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Using real-time electricity data to estimate response to time-of-use and flat rates: an application to emissions

Listed author(s):
  • James Cochell
  • Peter Schwarz


  • Thomas Taylor
Registered author(s):

    Using a generalized McFadden specification, we estimate the determinants of hourly response for the years 2006 through 2010 for all 16 standard retail customers who were on an optional real-time electricity rate offered by Duke Energy as of 2010, and provide a method to estimate how these customers would respond to time-of-use (TOU) and flat rates. We generalize the model to allow for inter-day response, as well as threshold prices, above which individual customer response may increase or decrease. With these inclusions, we find hourly elasticity for the group of customers to be as large as −0.7, larger than previous studies. We apply the method to examine a recent finding that time-differentiated rates could increase electric utility emissions. However, that result did not differentiate between real-time and TOU rates, and furthermore held energy use constant in comparing flat rates and time-differentiated rates. We perform a case study to examine emissions of SO 2 , NOx, Hg, and CO 2 based on predicted energy use changes as well as for an energy-neutral case for real-time, TOU and flat rates. Employing energy use predictions from the model, increased energy use results in increased emissions in almost all cases. For the energy-neutral case, time-differentiated rates increase CO 2 as compared to flat rates, and the TOU rate causes a larger increase than does real-time pricing. But both rates decrease other emissions in the majority of years, particularly SO 2 In addition, time-differentiated rates reduce NOx potency by shifting it to non-daylight hours when conditions for the formation of smog are less favorable. Our application leads to the conclusion that the effect of the rates on emissions must consider total energy use as well as the shift from peak to off-peak. Furthermore, the predictions require consideration of the generating mix at a more detailed level than was contained in previous studies. Copyright Springer Science+Business Media, LLC 2012

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

    Volume (Year): 42 (2012)
    Issue (Month): 2 (October)
    Pages: 135-158

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    Handle: RePEc:kap:regeco:v:42:y:2012:i:2:p:135-158
    DOI: 10.1007/s11149-012-9190-7
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    1. Severin Borenstein, 2007. "Customer Risk from Real-Time Retail Electricity Pricing: Bill Volatility and Hedgability," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 111-130.
    2. Martin L. Weitzman, 1974. "Prices vs. Quantities," Review of Economic Studies, Oxford University Press, vol. 41(4), pages 477-491.
    3. Thomas Taylor & Peter Schwarz & James Cochell, 2005. "24/7 Hourly Response to Electricity Real-Time Pricing with up to Eight Summers of Experience," Journal of Regulatory Economics, Springer, vol. 27(3), pages 235-262, January.
    4. Stephen P. Holland & Erin T. Mansur, 2008. "Is Real-Time Pricing Green? The Environmental Impacts of Electricity Demand Variance," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 550-561, August.
    5. Thomas Taylor & Peter Schwarz, 2000. "Advance notice of real-time electricity prices," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 28(4), pages 478-488, December.
    6. Peter M. Schwarz, 2005. "Multipollutant Efficiency Standards For Electricity Production," Contemporary Economic Policy, Western Economic Association International, vol. 23(3), pages 341-356, July.
    7. Stephen P. Holland & Erin T. Mansur, 2006. "The Short-Run Effects of Time-Varying Prices in Competitive Electricity Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 127-156.
    8. Hung-po Chao, 2011. "Demand response in wholesale electricity markets: the choice of customer baseline," Journal of Regulatory Economics, Springer, vol. 39(1), pages 68-88, February.
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