A fault classification method in power systems using DWT and SVM classifier

Abstract

This paper presents a method for fault classification in the power systems using a combination of support vector machine (SVM) classifier and Wavelet Transformation. Measurements from only one bus are utilized. Discrete Wavelet Transform (DWT) is used to extract the transient information of recorded voltages. The normalized wavelet energy of post-fault voltage and normalized energy of the post-fault currents are used as the input to the classifier. The classifier is trained with different fault scenarios in the power system. The transient voltages and phase currents for different types of faults and locations along the power system are obtained through ATP simulations. MATLAB is used to process the simulated transient voltages and apply the proposed method. The performance of the method is evaluated for two different networks; an overhead line combined with an underground cable and a 6-bus distribution network.