Economic Load Dispatch Using Hybrid Swarm Intelligence Based Harmony Search Algorithm

Abstract This article presents a novel stochastic optimization approach to solve the constrained economic load dispatch problem using a hybridization of the harmony search algorithm and particle swarm optimization, named hybrid harmony search based on the swarm intelligence principle. Harmony search is a recently developed derivative-free, meta-heuristic optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This work is an attempt to utilize the velocity-based particle updating process from particle swarm optimization in the improvisation process of the harmony search algorithm for a better convergence of the proposed algorithm. The proposed methodology also easily takes care of solving non-convex economic load dispatch problems along with different constraints, such as power balance, ramp rate limits of the generators, and prohibited operating zones. Simulations were performed over four various standard test systems with different numbers of generating units, and a comparative study is carried out with other existing relevant approaches. The findings affirm the robustness and proficiency of the proposed methodology over other existing techniques.