Title :
Very short term wind power prediction: A data mining approach
Author :
Negnevitsky, M. ; Johnson, P.
Author_Institution :
Univ. of Tasmania, Hobart, TAS
Abstract :
This panel paper reviews the available techniques for wind power forecasting in the very short term time frame out to 30 minutes ahead. A generic approach is proposed where the most appropriate techniques are selected based on data availability and data characteristics. The need for appropriate data generation for development and testing of a generic approach is also discussed.
Keywords :
data mining; load forecasting; power engineering computing; wind power; wind power plants; data availability; data generation; data mining; generic approach; very short term wind power prediction:; wind power forecasting; Data mining; Economic forecasting; Fluctuations; Power generation; Power system planning; Power system security; Wind energy; Wind energy generation; Wind farms; Wind forecasting; data generation; data mining; intelligent systems; very short term forecasting; wind power;
Conference_Titel :
Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE
Conference_Location :
Pittsburgh, PA
Print_ISBN :
978-1-4244-1905-0
Electronic_ISBN :
1932-5517
DOI :
10.1109/PES.2008.4596604
