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24/7 Hourly Response to Electricity Real-Time Pricing with up to Eight Summers of Experience

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Author Info

  • Thomas Taylor

    ()

  • Peter Schwarz

    ()

  • James Cochell

    ()

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    Abstract

    This paper provides hourly own and cross price elasticities for industrial customers with up to 8 years of experience on Duke Power optional real-time rates. We include the effects of customer characteristics and temperature conditions. Aggregated results show larger own elasticities than have previous studies, complementarity within the potential peak hours and substitution in the late evening. As customers gain experience with hourly pricing, they show larger load reductions during higher priced hours. As compared to a TOU rate, net benefits are $14,000 per customer per month, approximately 4% of the average customer’s bill, and much greater than metering costs. Copyright Springer Science+Business Media, Inc. 2005

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    File URL: http://hdl.handle.net/10.1007/s11149-005-6623-6
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    Bibliographic Info

    Article provided by Springer in its journal Journal of Regulatory Economics.

    Volume (Year): 27 (2005)
    Issue (Month): 3 (01)
    Pages: 235-262

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    Handle: RePEc:kap:regeco:v:27:y:2005:i:3:p:235-262

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    Web page: http://www.springerlink.com/link.asp?id=100298

    Related research

    Keywords: real-time pricing; hourly elasticities; industrial response;

    References

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    1. Herriges, Joseph A. & Baladi, S. M. & Caves, Douglas W. & Neenan, B. F., 1993. "The Response of Industrial Customers to Electric Rates Based Upon Dynamic Marginal Costs," Staff General Research Papers 1497, Iowa State University, Department of Economics.
    2. Robert H. Patrick & Frank A. Wolak, 2001. "Estimating the Customer-Level Demand for Electricity Under Real-Time Market Prices," NBER Working Papers 8213, National Bureau of Economic Research, Inc.
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    Cited by:
    1. Allcott, Hunt, 2011. "Rethinking real-time electricity pricing," Resource and Energy Economics, Elsevier, vol. 33(4), pages 820-842.
    2. Woo, C.K. & Li, R. & Shiu, A. & Horowitz, I., 2013. "Residential winter kWh responsiveness under optional time-varying pricing in British Columbia," Applied Energy, Elsevier, vol. 108(C), pages 288-297.
    3. James Cochell & Peter Schwarz & Thomas Taylor, 2012. "Using real-time electricity data to estimate response to time-of-use and flat rates: an application to emissions," Journal of Regulatory Economics, Springer, vol. 42(2), pages 135-158, October.
    4. 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.
    5. Shu Fan & Rob Hyndman, 2010. "The price elasticity of electricity demand in South Australia," Monash Econometrics and Business Statistics Working Papers 16/10, Monash University, Department of Econometrics and Business Statistics.
    6. Herter, Karen, 2007. "Residential implementation of critical-peak pricing of electricity," Energy Policy, Elsevier, vol. 35(4), pages 2121-2130, April.
    7. Boom, Anette & Schwenen, Sebastian, 2013. "Real-time Pricing in Power Markets: Who Gains?," Working Papers 01-2013, Copenhagen Business School, Department of Economics.
    8. Zarnikau, Jay & Hallett, Ian, 2008. "Aggregate industrial energy consumer response to wholesale prices in the restructured Texas electricity market," Energy Economics, Elsevier, vol. 30(4), pages 1798-1808, July.
    9. Paul L. Joskow, 2012. "Creating a Smarter U.S. Electricity Grid," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 29-48, Winter.

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