Application of radial basis function networks for wind power forecasting

Authors:
George Sideratos;N. D. Hatziargyriou
Affiliations:
National Technical University of Athens, Greece;National Technical University of Athens, Greece
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Year:
2006

Citing 1
Cited 1

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Abstract

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.