Title :
An enhanced ANN wind power forecast model based on a fuzzy representation of wind direction
Author :
Gavrilas, Mihai ; Gavrila, Gilda
Author_Institution :
Power Syst. Dept., Tech. Univ. of Iasi, Iasi, Romania
Abstract :
Due to high penetration of wind generation in modern power systems, the influence of wind power production over the efficient operation of the power system is increasingly complex. Hence, an increasing interest is shown by different actors in the wind energy market to develop and enhance existent forecasting methods for power generated by wind farms. This paper presents the experience with wind power prediction of a small size wind power producer in Romania. The model was designed using components from Artificial Neural Networks and Fuzzy System theory.
Keywords :
fuzzy set theory; neural nets; power engineering computing; wind power plants; ANN wind power forecast model; fuzzy representation; fuzzy system theory; wind direction; wind energy market; wind farms; wind generation system; wind power production; Artificial neural networks; Forecasting; Pragmatics; Wind forecasting; Wind power generation; Wind speed; Wind turbines; Artificial neural networks; Fuzzy systems; Wind power forecast; Wind power generator;
Conference_Titel :
Neural Network Applications in Electrical Engineering (NEUREL), 2010 10th Symposium on
Conference_Location :
Belgrade
Print_ISBN :
978-1-4244-8821-6
DOI :
10.1109/NEUREL.2010.5644050