Three-Parameter Weibull for Offshore Wind Speed Distribution in Malaysia

Aliashim Albani; Siti Syazwani Abdul Ghani; Mohd Zamri Ibrahim; Zulkifli Mohd Yusop; Mohd Afifi Jusoh; Mohd Azlan Musa; Kim Hwang Yong

doi:10.37934/araset.39.1.149158

Authors

Aliashim Albani Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia
Siti Syazwani Abdul Ghani Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia
Mohd Zamri Ibrahim Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia
Zulkifli Mohd Yusop Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia
Mohd Afifi Jusoh Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia
Mohd Azlan Musa Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia
Kim Hwang Yong Megawind Sdn. Bhd., 40150, Shah Alam, Selangor, Malaysia

DOI:

https://doi.org/10.37934/araset.39.1.149158

Keywords:

Wind Energy, Weibull, PDF

Abstract

It is usual practice to employ the probability density function in order to ascertain the wind energy potential. In this paper, the three-parameter Weibull model was suggested to distribute the low wind speed data at a site off the coast of Kijal, Terengganu. The maximum likelihood approach was used to determine the value of the distribution parameters. The Matrix Laboratory (MATLAB), better known for its user-friendly programming language, is used to carry out all of the analysis. The three-parameter Weibull was compared with the two-parameter Weibull and Rayleigh using the R-squared and the root mean square error (RMSE). These three distributions statistically model hourly ERA-5 reanalysis wind speeds. The three-parameter Weibull has a good performance, since it appears between the best R² closest to 1 and RMSE the closest to 0. The R² for the three-parameter Weibull is 0.9898, the two-parameter Weibull is 0.9874, and Rayleigh is 0.5153. While the RMSE Three-parameter Weibull is 0.0070, the two-parameter Weibull is 0.0082, and Rayleigh is 0.0677.