A MILP Based Approach for Hydrothermal Scheduling

Abstract

This paper presents new solution approaches capable of finding optimal solutions for the Hydrothermal Scheduling Problem (HSP) in power generation planning. The problem has been proven to be NP-hard and no exact methods have been able to tackle it, for problem sizes of practical relevance. We explore three approaches. The first method is an iterative algorithm that has been successfully used previously to solve the thermal commitment problem. The two other methods are ``Local Branching'' and a hybridization of ``Particle Swarm Optimization'' with a general purpose solver. Computational experiments show that the iterative piecewise linear approximation method outperforms more elaborated approaches, indicating that recourse to matheuristics for solving this problem is not necessary.