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  • 标题:Grounding fault detection and type determination of substation DC system
  • 本地全文:下载
  • 作者:Guozhong Wang ; Yin Zeng ; Juanping Shen
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:252
  • 页码:1-4
  • DOI:10.1051/e3sconf/202125201045
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:The DC system is used as the power supply for all kinds of protection, measurement and control, safety automation and other devices in the substation. It is the fundamental guarantee of power system control and protection. If the substation DC system fails, it will have a destructive impact on the entire substation system and function. Based on this, in order to solve the problems of maloperation and refusal of protection device caused by grounding fault of DC system, a method combining unbalanced bridge method with leakage current sensor is proposed to detect the grounding resistance of bus and branch. On this basis, the neural network optimized by quantum particle swarm optimization is used to determine the fault type. Finally, the effectiveness of the proposed method is verified by MATLAB/Simulink simulation.
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