• DocumentCode
    2407918
  • Title

    Fault pattern recognition in power system engineering

  • Author

    Zhang, Yagang ; Liu, Yutao ; Wang, Xiaozhe ; Wang, Zengping

  • Author_Institution
    Key Lab. of Power Syst. Protection & Dynamic Security Monitoring & Control, North China Electr. Power Univ., Baoding, China
  • fYear
    2009
  • fDate
    15-16 May 2009
  • Firstpage
    109
  • Lastpage
    112
  • Abstract
    In the paper, we will introduce a new approach of pattern recognition theory. In the control of power systems, the prerequisite of protection device´s accurate, fast and reliable performance is its corresponding fault type and fault location can be detected quickly and defined exactly. In our researches, global information will be introduced into the backup protection system, basing on linear discriminant analysis of pattern recognition theory, we are going to seek after for the data characteristics of electrical quantities´ marked changes by analyzing and computing real-time PMU measurements, so that we carry out fast and exact discrimination of fault components and fault sections.
  • Keywords
    fault location; pattern recognition; phase measurement; power system control; power system faults; backup protection system; fault location; fault pattern recognition theory; linear discriminant analysis; phasor measurement unit; power system engineering; real-time PMU measurement; Control systems; Pattern recognition; Power engineering and energy; Power system analysis computing; Power system control; Power system faults; Power system protection; Power system reliability; Reliability engineering; Systems engineering and theory; PMU; linear discriminant function; pattern recognition; power system engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Mechatronics and Automation, 2009. ICIMA 2009. International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-3817-4
  • Type

    conf

  • DOI
    10.1109/ICIMA.2009.5156572
  • Filename
    5156572