Algoritmo evolução diferencial modificado aplicado ao problema do despacho econômico de carga

Abstract

This work proposes a modifiation of the Diffrential Evolution (Evolução Diferencial ED) algorithm to solve the problem of the Economic Load Dispatch (Despacho Econômico - DE), where it is desired to fid the generation level of each thermo electric generating unit satisfying the total system demand at the lowest cost, satisfying the constraints of the problem. The ED is an algorithm based on the theory of natural selection of species of Charles Darwin, where the fites t are more likely to survive. In the original ED we have an initial population composed of each possible solution to the target problem. This population is evolved through of the genetic operators of mutation, crossover and selection of the individuals to be inserted in the new population. At each iteration of the ED a new population is generated, replacing the old, which is discarded. At the end of execution, the ED should return the best solution found. The modification of the ED (EDM) in this dissertation considers that, in the selection stage, the most able individual will replace the old one in the current population, instead of being inserted in the new population. To verify the performance of the EDM in relation to the original ED, we solve a set of test functions in order to obtain the global minimum and different instances of the DE. Both algorithms were effective in minimizing the three least dimensional functions. Our results showed that ED proved more effective than EDM in minimizing the set of higher dimensional test functions, presenting a solution up to 99.99% better. However, none of the algorithms managed to obtain the optimal solution. In the ED resolution, ED M proved to be more effective than ED in all cases, finding a solution up to 10.22% better. In addition, the computation time reduction of EDM in relation to ED was up to 98.69%. Therefore, we confirm the effiency of the proposed modification over the original ED version.