Statistical Modelling of Long-Term Wind Speed Data

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, c...

Full description

Bibliographic Details
Main Authors: Lawan, S.M, Abidin, W.A.W.Z, Chai, W.Y, Baharun, A., Masri, T.
Format: Article
Language:English
Published: Pubicon International Publications 2015
Subjects:
Online Access:http://ir.unimas.my/id/eprint/13365/
http://ir.unimas.my/id/eprint/13365/1/Statistical%20Modelling%20of%20Long-Term%20Wind%20speed%20data%20%28abstract%29.pdf
_version_ 1848837390857142272
author Lawan, S.M
Abidin, W.A.W.Z
Chai, W.Y
Baharun, A.
Masri, T.
author_facet Lawan, S.M
Abidin, W.A.W.Z
Chai, W.Y
Baharun, A.
Masri, T.
author_sort Lawan, S.M
building UNIMAS Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-15T06:38:54Z
format Article
id unimas-13365
institution Universiti Malaysia Sarawak
institution_category Local University
language English
last_indexed 2025-11-15T06:38:54Z
publishDate 2015
publisher Pubicon International Publications
recordtype eprints
repository_type Digital Repository
spelling unimas-133652016-09-06T22:08:02Z http://ir.unimas.my/id/eprint/13365/ Statistical Modelling of Long-Term Wind Speed Data Lawan, S.M Abidin, W.A.W.Z Chai, W.Y Baharun, A. Masri, T. TC Hydraulic engineering. Ocean engineering 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. Pubicon International Publications 2015 Article PeerReviewed text en http://ir.unimas.my/id/eprint/13365/1/Statistical%20Modelling%20of%20Long-Term%20Wind%20speed%20data%20%28abstract%29.pdf 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 http://pubicon.info/index.php/AJCSIT/article/view/9
spellingShingle TC Hydraulic engineering. Ocean engineering
Lawan, S.M
Abidin, W.A.W.Z
Chai, W.Y
Baharun, A.
Masri, T.
Statistical Modelling of Long-Term Wind Speed Data
title Statistical Modelling of Long-Term Wind Speed Data
title_full Statistical Modelling of Long-Term Wind Speed Data
title_fullStr Statistical Modelling of Long-Term Wind Speed Data
title_full_unstemmed Statistical Modelling of Long-Term Wind Speed Data
title_short Statistical Modelling of Long-Term Wind Speed Data
title_sort statistical modelling of long-term wind speed data
topic TC Hydraulic engineering. Ocean engineering
url http://ir.unimas.my/id/eprint/13365/
http://ir.unimas.my/id/eprint/13365/
http://ir.unimas.my/id/eprint/13365/1/Statistical%20Modelling%20of%20Long-Term%20Wind%20speed%20data%20%28abstract%29.pdf