ANN-Based Fault Classification and Section Identification Technique Using Superimposed Currents for Three-Terminal Transmission Line

Abstract

This paper presents artificial neural network (ANN)-based faulty section identification and fault classification technique on three-terminal power transmission lines. Tapped point of electrical power transmission lines has more complex network with protective circuits. Faulty section identification and fault classification are challenging task on a three-terminal transmission lines. The superimposed currents which are difference of similar phase currents of different terminals is utilized for the classification and section identification on a 400 kV Indian three-terminal power transmission system simulated in PSCAD/EMTDC software. The superimposed current based feature is given to the ANN-based classifiers. The performance of proposed technique is studied by changing various fault and system parameters. The accuracy achieved with the proposed method is more than 99% for section identification and fault classification.