Fault Detection and Classification in Transmission lines based on a Combination of Wavelet Singular Values and Fuzzy Logic

Abstract

Abstract. In this paper, a new method for fault detection and classification in transmission lines has been used. This method, called Fuzzy-Wavelet Singular Values, combines the advantages of wavelet transform and singular value decomposition, then uses fuzzy logic to detect and classify the fault. The proposed algorithm uses the singular values of wavelet transform of three phases and zero sequence current for fault detection and classification. The input of fuzzy logic is singular values wavelet transform of zero sequence and three phase currents, three phase indexes are used to detect the faulty phase from sound phase, and the zero sequence index is used to detect phase to ground fault. The designed algorithm is able to detect various types of fault such as single phase to ground, double phase to ground, three phase to ground and phase to phase and this protection scheme is robustness to parameters such as fault resistance, fault location and fault type. The proposed scheme is able to detect the fault within 10 ms from the fault inception to prevent some problems such as stability and equipment damage. The Matlab software is used to model the system and performance of the algorithm.