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Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

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Detalhes bibliográficos
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.
Autores principais:Pousinho, Hugo Miguel Inácio
Outros Autores:Mendes, Victor; Catalão, João Paulo da Silva
Assunto:Wind power Forecasting Neural networks Fuzzy logic Arima models System Speed Anfis Prediction Turbines Market
Ano:2011
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Lisboa
Idioma:inglês
Origem:Repositório Científico do Instituto Politécnico de Lisboa
Descrição
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.