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Industrial Response to Electricity Real-Time Prices: Short Run and Long Run

Author

Listed:
  • Peter M. Schwarz
  • Thomas N. Taylor
  • Matthew Birmingham
  • Shana L. Dardan

Abstract

Real-time pricing reduces summer peak demand by approximately 8% for 110 Duke Energy industrial customers. With up to six summers on the rate, the aggregate customer response increases with experience. Examining individual customers, only a subset respond significantly, primarily those who can self-generate or with discrete (batch) production processes. These customers respond significantly above a threshold level of price. Although elasticities decrease slightly at the highest temperatures, the absolute quantity reductions are largest at these times. Copyright 2002, Oxford University Press.

Suggested Citation

  • Peter M. Schwarz & Thomas N. Taylor & Matthew Birmingham & Shana L. Dardan, 2002. "Industrial Response to Electricity Real-Time Prices: Short Run and Long Run," Economic Inquiry, Western Economic Association International, vol. 40(4), pages 597-610, October.
    • Handle: RePEc:oup:ecinqu:v:40:y:2002:i:4:p:597-610
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    Cited by:

    1. Pascal Courty & Mario Pagliero, 2011. "Does responsive pricing smooth demand shocks?," Applied Economics, Taylor & Francis Journals, vol. 43(30), pages 4707-4721.
    2. Kim, Min-Jeong, 2017. "A field study using an adaptive in-house pricing model for commercial and industrial customers in Korea," Energy Policy, Elsevier, vol. 102(C), pages 189-198.
    3. Kopsakangas Savolainen, Maria & Svento, Rauli, 2012. "Real-Time Pricing in the Nordic Power markets," Energy Economics, Elsevier, vol. 34(4), pages 1131-1142.
    4. 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.
    5. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
    6. Zhou, Yang & Ma, Rong & Su, Yun & Wu, Libo, 2019. "Too big to change: How heterogeneous firms respond to time-of-use electricity price," China Economic Review, Elsevier, vol. 58(C).
    7. Wai Choi & Anindya Sen & Adam White, 2011. "Response of industrial customers to hourly pricing in Ontario’s deregulated electricity market," Journal of Regulatory Economics, Springer, vol. 40(3), pages 303-323, December.
    8. Zarnikau, Jay & Thal, Dan, 2013. "The response of large industrial energy consumers to four coincident peak (4CP) transmission charges in the Texas (ERCOT) market," Utilities Policy, Elsevier, vol. 26(C), pages 1-6.
    9. Derya Eryilmaz, Timothy M. Smith, and Frances R. Homans, 2017. "Price Responsiveness in Electricity Markets: Implications for Demand Response in the Midwest," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    10. Jang, Dongsik & Eom, Jiyong & Jae Park, Min & Jeung Rho, Jae, 2016. "Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers," Energy Policy, Elsevier, vol. 88(C), pages 11-26.
    11. Sezgen, Osman & Goldman, C.A. & Krishnarao, P., 2007. "Option value of electricity demand response," Energy, Elsevier, vol. 32(2), pages 108-119.
    12. Derya Eryilmaz & Jeffrey Apland & Timothy M. Smith, 2022. "Dynamic Electricity Pricing – Modeling Manufacturer Response and an Application to Cement Processing," Energy and Environment Research, Canadian Center of Science and Education, vol. 9(2), pages 1-1, December.
    13. Courty, Pascal & Pagliero, Mario, 2003. "Does Responsive Pricing Increase Efficiency? Evidence from Pricing Experiments in an Internet Café," CEPR Discussion Papers 4149, C.E.P.R. Discussion Papers.

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