Detection and classification of faults on transmission line using time-frequency approach of current transients

This paper presents an algorithm for detection and classification of transmission line faults using time-frequency analysis (Stock-Well Transform) on current signal obtained from both the ends of transmission line. The current samples are synchronized with GPS clock and their absolute values are added at each end, to obtained resultant current signal. The cumulative differential sum of the resultant signal over a moving window of half-cycle is compared with the disturbance threshold, to detect a disturbance. Subsequently energy of the signal over a half-cycle prior to the detection of disturbance is computed based on (Stock-Well Transform) and compared with fault threshold, to classify the disturbance into faulty and non-faulty transients. Finally, the faults are classified by computing energy of three-phase currents and zero sequence current in comparing with fault threshold. The proposed algorithm has been successfully tested for types of fault, fault impedance, fault incidence angle and fault location.