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Smart Meter Devices and The Effect of Feedback on Residential Electricity Consumption: Evidence from a Natural Experiment in Northern Ireland

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Author Info

  • Will Gans

    ()
    (AREC, University of Maryland, College Park)

  • Anna Alberini

    ()
    (Department of Agricultural Economics, university of Maryland, US and Centre for Energy Policy and Economics (CEPE), ETH Zurich, Switzerland)

  • Alberto Longo

    ()
    (Gibson Institute for Land Food and Environment, UKCRC Centre of Excellence for Public Health (NI), School of Biological Sciences, Queen‘s University, Belfast)

Abstract

Using a unique set of data and exploiting a large-scale natural experiment, we estimate the effect of real-time usage information on residential electricity consumption in Northern Ireland. Starting in April 2002, the utility replaced prepayment meters with "smart" meters that allow the consumer to track usage in real-time. We rely on this event, account for the endogeneity of price and plan with consumption through a plan selection correction term, and find that the provision of information is associated with a decline in electricity consumption of up to 20 percent. We find that the reduction is robust to different specifications, selection-bias correction methods and subsamples of the original data. At GBP 15-17 per tonne of CO2e (2009), the smart meter program delivers cost-effective reductions in carbon dioxide emissions.

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Bibliographic Info

Paper provided by CEPE Center for Energy Policy and Economics, ETH Zurich in its series CEPE Working paper series with number 11-78.

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Length: 47 pages
Date of creation: Apr 2011
Date of revision:
Handle: RePEc:cee:wpcepe:11-78

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Keywords: Residential Energy; Electricity Demand; Feedback; Smart Meter; Information;

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References

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  1. Gordon B. Dahl, 2002. "Mobility and the Return to Education: Testing a Roy Model with Multiple Markets," RCER Working Papers 488, University of Rochester - Center for Economic Research (RCER).
  2. Joe O'Doherty & Seán Lyons & Richard S. J. Tol, 2007. "Energy-Using Appliances and Energy-Saving Features: Determinants of Ownership in Ireland," Papers WP219, Economic and Social Research Institute (ESRI).
  3. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
  4. Isamu Matsukawa, 2005. "The Benefits of Information on the Efficient Usage of Consumer Durables," Others 0501005, EconWPA.
  5. Dulleck, Uwe & Kaufmann, Sylvia, 2004. "Do customer information programs reduce household electricity demand?--the Irish program," Energy Policy, Elsevier, vol. 32(8), pages 1025-1032, June.
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Cited by:
  1. di Cosmo, Valeria & Lyons, Seán & Nolan, Anne, 2014. "Estimating the Impact of Time-of-Use Pricing on Irish Electricity Demand," Papers RB2014/2/2, Economic and Social Research Institute (ESRI).
  2. López-Rodríguez, M.A. & Santiago, I. & Trillo-Montero, D. & Torriti, J. & Moreno-Munoz, A., 2013. "Analysis and modeling of active occupancy of the residential sector in Spain: An indicator of residential electricity consumption," Energy Policy, Elsevier, vol. 62(C), pages 742-751.
  3. Cossent, Rafael & Gómez, Tomás & Olmos, Luis, 2011. "Large-scale integration of renewable and distributed generation of electricity in Spain: Current situation and future needs," Energy Policy, Elsevier, vol. 39(12), pages 8078-8087.

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