• DocumentCode
    3245081
  • Title

    Three-phase fault location based on Multiple Classifier Systemin double-circuit transmission lines

  • Author

    Chan, Patrick P K ; Zhu, Jing ; Qiu, Zid-Wei

  • Author_Institution
    Machine Learning & Cybern. Res. Center, South China Univ. of Technol., Guangzhou, China
  • fYear
    2012
  • fDate
    15-17 July 2012
  • Firstpage
    250
  • Lastpage
    254
  • Abstract
    Fault location estimation, which can actually be addressed as a classification or categorization problem, is a vital feature in protective relaying scheme for power transmission lines. In this paper, a novel three-phase fault location approach based on a Multiple Classifier System (MCS) not only using the information of the faulty lines but also considering others lines adjacent with the faulty line. Meanwhile, the number of samples used as an input also can have considerable effects on accuracy. In our proposed method, each base classifier predicts the fault location according to the information of different transmission line based on different number of samples as an input. Experimental results show that the better performance is achieved by the proposed method than the MLPs only using the information of the faulty line.
  • Keywords
    fault diagnosis; pattern classification; power engineering computing; power transmission faults; power transmission lines; relay protection; MCS; MLP; base classifier; categorization problem; classification problem; fault location estimation; faulty lines information; multiple classifier system double-circuit transmission; power transmission lines; protective relaying scheme; three-phase fault location approach; Artificial neural networks; Circuit faults; Fault location; Power system dynamics; Power transmission lines; Transmission line measurements; Classifier; Double circuit transmission line; Fault location; MCS; Three-Phase;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition (ICWAPR), 2012 International Conference on
  • Conference_Location
    Xian
  • ISSN
    2158-5695
  • Print_ISBN
    978-1-4673-1534-0
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2012.6294787
  • Filename
    6294787