High impedance fault detection in radial distribution system using wavelet transform

Abstract

This paper presents a novel wavelet transform based approach to detect High impedance fault (HIF) in the distribution line. Due to the limitation of distance relays and over current relays like insensitive to detect very low value fault current, it is unreliable to apply as a fault detector for HIF in distribution line. As wavelet transform (WT) is a very useful tool for analyzing transient fault signal which also provides both time and frequency information, the same has been considered for High impedance fault detection. This method based on various features like the sum of energy contents, standard deviation and entropy of coefficients in multiresolution analysis (MRA) based on wavelet transform. Artificial Neural Network (ANN) and Support Vector Machines (SVM) are used as a machine learning technique to discriminate the HIF from other transient phenomenon (Load switching, capacitor Switching) and normal fault. The proposed schemes are fully analyzed by extensive MATLAB simulation studies that clearly reveal that the proposed method can detect HIF in high voltage distribution line with high accuracy.