Improved Particle Swarm Algorithm for Power Supply Reliability Improvement Optimization Study

Abstract

Particle swarm algorithm is a new intelligent optimization method based on the ability of individual cooperation optimization between individuals. This method obtains the optimal PSO in random optimization.   On this basis, an improved scheme based on particle swarm algorithm is proposed, which adopts a dynamic adjustment of inertia weight, and improves it so that it has good global optimization performance and local search performance. With the continuous improvement of PSO theory, its application in market auction trading, bidding strategy, market simulation and other aspects will have great room for development. Today, when human beings seek new ways of coordination and development with economy, technology and environment, computer technology is an important link in human development and the connection between science and technology and society. By dynamically adjusting the inertia weight and improving the position update strategy, the global optimization ability and local search ability can be better balanced, and the improved particle swarm algorithm can be applied to the reactive power optimization problem of power system to better solve the reactive power optimization problem.