Swarm Intelligence Methods for Optimal Network Reconfiguration of Distribution System

There are numerous approaches being used to reduce power losses in the distribution system. In this work, the concept of network reconfiguration is used in an effort to provide new algorithms to decrease distribution system losses. The network reconfiguration issue must be solved with effective distribution load flow (DLF). Two key components are required for the Optimal Network Reconfiguration (ONR) strategy to reduce losses: first, promising radiality for the reconfigured network, and second, providing optimal losses for the final reconfigured network. The complex computational problem of network reconfiguration is addressed using five meta-heuristic techniques: Genetic Algorithm (GA), Shuffled Frog Leap Algorithm (SFLA), Particle Swarm Optimization (PSO), Pigeon Inspired Optimization (PIO), and Jaya Optimization algorithm. These techniques take into account equality and inequality constraints to find the best network reconfiguration with the minimum power losses in the system. The IEEE 33 bus distribution system is used as a test case, and the test system is subjected to network reconfiguration. Results of different algorithms were included. Over the other algorithms, the Pigeon Inspired Optimization (PIO) algorithm outperforms them.