AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM APPROACH FOR PREDICTION OF POWER FACTOR IN WIND TURBINES
Öz
Anahtar Kelimeler
Kaynakça
- Global Wind Energy Council News.
- http://www.wwindea.org/home/images/storie s/pr statistics 2007_210208_red.pdf, World WindEnergy Association press release retrieved 2008 03 18.
- M.A. Yurdusev, R. Ata and N.S. Çetin, “Assessment of optimum tip speed ratio in wind turbines using artificial neural networks”, Energy, 2006, 31:1817-1825.
- R. Ata, N.S. Çetin, “Neural Prediction of Power Factor in Wind Turbines” Istanbul University Journal of Electrical & Electronics Engineering, 2007, Vol:7, No.2, pp. 431-438.
- E. Cam and O. Yıldız, “Prediction of wind speed and power in the central Anatolian region of Turkey by adaptive neuro-fuzzy inference systems (ANFIS)”, Turkish J. Eng. Env. Sci. 30 2006, pp. 35- 41.
- A. Sfetsos, “A comparison of various forecasting techniques applied to mean hourly wind speed time series”, Renewable Energy, 21, 2000, pp. 23-35.
- C. Potter, M. Ringrose and M. Negnevitsky, “Short-term wind forecasting techniques for power generation”, Australasian Universities Power Engineering Conference (AUPEC 2004), 26-29 September, 2004, Brisbane, Australia.
- M. Negnevitsky and C.W. Potter, “Innovative short-term wind generation prediction techniques”, Power Systems Conference and Exposition, IEEE PES, Oct. 29, 2006-Nov. 1 2006, pp. 60-65.
Ayrıntılar
Birincil Dil
İngilizce
Konular
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Bölüm
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Yazarlar
Rasit Ata
Bu kişi benim
Yayımlanma Tarihi
14 Şubat 2012
Gönderilme Tarihi
14 Şubat 2012
Kabul Tarihi
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Yayımlandığı Sayı
Yıl 2009 Cilt: 9 Sayı: 1