Hybridization of Particle Swarm Optimization with Differential Evolution for Solving Combined Economic Emission Dispatch Model for Smart Grid

Abstract

This paper introduces a CEED model for smart grid system and solves it by hybridizing the renowned optimization algorithms such as Particle Swarm Optimization (PSO) and Differential Evolution (DE). The hybridization of these two renowned algorithms is accomplished by using the solution updating process of both the algorithms and combining them with random searching procedure.  The CEED model is subjected to minimize its cost so that adequate trade – off between the economic and emission costs can be maintained in minimizing them. The proposed hybrid algorithm is experimented on three different bus systems and its performance is compared against individual PSO and DE and a recently framed hybridization of PSO and DE. The comparison results show the superiority of the proposed hybrid heuristic search algorithm in terms of solution quality and the computational efficiency.