• DocumentCode
    508193
  • Title

    Recognition of Voltage Sag Disturbance by Mamdani Fuzzy Inference

  • Author

    Ning, Ding ; Guodong, Li ; Yonghai, Xu

  • Author_Institution
    Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
  • Volume
    2
  • fYear
    2009
  • fDate
    16-18 Oct. 2009
  • Firstpage
    205
  • Lastpage
    208
  • Abstract
    A classification method of detecting the voltage sag sources based on Mamdani fuzzy inference is introduced in this paper. Three main sag reasons of short-faults, transformers energizing and large-capacity induction motor starting are analyzed. There are some different phenomena during the voltage sags caused by different sources. The characters of the balanced of the three phases, the changing trend of the voltage when the sag ends and voltage harmonic ratio during the sag are considered to be the criteria of recognizing the different voltage sag sources by using Mamdani fuzzy inference. Mamdani fuzzy inference uses the rules which are already known to carry out the reasoning computations from input to output. The correction of this method is proved by some simulations taken in the paper.
  • Keywords
    power supply quality; power system faults; Mamdani fuzzy inference; induction motor; short-faults; transformers energizing; voltage sag disturbance recognition; Character recognition; Computational modeling; Fuzzy systems; Induction motors; Power engineering and energy; Power harmonic filters; Power quality; Transformers; Voltage fluctuations; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energy and Environment Technology, 2009. ICEET '09. International Conference on
  • Conference_Location
    Guilin, Guangxi
  • Print_ISBN
    978-0-7695-3819-8
  • Type

    conf

  • DOI
    10.1109/ICEET.2009.287
  • Filename
    5365932