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Electricity Generation with Looped Transmission Networks: Bidding to an ISO

Author

Listed:
  • Xinmin Hu

    (Australian Graduate School of Management, Sydney)

  • Daniel Ralph

    (Judge Institute of Management, University of Cambridge)

  • Eric K. Ralph

    (EKonomics LLC, 2323 Audubon St, New Orleans)

  • Peter Bardsley

    (Department of Economics, University of Melbourne)

  • Michael C. Ferris

    (Department of Computer Sciences, University of Wisconsin–Madison)

Abstract

This paper uses a bi-level game to model markets for delivery of electrical power on looped transmission networks. It analyzes the effectiveness of an independent system operator (ISO) when generators (and, in some cases, retailers) with market power bid a single parameter of their linear supply (demand) functions to the ISO. The ISO, taking these bids at face value, maximizes welfare subject to transmission constraints. We find that equilibrium outcomes are sensitive to firms’ strategy spaces: 1. In the presence of transmission congestion and loop flows, supply function equilibria (SFE) are not bounded from above by Cournot equilibria, so Cournot outcomes may be more effcient than SFE, a difference that can be accentuated by increasing the number of rivals at a given node; 2. Allocation of transmission rights to generators can reduce effciency; and 3. Countervailing power on the part of buyers can lower effciency.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Xinmin Hu & Daniel Ralph & Eric K. Ralph & Peter Bardsley & Michael C. Ferris, 2004. "Electricity Generation with Looped Transmission Networks: Bidding to an ISO," Working Papers EP65, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:ep65
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Willems, Bert & Rumiantseva, Ina & Weigt, Hannes, 2009. "Cournot versus Supply Functions: What does the data tell us?," Energy Economics, Elsevier, vol. 31(1), pages 38-47, January.
    2. Xinmin Hu & Daniel Ralph, 2007. "Using EPECs to Model Bilevel Games in Restructured Electricity Markets with Locational Prices," Operations Research, INFORMS, vol. 55(5), pages 809-827, October.
    3. Bjørndal, Mette & Gribkovskaia, Victoria & Jörnsten, Kurt, 2014. "Market Power in a Power Market with Transmission Constraints," Discussion Papers 2014/29, Norwegian School of Economics, Department of Business and Management Science.
    4. Robert Wilson, 2008. "Supply Function Equilibrium in a Constrained Transmission System," Operations Research, INFORMS, vol. 56(2), pages 369-382, April.
    5. Hu, X. & Ralph, R., 2006. "Using EPECs to model bilevel games in restructured electricity markets with locational prices," Cambridge Working Papers in Economics 0619, Faculty of Economics, University of Cambridge.
    6. Spiridonova, Olga, 2016. "Transmission capacities and competition in Western European electricity market," Energy Policy, Elsevier, vol. 96(C), pages 260-273.
    7. Guo, Zhaomiao & Fan, Yueyue, 2017. "A Stochastic Multi-Agent Optimization Model for Energy Infrastructure Planning Under Uncertainty and Competition," Institute of Transportation Studies, Working Paper Series qt89s5s8hn, Institute of Transportation Studies, UC Davis.
    8. Zhaomiao Guo & Yueyue Fan, 2017. "A Stochastic Multi-agent Optimization Model for Energy Infrastructure Planning under Uncertainty in An Oligopolistic Market," Networks and Spatial Economics, Springer, vol. 17(2), pages 581-609, June.
    9. Benjamin F. Hobbs & J. S. Pang, 2007. "Nash-Cournot Equilibria in Electric Power Markets with Piecewise Linear Demand Functions and Joint Constraints," Operations Research, INFORMS, vol. 55(1), pages 113-127, February.

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    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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