Transmission Line Fault Isolation Using Artificial Intelligence via Neural Networks

Abstract

Transmitting a bulk amount of power from one place into another is normally performed using transmission lines. The increase of these transmission lines in different areas with different conditions usually leads to developing faults in these lines. Hence, it becomes of high interest in locating the line faults to maintain system stability and resume normal power flow operation. Knowing the current and voltage data is mainly the key point in locating the network faults. In this paper, a transmission line fault isolation technique using Artificial Intelligence (AI) via Artificial Neural Networks (ANNs) is presented. The current and voltage values of faults in different areas of transmission lines are studied and identified. The identification of the fault location is performed utilizing the ANN backpropagation algorithm. Based on the data provided by the ANN, a designated circuit breaker is used to isolate the fault and avoid system instability. The proposed technique is investigated by performing a comparison with recently related published work while clearly seeing the advantages of the new approach.