Wind energy potential assessment using Weibull distribution with various numerical estimation methods: a case study in Mersing and Port Dickson, Malaysia

In this study, the Weibull distribution with various numerical estimation methods is utilized for the assessment of wind energy potential in Mersing and Port Dickson, Malaysia, by considering different monsoon seasons, i.e., northeast and southwest monsoons. This assessment is conducted based on hourly wind speed data obtained from the Malaysian Meteorological Department and the Department of Environment, Malaysia. A total of 28 numerical estimation methods are presented, and their performances are first investigated through a Monte Carlo simulation. The results of the Monte Carlo simulation indicate that no particular method outperforms all other methods. In different settings, i.e., different sample sizes and shape parameters, certain methods are more efficient than others in estimating the Weibull parameters. Based on the simulation results, 24 out of 28 numerical estimation methods are utilized for wind energy potential assessment in Mersing and Port Dickson. The performance efficiency of all the considered methods is evaluated using an integrated approach comprising four goodness of fit criteria, the modified Kolmogorov − Smirnov, modified Anderson − Darling, modified Cramér–von Mises, and power density error. Using this integrated approach allow us to obtain a single-value goodness of fit measure known as the global score to determine the best method. Based on the best fitted Weibull model, the wind characteristics in both sites are investigated. The wind characteristics during northeast monsoon is found to be favorable for wind energy generation in Mersing with the northeast (0 − 40°) as the prominent wind direction. However, small-scale wind energy is the best option for wind energy development in Mersing. On the other hand, the Port Dickson site demonstrates poor wind characteristics, indicating that this area is not favorable for wind energy development.