Application of a Hybrid Particle Swarm Optimization Algorithm in Optimal Operation of Reservoir

Abstract

Reservoir optimal operation is a nonlinear, multi-stage and strong constraint combinatorial optimization problem. As the standard particle swarm optimization (SPSO) easily trapped into local optima, this paper proposes a hybrid algorithm combining particle swarm optimization algorithm with chaotic search algorithm, also referred to as CPSO algorithm. Making use of the stochastic property and ergodicity of chaotic search, the CPSO algorithm not only overcome the disadvantage of premature convergence, but also strengthens global search ability and gets a higher convergent accuracy. The experimental results show that the proposed hybrid CPSO algorithm is better than the SPSO in convergent speed and convergent accuracy, and is an effective and efficient new optimization method to solve the problem of optimal operation of hydropower station reservoir.