Capacitor Replacement in Distribution Networks using Genetic Algorithm

In researches, some of the algorithms such as genetic algorithms belong to the larger class of evolutionary algorithm, which generates solutions to optimization problems using techniques inspired by natural evolution. Genetic algorithm, neural networks, and the methods such as cement grout, Morchegan theory and Body Immune Algorithm are involved in the algorithms and methods which have been obtained through phenomena and natural matters .through this, genetic algorithm is one of the optimal algorithms which is based on the base of Darwin’s theory of evolution, driven by the survival of the fittest .Today, genetic algorithm have found application in engineering science. In a genetic algorithm, a population of strings, chromosomes, which encode candidate solution to an optimization problem, is evolved toward better solutions. Traditionally, solutions are represented in binary, but other encodings are also possible. The evolution usually starts from a population of randomly generated individuals and happens in generations. In this article, different methods of Capacitor replacement in distribution networks have been considered, which these methods could be accomplished through genetic algorithm. Hence, in this article the optimal criterion and the Capacitor replacement in sensitive points of network would be determined; also the objective function and intervention of different economical parameters have been introduced in this article as well.

Genetic algorithm, capacitor, chromosome, economical parameters, distribution networks.