Performance Analysis Of GA And PSO Over Economic Load Dispatch Problem

Economic load dispatch problem is one of the most popular concerns in power system engineering. Many method have been proposed in past to solve this. Genetic algorithm and particle swarm optimization are the most popular algorithms in term of optimization. This paper is implementation of GA and PSO over the Economic Load Dispatch problem. Comparison of both algorithms is shown here with a standard example when considering Loss and no Loss conditions. Economic Load Dispatch (ELD) is one of an important optimization tasks which provides an economic condition for a power systems. In this paper, Particle Swarm Optimization (PSO) as an effective and reliable evolutionary based approach has been proposed to solve the constraint economic load dispatch problem. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. In this paper, a piecewise quadratic function is used to show the fuel cost equation of each generation units, and the B-coefficient matrix is used to represent transmission losses. The feasibility of the proposed method to show the performance of this method to solve and manage a constraint problem is demonstrated in 4 power system test cases, consisting 3, 6 generation units with neglected losses in two of the last cases.