Statistical Modeling of Long-Term Wind Speed Data

S.M., Lawan and W.A.W.Z., Abidin and W.Y., Chai and A., Baharun and T., Masri (2015) Statistical Modeling of Long-Term Wind Speed Data. American Journal of Computer Science and Information Technology, 3 (1). ISSN 2349-3917

NO 19 Statistical Modelling of Long-Term Wind Speed Data(abstract).pdf

Download (174kB) | Preview
Official URL:


The attention of most countries of the world has been shifted towards reducing the occurrences of greenhouse gasses, developing of renewable energy and energy efficiency towards building a sustainable energy in the near future. Wind energy as one of these renewable is perhaps the most suitable, clean and environmental friendly. In modeling wind speed, Weibull function is the most widely adopted model in the scientific literatures, however, other statistical functions are also need to be considered and judged their suitability based on certain criteria. In this study, five statistical models were selected for modeling of Miri wind speed data for a period of ten years. Distribution Function (PDF) and Probability (PP) plots are employed to verify the Goodness of fit (GOF) for the distributions. Lastly, graphical and GOF outcomes are compared, suggesting that, Lognormal and Gamma distributions are found to be most appropriate as compared to the Weibull, Rayleigh and Erlag distributions.

Item Type: Article
Uncontrolled Keywords: Renewable energy; Wind energy; Distribution model; Malaysia; Miri, greenhouse gasses, unimas, university, universiti, Borneo,Sarawak, Kuching, Samarahan, ipta, education, undergraduate, Postgraduate, research, Universiti Malaysia Sarawak
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Karen Kornalius
Date Deposited: 03 Nov 2015 02:51
Last Modified: 03 Nov 2015 02:51

Actions (For repository members only: login required)

View Item View Item