Using Radial Basis Neural Networks to Estimate Wind Power Production

This paper compares two statistical methodologies for short-term wind power forecasting in two different wind farms located on offshore area and complex terrain respectively. The methods require as input past power measurements and meteorological forecasts of wind speed and direction (Numerical Weat...

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Bibliographic Details
Published in2007 IEEE Power Engineering Society General Meeting pp. 1 - 2
Main Authors Hatziargyriou, N. D., Sideratos, G. N.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2007
Subjects
Meteorology
Neural networks
Power measurement
Predictive models
Production
Statistical analysis
Weather forecasting
Wind energy
Wind farms
Wind forecasting
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Summary:This paper compares two statistical methodologies for short-term wind power forecasting in two different wind farms located on offshore area and complex terrain respectively. 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 modeling based on fuzzy logic and wind power forecasting modeling using neural networks combination.
ISBN:142441296X
9781424412969
ISSN:1932-5517
DOI:10.1109/PES.2007.386190