• DocumentCode
    2039169
  • Title

    Modeling highly nonlinear load dynamics for harmonic assessment

  • Author

    Chang, G.W.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, an advanced method based on measured data and neural network for highly nonlinear loads such as electric arc furnaces (EAFs) is introduced. An industrial power system with the EAF load is used for field measurements. Modeling results obtained by the proposed method are then compared with the measured data. It shows that the presented method can model the highly nonlinear load dynamics with a good accuracy.
  • Keywords
    industrial power systems; neural nets; power system harmonics; power system simulation; EAF load; electric arc furnaces; field measurements; harmonic assessment; highly nonlinear load dynamic modelling; industrial power system; neural network; Current measurement; Furnaces; Harmonic analysis; Load modeling; Mathematical model; Power system harmonics; Voltage measurement; Electric arc furnace; harmonics; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6344563
  • Filename
    6344563