Summary of California DSM impact evaluation studies

Brown,; Mihlmester, P.E.

doi:10.2172/10105917

Cited by 4 publications

(3 citation statements)

References 2 publications

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“…There is no single reason to explain the discrepancy between the pre-program estimates and our savings estimates, based on actual billing data. This difference, however, is very consistent with the findings from numerous other evaluations that examined pre-program estimates (Brown and Mihlmester 1994). We have reviewed the pre-program analysis (see Lee et al 1995) and find that several factors might contribute to the difference between those results and ours.…”

Section: Comparison With Other Resultssupporting

confidence: 87%

Impact Evaluation for the Manufactured Housing Acquisition Program (Map)

Lee¹,

Taylor²,

Schrock³

et al. 1995

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EXECUTIVE SUMMARYThis report presents the results of an impact evaluation of the Manufactured Housing Acquisition Program. This evaluation was conducted for Bonneville by Pacific Northwest Laboratory to determine MAP'S energy impacts and cost-effectiveness. Two other reports supplement this overall report on the evaluation. Lee et al. (1995) provides technical details of the study. Sandahl, Lee, and Chin (1995) presents detailed information about the home owner survey conducted for this evaluation. DATA COLLECTIONTo estimate MAP savings we developed MAP and baseline home samples. We conducted telephone interviews to collect home and owner information for both homes. We completed 167 MAP occupant interviews and collected 134 utility billing release forms. For the baseline homes, we completed 183 interviews and obtained signed utility billing release forms from 123 respondents. ANALYSIS OVERVIEWWe conducted a three-tiered analysis of the utility billing data to estimate program electriccty savings. The first (a raw billing data comparison and simple regression analysis) and second (PRISM) tier analyses provided useful findings for the third-tier analysis by which program savings were estimated.The third-tier approach used a conditional demand type regression analysis to analyze monthly energy consumption, taking into account significant factors likely to influence electricrty usage. We used the regression results to estimate energy savings under "normal" weather conditions for each climate zone.For purposes of estimating savings we had to define a comparison home based on typical characteristics. The "pre-MAP baseline" home represents a home with dimensions typical of current homes, but with an efficiency level typical of homes built prior to MAP. The electricity savings estimates were very sensitive to assumptions made about the use of non-electric (primarily wood) space heat; about 20% of our combined sample of homes used some non-electric heat. We found no consistent evidence that MAP homes used non-electric heat more often.iii We used two approaches to estimate energy savings impacts of MAP. In the first, we calculated electricity savings based on the overall observed m'ix of heating types. In the second case, we calculated energy savings based on the assumption that all heating was supplied by an electric resistance furnace.The savings estimates were based on the third-tier, regression results. Acquisition energy savings were calculated as the energy consumption difference between preprogram baseline and MAP homes. These were the direct energy savings associated with homes built under MAP. MAP, however, had significant market transformation effects not accounted for by the acquisition savings.MAP occurred in two phases. During Phase 1, April 1992 through October 1994, the original national HUD code was in effect and utilities paid manufacturers $2,500 for each MAP home. Phase 2 started after October 1994, when a new, more efficient HUD code went into effect and the payment declined to $1,500. We estimated ene...

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Section: Comparison With Other Resultssupporting

confidence: 87%

Impact Evaluation for the Manufactured Housing Acquisition Program (Map)

Lee¹,

Taylor²,

Schrock³

et al. 1995

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“…Some of the programs offered direct assistance (measures are installed at no cost to the customer) and some shared savings incentives (where both the utility and the customer invest in measures and share the benefits of reduced bills). Brown and Mihlmester (1994) found that the lowest realization rates were in residential direct assistance programs ( w i t h a mean of 68% and a median of 53%). The realization rates for commercial, industrial, and agricultural programs were higher than residential realization rates, and the shared incentive programs had higher realization rates than the direct assistance programs.…”

Section: Previous Research On Audit Realization Ratesmentioning

confidence: 98%

“…Another study of realization rates in the Demand-Side Management programs of the four largest California utilities summarized the results of over 50 evaluation studies of programs operating between 1990 and 1992 (Brown and Mihlmester, 1994). The programs reviewed included efforts in several end-use sectors (including commercial, industrial, agricultural and residential).…”

Section: Previous Research On Audit Realization Ratesmentioning

confidence: 99%

Validation of the National Energy Audit (NEAT) with data from a gas utility low-income residential weatherization program in New York State

Gettings¹,

Berry²,

Beyer³

et al. 1998

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This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, rn pleteness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process. or service by trade name, trademark, manufacturer, or otherwise, does not necessarily consti M e or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. DISCLAIMER Portions of this document may be illegible electronic image products. Images are produced from the best available original document.

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What roles for utility sponsored DSM in a competitive environment?

Keating

1996

Energy Policy

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Summary of California DSM impact evaluation studies

Abstract: Portions of this document may be illegible in electronic image products. Images are produced from the best available original document.

Cited by 4 publications

References 2 publications

Impact Evaluation for the Manufactured Housing Acquisition Program (Map)

Impact Evaluation for the Manufactured Housing Acquisition Program (Map)

Validation of the National Energy Audit (NEAT) with data from a gas utility low-income residential weatherization program in New York State

What roles for utility sponsored DSM in a competitive environment?

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