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This paper presents a combined wavelet-support vector machine (SVM) technique for fault zone identification in a series compensated transmission line. The proposed method uses the samples of three line currents for one cycle duration to accomplish this task. Initially, the features of the line currents are extracted by first level decomposition of the current samples using discrete wavelet transform (DWT). Subsequently, the extracted features are applied as inputs to a SVM for determining the fault zone (whether the fault is before or after the series capacitor, as observed from the relay point). The feasibility of the proposed algorithm has been tested on a 300-km, 400-kV series compensated transmission line for all the ten types of faults through detailed digital simulation using PSCAD/EMTDC. Upon testing on more than 25000 fault cases with varying fault resistance, fault inception angle, prefault power transfer level, percentage compensation level, and source impedances, the performance of the developed method has been found to be quite promising.
Parikh et al. (Mon,) studied this question.