Application of Improved Adaptive Particle Swarm Optimization Algorithm in Reactive Power Optimization

Abstract

In this paper, the Particle Swarm Optimization (PSO) algorithm converges too fast, easy access to local convergence, leading to convergence accuracy is not high, to study the particle swarm algorithm improvements. Some parameters in the traditional PSO algorithm need to be predefined by tests, so the practicability of algorithms is restricted. For this reason, an improved adaptive particle swarm optimization (IAPSO) algorithm is proposed and applied to reactive power optimization of Power system. The establishment of a comprehensive consideration of the practical constraints and reactive power regulation means no power optimization mathematical model proposed by improved adaptive particle swarm optimization algorithm for solving the problem of reactive power method to determine the optimal reactive power optimization program. According to PSO handling characteristics of the variable capacity, particle swarm optimization algorithm applied to a continuous emphases on control variables to optimize regulation, reactive power optimized for efficient operation provides a practical and reliable foundation.