Title :
An Artificial Neural Network Approach for Short-Term Wind Power Forecasting in Portugal
Author :
Catalao, J.P.S. ; Pousinho, H.M.I. ; Mendes, V.M.F.
Author_Institution :
Univ. of Beira Interior, Covilha, Portugal
Abstract :
This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated, reporting the numerical results from a real-world case study.
Keywords :
neural nets; power engineering computing; power generation planning; wind power plants; artificial neural network; electric grid; short term wind power forecasting; Artificial intelligence; Artificial neural networks; Fuzzy logic; Power measurement; Predictive models; Statistical analysis; Temperature; Wind energy; Wind farms; Wind forecasting; Artificial neural networks; forecasting; wind power;
Conference_Titel :
Intelligent System Applications to Power Systems, 2009. ISAP '09. 15th International Conference on
Conference_Location :
Curitiba
Print_ISBN :
978-1-4244-5097-8
DOI :
10.1109/ISAP.2009.5352853