• DocumentCode
    1820477
  • Title

    A fuzzy based fault type detector for remote fault diagnosis of distribution feeders

  • Author

    Indhumathi, C. ; Vasantha Rani, S. P. Joy

  • Author_Institution
    Dept. of Electr. & Electron. Eng., T.J. Inst. of Technol., Chennai, India
  • fYear
    2015
  • fDate
    26-28 March 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Increasing energy demands has led to expansion of power infrastructure which also means that there is an increase in the number of lines subjected to faults due to short circuits or unintentional causes such as birds, falling of branches, etc,. Sometimes this causes an outage of power. Identification of the right fault type is necessary for quick power restoration. Hence accurate fault classification in power distribution substation is essential. The work presented in the paper aims to automate the fault type identification process using a fuzzy based algorithm thereby reducing the time required for power restoration. The experimental results indicate that the algorithm accurately detects the type of fault in single and multiple fault scenarios.
  • Keywords
    fault diagnosis; fuzzy logic; power distribution faults; power distribution reliability; power engineering computing; power system restoration; short-circuit currents; substations; distribution feeder; fault Identification; fault classification; fuzzy based fault type detector; multiple fault scenario; power distribution substation; power infrastructure expansion; power outage; power restoration; remote fault diagnosis; short-circuit current; Analytical models; Current measurement; Fault diagnosis; Substations; Training; Distribution substation Reliability; Faults in power system; Fuzzy Logic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communication and Networking (ICSCN), 2015 3rd International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4673-6822-3
  • Type

    conf

  • DOI
    10.1109/ICSCN.2015.7219832
  • Filename
    7219832