Discrete Particle Swarm Optimization to Network Reconfiguration for Loss Reduction and Load Balancing

Abstract

Abstract Particle swarm optimization (PSO) has emerged as a useful optimization tool for handling non-linear programming problems. Various modifications to the basic method have been proposed with a view to enhance speed and robustness. This method has been applied successfully on some benchmark mathematical problems. A few PSO applications have been reported on real-world problems, such as network reconfiguration for loss reduction, load balancing, and even capacitor placement in distribution systems being discrete in nature. PSO is modified to discrete particle swarm optimization (DPSO). The results of DPSO are compared with the results of the genetic algorithm.