• DocumentCode
    1991357
  • Title

    A DTW and BPN Based Approach for Modeling Nonlinear Load

  • Author

    Xu, Gang ; Tian, Shiyang

  • Author_Institution
    Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
  • fYear
    2012
  • fDate
    27-30 May 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    It is known that a direct application of artificial neural network (ANN) for modeling high power, nonlinear, and impact load may lead to inaccuracies. This paper proposes an approach that the characteristic of the high power, nonlinear and time varying load is modeled by advanced ANN, which is implemented by using back propagation network (BPN) and dynamic time warping (DTW) algorithms. The model of the nonlinear load can be accurately established, the consumption of the voltage, reactive power and the precision of the model can be obtained. Then the type of the reactive power compensation devices and the capacity of the reactive power compensation equipments can be effectively determined.
  • Keywords
    backpropagation; load (electric); neural nets; power system simulation; reactive power; time warp simulation; artificial neural network; back propagation network; dynamic time warping algorithm; high power load; nonlinear load modeling; reactive power compensation device; reactive power compensation equipment; time varying load; voltage consumption; Artificial neural networks; Fluctuations; Heuristic algorithms; Load modeling; Reactive power; Voltage fluctuations; Voltage measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering and Technology (S-CET), 2012 Spring Congress on
  • Conference_Location
    Xian
  • Print_ISBN
    978-1-4577-1965-3
  • Type

    conf

  • DOI
    10.1109/SCET.2012.6342068
  • Filename
    6342068