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Regulation by Simulation: The Role of Production Cost Models in Electricity Planning and Pricing

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  • Edward Kahn

    (University of California, Berkeley, California)

Abstract

This paper is a case study on the role of complex computer simulation models in the regulation of the electricity industry. The analysis focuses on electricity production cost simulation models as they are used to set prices for certain nonutility generators in California. This represents an early part of the trend toward “markets” for electric power, and away from pure monopoly supply. The introduction of even limited competition creates conditions both favoring and hindering the reliability of cost estimates, and demonstrates the sensitivity of results to problem specification and model implementation. Attention is focused on the representation of power system operational constraints, particularly the unit commitment problem, in the modeling process and their effect on the prices which result. Examples from the litigation history illustrate the problem of managing the strategic use and abuse of modeling techniques for competitive advantage. Highly structured procedures for using models in such situations offer some constraints on manipulation by competing parties. Otherwise, experts are apt to overwhelm regulators.

Suggested Citation

  • Edward Kahn, 1995. "Regulation by Simulation: The Role of Production Cost Models in Electricity Planning and Pricing," Operations Research, INFORMS, vol. 43(3), pages 388-398, June.
    • Handle: RePEc:inm:oropre:v:43:y:1995:i:3:p:388-398
    DOI: 10.1287/opre.43.3.388
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    Citations

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    Cited by:

    1. Kahn, Edward, 1998. "Introducing competition to the electricity industry in Spain: the role of initial conditions," Utilities Policy, Elsevier, vol. 7(1), pages 15-22, March.
    2. Carvallo, Juan Pablo & Sanstad, Alan H. & Larsen, Peter H., 2019. "Exploring the relationship between planning and procurement in western U.S. electric utilities," Energy, Elsevier, vol. 183(C), pages 4-15.
    3. Kahn, Edward & Bailey, Shawn & Pando, Luis, 1997. "Simulating electricity restructuring in California: Interactions with the regional market," Resource and Energy Economics, Elsevier, vol. 19(1-2), pages 3-28, March.
    4. Benjamin F. Hobbs & Yuandong Ji, 1999. "Stochastic Programming-Based Bounding of Expected Production Costs for Multiarea Electric Power System," Operations Research, INFORMS, vol. 47(6), pages 836-848, December.
    5. Munoz, F.D. & Hobbs, B.F. & Watson, J.-P., 2016. "New bounding and decomposition approaches for MILP investment problems: Multi-area transmission and generation planning under policy constraints," European Journal of Operational Research, Elsevier, vol. 248(3), pages 888-898.
    6. Jorge Valenzuela & Mainak Mazumdar, 2003. "Commitment of Electric Power Generators Under Stochastic Market Prices," Operations Research, INFORMS, vol. 51(6), pages 880-893, December.
    7. Saumweber, Andrea & Wederhake, Lars & Cardoso, Gonçalo & Fridgen, Gilbert & Heleno, Miguel, 2021. "Designing Pareto optimal electricity retail rates when utility customers are prosumers," Energy Policy, Elsevier, vol. 156(C).
    8. James Bushnell, 2003. "A Mixed Complementarity Model of Hydrothermal Electricity Competition in the Western United States," Operations Research, INFORMS, vol. 51(1), pages 80-93, February.
    9. Joseph Eto & Edward Vine & Leslie Shown & Richard Sonnenblick & Chris Payne, 1996. "The Total Cost and Measured Performance of Utility-Sponsored Energy Efficiency Programs," The Energy Journal, , vol. 17(1), pages 31-51, January.

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