A New Multiobjective Evolutionary Algorithm for Environmental/Economic Power Dispatch

Abstrack In this paper, a new multiobjective evohrtionary algorithm for EnvironmentaUEconomic power Dispatch (EED) optimimtion problem is presented. The EED problem is formulated as a nonlinear constrainedmultiobjective optimization problem with both equatity and inequality constraints. A new Nondominated Sorting Genetic Atgorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. The proposed approach employs a diversity-preservingtechnique to overcome the premature convergence and search bias problems and produce a wetl-distributed Pareto-optimal set of nondominated solutions. A hierarchical clustering technique is also imposed to provide the decision maker with a representative and manageable Paretooptirnal set. Severaloptimization runs of the proposed approach are carried out on a standard IEEE test system. The results demonstrate the capabilities of the proposed NSGA based approach to generate the true Pareto-optimal set of nondominated solutions of the multiobjective EED problem in one single run. Simulation results with the proposed approach have been compared to those reported in the literature.The comparison shows the superiority of the proposed NSGA based approach and confirms its potential to solve the multiobjectiveEED problem.