Environmental/economic power dispatch using a hybrid multi-objective optimization algorithm

Abstract To solve the highly constrained environmental/economic dispatch problem involving conflicting objectives, this paper presents a hybrid multi-objective optimization algorithm based on particle swarm optimization (PSO) and differential evolution (DE). In this algorithm, a PSO with time variant acceleration coefficients is designed to explore the entire search space, while a local version of DE is proposed to exploit the sub-space with sparse solutions. A crowing distance-based approach is introduced to assign the particles’ leaders and to update the external archive. Moreover, a new technique for equality constraints is proposed to hurdle the unfeasible solutions directly. Finally, several optimization trials of the proposed algorithm are carried out on the IEEE 30-bus test system. Results demonstrate superiority of the proposed approach and confirm its potential to solve the multi-objective EED problem.