Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.21/2075
Título: Application of adaptive neuro-fuzzy inference for wind power short-term forecasting
Autor: Pousinho, Hugo Miguel Inácio
Mendes, Víctor Manuel Fernandes
Catalão, João Paulo da Silva
Palavras-chave: Wind power
Forecasting
Neural networks
Fuzzy logic
Arima models
System
Speed
Anfis
Prediction
Turbines
Market
Data: Nov-2011
Editora: Wiley-Blackwell
Citação: POUSINHO, Hugo M. I.; MENDES, Victor M. F.; CATALÃO, João P. S. - Application of Adaptive Neuro-Fuzzy Inference for Wind Power Short-Term Forecasting. IEEJ Transactions on Electrical and Electronic Engineering. ISSN 1931-4973. Vol. 6, n.º6 (2011) p.571-576.
Resumo: 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. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Peer review: yes
URI: http://hdl.handle.net/10400.21/2075
ISSN: 1931-4973
Versão do Editor: http://onlinelibrary.wiley.com/doi/10.1002/tee.20697/abstract;jsessionid=2C5D6CC210D27655A2A70B233E71B336.d01t02
Aparece nas colecções:ISEL - Eng. Electrotécn. - Artigos



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