Methodologies in power systems fault detection and diagnosis

Abstract

Power systems frequently experience variations in their operation, which are mostly manifested as transmission line faults. Over the past decade, various techniques of fault diagnosis have been developed to ensure reliable and stable operation of power systems. This paper reviews the current literature on advanced application of fault diagnosis in power systems. Application of different fault diagnosis schemes is presented, with emphasis on reliable fault detection and classification of power system faults. The motivation behind applications of emerging process history, or pattern recognition, techniques in power system fault diagnosis has been reviewed. An extensive review of advanced mathematical techniques, in pattern recognition methods, involving wavelet transform, artificial neural networks and support vector machines has been presented. The paper also introduces a novel unsupervised technique of quarter-sphere support vector machine for power system fault detection and classification and reviews its application as future research in the developing area of fault diagnosis.