Transmission Line Fault Classification using Supervised Machine Learning

Among Generation, Transmission and Distribution systems of power 80-90 % faults occur in transmission lines. A small electricity interruption or disturbances can cause major problems Major lines because environmental events like high temperatures, animals, wind, etc also faulty devices connected to are a for these faults. In modern line one the significant leading losses electrical failure. So, it is necessary recover immediately avoid need eliminate quickly. There few tools protective installed prevent but during any complex bigger they require more time may sometimes fails be damaged excessive But data driven method helpful than conventional proposed methods as less installation cost fast responsive even system operators individual easily identify type fault. This paper analyzes supervised machine learning algorithms classifying different