Wind energy and estimating wind energy potential by artificial neural networks method

Increase in population in developing countries, technological advancements and industrialization has led the demand on energy to increase. Interest in renewable energy sources is increasing day by day due to the fact that fossil resources used in electricity generation cause environmental problems, their reserves will be consumed in the near future, dependency on source countries cause various political and economic problems. Many countries in the world prefer wind energy, which is one of the renewable energy sources, owing to the fact that it is a source that is indigenous, continuous and cost-effective, it reduces dependency on external sources, and its turbines could be rapidly built. This paper examines generally wind energy and the wind energy potential is estimated with artificial neural networks. In the model created, wind speed data is used during the test phase while output data of different types of wind turbines are used during the training phase. Following the practice, it is found out that the predictions made by the model created in the regression curves are reliable and consistent. Estimation results have shown that the selected region has very good wind potential and high quality energy production can be achieved with high quality turbines. It has demonstrated that artificial neural networks can be readily used as an alternative in studies on wind energy carried out by practitioners and decision makers in the energy sector. Keywords: Renewable Energy, Wind Energy, Wind Speed, Artificial Neural Network.