A neuro-wavelet approach for the performance improvement in SVC integrated wind-fed transmission line

Abstract

Abstract This paper proposes a combined neuro-wavelet approach of differential relaying for fault detection, classification and performance improvement in SVC (STATIC VAR Compensator) integrated wind-fed transmission line. The scheme starts with extracting the current signals from both sending and receiving ends of the transmission line through the current transformer (CT) and process through discrete wavelet transform (DWT) approach to evaluate spectral energy (SE). The differential spectral energy (DSE) signal input is evaluated by subtracting the SE obtained from sending end and the SE from receiving ends of the line. The DSE of phase current signal is fed to the input of an ANN fault detector to obtain the neuro-wavelet output to detect and classify the fault. The fault detection time (FDT) is obtained from this approach remains within a quarter cycle (5 ms) period of time and validated in single and double circuit line to justify the performance improvement of the scheme.