2025/03/13 by Tiantian Yang, Yang, Tiantian, Dongwei Chen +1 · 1 citation
Economics, Econometrics and Finance · Engineering · Environmental Science · #62P12 #Applications (stat.AP) #Aviation Industry Analysis and Trends #FOS: Computer and information sciences #Vehicle emissions and performance #Wind and Air Flow Studies
paper · doi:10.48550/arxiv.2503.09912
openalex publication_date 2025/03/13 · openalex created_date 2025/10/13 · openalex updated_date 2026/07/28
Wind speed distribution has many applications, such as the assessment of wind energy and building design. Applying an appropriate statistical distribution to fit the wind speed data, especially on its heavy right tail, is of great interest. In this study, we introduce a novel four-parameter class of generalized Lindley distribution, called the beta-generalized Lindley (BGL) distribution, to fit the wind speed data, which are derived from the annual and long-term measurements of the Flatirons M2 meteorological tower from the years 2010 to 2020 at heights of 10, 20, 50, and 80 meters. In terms of the density fit and various goodness-of-fit metrics, the BGL model outperforms its submodels (beta-Lindley, generalized Lindley, and Lindley) and other reference distributions, such as gamma, beta-Weibull, Weibull, beta-exponential, and Log-Normal. Furthermore, the BGL distribution is more accurate at modeling the long right tail of wind speed, including the 95th and 99th percentiles and Anderson-Darling statistics at different heights. Therefore, we conclude that the BGL distribution is a strong alternative model for the wind speed distribution.