Comparative study of the Genetic Algorithms and Hessians Method for Minimization of the Electric Power Production Cost

In this paper, we present a comparative study of the genetic algorithms and Hessian’s methods for optimal research of the active powers in an electric network of power. The objective function which is the performance index of production of electrical energy is minimized by satisfying the constraints of the equality type and inequality type initially by the Hessian’s methods and in the second time by the genetic Algorithms. The results found by the application of AG for the minimization of the electric production costs of power are very encouraging. The algorithms seem to be an effective technique to solve a great number of problems and which are in constant evolution. Nevertheless it should be specified that the traditional binary representation used for the genetic algorithms creates problems of optimization of management of the large-sized networks with high numerical precision. Keywords—Genetic algorithm, Flow of optimum load impedances, Hessians method, Optimal distribution.