Optimal capacitor placement in distribution systems by genetic algorithm

The genetic algorithm uses a biological analogy to evolve a population of search-space points toward an optimal solution, and has been applied to several disiplines in engineering and the sciences. The algorithm is attractive due to its ease of implementation, its lack of differentiability requirements on the objective function, and, its ability to find globally optimal solutions. These properties allow optimization of a practical formulation of the capacitor placement problem which includes the discrete nature of capacitor installations. In this paper, the genetic algorithm's structure, its application to the capacitor placement problem in distribution systems, and experimental numerical results are presented. Additionally, several implementation issues including selection pressure, fitness scaling and ranking, unity crossover probability, and the selection of generalized control parameters are examined in details.