• DocumentCode
    1928147
  • Title

    Fuzzy Power Quality Indicator

  • Author

    Hsiao, Ying-Tung ; Wu, Ying-Ming ; Lee, Yen-Hsing ; Ye, Fun

  • Author_Institution
    Nat. Taipei Univ. of Educ., Taipei
  • Volume
    3
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    1418
  • Lastpage
    1423
  • Abstract
    This paper proposes a novel fuzzy power quality indicator for representing the level of power quality status. In this work, we develop the fuzzy rules, degree membership function and inference rules for identifying the power quality level on six encountered types of power quality events. The traditional power quality indices are not performed well for assessing the status of the power quality because of their hard limits. Hence, this study develops the soft (human thinking like) indices for presenting the serious degree of power quality. Simulation results show the proposed fuzzy power quality indicator is suitable for representing the level of power quality events.
  • Keywords
    fuzzy reasoning; fuzzy set theory; power supply quality; fuzzy power quality indicator; inference rule; Cybernetics; Fuzzy sets; Fuzzy systems; Harmonic distortion; Humans; Machine learning; Power quality; Power supplies; Total harmonic distortion; Voltage; Fuzzy; Index; Power quality; Voltage quality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370367
  • Filename
    4370367