• DocumentCode
    3510224
  • Title

    Voltage Event Detection and Characterization Methods: A Comparative Study

  • Author

    Pérez, Enrique ; Barros, Julio

  • Author_Institution
    Dept. of Electron. & Comput., Cantabria Univ., Santander
  • fYear
    2006
  • fDate
    15-18 Aug. 2006
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The paper presents a comparative study of the most commonly used methods of detection and analysis of voltage events in power systems. The performance of the rms method, the fundamental component estimation using discrete Fourier transform and Kalman filtering and the use of wavelet analysis for detection and estimation of magnitude and duration of voltage events, are studied under simulation using voltage dips of different magnitude, duration and point-on-wave of beginning in a pure sinusoidal voltage supply and also for a voltage supply with different harmonic distortion levels. The methods employed are also tested using real voltage events measured in a low voltage distribution system discussing the results obtained
  • Keywords
    Kalman filters; discrete Fourier transforms; distribution networks; power harmonic filters; wavelet transforms; Kalman filtering; discrete Fourier transform; fundamental component estimation; harmonic distortion levels; low voltage distribution system; rms method; voltage dips; voltage event detection; voltage events analysis; wavelet analysis; Discrete Fourier transforms; Discrete wavelet transforms; Event detection; Filtering; Kalman filters; Power harmonic filters; Power system analysis computing; Power system simulation; Voltage; Wavelet analysis; Fourier Transform; Kalman filtering; Power Quality; RMS; Wavelets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transmission & Distribution Conference and Exposition: Latin America, 2006. TDC '06. IEEE/PES
  • Conference_Location
    Caracas
  • Print_ISBN
    1-4244-0287-5
  • Electronic_ISBN
    1-4244-0288-3
  • Type

    conf

  • DOI
    10.1109/TDCLA.2006.311552
  • Filename
    4104483