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  • 标题:A Survey on Machine Learning Based Techniques for HVDC Fault Location
  • 本地全文:下载
  • 作者:Abhishek Jagwanshi ; Manish Khemariya
  • 期刊名称:International Journal of Advances in Engineering and Management
  • 电子版ISSN:2395-5252
  • 出版年度:2022
  • 卷号:4
  • 期号:2
  • 页码:637-642
  • DOI:10.35629/5252-0402481487
  • 语种:English
  • 出版社:IJAEM JOURNAL
  • 摘要:In the present era of deregulation and competition, demand from every energy supplier is to have good continuity, dependability and reliability. Fault location can play a vital role in achieving this aim. As uninterrupted power supply is the prime demand by all consumers. However, faults in power system will leads to the interruption in power supply and it will make system vulnerable towards system outrage/collapsing and will lead to damage various electrical peripheral of switch gear/ electrical equipment.Hence all faults are required to be detected and clear as soon as possible to restart power supply to consumer. Having accuracy knowledge of fault location will come very handy in reducing system outrage time and they’re by improving continuity and reliability of system. Variousresearches has been done previously towards finding accurate result. In this paper presents a comprehensive survey on the existing work done in the domain of machine learning assisted fault location in HVDC systems.
  • 关键词:HVDC;Fault Location;Machine Learning;Mean Square Error;Accurayc
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