Commitment of Electric Power Generators Under Stochastic Market Prices

Jorge Valenzuela () and Mainak Mazumdar ()
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Jorge Valenzuela: Department of Industrial and Systems Engineering, Auburn University, Auburn, Alabama 36849-5346
Mainak Mazumdar: Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261

Operations Research, 2003, vol. 51, issue 6, 880-893

Abstract: A formulation for the commitment of electric power generators under a deregulated electricity market is proposed. The problem is expressed as a stochastic optimization problem in which expected profits are maximized while meeting demand and standard operating constraints. Under an assumption of perfect competition, when an electric power producer has the option of trading electricity at market prices, a unit commitment schedule can be obtained by optimizing the self-commitment of each unit separately subject to stochastic prices. Three certainty-equivalent formulations of the stochastic self-commitment problem are provided. The procedures involve application of dynamic programming, statistical analysis, and asymptotic probability computations. The price of electricity is represented by a stochastic model depending on demand, generating unit reliabilities, and temperature fluctuations. We use several approximation methods (normal, Edgeworth series expansion, and Monte Carlo simulation) for computing the required probability distributions. Numerical examples are provided for a market consisting of 150 generating units.

Keywords: Decision analysis: unit commitment decisions under uncertainty; Production/scheduling: electric power generation under deregulation (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (7)

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