• DocumentCode
    2197361
  • Title

    Fault diagnosis for substation automation based on Petri nets and coding theory

  • Author

    Ren, Hui ; Mi, Zengqiang ; Zhao, Hongshan ; Yang, Qixun

  • Author_Institution
    North China Electr. Power Univ., Baoding, China
  • fYear
    2004
  • fDate
    10-10 June 2004
  • Firstpage
    1038
  • Abstract
    In this paper, coding-based methodology for faults monitoring of discrete event systems is applied to electric power system. Using Petri nets and coding theory to perform the fault diagnosis is further studied. One feeder of the substation is modeled by Petri net using real time discrete events, and redundant places are introduced to form structure redundancy and facilitate fault diagnosis. Based on the previous work, the feeder´s all possible failures are analyzed and a new method to model these failures is given. Then parity check from coding theory is used to form an encoded Petri net, therefore faults can be detected and identified through error syndrome. Method to construct important matrix, generator matrix, is presented. The simulation is simple, fast and shows very high accuracy, as combining with error correction theory. The result of simulation shows that the scheme has good performance in real-time substation fault diagnosis.
  • Keywords
    Petri nets; discrete event systems; error correction; fault diagnosis; matrix algebra; parity check codes; substation automation; Petri nets; coding theory; discrete event systems; electric power system; error correction theory; error syndrome; fault diagnosis; faults monitoring; generator matrix; parity check; real time discrete events; substation automation; Discrete event systems; Failure analysis; Fault detection; Fault diagnosis; Monitoring; Parity check codes; Petri nets; Power system modeling; Redundancy; Substation automation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2004. IEEE
  • Conference_Location
    Denver, CO
  • Print_ISBN
    0-7803-8465-2
  • Type

    conf

  • DOI
    10.1109/PES.2004.1372998
  • Filename
    1372998