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Dynamic Pricing and Learning in Electricity Markets

Systems and Information Engineering Department, University of Virginia, Charlottesville, Virginia 22904
Department of Engineering Management and Systems Engineering, The George Washington University, Washington, DC 20052
The Brattle Group, 1133 20th Street, NW, Washington, DC 20036
agarcia{at}virginia.edu
ecamposn{at}gwu.edu
james.reitzes{at}brattle.com

We analyze the price-formation process in an infinite-horizon oligopoly model where hydroelectric generators engage in dynamic price-based competition. The analysis focuses on the role of "indifference" prices, i.e., prices that equate the gains from releasing or storing water. Strategies where players bid their indifference prices and the marginal player undercuts the lowest-cost unsuccessful bidder constitute a Markov Perfect Equilibrium (MPE) under appropriate conditions. These conditions involve symmetric production capacity and nonfractional (i.e., "all or nothing") output by successful bidders. Although the MPE solution represents an equilibrium consistent with dynamic strategic behavior, it requires computational sophistication by market participants. However, a basic "learning" procedure involving indifference prices converges to an MPE.

Subject classifications: games: stochastic; noncooperative; natural resources: energy; water resources; economics; restructured electricity markets; dynamic auctions.
History: Received April 2002; revision received November 2003; accepted January 2004.

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