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ANN Based Fault Detection & Classification in Power System Transmission line

The development of an artificial neural network to analyze power system faults is currently under way. However, the produced system is unsatisfactory because it is prone to failure and takes longer to detect faults. The ultimate goal of this project is to create an artificial neural network system that can identify and classify all forms of faults in power grid lines soon after they occur. In principle, three-phase currents are used as inputs, and the suggested approach takes into account all sorts of defects. Following that, an ANN training network for a power system was constructed in MATLAB/Simulink software, and the ANN network was trained using a feed-forward approach. Finally, the simulation shows that when a faulat occurs in a transmission line, the ANN accurately diagnoses the fault and minimizes any potential damage by efficiently identifying faults in overhead transmission systems.