Fuzzy logic controlled differential evolution to solve economic load dispatch problems


In recent years, soft computing methods have generated a large research interest. The synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. A particular evolutionary algorithm (EA) is differential evolution (DE). As for any EA, DE algorithm also requires parameters tuning to achieve desirable performance. In this paper tuning the perturbation factor vector of DE is done with a Fuzzy Logic Controller (FLC) that adjusts this parameter dynamically. We apply the fuzzy logic controlled differential evolution(FLC-DE) to solve the economic load dispatch problem of two test systems consisting of 13 and 40 thermal generators whose non-smooth fuel cost function takes into account the valve-point loading effects. Simulation results indicate that the performance of the FLC-DE present the best results when compared with other optimization approaches in solving economic load dispatch problems.