• DocumentCode
    1175413
  • Title

    Active power filter control using neural network technologies

  • Author

    Vazquez, J.R. ; Salmeron, P.

  • Author_Institution
    Departamento de Ingeniera Electrica, Univ. de Huelva, Spain
  • Volume
    150
  • Issue
    2
  • fYear
    2003
  • fDate
    3/1/2003 12:00:00 AM
  • Firstpage
    139
  • Lastpage
    145
  • Abstract
    A method for controlling an active power filter using neural networks Is presented. Currently, there is an increase of voltage and current harmonics in power systems, caused by nonlinear loads. The active power filters (APFs) are used to compensate the generated harmonics and to correct the load power factor. The proposed control design is a pulse width modulation control (PWM) with two blocks that include neural networks. Adaptive networks estimate the reference compensation currents. On the other hand, a multilayer perceptron feedforward network (trained by a backpropagation algorithm) that works as a hysteresis band comparator is used. Two practical cases with Matlab-Simulink are presented to check the proposed control performance.
  • Keywords
    active filters; backpropagation; compensation; harmonic distortion; multilayer perceptrons; neurocontrollers; power harmonic filters; power system control; power system harmonics; Matlab-Simulink; active power filter control; backpropagation algorithm; computer simulation; hysteresis band comparator; load power factor correction; multilayer perceptron feedforward network; neural network technologies; power system current harmonics; power system voltage harmonics; pulse width modulation control; reference compensation currents estimation;
  • fLanguage
    English
  • Journal_Title
    Electric Power Applications, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-2352
  • Type

    jour

  • DOI
    10.1049/ip-epa:20030009
  • Filename
    1192319