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

Author

Listed:
  • James Cochell
  • Peter Schwarz

  • Thomas Taylor

Abstract

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

Suggested Citation

  • 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.
    • Handle: RePEc:kap:regeco:v:42:y:2012:i:2:p:135-158
    DOI: 10.1007/s11149-012-9190-7
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    References listed on IDEAS

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    1. repec:aen:journl:2007v28-02-a05 is not listed on IDEAS
    2. Martin L. Weitzman, 1974. "Prices vs. Quantities," The Review of Economic Studies, Review of Economic Studies Ltd, 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. Palmer, Karen L. & Burtraw, Dallas, 2005. "The Environmental Impacts of Electricity Restructuring: Looking Back and Looking Forward," Discussion Papers 10656, Resources for the Future.
    6. 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.
    7. Peter M. Schwarz, 2005. "Multipollutant Efficiency Standards For Electricity Production," Contemporary Economic Policy, Western Economic Association International, vol. 23(3), pages 341-356, July.
    8. repec:aen:journl:2006v27-04-a06 is not listed on IDEAS
    9. 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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    Cited by:

    1. Amin Karimu & Chandra Kiran B. Krishnamurthy & Mattias Vesterberg, 2022. "Understanding Hourly Electricity Demand: Implications for Load, Welfare and Emissions," The Energy Journal, , vol. 43(1), pages 161-190, January.
    2. Daiya ISOGAWA & Hiroshi OHASHI & Tokunari ANAI, 2022. "Role of Advance Notice on High-priced Hours: Critical peak pricing on industrial demand," Discussion papers 22068, Research Institute of Economy, Trade and Industry (RIETI).
    3. Daiya Isogawa & Hiroshi Ohashi & Tokunari Anai, 2024. "The Role of Advance Notice in Shaping Industrial Response to Time-Varying Electricity Prices," CIRJE F-Series CIRJE-F-1226, CIRJE, Faculty of Economics, University of Tokyo.

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    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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