Assessment of Wind Energy Potential in North Central Nigeria Using Weibull Distribution for Sustainable Energy Planning and Generation

Abstract

This study assesses the wind energy potential of five states in North Central Nigeria: Benue, FCT Abuja, Kogi, Kwara, and Nasarawa using statistical modeling of wind speed data. Monthly mean wind speed data were analyzed with the two-parameter, Weibull probability distribution function to estimate key parameters: the shape factor (k), scale factor (c) and mean wind speed. Probability density functions (PDF) and cumulative distribution functions (CDF) were also plotted to evaluate the frequency and exceedance probabilities of wind speeds relative to wind turbine cut-in thresholds. The results show that wind speeds in the region are generally moderate, with seasonal variation influenced by the Harmattan winds. Benue and Kwara States demonstrated the highest potential, with wind speeds exceeding 3 m/s for over 50% of the year, while Abuja and Kogi recorded weaker wind resources. Nasarawa exhibited intermediate potential. The findings suggest that while large-scale wind farms may not be feasible in the region, small to medium-scale wind systems are viable, especially when integrated with solar energy in hybrid systems. This study concludes that hybrid renewable systems (solar-wind) represent the most sustainable pathway for improving energy access in North Central Nigeria, particularly in rural communities.