Production planning under uncertainty: the case of hydrothermal systems

Abstract

This paper formulates the hydrothermal production planning problem as a multi-stage stochastic programming model. This problem is usually solved using algorithms that are based on dynamic programming and nested Benders decomposition (NBD). The hydrothermal planning problem is remodelled as a capacitated production planning model with convex costs; then a vanishing effect property of the first period decision is derived. Based on this property, a special implementation scheme of the NBD algorithm is proposed, providing faster convergence and less computational effort. The NBD algorithm is implemented for a large-scale hydrothermal power system of the Pacific Northwest in the USA with 20 thermal plants and 21 thermal plants.