Research on Power Quality Data Placement Strategy Based on Improved Particle Swarm Optimization Algorithm

Abstract

For the national grid power quality monitoring system, the effective integration of monitoring terminals, the master stations of each network and the province and the state grid data center work together, the reasonable placement of the monitoring data in the system, and the relief of the calculation pressure of the state grid data center are the project research focus. From a global perspective, this paper models and describes the data placement problem of the harmonic monitoring system, and proposes a data placement strategy based on an improved particle swarm optimization algorithm. This paper proposes an initial population generation algorithm based on Markov random walk, which enables individuals in the initial population to have a certain degree of clustering accuracy and strong diversity. The initial population generation algorithm cooperates with the particle swarm optimization algorithm, which effectively enhances the algorithm's optimization ability. Through comparative experiments with traditional data placement strategies, the experimental results show that the data placement strategy based on improved particle swarm optimization algorithm has higher efficiency.