Evolving Fault Detection Algorithm for Transmission Line Protection

Abstract

This paper designed a technique using Stockwell transform (ST), Wigner distribution function (WDF) and alienation coefficient to detect evolving fault conditions incident on a power transmission line with two terminals (PTLTT). Currents are decomposed applying the ST and evolving Stockwell fault index (ESFI) is computed. These current signals are also decomposed using WDF for computing evolving Wigner fault index (EWFI). Alienation coefficient is used to process current signals for computing evolving alienation fault index (EAFI). The ESFI, EWFI and EAFI are multiplied with a evolving weight factor (EWF) to compute evolving hybrid fault index (EHFI). EHFI is compared with evolving threshold (ETH) for identifying the evolving fault. During scenario of evolving fault, the EHFI is greater than ETH for the faulty phases and observed lower than ETH for healthy phases. This is established that proposed method effectively detects the different types of evolving faults incident on PTLTT. Proposed EHFI is effective to detect evolving faults with variations in the fault incidence angle and fault impedance. Performance of proposed method is better relative to discrete Meyer wavelet transform (DMWT) supported evolving faults recognition method.