• DocumentCode
    1900731
  • Title

    A framework to determine the probability density function for the output power of wind farms

  • Author

    Dhople, Sairaj V. ; Domínguez-García, Alejandro D.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2012
  • fDate
    9-11 Sept. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper proposes a numerical framework to propagate wind-speed uncertainty through to the power output of a wind farm while factoring in the availability of the wind turbines in the farm. In particular, given a probability density function (pdf) that describes wind speed, and a statistical availability model for the wind turbines, we propose a method to determine the wind-farm power output pdf. The proposed framework offers several advantages over conventional methods, e.g., it is agnostic to the wind-speed distribution and easily incorporates wind farm availability. Case studies compare the wind farm power distributions computed using the proposed framework with field data for an actual wind farm. In addition, we demonstrate how the framework allows the computation of common wind generation indices such as the expected available wind energy, expected generated wind energy, and capacity factor.
  • Keywords
    numerical analysis; probability; wind power plants; wind turbines; capacity factor; expected generated wind energy; numerical framework; probability density function; wind farm power distributions; wind generation indices; wind turbines; wind-farm power output PDF; wind-speed distribution; wind-speed uncertainty; Availability; Computational modeling; Mathematical model; Wind energy; Wind farms; Wind speed; Wind turbines; Availability; random variable transformations; wind farms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    North American Power Symposium (NAPS), 2012
  • Conference_Location
    Champaign, IL
  • Print_ISBN
    978-1-4673-2306-2
  • Electronic_ISBN
    978-1-4673-2307-9
  • Type

    conf

  • DOI
    10.1109/NAPS.2012.6336368
  • Filename
    6336368