Economic Dispatch of Power System Optimization with Power Generation Schedule Using Evolutionary Technique

Abstract

This paper presents an algorithm for solving optimal power flow problem through the application of Differential Evolution (DE). Reduction in fuel costs done of power generation by proper load dispatch schedule. So the overall costing of operation of power system can be reduced. The differential evolution algorithm is an evolutionary algorithm that uses a rather greedy and less stochastic method than do classical evolutionary algorithms such as particle swarm optimization (PSO) .Differential Evolution also incorporates an efficient way of self-adapting mutation using small population. The effectiveness of algorithm has been tested for a practical economic dispatch problem on a test system having three generating units. Thermal power generating firms needs to minimize fuel cost, for better profit at the same time it should satisfy system load demand, real, reactive power limit, voltage limit, power transmission limit and other limitations. For generation cost minimization Economic Load Dispatch (ELD) was developed. When cost is the single objective, the power generation may pollute the environment. Thermal electric power could not be generated without pollution but this pollution can be reduced for the sake of good and healthy atmospheric condition. To reduce emission the firm has to spent money, which is burden and reduces the power generating firms profit. These two opposite objectives should be compromised to find optimal operating condition of thermal power plants which may yield minimum fuel cost. Differential Evolution (DE) algorithm is used to solve this complex problem.