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  • 标题:Fault Diagnosis Technology of Intelligent Substation UPFC System Based on Abnormal Sub-module Port Voltage
  • 本地全文:下载
  • 作者:Jinghong Zhao ; Lei Jin ; Fanbo Meng
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2019
  • 卷号:136
  • 页码:1-5
  • DOI:10.1051/e3sconf/201913601025
  • 出版社:EDP Sciences
  • 摘要:Unified power flow controller (UPFC) combines the advantages of FACTS devices of series and parallel, which is an important direction for the development of intelligent substations in the future. However, a large number of MMC submodules have become potential fault points of UPFC system. The rapid judgment of fault state and accurate positioning of fault sub-modules are the primary conditions to ensure the safe and stable operation of UPFC system, which can effectively reduce the mobile operation and maintenance time of power engineering operation and maintenance personnel, and guarantee the safety of operation and maintenance. Therefore, this paper proposes a fault diagnosis technology of intelligent substation UPFC system based on abnormal sub-module port voltage (SPVE). Experimental results show that the SPVE method has advantages in identification accuracy and rapidity.
  • 其他摘要:Unified power flow controller (UPFC) combines the advantages of FACTS devices of series and parallel, which is an important direction for the development of intelligent substations in the future. However, a large number of MMC submodules have become potential fault points of UPFC system. The rapid judgment of fault state and accurate positioning of fault sub-modules are the primary conditions to ensure the safe and stable operation of UPFC system, which can effectively reduce the mobile operation and maintenance time of power engineering operation and maintenance personnel, and guarantee the safety of operation and maintenance. Therefore, this paper proposes a fault diagnosis technology of intelligent substation UPFC system based on abnormal sub-module port voltage (SPVE). Experimental results show that the SPVE method has advantages in identification accuracy and rapidity.
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