heating.
2-1

0I, I:~TheGas'~Samplewas retrofed with efficient gas furn~aces,-electric ait conditionThe Gas Sample was retrofitted with efficient gas furnaces, electric air conditioners, and gas water heaters.. In addition, these gas and electric homes were selected from the same housing tracts, in order to reduce variation induced by building envelope characteristics. The heat pump space conditioning systems have connected loads of approximately 6 kW, or 20.5 kBTU/hour. The heat pump systems have a resistance backup system designed to provide supplemental heat on cold days; this system can draw loads upto 16 kW. The gas homes are equipped with high efficiencygas heating systems that have capacities ofapproximately 60to 72 kBTU/hr and electric fans that have loads under 800 watts. As mentioned above,the electric homes received new electric heat pumps for space'conditioning (typical Seasonal Energy Efficiency Ratio [SEER] of 9, or Heating Season Performance Factor 'HSPF] of 7)and heat pump water heating (Coefficient of Performance [COP] of 3).- The gas homes received new gas furnaces (80 percent efficiency), electric air conditioners (typical SEER of 9)and gas water heaters (58 percent efficiency). The cooking appliance experiment relies on the existing gas and electric resistance ranges, except in the Mission Viejo electric test sites, where new electric induction ranges were installed. The induction cooktop uses a high-frequency, electronically controlled electromagnet to produce.heat inferromagnetic cookware. Induction stoves feature the same quick responsiveness as gas ranges because of their low thermal capacity. Also, they are safer than either electric resistance or gas cooking because the cooking surface remains relatively cool. Though no new technologies have been applied to clothes drying, new gas and electric clothes dryers were installed in the test homes to evaluate customer attitudes and collect end-use consumption information. In addition to energy usage comparison, the REUC project data can support assessment ofqualitative differences between appliance technologies and fuels. In attempting to measure these differences, the REUC project differs from most other customer load monitoring projects in two key ways. First, all participants have hadtheir homes retrofitted with new appliances, halfwith gas appliances and halfwith electric or electric heat pump appliances. Second, the participants have been repeatedly surveyed in order to assess their experiences with their new 2-2 4-. 

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# I iappliances and the influencethese appliances may have had ontheir image ofgas and electricity. Since in the selected test areas almost all homes rely on gas for space and water heating, the REUC experiment inthese cases consists ofasample of fuel-switched former gas customers matched with a"control group" of comparably equipped gas customers. The REUC project analyses cover three main topic areas: realized appliance energy usage comparisons; load profile analysis; andthe integration ofthese topics with market researchdata. Each ofthese areas issummarized below. Energy Usage Comparisons Comparisons of the appliances' energy usage have been made by customer strata that reflect the initial sample design, as well as by appropriate alternative stratifications or segmentations of the sample derived from the analysis of the market research data. These energy usagecomparisons account for seasonal andweather effects. Load Profiles The REUC load profiles can aid utilities in assessing the cost-effectiveness of promoting customer adoption of particular appliances. The estimated REUC'load profiles also have been combined with the project's market research/attitudinal data in an attempt to understand the factors influencing the load shapes. The unique pairing of gas and electric homes affords an opportunity to carefully compare the usage patterns of appliances with different energy sources, since gas end-use data are rarely collected. Market Research Analysis The REUC market research was undertaken to better understand customer attitudes and behavior toward the electric and gas appliances. Analysis of the market research data has concentrated on three basic issues. First, these data were used to determine which aspects orfeatures of gas and electricity affect customers' images ofthose energy sources. Are these features limited to cost, or do they include other qualities associated with thetwofuels? Second, analysisofcustomer reaction to the performance of their new appliances allows qualitative assessment of non-pecuniary benefits, notjustthe dollar value of the savingsfrom operating and capital costs. Finally, the integration of this expanded set of 2-3

I I Icustomer data with the traditionally collected set of household characteristics enhanced the capability to model, or explain, customer energy usage by different market segments. HISTORY OF REUC DATA COLLECTION The REUC Orange County data collection activities have consisted of load and surveydata collected from twosamples: 42 homes in MissionViejo and 50 homes in Irvine. Figure 2-1 summarizes the surveyand load data collection activitiesfrom September 1986 through December 1989 of the REUC project.

Figure 2-1 Four different survey instruments have been administered to each sample. The first survey, REUC-RSS, was designed to gather specificappliance saturation data in order toselect prospective participants. The REUC-RSS survey instrument isbased on the SCE 1985 RSS survey but augmented by several attitudinal and demographic questions. The second survey, administered in June 1987, contained all new questions which focus on customer attitudes towards attributes offuel types and end-uses as well as the customer's propensity to "invest" in energy-efficient appliances. The third survey instrument included refined versions of the second

2-4 REUC Orange Couity Survey and Load Data Collection History
9/86 6/87 3/88 6/8.9 12/89 Mission I I Viejo R M1 M2 M3 M4 Irvine I I R M M 2 : M3 M4
I- '= Load data collection R = REUC-RSS survey Mi = REUC Market Research survey II

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I Y

__ _ __ Isurvey's questions, additional questions that measure customer acceptance ofthe new appliances, and the EPRI "20Question" CLASSIFYTM questionnaire. Inorder to perform longitudinal analysis of the participants' acceptance ofthe new appliances, thethird survey was administered twice (March 1988 andJune 1989). The fourthand final surveywasashorter version ofthethird surveyand contained portions of SCE's'residential attitude survey instrument. Inthisway, thefinal survey measures the long-term acceptance ofthe REUC appliances and provides alinkto similar surveysadministered to other SCE customers. Appliance load data collection has continued through December 1989. As is shown, the data collection history for the Irvine sample differs from the Mission Viejo sample. In Phase I, the REUC project was limited to the Mission Viejo sample and was primarily envisionedas an end-use load monitoring project. Once the Mission Viejo sample was selected and retrofitted with new appliances, the scope ofthe project broadened in Phase IIto include asecond customer sample in Irvine and to undertake acomprehensive market research study. As aresult of adding Irvine, "before" (before the new appliances were installed) and "after" market research data were collected for these 50 homes. REUC SAMPLE DESIGN Inorder to identify a potential sample of Orange County residential customers, SCE administered an initial survey, called the REUC-RSS, to 2,380 potential participants. This surveywas based on SCE's 1985 Residential Saturation Survey. From the 756 survey responses, asubset ofpotential participants wasvisited bySCE project staff to gather additional information on specific appliances in the household, household characteristics, and occupancypatterns. Extensive experimental design analysis was undertaken to identify asample of customers that could provide the most pertinent and valuable information for the study, namely end-use load shapes and customer characteristics, within the constraint imposed by abudget limitation to asample of92 households. Analysis was performed on key demographic variables used as stratification variables in load research projects. Ultimate selection of the stratification variables reflected the project objectives of selecting asample thatwas statistically supportable and that represented key customer segments of interest to SCE. In particular, this

2-5sample represents the owner-occupied, single-family new home market in SCE's large Southern Division. A related design goal was to determine the optimal allocation of the available 92 sets of appliances and energy' monitors so that the difference in energy usage between electric and gas appliances could be measured as accurately as possible. This allocation was achieved by identifying observable household characteristics that best predict overall household electric load shape and then stratifying the sample according tothose characteristics. Required sample sizes were calculated using estimated variancesdetermined in the experimental design analyses and the criterion that a95 percent confidence interval around the estimated difference in energy usage between gas and electric appliances be no wider than 5 percent of total load foreach appliance. Household income and square feet were selected as the key stratification variables. Inorder to control forthe effects ofother household characteristics, the sample islimited to'single-family owner-occupied homes built between 1975 and 1982. Inaddition, an attempt was made to select households with between two and five members. Age and education level of the head of household were not controlled for in the sample design. DEMOGRAPHIC DESCRIPTION OF THE REUC SAMPLE Analysis of utility demand-side programs typically can involve relating customer energy usage, appliance choice, and program acceptance to key demographic variables, such as household income, age of head of household, and family size, and dwelling characteristics such as square feet, number of bedrooms, and type. These data describing household characteristics and appliance inventories were collected for the REUC bysurveying the REUC Orange County participants. Table 2-1 tabulates the key demographic data for the REUC sample based on the stratification variables. The determination of household characteristics by which the sample was drawn was based on the REUC project's objective of studyingthe customer segments that best represent the characteristics of persons in the new home market. Table 2-2 illustrates the distribution of the highest education level completed among the heads of household. Education was identified as an

2-6 

# I

Iimportant potential stratification variable. Unfortunately, the sample size limitationscould notsupport level ofeducation as aseparate stratification variable.

Table 2-1 REUC Participant Demographics Sample Design Stratification Variables ElectricSample
House Size SMALL Lessthan'1750 sq ft Income < $50K 50-80K > 80K Number of Irvine

12

2 Households Mission

Vieio 3 5 1 MEDIUM 1750 to 2000 sq ft LARGE Greaterthan 2000 sq ft

Gas Sample
House Size SMALL Less than 1750 sq ft Income < $50K 50-80K > 80K Number of Irvine 2 12 Households Mission

Vieio

3 5 1 MEDIUM 1750 to 2000 sq ft
LARGE Greaterthan 2000 sq ft < 50K 50-80K > 80K <50K 50-80K > 80K 4 6 2

21 2 8 1 25

< 50K 50-80K > 80K
< 50K 50-80K > 80K 4 6 2

21 1 8 2 25

2-7Table 2-2 REUC Participant Demographics Highest Completed Education Level Among Key Household Members

Level Completed High School 2-Year Associate Bachelor Masters Doctorate Electric Sample Number of Households Irvine MissionVieio 2 3 3 4 14 3

5 6 1 2
Gas Sample Number of Households Irvine MissionVieio 1 2 Level Completed High School 2-Year Associate Bachelor Masters Doctorate 5 8 10 3 8 2 2

2-8 I

ISection 3 REUC APPLIANCE ENERGY USAGE

INTRODUCTION This section presents asynopsis of results from the analysis of twelve months of energy data collected from the REUC participants, followed by adescription of how the end-uses are monitored, how the data are collected, and adescription of the analysis methodology employed. We then present estimates, for each end-useandfueltype, ofaverage seasonaland annual energy usage. LOAD DATA COLLECTION AND ANALYSIS End-use load data were gathered from householdsforthe REUC project with load monitoring devices, each equipped with load measurement channels that record usage readings infive-minute intervals. Each household provides data on from four to twelve channels. This section summarizes resultsfrom the edited energy data from the REUC's Orange County customer sample. Total household electric usage iscollectedfrom each site, providing an important cross-check for validating the end-use data. Each load monitoring device downloads its data via modem to the central station microcomputer approximately once per week. Simultaneously monitoring both' gas and electric appliances from a single household including heat pump technologies posed new data collection and validation challenges. Moreover, this isthe first SCE load monitoring project conducted entirely with microcomputers rather than mainframe computers -- from initial data collection tofinal data analysis. As noted earlier, the load data were downloaded from the recorders to amicrocomputer via modem. The data were then written to cartridgetapes and mailed tothe EPRI contractorfor analysis. The REUC data analyses have been performed onthe EPRI Load Data Analysis Workstation (LDAW), amicrocomputer-based customer data analysis system. This has allowed rapid validation of monitored load data so that malfunctioning monitors 3-1

I I_ a I~Iand applianceswere quickly identified. Before consumption estimates and load shapes were developed, the data were extensivelyscreenedforvalidity. The twelve months of usage data presented in this report span the period February 1988 through January 1989 for both the Irvine and the Mission Viejo samples. Therefore, the complete 1988 summer season and acomplete winter season, beginning and ending in the month of February, isanalyzed for both cities. The final project report will includeanalysisofnearlyone additionalyear of data resulting in coverage of two complete summer and nearly two complete winter seasons. To assure aconsistent weighting ofweekdays and weekends, a "month" contains either acomplete four- or five-week period that closely, though not exactly, corresponds to thetrue calendar month.
AVERAGE ANNUALAND SEASONAL USAGE The average annual total usage for space conditioning, water heating, cooking and clothes dryingare presented inFigures 3-1 and 3-2.1 Energy consumption is given in MBTUs for direct comparison between the gas and electric samples. These average usage figures are also presented in their natural units (kWh and therms) and broken down by season inTable 3-1.2 During the observation period in Irvine, there were 206 cooling degree-days (base 75) during SCE's summer season and 607 heatingdegree-days (base 65) during SCE's winter season. The types ofappliances monitored differ by end-use category.' The space heating and water heating appliances are heat pumps for the electric sample,'which, given their expected engineering performance, should consume correspondingly less energy at point of use than the gas furnaces and water heaters. The electric and gas clothes dryers differ only by fuel type; although the total energy consumption of the gas dryer includes the electricity consumed by its motor.' The electric and gas ranges also differ principally by fuel type; however, half of the electric ranges inthe Irvine sample were induction ranges,as described earlier.

1All the energy comparisons made in this report are at the point of use; energy losses from generation and transmission are not reflected in these numbers. 2Summer isdefined by SCE as the months of June, July, August and September. These are the four months always used in generating summer usage and load profiles. The remaining eight months define the "winter" season. 3-2 

# IFigure 3-1 Space Conditioning As seen in Figure 3-1, the average annual household energy consumption for the electric heat pumps amounts to 45 percent of the gas furnace/electric air conditioner consumption. For the four-month summer period, electricity consumptionfor air conditioning isnearly identical for thegas and electric samples
- at about 800 kWh. During the eightwinter months, however, energy consumption for space conditioning for the electric sample amounted to less than 40 percent of that for the gas sample (winter usage could not be readily separated into space heating and airconditioning).

3-3

- III I u·w-IVMMi

Annual Average Energy Usage

Clothes DrvinvandCnnMna

4.7

3.4


# L

. I al I

0 1 2 At point ofuse. Gasclothes drying includes0.39 MBTU ofelectricity consumption for motordrive. UiTI I I I 3 4 5

| Gas Sample | | Electric Sample
Figure 3-2

Water Heating The electric sample's heat pump water heating consumption represents 40 percent ofthe consumption ofgas for the gas sample (aratio of gas to electric of 2.7 to 1). Seasonally, the ratio of energy consumption for the gas homes to the electric homes varies from 2.5 in the winter to 2.7 in the summer. Clothes Drying Clothes dryer energy consumption for the electric sample averages 80 percent of that for gas dryers. Note that the electric motor amounts to nearly 10 percent of the energy consumption ofgas dryers.

3-4 Clothe; Drying

Cooking

I' 6 W . , Ae**I

.~~~~~~~~~~. 

# d

I R~~-

- - - - . - . R

. , ^ . . p

. ^^^^^^^^^
_ |^^mE^flm^^ 13.

I

--- 

## I

I

a

_ I..W.iTable 3-1 Average Annual and Seasonal Energy Usage for Orange County Sample Households

Electric Sample kWh MBTU Gas Sample (Gas Components) MBTU Gas Sample (Electric Components) kWh MBTU Appliancea Whole Houseb Space Cond.C Water Heating Clothes Dryer Oven/Range Annual Average Usage (12 months) 14100 48.20

2970 2750 1100

390 10.10 9.38 3.76 1.33 NA 18.40 23.70

4.33 3.44 Winter Average Usage (8 months) Whole House Space Cond. Water Heating Clothes Dryer Oven/Range 9900 2160 2020

770 270 33.80 7.35 6.90 2.63 0.93 NA 18.30 17.00

2.93 2.37 5030 430 NA

76 NA 17.20 1.47 NA 0.26 NA
Summer Average Usage (4 months) Whole House Space Cond. Water Heating Clothes Dryer Oven/Range 4200 810 730 330 120 14.40 2.75 2.48 1.13 0.40 NA 0.10 6.60 1.40 1.07 3090 790 NA

37 NA 10.60 2.70 NA 0.13 NA
aClothes Dryer, Oven/Range and Water Heating are electric and gas appliances in the electric and gas samples, respectively. bWhole House isthe electricity usage forthe entire home. cSpace Conditioning is aheat pump in the electric sample and agas furnace and conventional electric air conditioner in the gas sample.

3-5 8120 1220

NA 113 NA 27.80 4.17 NA 0.39 NARange Somewhat surprisingly,the energy consumption for gas ranges is2.6 times that of the electric ranges. Finally, as shown in Figure 3-3, total household energy consumption for thefour end-uses averages nearly 30 MBTU less for the electric sample than the gas sample, with the largestsavings accruingto heat pump water heaters.

Figure3-3

3-6 Difference inAnnual Energy Consumption between GasAppliances and ElectricAppliancesa

Space Conditioning

14.3 Water Heating

2.1 Cooking

Clothes Drying

O 5 10 15 At Point of Use AtPoint of'Use 20 · I "--

I I--

- uI

An t

P *jSection 4 REUC APPLIANCE LOAD PROFILES
INTRODUCTION This section provides illustrative examples of the appliance load profiles developed from the REUC Orange County load data collected during the 12- month period between February 1988 through February 1989.
LOAD PROFILES Once again, the REUC appliance load data are unique inthat dailyenergy usage patterns of both electric andgas residential appliances have been calculated and compared from field data. The data were collected at five-minute intervals and subsequently averaged over half-hour or hour periods for purposes ofanalysis and graphical presentation. The data also have been aggregated over several day types in order to display the load profile results shown here. Figures4-1 through 4-3 illustrate selected average load profiles for the Orange County sample, for winter weekday space conditioning, water heating; and cooking, respectively. These profiles indicate the relative energy usage of the two fuel types, as well as the different daily usage patterns. Ingeneral, the load profile results mirror the'seasonal and annual energy usage presented in the previous section. The load shapesfor electric and gas appliances appear quite similar, differing primarily in the amount of energy under the respective's curves. Electric ranges alsoappear to have both lower peak usage as well as lower average energy usagethancomparable gas ranges, asshown in Figure 4-3.

4-1

I rFigure 4-1

SCE REUC: Average Load Profiles WinterWeekday Water Heating kBTU 10 per Hour

- Electric HP Water Heater

- Gas Water Heater 8 A
6 %

4

. I , I \

I

. i

0 3 6 9 12 15 18 21 24 Time of Day (in Hours.PST) Figure 4-2
4-2 SCE REUC: Average Load Profiles WinterWeekday SpaceConditioning kITU 12 per Hour 10

8

6

4

2

0 0 3 6 9 12 15 18 21 24 TimeofDay(in HoursPST)

-- · II iFigure4-3

4-3 SCE REUC: Average Load Profiles Winter WeekdayCooking kBTU 2.0 per Hour ElectricRange

---- GasRange

I\ I/

A I '
A 1.0 I ;\ \I % I 'I A\ I 0.0 ,, ·,
0 3 6 9 12 15 18 21 24 Time ofDay (inHours PST) II I--

II I--



### _ 1- aISection 5 REUC INTEGRATED MARKET RESEARCH
INTRODUCTION Integrated market research isthe creative synthesis of load research information with market research/survey information to provide insights about customers' energy usageand behavior patterns. This section provides asummary ofseveral of these resultsfrom the REUC project. PARTICIPANTS' IMAGE OF ELECTRICITY AND GAS The reliance on electricity and gas for particular end-uses in different regions of the country varies due to regional differences in prices and supplies of various fuels, climatic influences onthe efficiency ofappliances (e.g., heat pumps invery cold climates), and "other" factors. The results presented in this section begin to explore the "other" factors from the perspective of treating electricity and gas as products that have certain distinguishing qualities, or images. Here, the REUC Orange County participants' images of electricity and gas, as: heating fuels, are analyzed. Customers' images of electricityand gas have been derived by analyzing responses to the series offuel image questions contained in the REUC surveys. Figure 5-1 displays REUC participants' assessment ofarange ofqualities or characteristics of natural gas and electricity as fuel sources. Electricity appears to dominate gas on cleanliness and safety but suffers from an image of being more costly. The results for the list of qualities were reduced through factor analysis to apair offactors
- "Quality,"acomposite of the Safety, Convenience, Service and Reliability qualities;and "Value," representing elements of Expense, Appliance Cost, and Monthly Utility Bill qualities. These factors were used subsequently in various segmentations ofcustomer energy usagepatterns.

5-1REUC Participant Images ofElectric vs. Gas
Dirty Dangerous
Hard to Hookup
Inconvenient PoorService from Utility Unreliable Sluggish Heat High Cost Appliances Expensive High Monthly Utility Bills Electricity Image Clean Safe Easyto Hookup
Convenient Good Service

from Utility Reliable
Fast Heat--'-
LowCost Appliances Inexpensive Low Monthly

UtilityBills

## tZ-J

Gas Image
Figure 5-1

LOAD PROFILES BY CUSTOMER SEGMENT This section discusses the integration of the REUC's market research based customer data with data about the REUC participants' end-use energy consumption, using behavioral engineering statistical techniques (BEST).
These results provide information on appliance load profiles for different market research-based customer segments, giving utility market planners the capability to assess the value oftargeting demand-side programs to,that segment.

5-2 

# A.I I I___

I ''

- III - .' I -------- ;i------------ IThe results shown below demonstrate the value of developing integrated databases for demand-side programs consisting of both behavioral and engineering data. These techniques use existing utility customer data as afoundation to systematically address both "traditional" as well as new demand-side planning issues, producing enriched characterizations ofcustomer segments. Inthis section, average load shapesare calculatedfor several alternative customer subgroups of the sample. Three different stratification schemes are employed: the Customer Preference and Behavior (CP&B) CLASSIFYTM scheme, the factor analysis described inthe previous section, andthe traditional income/square foot stratification often used to define residential customer segments. For brevity, four of the many possible subgroup stratifications are presented here for two electric end-uses. Summer weekday average electric space conditioning load profiles are shown in Figures 5-2 and 5-3. Load shapes for "Appearance Conscious" and "Value Seekers," two ofthe six CP&B needs-based segments, are presented in Figure 5-2. The Value factorscore stratification from thefactor analysis ispresented in Figure 5-3. As noted inthe previous section,factor analysisofthe participants' responses to the image questions from the REUC surveys indicate that these customers possess distinct images of electricity and gas (see Figure 5-1). For each REUC respondent, a different factor score for the Quality and Value measures is calculated. Inthe stratification shown in Figure 5-3, the customers are grouped by their electric and gas Value scores (high versus low). The. figure shows four stratifications for summerweekday electric space conditioning. Interestingly,the space conditioning loads for thosecustomers with alowvalue score for electricity appear here to have ahigher peak (and usage) than those with ahigh valuescore. A low Value score indicates that the customer considers electricityan expensive fuel. Therefore, Figure 5-3 shows that customers with higher electricity usage have a stronger image of electricity as an expensive energy source. This conclusion isconsistent with studies atother utilities.

5-3

I· _. UI rFigure 5-2

5-4 SCE REUC: CP&B Needs-Based Segments Summer Weekday Electric SpaceConditioning Load

in kW

0 '3 6 9 12 15 18 21 24 .Timeof Day (in Hours PST)



# .SCE REUC: Value Factor Segments

Figure 5-3 Winter weekday average electric heat pump water heating load shapes are .shown iin Figures 5-4 and 5-5. Two Qualityfactor score stratifications are presented in Figure 5-4
- customers whose quality scores are high for electric and low for gas and customers whose quality scores are high for gas and low for electric. This dimension offuel image also groups customers intodistinct load shapes, with higher loads for those havingarelatively lower electric quality score. A more traditional stratification scheme, income-by-square-feet, is presented in Figure 5- 5. The load shapes for these customer subgroups have somewhat different profiles, but appearfar less distinctthanthose in Figure 5-4.

5-5 Summer Weekday ElectricSpace Conditioning Load 1.2-

in kW kW Lo Electric/Lo GasValue 1.0
- .------- Lo Electric/Hi Gas Value

.-.-- - . Hi Electric/Lo GasValue 1.0- Hi Electric/Hi Gas Value 0.8

0.6 1 AA 0.4-

Time of Day (in Hours PST) Time of Day (in Hours PST) I

__ _



### U I, ,SCE REUC: QualityFactor Segments Winter Weekday Heat PumpWater Heater Lced 1.0-

in k

- to Electric/Hi GasQuality 8---- Hi Electric/Lo GasQuality 0.8

0.2-

0.0

. 0 3 6 9 12 15. 18 21 24 Time of Day (in Hours PST) Figure 54 These REUC load profile results illustrate the potential value of developing integrated databases for demand-side programs consisting of both behavioral and engineering data. Segmenting customers on the basis of energy needs and fuel image will prove valuable both for attracting customers to specific demand-side programs and for targeting those customers with more attractive load shapes and usage patterns. 0.0 · · , , - - ,'- ' ,- , ' 0 3 6 912 15. 8 21 2 ~~~~~~im ofDy(nHusPT mmmmm~~~~~~mlmm

~ ~ ~

usage patterns. ,

5-6

'II~~~~~~~~~~~~~~~~~~Figure 5-5

APPLIANCE LIFE-CYCLE COSTS One ofthe objectives of the REUC project was to collect sufficient information to permit, a comparison of the range of overall customer costs of operating comparable sets of electric and gas appliances.' Another application of the integrated market research data has been comparison of electric and gas appliance life-cyclecosts. Thefollowing discussion summarizes several aspects of these analyses. The cost comparison approach developed for these analyses, termed the Cost Payback Approach, combines appliance purchase price, energy consumption, fuel price and customer survey data collected on the project to compare the life-cycle costs of the monitored appliances. The results for space conditioning appliances are summarized here. Water heating, drying, cooking and whole house life-cycle costs alsowere analyzed.

5-7 SCE REUC: Income-by-Square-Feet Segments

Winter Weekday Heat PumpWater Heater Load 1.0

in kW 0.8

0.6

0.4

0.2

0.0 0 3 6 9 12 15 18 21 24 Time of Day (in-HoursPST)

_ _LI, I ma~~~~~~~~~~~~~~~~~~~~~~~~~~~~The cost comparison method istermed the Cost Payback Approach because it is based on calculating a range of life-cycle costsfor electric and gas appliances based on arange of customer payback periods. The approach accounts for the three cost components of a customer's appliance investment decision: (1) appliance operating costs; (2)the appliance's capital costs; and (3)the customer's required payback period. The cost information has been derived from the REUC end-use load data and other sources. The customer required payback periods havebeen derived from the REUC survey responses. As used here, customer payback periods represent the amount of time needed before an initial energy investment isrecovered through reduced operation costs. Requiredpayback period represents the maximum length of payback period that a customer will accept in deciding upon an energy investment. Required paybackperiod isclosely related to the concept of implicitdiscount rate.1 Higher consumer implicitdiscount rates imply shorter required payback periods. Analyses ofsurveyresponsesto aseries ofquestions on possibleenergy investment decisions indicate that the required payback period on an energy investment for almost three-quarters of the REUC customers is'less than five years. The distribution of these customers' required payback periods isillustrated inFigure 5-6, rangingfrom lessthan twoyearsto 20years. In many areas, natural gas for residential customers is currently priced more favorablyon aBTU basis than iselectricity. Thus, gas systems (gas furnace/electric air conditioner) generally cost less to operate than standard electric (resistance heating/air conditioning) systems. However, the improved energy efficiency of heat pumps over standard electric systems closes the gas-electric cost gap considerably. For customers with ashort payback period (implying less importance on future operating cost savings), asmall capital cost advantage for heat pumps over agas system will result in lower life-cycle costs for the heat pump system. That is,the somewhat lower operating cost ofthe gassystem can be offset byalower cost heatpump systemto result in lower life-cyclecosts.

1See "Implicit Discount Rates in Residential Customer Choices," February 1988, EPRI EM-5587, for asurveyofestimates.5-8

.. ~~~~~~~ ~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.- ,v IREUC Participants' Required Payback Periods

Figure5-6 The Cost Payback Approach results illustrate thisfinding. Figure 5-7 indicates the combinations of appliance capital cost differences and payback periods forwhich electric heat pumps have a lower life-cycle cost than comparable gas systems. Each point on the curve has been derived by combining the REUC appliance energy consumption averages and payback information.. Itshould be noted that the estimates of electricity. and gas consumption exhibit a range around an average value. The curve shown in Figure 5-7 represents the fuel choice "indifference curve" based only on these average values. The shaded region on the figure indicates the combinations of capital cost differences and payback periods for which the electric heat pump has alower life-cycle costthan the gas system.

5-9 Percent of 50 Participants

40

30

20

10

0 <2 2-5 6-12 1-3-20 Payback Period (Yrs.)


### 'narrows the gap between the operating costs of electric and gas appliances. Using the average customer operatingcosts and distribution ofrequired paybacks, the Cost Payback Approach analyzes the life cycle costs of the newer electric appliances relative to gas appliances. This approach combines information measured directly by the REUC project
- energy usage and required paybacks
- and leaves assumptions about relative capita! costs as an unknown that can be filled inbythe readerwhen examining Figure 5-7. It isimportant to remember that underlying a life cycle cost analysis are various assumptions about customer appliance utilization, required paybacks, and the capital and installation costs of the appliances themselves. The results of this approach for individual customers will vary. Each customer utilizes appliances differently and has adifferent forecast ofenergy prices and overall assessment of future uncertaintythat affects its required payback. Furthermore, life cycle costs are only one of many appliance attributes that may be considered by a customer selecting an appliance. The fuel image results support the conclusion that customers value non-cost characteristics of fuelsthat are the energy source for appliances. These non-cost attributes can be given a dollar value and used to adjust the "Required Capital Cost Difference." For example, if electricity isperceived to be cleaner and more reliable than gas, a dollar premium for this attribute can be used to lower the required capital cost difference to equalize the life cycle costs since customers would be willing to pay more for electric technologies.

5-11