Using genetic algorithm for optimal dispatching of reactive power in power systems

Abstract

Genetic algorithms are widely recognized as efficient tool for solution of complex and non-linear optimization problem of optimal reactive power dispatch and voltage control in power systems. The paper is addressed to the consideration of influence of different methods for generating initial population for genetic algorithm performance. Genetic algorithm operates on individuals representing some solutions. Randomly generated initial population evolve during the evolutionary process with use of some operations into the final population including probably the best task solution. The way of creating initial population decides on covering initial solution space. Hence, it may affect genetic algorithm performance. There exist variety of methods to generate members of initial population covering solution space. The paper presents an evaluation of pseudo-random numbers, gaussian and some space point process based algorithms to produce initial population in terms of the convergence speed and quality of the obtained optimization results.