Transmission Line Single Phase Auto Re-closing Scheme Based on Wavelet Transform and Adaptive Fuzzy Neuro Inference System

Abstract

This paper proposes an adaptive single phase auto re-closing scheme for transmission lines using wavelet transform (WT) and adaptive fuzzy neuro inference system (ANFIS). The WT acts as a preliminary feature extractor to bus voltages. For transmission line single phase fault, the WT can provide an effective signal representation of the voltage at the faulty phase by calculating the index of Percentage of Energy (PE) corresponding to each detail in the WT, The PE indices can be used to effectively classify different transient and permanent faults occurring on transmission lines. In the case of transient faults, the ANFIS further utilizes the PE indices during three consecutive windows to accurately determine the secondary arc extinction time, which is used by protective relay to issue auto re-closing order. Extensive simulation studies show that the combination of WT and ANFIS achieves excellent performance in classifying transient and permanent single-phase faults and estimating the secondary arc extinction time for correct auto re-closing.