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Multi-stage stochastic optimization applied to energy planning
Authors:M V F Pereira  L M V G Pinto
Institution:(1) Electric Engineering Department, Catholic University of Rio de Janeiro, P.O. Box 38063, 22452 Gavea, Rio de Janeiro, RJ, Brazil
Abstract:This paper presents a methodology for the solution of multistage stochastic optimization problems, based on the approximation of the expected-cost-to-go functions of stochastic dynamic programming by piecewise linear functions. No state discretization is necessary, and the combinatorial ldquoexplosionrdquo with the number of states (the well known ldquocurse of dimensionalityrdquo of dynamic programming) is avoided. The piecewise functions are obtained from the dual solutions of the optimization problem at each stage and correspond to Benders cuts in a stochastic, multistage decomposition framework. A case study of optimal stochastic scheduling for a 39-reservoir system is presented and discussed.
Keywords:
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