CVT Stray Capacitance Optimization Based on Multi-Random Variable Parameter Optimization Method

Abstract

Aiming at the problem that the capacitive voltage transformer is affected by the fluctuation of stray capacitance parameters during harmonic measurement and the uncertainty of stray capacitance parameters, a parameter optimization method based on multi-random variable parameters is proposed to optimize the combination of stray capacitance parameters. The search ability of multi-random variable parameter optimization method is weak, and the search is assisted by particle swarm optimization. Considering that the particle swarm optimization algorithm is easy to fall into the local optimum and the existing problems of using the cross and cross algorithm to improve the particle swarm optimization algorithm, the vertical crossover operator based on the CSO re-improves the particle swarm optimization algorithm. According to the actual measured CVT harmonic transfer characteristic curve and the simulation results after optimizing the stray capacitance parameters, the accuracy of the multi-random variable parameter optimization method is verified. It provides a certain method basis for parameter optimization such as CVT stray capacitance and CVT harmonic correction for different models in the future.