Modified particle swarm optimization for economic-emission load dispatch of power system operation

摘要

This paper proposes a modified particle swarm optimization considering time-varying acceleration coefficientsfor the economic-emission load dispatch (EELD) problem. The new adaptive parameter is introduced to update theparticle movements through the modification of the velocity equation of the classical particle swarm optimization (PSO)algorithm. The idea is to enhance the performance and robustness of classical PSO. The price penalty factor method isused to transform the multiobjective EELD problem into a single-objective problem. Then the weighted sum method isapplied for finding the Pareto front solution. The best compromise solution for this problem is determined based on thefuzzy ranking approach. The IEEE 30-bus system has been used to validate the effectiveness of the proposed algorithm.It was found that the proposed algorithm can provide better results in terms of best fuel cost, best emissions, convergencecharacteristics, and robustness compared to the reported results using other optimization algorithms.