• DocumentCode
    3253138
  • Title

    Advantages of ARMA-GARCH wind speed time series modeling

  • Author

    Lojowska, Alicja ; Kurowicka, Dorota ; Papaefthymiou, Georgios ; Van der Sluis, Lou

  • Author_Institution
    Electr. Power Syst. Group, Delft Univ. of Technol., Delft, Netherlands
  • fYear
    2010
  • fDate
    14-17 June 2010
  • Firstpage
    83
  • Lastpage
    88
  • Abstract
    This paper presents the advantages of using wind speed time series models from ARMA-GARCH class. The models are found using good statistical practice and are able to capture the most important characteristics of the data like distribution, time dependence structure and periodicity in a satisfying manner. It is shown that the models offer several crucial advantages. The artificial wind speeds simulated from the obtained models are statistically indistinguishable from the wind speed time series measurements recorded in other years than the original data. Moreover, models can contribute to the considerations of extreme scenarios of wind power generation by simulating wind speeds characterized by a very high energy content. Thanks to the use of continuous cdf transformations, the synthetic time series do not possess the measurement error.
  • Keywords
    autoregressive moving average processes; electric power generation; time series; wind power; ARMA-GARCH class; artificial wind speeds; autoregressive moving average; data like distribution; energy content; generalized autoregressive conditional heteroscedasticity; periodicity; statistical practice; time dependence structure; wind power generation; wind speed time series; Autoregressive processes; Buildings; Mathematical model; Paper technology; Power system modeling; Power system simulation; Time measurement; Velocity measurement; Wind energy; Wind speed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5720-5
  • Type

    conf

  • DOI
    10.1109/PMAPS.2010.5528979
  • Filename
    5528979