• DocumentCode
    3086560
  • Title

    Analytical study of different probability distributions for wind speed related to power statistics

  • Author

    Chiodo, E. ; Lauria, D.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Napoli Federico II, Naples, Italy
  • fYear
    2009
  • fDate
    9-11 June 2009
  • Firstpage
    733
  • Lastpage
    738
  • Abstract
    The paper discusses the problem of an efficient assessment or estimation of wind probabilistic distribution for the quantitative evaluation of wind power generation statistics. In particular, the characteristics of the popular Weibull distribution widely (in fact, uniquely) adopted in the field of wind-speed statistics are recalled and discussed; then, they are compared with the ones of a less popular model, the Log-logistic one. Indeed, this latter model appears to be another natural candidate for the wind statistics modeling, according to the analysis of some field data, which shows significant ldquoheavy tailsrdquo in wind-speed probabilistic distribution for large values of wind speed. A novel function is defined in order to discriminate among the probabilistic models. Numerical results are reported at the aim to highlight the feasibility of the sensitivity analysis for wind farm designer.
  • Keywords
    sensitivity analysis; statistical analysis; wind power plants; different probability distributions; power statistics; sensitivity analysis; wind farm designer; wind power generation statistics; wind probabilistic distribution; wind-speed statistics; Atmospheric modeling; Mathematical model; Power system modeling; Probability distribution; Shape; Statistical analysis; Statistical distributions; Weibull distribution; Wind power generation; Wind speed; Log-logistic distribution; Weibull; Wind power generation; distribution; probability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Clean Electrical Power, 2009 International Conference on
  • Conference_Location
    Capri
  • Print_ISBN
    978-1-4244-2543-3
  • Electronic_ISBN
    978-1-4244-2544-0
  • Type

    conf

  • DOI
    10.1109/ICCEP.2009.5211970
  • Filename
    5211970