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Customer Response to RTP in Competitive Markets: A Study of Niagara Mohawk's Standard Offer Tariff

Author

Listed:
  • Richard N. Boisvert
  • Peter Cappers
  • Charles Goldman
  • Bernie Neenan
  • Nicole Hopper

Abstract

Utilizing load, price, and survey data for 119 large customers that paid competitively determined hourly electricity prices announced the previous day between 2000 and 2004, this study provides insight into the factors that determine the intensity of price response. Peak and off-peak electricity can be: perfect complements, substitutes, or substitutes where high peak prices cause temporary disconnection from the grid, as for some firms with on-site generation. The average elasticity of substitution is 0.11. Thirty percent of the customers use peak and off-peak electricity in fixed proportions. The 18% with elasticities greater than 0.10 provide 75% of the aggregate price response. In contrast to Industrial customers, Commercial/Retail and Government/Education customers are more price responsive on hot days and when the ratio of peak to off-peak prices is high. Price responsiveness is not substantially reduced when customers operate near peak usage. Diversity of customer circumstances and price response suggest dynamic pricing is suited for some, but not all customers.

Suggested Citation

  • Richard N. Boisvert & Peter Cappers & Charles Goldman & Bernie Neenan & Nicole Hopper, 2007. "Customer Response to RTP in Competitive Markets: A Study of Niagara Mohawk's Standard Offer Tariff," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 53-74.
    • Handle: RePEc:aen:journl:2007v28-01-a03
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    Citations

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    Cited by:

    1. Guo, Bowei & Weeks, Melvyn, 2022. "Dynamic tariffs, demand response, and regulation in retail electricity markets," Energy Economics, Elsevier, vol. 106(C).
    2. 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.
    3. Allcott, Hunt, 2011. "Rethinking real-time electricity pricing," Resource and Energy Economics, Elsevier, vol. 33(4), pages 820-842.
    4. 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.
    5. Anette Boom & Sebastian Schwenen, 2021. "Is real-time pricing smart for consumers?," Journal of Regulatory Economics, Springer, vol. 60(2), pages 193-213, December.
    6. 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.
    7. Mills, Andrew D. & Wiser, Ryan H., 2015. "Strategies to mitigate declines in the economic value of wind and solar at high penetration in California," Applied Energy, Elsevier, vol. 147(C), pages 269-278.
    8. Furió, Dolores & Moreno-del-Castillo, Javier, 2024. "Dynamic demand response to electricity prices: Evidence from the Spanish retail market," Utilities Policy, Elsevier, vol. 88(C).

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    JEL classification:

    • F0 - International Economics - - General

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