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  • Open Access

    ARTICLE

    Arc Grounding Fault Identification Using Integrated Characteristics in the Power Grid

    Penghui Liu1,2,*, Yaning Zhang1, Yuxing Dai2, Yanzhou Sun1,3

    Energy Engineering, Vol.121, No.7, pp. 1883-1901, 2024, DOI:10.32604/ee.2024.049318 - 11 June 2024

    Abstract Arc grounding faults occur frequently in the power grid with small resistance grounding neutral points. The existing arc fault identification technology only uses the fault line signal characteristics to set the identification index, which leads to detection failure when the arc zero-off characteristic is short. To solve this problem, this paper presents an arc fault identification method by utilizing integrated signal characteristics of both the fault line and sound lines. Firstly, the waveform characteristics of the fault line and sound lines under an arc grounding fault are studied. After that, the convex hull, gradient product,… More >

  • Open Access

    ARTICLE

    Research on Low Voltage Series Arc Fault Prediction Method Based on Multidimensional Time-Frequency Domain Characteristics

    Feiyan Zhou1,*, Hui Yin1, Chen Luo2, Haixin Tong2, Kun Yu2, Zewen Li2, Xiangjun Zeng2

    Energy Engineering, Vol.120, No.9, pp. 1979-1990, 2023, DOI:10.32604/ee.2023.029480 - 03 August 2023

    Abstract The load types in low-voltage distribution systems are diverse. Some loads have current signals that are similar to series fault arcs, making it difficult to effectively detect fault arcs during their occurrence and sustained combustion, which can easily lead to serious electrical fire accidents. To address this issue, this paper establishes a fault arc prototype experimental platform, selects multiple commonly used loads for fault arc experiments, and collects data in both normal and fault states. By analyzing waveform characteristics and selecting fault discrimination feature indicators, corresponding feature values are extracted for qualitative analysis to explore… More > Graphic Abstract

    Research on Low Voltage Series Arc Fault Prediction Method Based on Multidimensional Time-Frequency Domain Characteristics

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