Analysis of Wind Speed Data and Energy Potential Using Weibull Distribution Method: A Case Study of Damaturu, Yobe State, North-East, Nigeria
Abstract
In this study, the wind speed characteristics and energy potential in Yobe State University area, Damaturu were investigated using wind speed data that span for 4 years from 2016 to 2019 and was measured at a height of 10 meters from the ground level using cup anemometers and modeled via the Weibull probability framework. The Maximum Likelihood Estimation (MLE) method were deployed to compute the Weibull shape (k) and scale (c) parameters. These parameters facilitated a detailed evaluation of temporal wind dynamics. It was observed that the maximum wind speed (3.21–4.80 m/s), energy density ranges (15.07–50.40 kWh/m2), and power density (20.26–67.74 W/m2) peaked between January and April, whereas July to October exhibited significantly reduced performance. The years 2017 and 2018 proved most favorable for energy extraction, driven by elevated scale parameters (c = 2.70) and consistent mean speeds (2.44 m/s). In contrast, 2016 recorded the highest shape factor (k = 4.14), reflecting stable yet slower winds ideal for low power, steady output applications. Although annual wind speeds remained below 3 m/s, the region shows promise for small-scale wind energy installations employing turbines with low activation thresholds, especially during months with extended wind duration (January’s, T(V) = 368.61). However, periods such as September 2019 marked by minimal speeds (0.86 m/s) and high probability density values (F(V) = 0.92) highlight challenges in energy predictability, necessitating turbines optimized for variable conditions. Damaturu holds some potential for wind energy development, achieving maximum power density of 67.74 W/m2 and an energy density of 50.40 kW h/m2, positioning it below the Class I threshold. This suggests its suitability for low energy applications such as water pumping, battery charging, and powering small electronic devices.
