• DocumentCode
    3300538
  • Title

    Equivalent power curve model of a wind farm based on field measurement data

  • Author

    Hayes, Barry P. ; Ilie, I. ; Porpodas, A. ; Djokic, S.Z. ; Chicco, Gianfranco

  • Author_Institution
    Inst. for Energy Syst., Univ. of Edinburgh, Edinburgh, UK
  • fYear
    2011
  • fDate
    19-23 June 2011
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    This paper discusses how a simple equivalent model of a whole wind farm can be obtained using field measurement data for individual wind turbines at the site. The equivalent model, which is formulated as a power curve, is specifically intended for steady state performance assessment, i.e. estimation of annual energy production of the wind farm. Two general approaches for building the equivalent steady state model of the wind farm are analysed: a) aggregate-measured power curve, obtained as an averaged aggregate representation of the outputs from all wind turbines, and b) cluster-measured power curve, obtained using the support vector clustering technique. Recorded measurement data from two actual wind farms are used to perform the analysis and to validate the results, where the accuracy of both proposed methods is assessed by direct comparison with the available recordings.
  • Keywords
    pattern clustering; power engineering computing; support vector machines; wind turbines; annual energy production; cluster-measured power curve; equivalent model; equivalent power curve model; field measurement data; power curve; steady state performance assessment; support vector clustering technique; wind farm; Blades; Energy measurement; Power measurement; Sea measurements; Steady-state; Wind farms; Wind speed; Distributed power generation; power curve; steady state power system analysis and modelling; wind farm; wind turbine; wind-based power and energy generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PowerTech, 2011 IEEE Trondheim
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-8419-5
  • Electronic_ISBN
    978-1-4244-8417-1
  • Type

    conf

  • DOI
    10.1109/PTC.2011.6019318
  • Filename
    6019318