Solving long-term hydro-thermal scheduling problems

Abstract

The Long-Term Hydrothermal Scheduling (LTHS) problem plays an important role in power systems that rely heavily on hydroelectricity. The purpose of the LTHS problem is to define an optimal operation policy that uses stored water as inexpensively as possible. A popular solution approach to this problem is called Stochastic Dual Dynamic Programming (SDDP). In this paper we describe LTHS and SDDP, as well as discussing strategies to improve the performance of the algorithm. These strategies are tested with some numerical experiments on the New Zealand hydrothermal system. We show empirically that the computational burden can be reduced significantly by adopting some of these strategies.