Application of artificial neural networks for short term wind speed forecasting in Mardin, Turkey

 

 

H. Selcuk Nogay^I; Tahir Cetin Akinci^II; Marija Eidukeviciute^III

^IDepartment of Electrical Education, Technical Education Faculty, Kirklareli University, Kirklareli, Turkey
^IIDepartment of Electrical & Electronics Engineering, Engineering Faculty, Kirklareli University, Kirklareli, Turkey
^IIIDepartment of Theoretical Mechanics, Kaunas University of Technology, Kaunas, Lithuania

 

 

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ABSTRACT

Artificial neural network models were used for short term wind speed forecasting in the Mardin area, located in the Southeast Anatolia region of Turkey. Using data that was obtained from the State Meteorological Service and that encompassed a ten year period, short term wind speed forecasting for the Mardin area was performed. A number of different ANN models were developed in this study. The model with 60 neurons is the most successful model for short term wind speed forecasting. The mean squared error and approximation values for training of this model were 0.378088 and 0.970490, respectively. The ANN models developed in the study have produced satisfactory results. The most successful among those models constitutes a model that can be used by the Mardin Electric Utility Control Centre.

Keywords: artificial neural network, back propagation, forecasting, wind speed

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Acknowledgments

The authors are thankful to the Turkish State Meteorological Service, for the support in the accomplishment of the present study.

 

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Received 5 January 2011
Revised 29 October 2012