TY  - JOUR
TT  - Estimating Wind Energy Potential by Artificial Neural Networks Method
AU  - Şenol, Ümit
AU  - Musayev, Zabit
PY  - 2017
DA  - July
JF  - Bilge International Journal of Science and Technology Research
JO  - bilgesci
PB  - Kutbilge Akademisyenler Derneği
WT  - DergiPark
SN  - 2651-401X
SP  - 23
EP  - 31
VL  - 1
IS  - 1
KW  - Rüzgar enerjisi
KW  - Rüzgar santrali
KW  - Rüzgar hızı
KW  - Yapay sinir ağı
N2  - In thisstudy, wind energy potential estimation is made by creating various windturbines and artificial neural networks (YSA) models. The wind speed data to beused in the model was used during the test phase, while the output powers fromdifferent types of wind turbines were used during the training phase. It hasbeen understood that the predictions made by the model created in theregression curves that emerged after the application are reliable andconsistent. According to the estimation results, it is seen that the selectedzone has very good wind potential and high quality energy production can beachieved with high quality turbines. Moreover, it has been revealed that YSAcan easily use alternatives in wind energy applications in the days when theelectricity energy needs of the people in the energy sector and the decisionmakers are constantly increasing.
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CR  - Türkiye rüzgar enerjisi istatistik raporu, Türkiye Rüzgar Enerjisi Birliği, http://www.tureb.com.tr, (25.02.2017).
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CR  - Hamzaçebi, C., Yapay Sinir Ağları: Tahmin Amaçlı Kullanımı Matlab ve Neurosolution Uygulamalı, Ekin Yayınevi, Bursa, 2011.
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UR  - https://dergipark.org.tr/en/pub/bilgesci/article/315824
L1  - https://dergipark.org.tr/en/download/article-file/324901
ER  -