When a single-phase-to-ground (SPG) fault occurs in a resonant grounding distribution system, the amplitude of the transient zero-sequence current waveform at the upstream detection node of the fault point is greater than the amplitude of the transient zero-sequence current waveform at the downstream detection node, and the two polarities are opposite. The transient zero-sequence currents at the detection nodes on the same side of the fault point are very similar. Based on this, the paper proposes a new method of SPG fault location based on a deep belief network (DBN). Firstly, this method uses the fault transient zero-sequence current waveform obtained from each detection node in the simulation model as the input of DBN, and the deep features of the fault signals are extracted. Secondly, the deep features are divided into upstream detection nodes category and downstream detection nodes category by a supervised classifier. And then, the fault location is implemented by analyzing the network structure of fault detection nodes. Finally, the testing results of the simulation data prove that the algorithm has high recognition accuracy under different fault grounding points, different initial phase angles of faults, different grounding resistances, and different types of faults, and has certain practical engineering application value.


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    Title :

    A Single-Phase-to-Ground Fault Location Method Based on Deep Belief Network


    Additional title:

    Smart Innovation, Systems and Technologies


    Contributors:


    Publication date :

    2021-11-30


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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