A Hybrid Particle Swarm Optimization Algorithm For the Economic Dispatch Problem

This article proposes a hybrid global-local algorithm - hybrid particle swarm optimization (hpso) - applied to solve the economic dispatch (ed) problem. the hpso algorithm combines the classical particle swarm optimization (pso) with the conjugate gradient (cg) non-linear optimizing method, included in the optimizing tool within mathcad commercial software product. the global optimizer is the pso algorithm, and the local one is the cg method. two variants including the cg within the pso, which are analyzed, called hpso-rc (randomly controlled) and hpso-ru (randomly uncontrolled). both pso and cg methods are easy to implement and together help reaching the best solution. the hpso algorithm’s ability to avoid premature convergence and provide a stabile solution is tested on three systems consisting of 6, 13 and 38 thermal generating units. the hpso algorithm’s efficiency in solving the ed problem is shown through a comparison with several other recently published algorithms.