• DocumentCode
    2059210
  • Title

    Electric load modeling based on characteristic fusion

  • Author

    Jianquan Zhu ; Feng Liu ; Shengwei Mei ; Shaoming Zheng

  • Author_Institution
    Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    A novel load modeling method based on characteristics fusion is proposed in this paper. First, for utilizing fully the information of the individual component devices and representing adaptively the change of the model structure of the composite load bus, the basic characteristics of the composite load bus, including the static, dynamic, withdrawing, and restarting characteristics, are obtained based on the typical load devices. To employ the measurement information adequately, the composite load mode is established by fusing the basic characteristics according to the recorded measurements during the system disturbances. The support vector regression (SVR) is used as a fusion tool due to its excellent performance. The simulation results demonstrate the effectiveness of the proposed method in the end.
  • Keywords
    load forecasting; power engineering computing; regression analysis; support vector machines; SVR; characteristic fusion; composite load bus; dynamic characteristics; electric load modeling; power withdrawing characteristics; restarting characteristics; static characteristics; support vector regression; system disturbance; Absorption; Adaptation models; Analytical models; Industries; Load modeling; Mathematical model; Reactive power; Characteristic Analysis; Fusion; Load Model; Power System; Support Vector Regression;
  • 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.2012.6345321
  • Filename
    6345321