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Akademický článek

Series arc fault identification based on complete ensemble empirical mode decomposition with adaptive noise and convolutional neural network

Autor: Shang Tongtong, Wang Wei, Peng Jigang, Xu Bingyin, Gao Haiyang, Zhai Guoliang

Publikováno v: International Journal of Metrology and Quality Engineering, Vol 13, p 11 (2022)

The effective identification of series arc faults is of considerable significance for preventing fires in residential buildings. Series arc fault currents and load currents have a similar waveform, and the fault features and nonfault features are sup

Externí odkaz: https://doaj.org/article/0b616dc150324238ba66bff2cecb91b0

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Akademický článek

Measurement of impedance angle for anti-islanding protection in multi-source distribution network

Autor: Wang, Chao, Xu, Huabo, Yang, Fan, Yang, Zhichun, Chen, Hechong, Chen, Yu, Xu, Bingyin

Publikováno v: In Energy Reports June 2024 11:3022-3036

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Detection and Feeder Identification of the High Impedance Fault at Distribution Networks Based on Synchronous Waveform Distortions

Autor: Wei, Mingjie, Shi, Fang, Zhang, Hengxu, Chen, Weijiang, Xu, Bingyin

Diagnosis of high impedance fault (HIF) is a challenge for nowadays distribution network protections. The fault current of a HIF is much lower than that of a normal load, and fault feature is significantly affected by fault scenarios. A detection and

Externí odkaz: http://arxiv.org/abs/2005.03411