Economic Load Dispatch Using Evolutionary Algorithms

Abstract

Ensuring a smooth electrical energy to the consumer has been identified as the main role of electric supply utility. The power utility needs to ensure that the electrical power is generated with minimum cost. Hence, for economic operation of the system, the total demand must be appropriately shared among the generating units with an objective to minimize the total generation cost for the system. Thus, Economic load dispatch (ELD) is one of the important problems of power system operation and control. This work proposes evolutionary optimization techniques namely Genetic Algorithm and Evolutionary Programming to solve ELD in the electric power system, which are generic population, based probabilistic search optimization algorithms and can be applied to real world problem. In this thesis, the two main types of EAs, which are genetic algorithm (GA) and evolutionary programming (EP), are respectively applied to solve an ELD problems. Also, a Classical Lagrange Multiplier Method is used to solve the same problem. And at the last the comparison between the three methods has been presented. The EAs provides the generation level such that the total losses are reduced and the generation cost is coming out to be lower than the cost resulted with Lagrange Multiplier method.