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Reducing Electricity Demand through Smart Metering: The Role of Improved Household Knowledge

  • James Carroll

    ()

    (Department of Economics, Trinity College, Dublin)

  • Seán Lyons

    ()

    (Economic and Social Research Institute)

  • Eleanor Denny

    ()

    (Department of Economics, Trinity College, Dublin)

The international rollout of residential smart meters has increased considerably in recent years. The improved consumption feedback provided, and in particular, the installation of in-house displays, has been shown to significantly reduce residential electricity demand in some international trials. This paper attempts to uncover the underlying drivers of such information-led reductions by exploring two research questions. First, does feedback improve a household’s knowledge of energy reducing behaviors? And second, do knowledge improvements explain demand reductions? Data is from a randomized controlled smart metering trial (Ireland) which also collected extensive information on household attitudes towards and knowledge of electricity use. Results show that feedback significantly increases a household’s knowledge but improvements are not correlated with observed demand reductions. Increasing the level of knowledge ceteris paribus is therefore unlikely to bring short-run demand reductions in residential electricity markets. Given this result, it is possible that feedback acts mainly as a reminder and motivator, rather than an educational tool

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File URL: http://www.tcd.ie/Economics/TEP/2013/TEP0313.pdf
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Paper provided by Trinity College Dublin, Department of Economics in its series Trinity Economics Papers with number tep0313.

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Length: 28 pages
Date of creation: Jan 2013
Date of revision:
Handle: RePEc:tcd:tcduee:tep0313
Contact details of provider: Postal: Trinity College, Dublin 2
Phone: (+ 353 1) 6081325
Fax: 6772503
Web page: http://www.tcd.ie/Economics/

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  1. Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
  2. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
  3. Krishnamurti, Tamar & Schwartz, Daniel & Davis, Alexander & Fischhoff, Baruch & de Bruin, Wändi Bruine & Lave, Lester & Wang, Jack, 2012. "Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters," Energy Policy, Elsevier, vol. 41(C), pages 790-797.
  4. Jeffrey M. Wooldridge, 2001. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262232197, June.
  5. Faruqui, Ahmad & George, Stephen, 2005. "Quantifying Customer Response to Dynamic Pricing," The Electricity Journal, Elsevier, vol. 18(4), pages 53-63, May.
  6. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
  7. Ahmad Faruqui & Sanem Sergici, 2011. "Dynamic pricing of electricity in the mid-Atlantic region: econometric results from the Baltimore gas and electric company experiment," Journal of Regulatory Economics, Springer, vol. 40(1), pages 82-109, August.
  8. Hledik, Ryan, 2009. "How Green Is the Smart Grid?," The Electricity Journal, Elsevier, vol. 22(3), pages 29-41, April.
  9. Newsham, Guy R. & Bowker, Brent G., 2010. "The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review," Energy Policy, Elsevier, vol. 38(7), pages 3289-3296, July.
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