• DocumentCode
    1594332
  • Title

    An advanced active power filter with adaptive neural network based harmonic detection scheme

  • Author

    Rukonuzzaman, M. ; Nakaoka, M.

  • Author_Institution
    Power Electron. Syst. & Control Lab., Yamaguchi Univ., Japan
  • Volume
    3
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    1602
  • Abstract
    An advanced active power filter for the compensation of instantaneous harmonic current components in nonlinear current load is presented in this paper. A novel signal processing technique using an adaptive neural network algorithm is applied for the detection of harmonic components generated by nonlinear current loads and can efficiently determine the instantaneous harmonic components in real time. The control strategy of the switching signals to compensate current harmonics of the inverter is also discussed and the switching signals are generated with the space voltage vector modulation scheme. The validity of this active filtering processing system to compensate current harmonics is proved on the basis of simulation results
  • Keywords
    active filters; compensation; invertors; neural nets; power harmonic filters; power system harmonics; signal processing; switching circuits; voltage control; adaptive neural network algorithm; advanced active power filter; control strategy; harmonic components detection; instantaneous harmonic current components compensation; inverter; nonlinear current load; signal processing technique; space voltage vector modulation; switching signals; this active filtering processing system; voltage control; Active filters; Adaptive signal detection; Adaptive signal processing; Adaptive systems; Neural networks; Power harmonic filters; Power system harmonics; Signal generators; Signal processing algorithms; Voltage control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics Specialists Conference, 2001. PESC. 2001 IEEE 32nd Annual
  • Conference_Location
    Vancouver, BC
  • ISSN
    0275-9306
  • Print_ISBN
    0-7803-7067-8
  • Type

    conf

  • DOI
    10.1109/PESC.2001.954348
  • Filename
    954348