Genetic Algorithm Application in Distribution System Reconfiguration

This chapter describes genetic algorithm (GA) in detail and presents several examples to show its efficiency and effectiveness in solving the problem of distribution network reconfiguration. GA includes three basic operators (selection or reproduction, crossover, and mutation) that conduct chromosomes into the best fitness. The proposed GA-based distribution system reconfiguration (DSR) model is applied to several test systems using decimal codification of a branch (DCGA), improved DCGA (IDCGA), and efficient DCGA (EDCGA), and the results are presented in comparison with other GA methods. Evaluation of simulation results show that IDCGA and EDCGA solve the DSR problem in small-sized distribution networks more accurately and faster than DCGA and other genetic algorithms, in which EDCGA is the fastest method for solving DSR. It is concluded that EDCGA is the best method for studying the reconfiguration of radial distribution systems because of its high accuracy and low computational time.