Identify and classify fault in power system using wavelet transform

Identify and classify fault in power system using wavelet transform

Abstract—The power utility companies have been trying to identify and locate three-phase transmission line faults in the shortest possible time in order to prevent economic losses. In the last few decades, technology used for power system protection has evolved from electromechanical devices to solid state and processor-based intelligent devices. This study presents the design and implementation of a wavelet analysis-based fault detection and identification module that contemplates< Final Year Project > the analysis of high frequency transients produced during faults. The design was implemented on a cost effective low-end embedded system. The proposed logic employs a multi-resolution wavelet analysis of high frequency details in the range of 5-10 kHz. The amount of high frequency components present in the transformed current signals, obtained after processing, identifies the fault. The ground and line-to-line faults were classified on the basis of the adaptive thresholds obtained from system behaviour. The proposed approach, after the completion of simulations, was implemented on a digital signal controller. The developed fault detection and identification prototype was successful in accurately identifying the power system faults, thus validating the feasibility of the proposed methodology.