Title :
Using Radial Basis Neural Networks to Estimate Wind Power Production
Author :
Sideratos, G. ; Hatziargyriou, N.
Abstract :
This paper compares two statistical methods for short-term wind power forecasting applied in a real wind farm located on complex terrain. The methods require as input past power measurements and meteorological forecasts of wind speed and direction (Numerical Weather Predictions or NWPs) interpolated at the site of the wind farm. Both methods include NWPs estimator models based on fuzzy logic and wind power forecasting models using neural networks combination.
Keywords :
fuzzy logic; load forecasting; power engineering computing; radial basis function networks; wind power; NWP estimator models; fuzzy logic; numerical weather predictions; power measurements; radial basis neural networks; wind power forecasting; wind power production estimation; Meteorology; Neural networks; Power measurement; Predictive models; Production; Statistical analysis; Weather forecasting; Wind energy; Wind farms; Wind forecasting; Fuzzy Sets; Radial Base Function Networks; Self-Organized Map; Wind Power Forecasting;
Conference_Titel :
Power Engineering Society General Meeting, 2007. IEEE
Conference_Location :
Tampa, FL
Print_ISBN :
1-4244-1296-X
Electronic_ISBN :
1932-5517
DOI :
10.1109/PES.2007.385812
