• DocumentCode
    1748869
  • Title

    Adaptive neural network based harmonic current compensation in active power filter

  • Author

    Rukonuzzaman, M. ; Nakaoka, Mutsuo

  • Author_Institution
    Power Electron. Syst. & Control Lab., Yamaguchi Univ., Japan
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    2281
  • Abstract
    An advanced active power filter for the compensation of instantaneous harmonic current components in non-linear current load is presented. A 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 the current harmonic 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; electric current control; invertors; neural nets; power harmonic filters; power system harmonics; signal processing; voltage control; active power filter; adaptive neural network based harmonic current compensation; instantaneous harmonic components; instantaneous harmonic current components; inverter; nonlinear current load; signal processing technique; space voltage vector modulation scheme; switching signals; 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
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7044-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2001.938522
  • Filename
    938522