Environmental/Economic Power Dispatch Using Multi-objective Gravitational Search Algorithm

One of the most important operational functions in todayenergy management system is environmental/economic dispatch (EED). The environmental issues that arise from the pollutant emissions produced by fossil-fueled electric power plants have become a matter of concern recently. This paper presents a multi-objective Gravitational Search Algorithm (MOGSA) for environmental/economic power dispatch (EED) problem.The EED problem is formulated as a nonlinear constrained multi-objective problem with competing and incommensurable objectives of fuel cost, emission and system loss. The proposed MOGSA approach adopts an external elitist archive to retain non-dominated solutions found during the evolutionary process. In order to preserve the diversity of Pareto optimality, a crowding entropy diversity measuring tactic is proposed. The crowding entropy strategy is able to measure the crowding degree of the solutions more accurately. IEEE30 and 118 bus test systems were studied. The effectiveness of the proposed approach are demonstrated by comparing its performance with other evolutionary multi-objective optimization algorithms such as NSGA, NPGA, SPEA, MOPSO and MODE. The comparison with reported results of other multi objective optimization algorithms reveals the superiority of the proposed MOGSA algorithm and confirms its great potential in handling the multi-objective problems in power systems.