Title :
Hybrid neuro-fuzzy evolutionary approach for short-term wind power forecasting
Author :
Osório, G.J. ; Matias, J.C.O. ; Pousinho, H.M.I. ; Catalão, J. P S
Author_Institution :
Dept. of Electromech. Eng., Univ. of Beira Interior & CAST, Covilha, Portugal
Abstract :
This paper present a novel hybrid approach based on a combination of wavelet transform (WT), evolutionary particle swarm optimization (EPSO) and adaptive-network-based inference system (ANFIS), for short-term wind power forecasting in Portugal. The accuracy of the wind power forecasting attained with the proposed approach is evaluated, reporting its proficiency from a real-world case study in comparison with other methodologies. Conclusions are duly drawn.
Keywords :
evolutionary computation; fuzzy neural nets; fuzzy reasoning; load forecasting; particle swarm optimisation; power engineering computing; wavelet transforms; wind power plants; adaptive network-based inference system; evolutionary particle swarm optimization; hybrid neurofuzzy evolutionary approach; wavelet transform; wind power forecasting; Accuracy; Artificial neural networks; Forecasting; Wavelet transforms; Wind forecasting; Wind power generation;
Conference_Titel :
Electrotechnical Conference (MELECON), 2012 16th IEEE Mediterranean
Conference_Location :
Yasmine Hammamet
Print_ISBN :
978-1-4673-0782-6
DOI :
10.1109/MELCON.2012.6196427
