Modeling wind data in Karabük Kahyalar, Türkiye, using Weibull distribution and its implications for investment decisions

This study investigates the wind energy potential of Karabuk Kahyalar village, Türkiye, using comprehensive statistical characterizations and techno-economic evaluations based on measured wind data collected between August 2013 and June 2014. Representing the inaugural academic investigation of wind energy investment feasibility in this rural inland region, the study characterizes the wind regime using the Weibull distribution, with parameters optimized via the Method of Moments (MM), Least Squares Method (LSM), and the Generalized Reduced Gradient Method (GRG). Statistical error metrics indicate that the GRG and MM methods provide superior alignment with the observed frequency data. To mitigate the inherent limitations of the 11-month sampling period and capture regional annual cycles, non-parametric Classical and temporal-dependent Block Bootstrap resampling analyses were conducted, establishing narrow confidence intervals and validating the data against long-term NASA POWER climatological trends (R^2 > 0.75). Based on these robust statistical frameworks, five commercial horizontal-axis wind turbines were evaluated across utility and micro-scales. Techno-economic metrics reveal that while the Nordex N100/2500 model delivers the lowest Cost of Energy (0.08195 $/kWh) due to economies of scale, the Proven 15 kW micro-turbine stands out as the most technically viable decentralized option, achieving the highest capacity factor (14.2%). Ultimately, this analysis demonstrates that despite a low regional average wind speed (3.47 m/s), strategically selected small-scale or optimized hybrid renewable configurations can achieve cost-effective electricity generation, offering a repeatable planning framework for rural decarbonization.