Statistical analysis of wind energy potential for Bartın province: Weibull distribution approach

Abstract

Our study aimed to investigate the wind potential of Bart & imath;n, one of T & uuml;rkiye's northernmost provinces. To determine this potential, we analyzed the region's wind power density and wind speed parameters. 3561 hourly wind speed data obtained from the stations of the General Directorate of Meteorology between the years 2015-2024 were used in the analyses. The obtained data were evaluated to examine the annual, seasonal, and monthly distributions of wind speed. In the actual data collected, the highest wind speed was measured as 1.5645 m/s and the lowest as 0.3345 m/s. Based on the Weibull analysis, the highest average wind speed was determined to be 1.2712 m/s in 2024, and the highest power density corresponding to this average wind speed was 1.6453 W/m2. The obtained data were evaluated in order to examine the annual, seasonal and monthly distributions of wind speed. Weibull distribution function, which isfrequently preferred in the literature and known to provide reliable results, was used for statistical modeling of wind speeds. The shape (k) and scale (c) parameters of the Weibull distribution were determined by the least squares method; the suitability of the model was statistically verified by the coefficient of determination (R2), root mean square error (RMSE) and chi-square (chi 2) tests. The analyses show that the wind data of Bart & imath;n province can be successfully represented by the Weibull distribution. The findings shed light on the feasibility of wind energy-based investments in Bart & imath;n and provide a solid data basis for new studies in this field. It is also anticipated that they may contribute to the planning of sustainable energy policies at the regional level.