• DocumentCode
    690361
  • Title

    Application of ARMA Model in Ultra-short Term Prediction of Wind Power

  • Author

    Jianyong Zhang ; Cong Wang

  • Author_Institution
    Dept. of Math. & Phys., Hohai Univ., Changzhou, China
  • fYear
    2013
  • fDate
    14-15 Dec. 2013
  • Firstpage
    361
  • Lastpage
    364
  • Abstract
    The randomness of the wind velocity causes the fluctuation of wind power. Therefore, It is necessary to forecast the wind power in a certain time. In this paper, the ultra-short term predication of wind power has been carried out based on the Auto-Regressive-and-Moving-Average (ARMA) model. The wind power was predicted by prediction steps of ARMA in section II. According to the corresponding national standard, the predicted results were evaluated in TABLE I and II, simultaneously, compared with the predicted results of BP neural network in subsection C of section III. Finally, it is found that the ARMA model is more suitable for ultra-short term prediction of wind power.
  • Keywords
    autoregressive moving average processes; wind power; ARMA model; auto regressive and moving average model; ultra short term prediction; wind power; wind velocity; Accuracy; Analytical models; Mathematical model; Neural networks; Power systems; Predictive models; Wind power generation; ARMA; prediction; wind power;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Sciences and Applications (CSA), 2013 International Conference on
  • Conference_Location
    Wuhan
  • Type

    conf

  • DOI
    10.1109/CSA.2013.91
  • Filename
    6835618