Stochastic Dynamic Programming Applied to Multireservoir Systems

by Thanos Trezos, Southern California Edison, United States,
William W. -G. Yeh, Southern California Edison, United States,

Abstract: The main goal of this work was to develop a large scale optimization algorithm incorporating the principle that the uncertainty of future events increases with time. This principle governs the forecast of hydrological processes as well as hydropower production needs. This paper discusses the development of a stochastic dynamic programming (DP) algorithm for reservoir management. The algorithm uses the decomposition principle of DP without discretizing the state or control space. It is an iterative procedure which solves a series of quadratic programming problems at each iteration. The paper concludes with the problems encountered in the technology transfer of the developed methodology from an academic, mathematically precise model to an applied working tool.

Subject Headings: Computer programming | Algorithms | Hydrology | Stochastic processes | Reservoirs | Hydro power | Optimization models

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