• DocumentCode
    3665709
  • Title

    A substation fault diagnosis method based on IEC61850

  • Author

    Gao Zhanjun; Wang Junshan; Gao Nuo

  • Author_Institution
    Key Laboratory of Power System Intelligent Dispatch and Control (Shandong University), Ministry of education, Jinan, China
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Substations play an important role in power systems. The application of the IEC61850 standard changes the situation of the traditional substation greatly. The information in the intelligent substation is rich, but it is difficult for the operators to digest them in a short time without an effective assistant tool. A fault diagnosis method which uses the alarming information of the primary and secondary system of the intelligent substation is proposed in this paper. This method first uses the Bayesian based algorithm to find the possible faulty set H1. And at the same time, the information entropy difference algorithm is used to obtain the fault assumption set H2. Then the fault assumption set H2 is used to calculate the fault correctness and a decision fusion algorithm can locate the fault components accurately. Finally, a fault scenario is served for demonstrating the feasibility and validity of the method presented.
  • Keywords
    "Tin","Jacobian matrices","Substations","Artificial intelligence","Monitoring","Switches"
  • Publisher
    ieee
  • Conference_Titel
    Power & Energy Society General Meeting, 2015 IEEE
  • ISSN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PESGM.2015.7286171
  • Filename
    7286171