Chaotic Particle Swarm Optimization with Attractive Search Space Border Points for Optimal Reactive Power Dispatch

Abstract

This paper presents a reliable approach for optimal reactive power dispatch based on chaotic particle swarm optimization with attractive search space border points, where the particles are randomly attracted to the boundary points of the search space in each direction avoiding stagnation of the population. The introduction of chaotic dynamics improves the stability and rate of convergence. The algorithm is further improved by using Latin Hypercube Sampling (LHS) to create diversity in the population. The proposed algorithm is used for optimal reactive power dispatch with three objective functions, namely: minimization of real power loss, voltage stability index, and sum squared voltage deviations. The algorithm is tested on a standard 30-bus system of the Institute of Electrical and Electronics Engineers (IEEE) and on a practical 75-bus Indian Power System. The results obtained with the proposed algorithm are compared with the conventional interior point method and the basic particle swarm optimization algorithm, and the effectiveness of the proposed algorithm is demonstrated.