• DocumentCode
    2376342
  • Title

    Particle swarm optimization based load model parameter identification

  • Author

    Kim, Young-Gon ; Song, Hwachang ; Kim, Hong Rae ; Lee, Byongjun

  • Author_Institution
    Dept. of Electr. Eng., Seoul Nat. Univ. of Technol., Seoul, South Korea
  • fYear
    2010
  • fDate
    25-29 July 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a method for estimating the parameters of dynamic models for induction motor dominating loads. Using particle swarm optimization, the method finds the adequate set of parameters that best fit the sampling data from the measurement for a period of time, minimizing the error of the outputs, active and reactive power demands and satisfying the steady-state error criterion.
  • Keywords
    induction motors; parameter estimation; particle swarm optimisation; induction motor; load model parameter identification; particle swarm optimization; reactive power demands; steady-state error criterion; dynamic load model; parameter estimation; particle swarm optimization; system identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2010 IEEE
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4244-6549-1
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PES.2010.5589394
  • Filename
    5589394
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2376342