Statistical Modelling of Long-Term Wind Speed Data

Lawan, S.M and Abidin, W.A.W.Z and Chai, W.Y and Baharun, A. and Masri, T. (2015) Statistical Modelling of Long-Term Wind Speed Data. American Journal of Computer Science and Information Technology, 5 (1). ISSN 2349-3917

Statistical Modelling of Long-Term Wind speed data (abstract).pdf

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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, Miri, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: T Technology > TC Hydraulic engineering. Ocean engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Depositing User: Karen Kornalius
Date Deposited: 06 Sep 2016 22:08
Last Modified: 06 Sep 2016 22:08

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