Harmonic Coupling Characteristic Analysis of VSC under Single-phase Fault Conditions

With the widespread application of voltage source converters (VSCs) in power systems, the harmonic issue is becoming increasingly prominent. Although this harmonic issue has been comprehensively and deeply studied in recent years, the harmonic coupling characteristics of VSC under power system fault conditions still remain and urgently need to be analyzed in-depth. Focusing on the topology of two-level VSC and respectively using the methods of Short Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT), this article analyzes the time-frequency characteristics of current waveforms flowing through the AC and DC ports of the VSC under power system fault conditions. And a wavelet neural network algorithm with particle swarm optimization (PSO-WNN) is proposed for quickly obtaining the harmonic content indexes of above current waveforms. Also, an overall framework is specially designed for programmable analysis of the harmonic coupling characteristics of VSCs operating in power system. In this article the results of a case study are given, and show that compared with the existing BP neural network methods, the proposed PSO-WNN algorithm has higher solving accuracy and faster convergence speed.