English, Article, Journal or magazine article edition: An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs Deddy Koesrindartoto; Junjie Sun; Koesrindartoto, Deddy; ...

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Physical Description
  • preprint
Language
  • English

Edition details

Title
  • An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs
Author
  • Deddy Koesrindartoto
  • Junjie Sun
  • Koesrindartoto, Deddy
  • Sun, Junjie
  • Tesfatsion, Leigh S.
Physical Description
  • preprint
Notes
  • In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by all U.S. wholesale power markets. The WPMP is a complicated market design envisioning day-ahead, real-time, and ancillary service markets maintained and operated by an independent system operator or regional transmission organization. Variants of the WPMP have been implemented or accepted for implementation in several regions of the U.S. However, strong opposition to the WPMP still persists in many regions due in part to a perceived lack of adequate reliability testing. This presentation will report on the development of an agent-based computational laboratory for testing the economic reliability of the WPMP market design. The computational laboratory incorporates several core elements of the WPMP design as actually implemented in March 2003 by the New England independent system operator (ISO-NE) for the New England wholesale power market. Specifically, our modeled wholesale power market operates over a realistically rendered AC transmission grid. Computationally rendered generator agents (bulk electricity sellers) and load-serving entity agents (bulk electricity buyers) repeatedly bid into the day-ahead and real-time markets using the same protocols as actual ISO-NE market participants. In each trading period the agents use reinforcement learning to update their bids on the basis of past experience. We are using our agent-based computational laboratory to test the extent to which the core WPMP protocols are capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain individual advantage through strategic pricing, capacity withholding, and induced transmission congestion. This presentation will report on some of our initial experimental findings.
  • Agent-based computational economics; Wholesale power market design; Learning agents
  • RePEc:sce:scecf5:50
  • In April 2003 the U.S. Federal Energy Regulatory Commission (FERC) proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design that has been adopted in some regions of the U.S. but resisted in others on the grounds that its reliability has not yet been sufficiently tested. This article reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue under study is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion. Related work can be accessed at: http:/​/​www.econ.iastate.edu/​tesfatsi/​AMESMarketHome.htm
  • Restructured wholesale power markets; FERC market design; Agent-based modeling
  • RePEc:isu:genres:12388
Language
  • English
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