Analysis on transient power disturbance detection and characterization

Several methods of transient power disturbance detection are presented in this paper. The methods are used to detect disturbances and extract features and the results of simulation indicate respectively their characteristics. Fast Fourier transform can identify accurately frequency information of stable signals. Wavelet transform can detect discontinue points of signals. S transform can extract time domain and frequency domain features of signals. TLS-ESPRIT algorithm has high extremely frequency resolution, which can process the disturbance signals of several close frequency components.

I. Introduction

With the rapid development of waveform monitoring technology of power system in recent years, some scholars use waveform data analysis to monitor the operation condition of electrical equipment and estimate the safety of power gird. The appearances of some abnormal running states cause serious impact on industrial production and sensitive load. So it is necessary to detect and classify accurately various kinds of power disturbance detection.