Multi Objective Economic Emission Dispatch Using Modified Multi Objective Particle Swarm Optimization

Abstract

Today the major objective for thermal power generation is to optimize cost as well as emissions because operating at absolute minimum cost can no longer be the only criterion for dispatching thermal power due to increasing concern over the environmental considerations. The multi objective economic-emission dispatch (MOEED) is a conflicting objective function problem which accounts for minimization of both cost and emission. Modified multi objective particle swarm optimization (MOPSO) technique presents a multiobjective version of the conventional PSO technique and utilizes its efficiency to solve the multi objective optimization problems. In this dissertation work, dynamic search space squeezing strategy based MOPSO has been implemented to solve MOEED optimization problem. By applying modified MOPSO, multiple Pareto-optimal set (non dominated solutions) is produce in a one simulation run. The simulation results also expose the advantage of the modified MOPSO technique in terms of the variety and excellence of the obtained Pareto-optimal solutions. To extract best compromise solution from the set of non-dominated solutions a fuzzy cardinal approach is used. In this dissertation MOEED problems have been solved for six and ten generating unit systems using dynamic search space strategy based modified MOPSO algorithm.