A Hybrid Particle Swarm Optimization Employing Crossover Operation for Economic Dispatch Problems with Valve-point Effects

Abstract

This paper presents an efficient approach for solving the economic dispatch (ED) problems with valve-point effects using a hybrid particle swarm optimization (PSO) technique. Although PSO-based algorithms are easy to implement and have been empirically shown to perform well on many power system optimization problems, they may get trapped in a local optimum due to premature convergence when solving heavily constrained optimization problems with multiple local optima. This paper proposes an improved hybrid PSO (HPSO), which combines the conventional PSO framework with the crossover operation of genetic algorithm. By applying the crossover operation in PSO, it not only discourages premature convergence to local optimum but also explores and exploits the promising regions in the search space effectively. To verify the effectiveness of the proposed method, numerical studies have been performed for the large-scale test system of 40 generating units with valve-point effects. The simulation results show that the proposed HPSO outperforms other state-of-the-art algorithms as well as the conventional PSO method in solving ED problems with valve-point effects.