An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs
AbstractIn 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.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2005 with number 50.
Date of creation: 11 Nov 2005
Date of revision:
Agent-based computational economics; Wholesale power market design; Learning agents;
Other versions of this item:
- Koesrindartoto, Deddy P. & Sun, Junjie & Tesfatsion, Leigh, 2005. "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs," Staff General Research Papers 12388, Iowa State University, Department of Economics.
- L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
- L5 - Industrial Organization - - Regulation and Industrial Policy
- L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
- C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
- C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-11-19 (All new papers)
- NEP-CMP-2005-11-19 (Computational Economics)
- NEP-COM-2005-11-19 (Industrial Competition)
- NEP-ENE-2005-11-19 (Energy Economics)
- NEP-GTH-2005-11-19 (Game Theory)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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