Determining coefficients of Weibull distribution function using machine learning methods and estimating wind potential in different regions

The significance of renewable energy sources has increased to fulfil global energy demands. However, the potential of wind energy is not being adequately harnessed. On a regional basis, the selection of sites and installation expenses directly influence the efficiency of wind power plants (WPP). Despite the presence of significant challenges in the site selection process for a WPP, no globally recognized methodology has been established. Evaluating regional wind potential is crucial for optimizing the utilization of wind energy resources. This study utilized wind data from the General Directorate of Meteorology to assess the wind energy potential of 11 cities—Adana, Alanya, Ankara, Antalya, Çanakkale, Gaziantep, İzmir, Kahramanmaraş, Konya, Mersin, and Osmaniye—over the period from 2017 to 2021. The examination was performed with the MATLAB program. The Weibull distribution function was utilized for estimating the average wind speed and wind power values for the regions, which were subsequently compared with actual observations. Various approaches were employed to determine the coefficients of the Weibull distribution function, and the accuracy of these methods was evaluated by various statistical error analysis tests. Consequently, the optimal strategy regarding performance for the chosen region was determined. This study offers a comprehensive evaluation of the region's wind energy potential and provides an estimation for wind energy development in the area. This comprehensive study will significantly enhance future research projects and academic studies in this domain. It seeks to determine efficient measures for the accelerated advancement of the wind energy sector in Türkiye and to enhance the proportion of wind energy within the total installed capacity.