Distribution cycle of wind speed: A case study in the Southern Part of Malaysia

Abstract

AbstractWind energy has historically helped many people and has been utilized for farming and seafaring. Today, modern usage is more comprehensive such as generating electricity. However, its usage in Malaysia remains at an all-time low. Numerous factors contribute to this result. Consequently, a full assessment of wind energy in a particular region is deemed necessary. This study investigates wind speed distribution in Mersing. It also illustrates the period during which the regional distribution statistics changed. The researcher used Autofit 5.6 and the Maximum Likelihood Method to figure out the parameter value of each distribution for wind speed data from 2012 to 2016. This study utilized three distinct methods of Goodness of fit (GOF) to estimate the optimal distribution ranking, such as Chi-Square, Anderson-Darling, and Kolmogorov-Smirnov. The results reveal that the Burr, Gamma, and Lognormal distributions correlate to the wind speed data in Mersing and the Burr distribution is the most appropriate. In addition, the findings indicate that distribution changes occur at a minimum rate of 8.89%. In conclusion, these findings reveal that there has been no significant change over the five years. This information enables stakeholders to determine whether they will earn a profit owing to changes in the distribution of a particular area, reducing risk.