• DocumentCode
    270569
  • Title

    Optimal voltage control by wind farms using data mining techniques

  • Author

    Sáiz-Marín, Elena ; Lobato, Enrique ; Egido, Ignacio

  • Author_Institution
    Inst. for Res. & Technol. (IIT), Univ. Pontificia Comillas, Madrid, Spain
  • Volume
    8
  • Issue
    2
  • fYear
    2014
  • fDate
    Mar-14
  • Firstpage
    141
  • Lastpage
    150
  • Abstract
    Owing to the rapid growth in the use of wind power, there is a need to carry out an evaluation of the frequency and voltage control of this technology. This study focuses on the voltage control of the evacuation network which connects different wind farms to the transmission network bus. The main contribution of this study is to present a novel real time algorithm which can be used as an alternative to classical techniques such as optimal power flow or artificial intelligence to determine the amount of reactive power that each wind farm should supply in order to minimise the power losses of a whole evacuation network. The optimal voltage control proposed in this study uses data mining techniques (regression rules to estimate the optimum reactive power of the wind farms and classification trees to estimate the optimum transformer taps). The methodology proposed in this study is illustrated with a study of two actual evacuation networks in the Spanish power system. The first one is representative of long feeders whereas the second one is representative of short feeders. The variability in the results of the methodology seems to be dependent on the features of the grids.
  • Keywords
    data mining; frequency control; optimal control; power engineering computing; power generation control; power grids; power transformers; reactive power control; transmission networks; voltage control; wind power plants; Spanish power system; artiflcial intelligence; classiflcation trees; data mining techniques; evacuation network; grids; optimal power flow; optimal voltage control; optimum reactive power; optimum transformer taps; reactive power; real time algorithm; regression rules; short feeders; transmission network bus; wind farm; wind farms;
  • fLanguage
    English
  • Journal_Title
    Renewable Power Generation, IET
  • Publisher
    iet
  • ISSN
    1752-1416
  • Type

    jour

  • DOI
    10.1049/iet-rpg.2013.0025
  • Filename
    6746586