Study of Transients using Wavelet Transform

Abstract

This paper presents the study of power system transients using wavelet transform. Transients due to energization of capacitor banks and due to fault has been taken for consideration. The wavelet transform generates wavelet coefficients for the generated transients. Using Parsevals's theorem, energy and standard deviation are retrieved for transients. The wavelet transform is used to produce instantaneous frequency vectors of the signals, and then the energies of these vectors, obtained using Parseval's theorem, are utilized for the classification of different transients. The advantage of the proposed algorithm is its ability to distinguish different transients based on frequency change. The performance of this algorithm is bought bespeak by simulation of different events using MATLAB & SIMULINK software. The test results show that the new algorithm is very fast and accurate in identifying events. Keyword: Transients due to fault, Oscillatory transients, Wavelet transform and Parseval's theorem. I. INTRODUCTION Transients in power systems are temporary over voltages or over currents of short duration that lasts from few nano seconds to few milliseconds. The duration for which transients lasts is very insignificant when compared to the total operating time of the power system. But they cause immediate and most severe danger to sensitive electrical and electronic equipments, fire in some buildings, blackout in a city and shutdown of a plant, etc. Almost 80% of transients are internally generated like normal switching on or off of equipments, heating and ventilation systems, etc. Every industrial machine on power system practically causes transients or is adversely affected by transients. For better understanding the nature of the transient, they have to be sampled at a higher sampling rate because they are very fast and short duration waves [1]. In literature, there are several signal processing techniques like Fourier Transform (FT), Short-Time Fourier Transform (STFT), S-Transform, wavelet transform (WT) and wavelet packet transform (WPT) are used for examining the transients. Fourier Transform and Short-Time Fourier Transform can be used only for a fixed window width which is inadequate for the analysis of the transient non-stationary signals [2]. In modern spectrum and harmonic analysis, Discrete Fourier Transform (DFT) is used to monitor and assess the recorded data. Transient signal tracking using DFT is not successful, because of its fixed length window. The DFT method gives magnitude and phase angle of different frequency components of a periodic and stationary voltage or current waveform. Rectangular sampling windows of 10 cycles width in 50Hz power system is used and grouping of output bins of DFT analysis is done to compute the voltage and current waveform harmonic distortion. However DFT analysis only provides information in the frequency domain with a resolution that depends on the width of the time window. It doesn't give any time information about the signal provided [3]. The wavelet transform approac...

New Method for Transient Signal Analysis using the Continuous Wavelet Transform

“…Researchers have also explored the application of WT in various domains such as power quality analysis, acoustic signal processing, and seismic signal analysis [21][22][23]. The unique ability of WT to provide time-frequency localization makes it a valuable tool for analyzing nonstationary signals with transient characteristics [24,25]. Furthermore, the energy method based on wavelet packets has been utilized to calculate the energy of received signals in structural analysis [26].…”