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The value of reducing distribution losses by domestic load-shifting: a network perspective

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  • Shaw, Rita
  • Attree, Mike
  • Jackson, Tim
  • Kay, Mike
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    Abstract

    Shifting domestic load to off-peak time periods could potentially reduce electrical distribution losses and associated carbon emissions. This paper provides the first quantitative estimate of the possible reduction in losses, for a situation where domestic energy demand is shifted in time but not reduced. At a likely 0.02% of energy distributed by the network, the reduction is small relative to overall losses and to their variability, giving little rationale for distribution network operators in Great Britain to encourage such load-shifting for that reason. The paper also considers the limited regulatory incentives for the reduction, and the fragmentation of costs and benefits across different parties. The societal value is considerably higher than the current regulatory incentive, but nonetheless may still not warrant the cost of action. Reducing rather than shifting load is likely to give greater environmental benefits.

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    File URL: http://www.sciencedirect.com/science/article/B6V2W-4W73H85-2/2/4786515bd36ba843295b8b48771022f0
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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Policy.

    Volume (Year): 37 (2009)
    Issue (Month): 8 (August)
    Pages: 3159-3167

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    Handle: RePEc:eee:enepol:v:37:y:2009:i:8:p:3159-3167

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    Web page: http://www.elsevier.com/locate/enpol

    Related research

    Keywords: Distribution network losses Load management Regulation;

    References

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    1. Faruqui, Ahmad & George, Stephen, 2005. "Quantifying Customer Response to Dynamic Pricing," The Electricity Journal, Elsevier, vol. 18(4), pages 53-63, May.
    2. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    3. Hopper, Nicole & Goldman, Charles & Bharvirkar, Ranjit & Neenan, Bernie, 2006. "Customer response to day-ahead market hourly pricing: Choices and performance," Utilities Policy, Elsevier, vol. 14(2), pages 126-134, June.
    4. Newborough, M. & Probert, S. D., 1990. "Intelligent automatic electrical-load management for networks of major domestic appliances," Applied Energy, Elsevier, vol. 37(2), pages 151-168.
    5. Deering, S. & Newborough, M. & Probert, S. D., 1993. "Rescheduling electricity demands in domestic buildings," Applied Energy, Elsevier, vol. 44(1), pages 1-62.
    6. Swisher, Joel & Orans, Ren, 1995. "The use of area-specific utility costs to target intensive DSM campaigns," Utilities Policy, Elsevier, vol. 5(3-4), pages 185-197.
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    Cited by:
    1. Gottwalt, Sebastian & Ketter, Wolfgang & Block, Carsten & Collins, John & Weinhardt, Christof, 2011. "Demand side management—A simulation of household behavior under variable prices," Energy Policy, Elsevier, vol. 39(12), pages 8163-8174.
    2. Feuerriegel, Stefan & Neumann, Dirk, 2014. "Measuring the financial impact of demand response for electricity retailers," Energy Policy, Elsevier, vol. 65(C), pages 359-368.
    3. Adela Conchado & Pedro Linares, 2010. "The Economic Impact of Demand-Response Programs on Power Systems. A survey of the State of the Art," Working Papers 02-2010, Economics for Energy.

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