Soft Computing Based Approach for Ascertaining Evolving Faults in Compensated Lines

This paper describes, a soft computing based framework for ascertaining the evolving faults (EF) in compensated lines. The faults triggered in one phase and eventually involve another phase are termed as evolving events. Its transforming characteristics make it more intricate than usual shunt abnormalities in the transmission system. The switching of involved phases within a few cycles creates additional challenges for the conventional relaying system. In this work an integrated mechanism based on signal processing and soft computing has been presented for identifying the evolving events. The pronounced features have been captured after empirical mode decomposition of the current waveform corresponding to numerous fault events. The secured features are applied as input to developed computing based strategy classifying the EF and shunt abnormalities in power lines. For the purpose of estimating the adequacy of the proposed framework several test cases have been simulated. It has been seen that the proposed approach is quite effective in ascertaining the evolving events in the compensated lines.