Analysis of Wind Speed Data Using Weibull Distribution in KENITRA Morocco

Wind power is among the fastest-growing renewable energy sources for generating electricity and has demonstrated the potential to offer clean, efficient, and renewable energy while mitigating environmental degradation. With the aim of evaluating the capacity for wind energy in the Kenitra area of Morocco, this study employed statistical methods, specifically the Weibull distribution’s probability density function to analyze data on the speed of the wind obtained from two precision weather stations. The graphical method was used to calculate the Weibull parameters based on wind speed data measured at 30-min and 10-min intervals. The data was collected over a five-year period (2017–2021) from the National School of Applied Sciences (NSAS) weather station, while the Ibn Tofail University (ITU) station provided 10-min interval data for two years (2021–2022). The study also examined the monthly and annual variations in wind speed. The findings suggest that the average wind speed in Kenitra varies within the span of 1.03 m/s and 2.59 m/s, with the ITU station recording the utmost mean wind velocity of 2.59 m/s and the lowest value of 1.03 m/s. At the NSAS station, the maximum mean wind speed was recorded at 2.21 m/s, and the minimum mean wind speed at 1.22 m/s. The Weibull distribution analysis revealed that the shape and scale parameters for both stations were within the ranges of 1.071 to 1.884 and 1.081 to 3.029 m/s, respectively, indicating that wind speeds in Kenitra are typically low to moderate. However, it is important to note that small wind turbines require a minimum cut-in wind speed of around 3–4 m/s to generate electricity.