Abstract

The depletion of resources and emission of hazardous gases have been identified with conventional sources of energy. The negative influence of conventional sources of energy on the environment necessitates the call for the use of renewable and sustainable energy sources, such as wind. Wind power is one of the available renewable energy sources in Nigeria with huge potential that can be tapped in order to contribute to its energy mix. Wind energy utilization in Nigeria is poor because the available data in all six geopolitical political regions for system design have not been fully analysed and implemented. Wind energy projects are liable to failure if proper analysis is not done. Therefore, before any location could be considered suitable or unsuitable for wind power generation, the power density must be determined using the standard approach. This study, therefore evaluated the wind energy potential of Omu Aran, Nigeria using Weibull and Rayleigh models. Five years data collected from the metrological station of the Landmark University on Lat. 8.14 oN; Long. 5.10 oE were processed and analysed in Matlab computer software using a code developed for two statistical modelling methods (Weibull and Rayleigh). The actual mean yearly wind speed of 3.964 m/s for Kwara falls in the low wind speed. Although, the power density for hours of the day, months, and seasonal variation ranged from 24 to 141 W/m2. More than 50% of the power density for daily hours was less than 100 W/m2 which indicated that Omu Aran, Nigeria belongs to class 1. The coefficient of efficiency (COE) for Weibull probability distribution ranged from 39.95 to 94.9 while the coefficient of determination (COD) R2 ranged from 0.66 to 0.98. This range of performance values for the Weibull model, when compared to the Rayleigh model, were within the acceptable limits for prediction accuracy, hence the Weibull probability distribution function can be used for the preliminary design of wind power plants for Kwara State, Nigeria. Therefore, it would help the relevant stakeholders in wind power project investment to make the appropriate decision.