A method for determining the location and type of fault in transmission network using neural networks and power quality monitors

In this paper, a procedure for determining the location of a fault on a power line using neural networks is proposed. Specifically, the procedure involves four stages (three of which employ neural networks): gathering voltage input data from power quality monitors via simulation, classifying the fault type, detecting the faulted line, and determining the fault position on the power line. The IEEE 39 bus test system was used to develop and test the mentioned model. Input voltages are obtained using DigSILENT PowerFactory software in which a set of three-phase and single-phase short circuits are simulated. For the next steps of the method, voltages from all buses are not used, but only voltages from optimally placed power quality monitors on 12 buses in the IEEE 39 bus test system. In the second step, the first neural network is employed in order to classify the fault type – single-phase or three-phase. In the third stage, another neural network is used to determine the faulted line and in the fourth stage, the last neural network is developed to determine the fault position on the faulted line.

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Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).