A Case Study on Investigating Probabilistic Characteristics of Wind Speed Data for Green Airport

Accurate estimation of wind distribution plays a vital role in modelling more efficiently and minimizing theoretical computation errors in terms of practical applications. This research strives to conduct elaborately an assessment of the wind behavior and features of an international airport based on various heights from the ground level. Wind speed at each height, composed of 10 m, 20 m, 30 m, 40 m, and 50 m, is computed by applying the power-law equation. After that, the wind profile at each height is comparatively estimated based on the graphical, empirical, and maximum-likelihood method. Several statistical tools, namely, root mean square (RMSE) and R-squared (R2), are performed to make a fair comparison among the methods that help estimate the Weibull parameters. The results of this study reveal that the empirical and maximum-likelihood methods exhibit better performance than the graphical method in estimating the shape and scale parameter, irrespective of heights. Moreover, the findings of the study imply that the airport has a moderate potential to make use of generating electricity and hydrogen from wind power.