Wind speed analysis using Weibull and lower upper truncated Weibull distribution in Bangladesh
Saima Jahan, Nurulkamal Masseran, Wan Zawiah Wan Zin
Abstract
Wind speed (WS) is the most important factor for modeling wind energy. WSs below a lower truncation point are usually not able to generate energy. Conversely, WSs higher than the upper truncation point may damage wind turbines. Moreover, the presence of missing values in WS data may hamper the analysis results of WS estimates. This study used the mean imputation and linear regression methods for estimating missing values and aimed to analyze the characteristics of WS data in Bangladesh using the Weibull distribution and the lower–upper-truncated Weibull distribution (TWD). The maximum likelihood method was used to determine the Weibull and truncated Weibull parameters. Our data revealed that TWD showed better performance than WD in terms of root mean square error (RMSE) and KolmogorovSmirnov (KS) in WS distribution estimation. Lower–upper-TWD can be used in the assessment of wind energy potential.