• DocumentCode
    1777716
  • Title

    Minimum frequency prediction of power system after disturbance based on the v-support vector regression

  • Author

    Qibin Bo ; Xiaoru Wang ; Ketian Liu

  • Author_Institution
    Sch. of Electr. Eng., Southwest Jiaotong Univ., Chengdu, China
  • fYear
    2014
  • fDate
    20-22 Oct. 2014
  • Firstpage
    614
  • Lastpage
    619
  • Abstract
    The prediction of power system minimum frequency after disturbance is the main content of power system measures. This paper presents a method based on the v-SVR to predict the minimum frequency and the frequency dynamic rapidly after disturbance. Several conditions which have effects on the power system frequency dynamic, such as the maximum output limit of the generator, spinning reserve levels and its distribution, turbine-governor, load et al. The method presented in this paper is accurate and quick enough to predict the frequency dynamic and its minimum value, and the method is based on support vector regression which is of good generalization ability and extension. Furthermore, the method presented in this paper can be used online for power system frequency stability assessment.
  • Keywords
    frequency stability; load forecasting; power system stability; regression analysis; support vector machines; frequency prediction; power system frequency stability; power system measures; v-SVR; v-support vector regression; Frequency measurement; Generators; Load modeling; Power system dynamics; Power system stability; Predictive models; Support vector machines; Frequency dynamic; Power system; Support Vector Regression; WAMS;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology (POWERCON), 2014 International Conference on
  • Conference_Location
    Chengdu
  • Type

    conf

  • DOI
    10.1109/POWERCON.2014.6993789
  • Filename
    6993789