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Customer Risk from Real-Time Retail Electricity Pricing: Bill Volatility and Hedgability

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  • Severin Borenstein

Abstract

One of the most critical concerns that customers have voiced in the debate over real-time retail electricity pricing is that they would be exposed to risk from fluctuations in their electricity cost. The concern seems to be that a customer could find itself consuming a large quantity of power on the day that prices skyrocket, resulting in a high monthly bill. I analyze the magnitude of this risk, using demand data from 1142 large industrial customers, and then ask how much of this risk can be eliminated through various straightforward financial instruments. I find that very simple hedging strategiesÑforward purchase contracts that are already used with many RTP programsÑcan eliminate more than 80% of the bill volatility that would otherwise occur. I then show that a slightly more sophisticated application of these forward power purchases can significantly enhance their effect on reducing bill volatility.

Suggested Citation

  • 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.
    • Handle: RePEc:aen:journl:2007v28-02-a05
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    References listed on IDEAS

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    1. Severin Borenstein & James Bushnell & Christopher R. Knittel & Catherine Wolfram, 2008. "Inefficiencies And Market Power In Financial Arbitrage: A Study Of California'S Electricity Markets," Journal of Industrial Economics, Wiley Blackwell, vol. 56(2), pages 347-378, June.
    2. Severin Borenstein & Stephen Holland, 2005. "On the Efficiency of Competitive Electricity Markets with Time-Invariant Retail Prices," RAND Journal of Economics, The RAND Corporation, vol. 36(3), pages 469-493, Autumn.
    3. Gregory W. Brown & Klaus Bjerre Toft, 2002. "How Firms Should Hedge," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1283-1324.
    4. Ronald I. McKinnon, 1967. "Futures Markets, Buffer Stocks, and Income Stability for Primary Producers," Journal of Political Economy, University of Chicago Press, vol. 75, pages 844-844.
    5. Severin Borenstein, 2007. "Wealth Transfers Among Large Customers from Implementing Real-Time Retail Electricity Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 131-150.
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    Cited by:

    1. Milstein, Irena & Tishler, Asher, 2015. "Can price volatility enhance market power? The case of renewable technologies in competitive electricity markets," Resource and Energy Economics, Elsevier, vol. 41(C), pages 70-90.
    2. Sioshansi, Ramteen, 2016. "Retail electricity tariff and mechanism design to incentivize distributed renewable generation," Energy Policy, Elsevier, vol. 95(C), pages 498-508.
    3. Ramteen Sioshansi, . "Retail Electricity Tariff and Mechanism Design to Incentivise Distributed Generation," Chapters, in: Shigeru Kimura & Youngho Chang & Yanfei Li (ed.), Financing Renewable Energy Development in East Asia Summit Countries A Primer of Effective Policy Instruments, chapter 9, pages 267-296, Economic Research Institute for ASEAN and East Asia (ERIA).
    4. Yumi Yoshida & Kenta Tanaka & Shunsuke Managi, 2017. "Which dynamic pricing rule is most preferred by consumers?—Application of choice experiment," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 6(1), pages 1-11, December.
    5. Allcott, Hunt, 2011. "Rethinking real-time electricity pricing," Resource and Energy Economics, Elsevier, vol. 33(4), pages 820-842.
    6. Zhao, Huan, 2011. "Four Market Studies for the Beef and Electric Power Industries," ISU General Staff Papers 201101010800001360, Iowa State University, Department of Economics.
    7. Kopsakangas Savolainen, Maria & Svento, Rauli, 2012. "Real-Time Pricing in the Nordic Power markets," Energy Economics, Elsevier, vol. 34(4), pages 1131-1142.
    8. Bajo-Buenestado, Raúl, 2017. "Welfare implications of capacity payments in a price-capped electricity sector: A case study of the Texas market (ERCOT)," Energy Economics, Elsevier, vol. 64(C), pages 272-285.
    9. S. Borenstein, 2013. "Effective and Equitable Adoption of Opt-In Residential Dynamic Electricity Pricing," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 42(2), pages 127-160, March.
    10. Fred Schroyen & Adekola Oyenuga, 2011. "Optimal pricing and capacity choice for a public service under risk of interruption," Journal of Regulatory Economics, Springer, vol. 39(3), pages 252-272, June.
    11. Reus, Lorenzo & Munoz, Francisco D. & Moreno, Rodrigo, 2018. "Retail consumers and risk in centralized energy auctions for indexed long-term contracts in Chile," Energy Policy, Elsevier, vol. 114(C), pages 566-577.
    12. 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.
    13. Streimikiene, Dalia & Siksnelyte, Indre, 2016. "Sustainability assessment of electricity market models in selected developed world countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 72-82.
    14. Willems, Bert & Morbee, Joris, 2010. "Market completeness: How options affect hedging and investments in the electricity sector," Energy Economics, Elsevier, vol. 32(4), pages 786-795, July.
    15. 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.
    16. Pretto, Madeline, 2021. "Tail-risk Comprehension and Protection in Real-time Electricity Pricing : Experimental Evidence," Warwick-Monash Economics Student Papers 25, Warwick Monash Economics Student Papers.

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