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Setting a standard for electricity pilot studies

Author

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  • Davis, Alexander L.
  • Krishnamurti, Tamar
  • Fischhoff, Baruch
  • Bruine de Bruin, Wandi

Abstract

In-home displays, dynamic pricing, and automated devices aim to reduce residential electricity use—overall and during peak hours. We present a meta-analysis of 32 studies of the impacts of these interventions, conducted in the US or Canada. We find that methodological problems are common in the design of these studies, leading to artificially inflated results relative to what one would expect if the interventions were implemented in the general population. Particular problems include having volunteer participants who may have been especially motivated to reduce their electricity use, letting participants choose their preferred intervention, and having high attrition rates. Using estimates of bias from medical clinical trials as a guide, we recalculate impact estimates to adjust for bias, resulting in values that are often less than half of those reported in the reviewed studies. We estimate that in-home displays were the most effective intervention for reducing overall electricity use (~4% using reported data; ~3% after adjusting for bias), while dynamic pricing significantly reduced peak demand (~11% reported; ~6% adjusted), especially when used in conjunction with home automation (~25% reported; ~14% adjusted). We conclude with recommendations that can improve pilot studies and the soundness of decisions based on their results.

Suggested Citation

  • Davis, Alexander L. & Krishnamurti, Tamar & Fischhoff, Baruch & Bruine de Bruin, Wandi, 2013. "Setting a standard for electricity pilot studies," Energy Policy, Elsevier, vol. 62(C), pages 401-409.
  • Handle: RePEc:eee:enepol:v:62:y:2013:i:c:p:401-409
    DOI: 10.1016/j.enpol.2013.07.093
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    References listed on IDEAS

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    1. Joseph G. Ibrahim & Ming-Hui Chen & Stuart R. Lipsitz & Amy H. Herring, 2005. "Missing-Data Methods for Generalized Linear Models: A Comparative Review," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 332-346, March.
    2. Davis, Alexander L. & Krishnamurti, Tamar, 2013. "The problems and solutions of predicting participation in energy efficiency programs," Applied Energy, Elsevier, vol. 111(C), pages 277-287.
    3. Sexton, Richard J & Johnson, Nancy Brown & Konakayama, Akira, 1987. " Consumer Response to Continuous-Display Electricity-Use Monitors in a Time-of-Use Pricing Experiment," Journal of Consumer Research, Oxford University Press, vol. 14(1), pages 55-62, June.
    4. Battalio, Raymond C, et al, 1979. "Residential Electricity Demand: An Experimental Study," The Review of Economics and Statistics, MIT Press, vol. 61(2), pages 180-189, May.
    5. Mostafa Baladi, S. & Herriges, Joseph A. & Sweeney, Thomas J., 1998. "Residential response to voluntary time-of-use electricity rates," Resource and Energy Economics, Elsevier, vol. 20(3), pages 225-244, September.
    6. Hutton, R Bruce, et al, 1986. " Effects of Cost-Related Feedback on Consumer Knowledge and Consumption Behavior: A Field Experimental Approach," Journal of Consumer Research, Oxford University Press, vol. 13(3), pages 327-336, December.
    7. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    8. Weisser, Daniel, 2007. "A guide to life-cycle greenhouse gas (GHG) emissions from electric supply technologies," Energy, Elsevier, vol. 32(9), pages 1543-1559.
    9. Rebecca M. Turner & David J. Spiegelhalter & Gordon C. S. Smith & Simon G. Thompson, 2009. "Bias modelling in evidence synthesis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 21-47.
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    Cited by:

    1. Stenner, Karen & Frederiks, Elisha R. & Hobman, Elizabeth V. & Cook, Stephanie, 2017. "Willingness to participate in direct load control: The role of consumer distrust," Applied Energy, Elsevier, vol. 189(C), pages 76-88.

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