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Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework

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  • Junjie Sun
  • Leigh Tesfatsion

Abstract

In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design—the Wholesale Power Market Platform (WPMP)—for common adoption by all US wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration.
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Suggested Citation

  • Junjie Sun & Leigh Tesfatsion, 2007. "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 291-327, October.
  • Handle: RePEc:kap:compec:v:30:y:2007:i:3:p:291-327
    DOI: 10.1007/s10614-007-9095-1
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    1. Koesrinartoto, D. & Sun, Junjie & Tesfatsion, Leigh, 2005. "An agent-based computational laboratory for testing the economic reliability of wholesale power market designs," ISU General Staff Papers 200501010800001043, Iowa State University, Department of Economics.
    2. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
    3. Paul L. Joskow, 2006. "Markets for Power in the United States: An Interim Assessment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 1-36.
    4. Sun, Junjie & Tesfatsion, Leigh, 2006. "DC Optimal Power Flow Formulation and Solution Using QuadProgJ," Working Papers 18221, Iowa State University, Department of Economics.
    5. Widergren, S. & Sun, Junjie & Tesfatsion, Leigh, 2006. "Market design test environments," ISU General Staff Papers 200601010800001042, Iowa State University, Department of Economics.
    6. James Nicolaisen & Valentin Petrov & Leigh Tesfatsion, 2000. "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing," Computational Economics 0004005, University Library of Munich, Germany.
    7. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    8. Bower, John & Bunn, Derek, 2001. "Experimental analysis of the efficiency of uniform-price versus discriminatory auctions in the England and Wales electricity market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 561-592, March.
    9. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    10. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    11. Robert Wilson, 2002. "Architecture of Power Markets," Econometrica, Econometric Society, vol. 70(4), pages 1299-1340, July.
    12. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2, 00.
    13. Sun, Junjie, 2005. "U.S. Financial Transmission Rights: Theory and Practice," Staff General Research Papers Archive 12266, Iowa State University, Department of Economics.
    14. Sun, Junjie & Tesfatsion, Leigh S., 2007. "Open-Source Software for Power Industry Research, Teaching, and Training: A DC Optimal Power Flow Illustration," Staff General Research Papers Archive 12775, Iowa State University, Department of Economics.
    15. Axelrod, Robert & Tesfatsion, Leigh, 2006. "A Guide for Newcomers to Agent-Based Modeling in the Social Sciences," Staff General Research Papers Archive 12515, Iowa State University, Department of Economics.
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    More about this item

    Keywords

    Wholesale power market restructuring; Empirical input validation; Market design; Behavioral economics; Learning; Market power; Agent-based modeling; AMES wholesale power market framework; Java; RepastJ; L1; D8; L9; C6;
    All these keywords.

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • L9 - Industrial Organization - - Industry Studies: Transportation and Utilities
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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