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A Stochastic Programming Approach to Power Portfolio Optimization

SIE Department, MORE Institute, University of Arizona, Tucson, Arizona 85721
SIE Department, MORE Institute, University of Arizona, Tucson, Arizona 85721
SIE Department, MORE Institute, University of Arizona, Tucson, Arizona 85721
sen{at}sie.arizona.edu
lyu{at}pplweb.com
tgenc{at}uoguelph.ca

We consider a power portfolio optimization model that is intended as a decision aid for scheduling and hedging (DASH) in the wholesale power market. Our multiscale model integrates the unit commitment model with financial decision making by including the forwards and spot market activity within the scheduling decision model. The methodology is based on a multiscale stochastic programming model that selects portfolio positions that perform well on a variety of scenarios generated through statistical modeling and optimization. When compared with several commonly used fixed-mix policies, our experiments demonstrate that the DASH model provides significant advantages.

Subject classifications: programming; stochastic; industries; electric; finance; portfolio.
History: Received December 2002; revision received August 2003; revision received September 2004; accepted November 2004.

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