@article{article_168364, title={Statistical Analysis of Wind Resources at Darling for Energy Production}, journal={International Journal Of Renewable Energy Research}, volume={2}, pages={250–261}, year={2012}, author={Olaofe, Zaccheus Olaniyi and Folly, Komla A.}, keywords={Wind Data, Maximum Likelihood Estimation (MLE), Air Density, Wind Distributions, Wind Power Density}, abstract={This paper presents a statistical analysis of wind resources at the Darling site for wind energy assessment and evaluation. Three statistical distribution functions were fitted to a collection of wind speed data at 10, 50 and 70m hub heights to determine the best distribution function to be used for modeling of the wind speed at these hub heights. Results show that the Rayleigh function modeled the wind speed best at these hub heights as compared to the other functions. Accuracy test was conducted using an independent wind dataset, collected on 40m hub height to validate the goodness of fit of these statistical functions. The Rayleigh function proved to be accurate for modeling the wind speed at various hub heights. The choice of Rayleigh function is based on the accuracy of the function modeling the wind speed at various heights and the testing criteria. Furthermore, the wind resources were mapped with the wind power densities as the annual mean wind power densities were estimated at 289 W/m² and 333 W/m², and the annual mean wind speed were estimated at 6.19 m/s and 6.49m/s on 50m and 70m heights respectively.}, number={2}, publisher={İlhami ÇOLAK}