Application of Radial Basis Function Networks for Wind Power Forecasting

  • George Sideratos
  • N. D. Hatziargyriou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4132)


In this paper, an advanced system based on artificial intelligence and fuzzy logic techniques is developed to predict the wind power output of a wind farm. A fuzzy logic model is applied first to check the reliability of the numerical weather predictions (NWPs) and to split them in two sub-sets, of good and bad quality NWPs, respectively. Two Radial Basis Function (RBF) neural networks, one for each sub-set are trained next to estimate the wind power. Results from a real wind farm are presented and the added value of the proposed method is demonstrated by comparison with alternative methods.


Wind Speed Hide Layer Wind Turbine Wind Power Fuzzy Model 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • George Sideratos
    • 1
  • N. D. Hatziargyriou
    • 1
  1. 1.National Technical University of AthensGreece

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