Dynamic Economic Dispatch Solving in Power Systems Using Imperialist Competitive Algorithm

The dynamic economic dispatch (DED) problem is an extension of the conventional static load dispatch problem in the context of electrical power generation. In this paper,issues related to the implementation of the several soft computing techniques are highlighted for a successful application to solve dynamic economic dispatch (DED)problem, which is a constrained optimization problem in power systems. First of all, a survey covering the basics of thetechniques is presented and then implementation of the techniques in the DED problem is discussed. The soft computing techniques, namely multi-layered perceptronneural network (MLP NN), genetic algorithm (GA), Imperialist Competitive Algorithm(ICA), particle swarm(PSO) and are applied to solve the DED problem. The Evolutionary Algorithms are tested on power system consisting 3 generating units and the results are compared together. Suggestion is presented to improve techniques

Dynamic Economic Dispatch Solving in Power Systems Using Imperialist Competitive Algorithm Keywords:

MLP Neural Network , Imperialist Competitive Algorithm , Genetic Algorithm , Particle Swarm Optimization , Constrained Optimization