• DocumentCode
    2789562
  • Title

    Photovoltaic array power forecasting model based on energy storage

  • Author

    Jun Tian ; Yong-qiang Zhu ; Jia-neng Tang

  • Author_Institution
    North China Power Univ., Beijing, China
  • fYear
    2010
  • fDate
    20-22 Sept. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    With the rapid increase of the capacity in photovoltaic (PV) generated systems, how to deal with the problem caused by the random output in the system becomes more significant. One possible solution could be the use of energy storage. The forecasting output can be obtained by the support vector regression model (SVR) introduced in this article, then the capacity of energy storage can be optimized by the difference between actual and predicting outputs. That is to say, energy storage devices are taken to compensate the difference, so that the deviation between predictions and actual values can be decreased. The results show that the proposed algorithm ELSSVR is effective and the installed capacity of energy storage is reduced significantly.
  • Keywords
    forecasting theory; photovoltaic power systems; regression analysis; energy storage; photovoltaic array; power forecasting; support vector regression model; Analytical models; Arrays; Energy storage; Forecasting; Mathematical model; Predictive models; Solar radiation; Photovoltaic array; SVR; optimization of energy storage capacity; power forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Critical Infrastructure (CRIS), 2010 5th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-8080-7
  • Type

    conf

  • DOI
    10.1109/CRIS.2010.5617510
  • Filename
    5617510