A novel multi-objective genetic algorithm for economic power dispatch

A fuzzy multi-objective genetic algorithm (FMOGA) approach for the multi-objective economic power dispatch problem is presented in this paper. The economic power dispatch problem is a nonlinear constrained multi-objective optimization problem. The proposed FMOGA approach handles the problem as a multi-objective problem with competing and non-commensurable fuel cost, emission and system active power loss objectives. The proposed FMOGA employs a fuzzy evaluation factor to the fitness function of MOGA, which can prevent the premature convergence of the genetic algorithm. As well FMOGA can deal with "gene drift" caused by large bound of objectives. Several optimization runs of the proposed FMOGA approach are carried out on the standard IEEE 30-bus test system. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto-optimal non-dominated solutions of the multi-objective economic power dispatch.