Review on Fault Detection and Classification in Transmission Line using Machine Learning Methods

Abstract

Fast and precise fault categorization, location estimate, and fault detection are crucial because persistent faults can interrupt the power supply. The power outage zone will extend to nearby areas after the fault incident. Accurate and prompt fault identification is required for a power system to return to a healthy state. Protection, fault detection, diagnosis, identification, and localization are essential for efficient working of power system. Transmission line(TL) extensions are necessary due to rising industrialization and power demand, which greatly increases the complexity of the power system network. Analysis of faults in this intricate network becomes challenging. This paper reviews the latest machine-learning methods used for the identification and classification of faults in power systems.