Active Distribution Network Reactive Power Optimization Based on an Improved Genetic Particle Swarm Optimization Algorithm

Abstract

As the distributed generation is gradually connected to the distribution network, it will lead to an increase in node voltage deviation and network loss. The active distribution network reactive power optimization approach based on an improved genetic particle swarm optimization algorithm is proposed in this paper to increase voltage quality and system efficiency. First, a reactive power optimization model for active distribution networks that has the least possible active power loss and voltage variation is developed. Then, the genetic idea is applied to the particle swarm optimization algorithm to improve it and address the issues of the long iteration time of the genetic algorithm and the tendency of the particle swarm optimization algorithm to settle into local optimal solutions. Finally, the enhanced genetic particle swarm optimization algorithm described in this paper is validated using the enhanced IEEE-33 node system. The findings indicate that this strategy can significantly shorten computation times while also increasing calculation precision.