Parameter Identification of Low Frequency Oscillation based on FastICA and Prony Algorithm
Zhibin Hu · Electrical Measurement & Instrumentation · 2014
Parameters are often identified by using Prony algorithm, but this method is sensitive to the noise of signals and has a high demand to the input signal. Therefore, the paper introduced FastICA(Fast Independent Component Analysis) and its basic principles, and then proposed a new algorithm, which combined FastICA and Prony algorithms to identify power system low frequency oscillation. First of all, wide area measurement signal was used as the input signal. And then the preprocessing signal was denoised by ICA algorithm.Finally, the parameters of low frequency oscillation in the power system were obtained by using Prony algorithm to analyze the denoised signal.Through analyzing the ideal signal and four-machine system, it was verified that the method could improve Prony's ability of accuracy, rapidity and anti-noise in identifying the parameters of low frequency oscillation after the signal was denoised.