• DocumentCode
    2058907
  • Title

    The research of feeder automation based ONn IEC61850

  • Author

    Yao Chong-Gu ; Teng Huan

  • Author_Institution
    Sichuan Univ., Chengdu, China
  • fYear
    2012
  • fDate
    10-14 Sept. 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    To accelerate feeder automation detection and fault solution, this paper applied the communication protocol and related technologies of IEC61850, proposed the information exchange among the feeder terminals, and improved GSE model which provided a function of fast and reliable input/output value in the whole system. Adopting the layered IP network communication theory, it divided the entire network into the backbone network and the branch network, and constructed a three-layer FA architecture. The three layers respectively were master station layer, slave station layer and terminal layer. Logic nodes supplied by IEC61850 were used to accomplish the modeling of TTU information in the paper. And then, it discussed the realization of terminal self-describing. Finally, this method was applied in the DAS, and it achieved the purpose of accelerating the detection and fault solution and improving the power distribution reliability.
  • Keywords
    IEC standards; power distribution faults; power distribution reliability; substation automation; GSE model; ONn IEC61850; TTU information; backbone network; branch network; communication protocol; fault solution; feeder automation detection; feeder terminals; information exchange; layered IP network communication theory; logic nodes; master station layer; power distribution reliability; slave station layer; terminal layer; three-layer FA architecture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electricity Distribution (CICED), 2012 China International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-7481
  • Print_ISBN
    978-1-4673-6065-4
  • Electronic_ISBN
    2161-7481
  • Type

    conf

  • DOI
    10.1109/CICED.2012.6508523
  • Filename
    6508523