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NEURAL PREDICTION OF POWER FACTOR IN WIND TURBINES

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Abstract (2. Language): 
The power generated by wind turbines depends on several factors. One of them is the power factor also known as blade efficiency. In this study, the power factor is predicted using Artificial Neural Networks (ANN) and comparisons made with conventional model approach for the selected turbine profiles mostly used in practice. The study has shown that the prediction of power factors from seven input parameters by ANN yields better results than those of the conventional model.
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REFERENCES

References: 

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Rasit Ata was born in Manisa, Turkey on May 8, 1968. He received B.S., M. S. and Ph. D. degrees in Electrical
Engineering all from the University of Yıldız in 1991, 1993, 1997, respectively. In 1992 he joined the
Department of Electrical Engineering at the same university, then he joined the Department of Electrical
Engineering, Celal Bayar University in 1994 and became an assistant professor there in 2002. He is engaged in
the research of power systems, renewable energy and artificial neural networks.
Numan Sabit Cetin was born on January 28, 1969 in Turkey. He received the B.S. degree from Marmara
University in 1990 and the M.S. degree from Kocaeli University in 1999. He received Ph. D. degree in Solar
Energy Enstitute from Ege University in 2006. He is now a lecturer in the programs of Technique of Ege
Vocational School of Ege University. His major interests are wind energy, power electronic systems and electric
machines.

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