Optimal Reconfiguration of Distribution Network for Power Loss Reduction and Reliability Improvement Using Bat Algorithm

In power systems, reconfiguration is one of the simplest and most low-cost methods to reach many goals such as self-healing, reliability improvement, and power loss reduction, without including any additional components. Regarding the expansion of distribution networks, communications become more complicate and the number of parameters increases, which makes the reconfiguration problem infeasible using mathematical models. Therefore, using intelligent algorithms become candidate solutions. On the other hand, analysis of opened and closed switches should be without error and should be done in line with the network constraints like, tolerable current flow of each branch, permissible voltage of the busbars, and the line power flow. Therefore, among evolutionary algorithms, an algorithm with enough accuracy and convergence speed is used. In this study, the performance of binary bat, dragonfly, genetic, and PSO (Particle Swarm Optimization) algorithms is compared in the network reconfiguration IEEE 16-bus and 33-bus test systems with the aim of reaching a topology with the minimum loss in power and the maximum reliability. The results show that binary bat algorithm has the best performance among other algorithms.