A CVT Parameter Identification Method Based on Improved Grey Wolf Optimizer

Abstract

Aiming at the problem that harmonic simulation model parameters of capacitive voltage transformer (CVT) are difficult to determine, an identification method of equivalent circuit parameters of CVT is proposed. By studying the frequency response, a nonlinear equation about the equivalent circuit parameters of CVT is established. By analyzing the characteristics of the equation and combining with the actual use, an improved grey wolf optimizer is applied to achieve the accurate identification of the key parameters of CVT. On the basis of grey wolf optimizer, the algorithm introduced a good point set and comprehensive dimension learning strategy to prevent the algorithm from falling into local optimum, and modified the convergence factor according to the actual needs to improve the convergence accuracy. Finally, three numerical examples are simulated by MATLAB/Simulink software, which proves the feasibility and superiority of the proposed method in CVT application.