A framework for improving the cost-effectiveness of DSM program evaluations

Sonnenblick, Richard; Eto, J.

doi:10.2172/132717

Cited by 8 publications

(13 citation statements)

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“…See, for example, Sonnenblick and Et0 (1995) for detailed discussion of the three approaches and of the relationships among them. ..…”

Section: Tracking Database Methodsmentioning

confidence: 99%

“…58 Sonnenblick and Et0 (1995) demonstrate that the imprecision in savings estimates is typically dominated by imprecision in economic lifetimes rather than imprecision in annual energy savings. Economic Lifetime of Savings (Years)…”

Section: Assessing Uncertainties In the Estimation Of Economic Lifetimentioning

confidence: 99%

“…Sonnenblick and Et0 (1995) find large variation in the accuracy of tracking database estimates of savings, depending on the sources of the information input into a database and the sophistication and flexibility of the database. For example, programs with tracking databases that incorporate information fi-om rebate applications will probably not provide estimates as accurate (i.e., as unbiased and precise) as those from a tracking database incorporating information from site inspections of each participant's facility.…”

Section: The Transferability Of Realization Ratesmentioning

confidence: 99%

“…At the same time, as Sonnenblick and Et0 (1995) demonstrate, estimating energy savings from end-use metering is subject to a number of uncertainties, including omission of HVACAighting interactions, problems of shortduration metering such as the ability'to account for seasonal operating changes, and compromises to the representativeness of the sample resulting from the selection of metered circuits within a premise.…”

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confidence: 99%

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Where did the money go? The cost and performance of the largest commercial sector DSM program

Eto¹,

Kito²,

Shown³

et al. 1995

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“…See, for example, Sonnenblick and Et0 (1995) for detailed discussion of the three approaches and of the relationships among them. ..…”

Section: Tracking Database Methodsmentioning

confidence: 99%

Section: Assessing Uncertainties In the Estimation Of Economic Lifetimentioning

confidence: 99%

Section: The Transferability Of Realization Ratesmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Where did the money go? The cost and performance of the largest commercial sector DSM program

Eto¹,

Kito²,

Shown³

et al. 1995

Self Cite

View full text Add to dashboard Cite

“…Briefly, conventional thinking is that bias in the measurements will bias the model, while zero-mean noise in the measurements will not bias the model. However, when unbiased noise in the measurement of the independent variables is present, it leads to biased ("attenuated") parameter estimates when these data are used for modelling [27,28,32,33]. This is the errors-invariables effect.…”

Section: Uncertainty In Mandvmentioning

confidence: 99%

Low-cost energy meter calibration method for measurement and verification

2017

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Energy meters need to be calibrated for use in Measurement and Verification (M&V) projects. However, calibration can be prohibitively expensive and affect project feasibility negatively. This study presents a novel low-cost in-situ meter data calibration technique using a relatively low accuracy commercial energy meter as a calibrator. Calibration is achieved by combining two machine learning tools: the SIMulation EXtrapolation (SIMEX) Measurement Error Model and Bayesian regression. The model is trained or calibrated on half-hourly building energy data for 24 hours. Measurements are then compared to the true values over the following months to verify the method. Results show that the hybrid method significantly improves parameter estimates and goodness of fit when compared to Ordinary Least Squares regression or standard SIMEX. This study also addresses the effect of mismeasurement in energy monitoring, and implements a powerful technique for mitigating the bias that arises because of it. Meters calibrated by the technique presented have adequate accuracy for most M&V applications, at a significantly lower cost.

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Learning from integrated assessment of climate change

1996

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The objective of integrated assessment of climate change is to put available knowledge together in order to evaluate what has been learned, policy implications, and research needs. This paper summarizes insights gained from five years of integrated assessment activity at Carnegie Mellon. After an introduction, in Section 2 we ask: who are the climate decision makers? We conclude that they are a diffuse and often divergent group spread all over the world whose decisions are primarily driven by local non-climate considerations. Insights are illustrated with results from the ICAM-2 model. In Section 3 we ask: what is the climate problem? In addition to the conventional answer, we note that in a democracy the problem is whatever voters and their elected representatives think it is. Results from studies of public understanding are reported. Several other specific issues that define the problem, including the treatment of aerosols and alternative indices for comparing greenhouse gases, are discussed. In Section 4 we discuss studies of climate impacts, focusing on coastal zones, the terrestrial biosphere and human health. Particular attention is placed on the roles of adaptation, value change, and technological innovation. In Section 5 selected policy issues are discussed. We conclude by noting that equity has received too little attention in past work. We argue that many conventional tools for policy analysis are not adequate to deal with climate problems. Values that change, and mixed levels of uncertainty, pose particularly important challenges for the future.

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A framework for improving the cost-effectiveness of DSM program evaluations

Cited by 8 publications

References 0 publications

Where did the money go? The cost and performance of the largest commercial sector DSM program

Where did the money go? The cost and performance of the largest commercial sector DSM program

Low-cost energy meter calibration method for measurement and verification

Learning from integrated assessment of climate change

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