Comparing the performance of various mother wavelet functions in detecting actual 3-phase voltage sags

Abstract

Conventional methods currently used by power utilities for detecting power quality disturbances are primarily based on visual inspection of the rms value of voltage and current waveforms recorded by power quality recorders. The disturbance detection and classification results can help to identify any potential degrading trends in the electrical system. Once identified, inspection and preventive maintenance can be carefully targeted to the specific equipment, allowing us to avoid electrical disruptions altogether. However, to perform manual analyses on all the recorded voltage events is time consuming. Therefore an automated technique for analyzing the recorded signals is required. Currently, advanced signal processing techniques such as short time fourier transform (STFT) and continuous wavelet transform (CWT) are widely used for analyzing voltage events. In the CWT approach, the original signal is multiplied with a function known as the mother wavelet. The mother wavelet is actually a prototype for generating the other window functions. However, there are many mother wavelet functions to be selected for generating the other functions and it is important to determine the best mother wavelet function for accurate detection of disturbances. In this paper, an evaluation is done on the various mother wavelet functions in analyzing actual three phase voltage sags. The mother wavelet that portrays the best resolution for the contours is selected for further detection and classification of voltage sags in the local supply systems.