Fault Detection and Classification on a High voltage Transmission Line Using Wavelet Transforms

Abstract

Electrical power system consists of many different complex dynamic and interacting elements, which are always prone to disturbance or an electrical fault. Transmission lines are exposed to atmosphere, the faults due to transmission lines are about 50% as compared to different types of faults that occur in the power system. The faults on electrical power system transmission lines are supposed to be first detected and then be classified correctly and should be cleared in least fast as possible time. This paper describes a fault-detection technique of faults in high voltage transmission lines using the wavelet transform. The wavelet transform (WT) has been successfully applied in many fields. The technique is based on using the absolute sum value of coefficients in multi resolution signal decomposition (MSD) based on the discrete wavelet transform (DWT). A fault indicator and fault criteria are then used to detect the faults in the transmission line. Wavelet transform is best suited for fault detection and classification. This paper describes a new fault detection technique which involves capturing the current signals generated in a system under faults. The detection process is based on calculating the absolute sum of the wavelet transform detail coefficients for one period. Wavelet transform is used for the decomposition of signals and feature extraction.