Sensor configuring optimization for grid harmonic monitoring based on improved PSO algorithm

This paper proposes an improved particle swarm optimization (PSO) algorithm to solve the sensor configuring optimization problem for the harmonic monitoring in the power grid. The model of the tested and un-tested node voltage and current is firstly set up. Then the PSO algorithm, which uses the logistic chaos method to obtain the initialized value for a better ergodic property and normalizes the existence possibility of the harmonic source based on least square fitting, is employed to calculate the best sensor installing locations and the minimum sensor numbers. The case study of East China power system has confirmed the effectiveness of the proposed method. It is shown that the proposed method requires less computing cycle indexes but meanwhile has the satisfied accuracy. The achievements obtained in this paper will be beneficial for the sensor configuring optimization for grid harmonic monitoring.