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...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | E-Article |
| Language: | English |
| Published: |
Pubicon International Publications
2015
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/13365/1/Statistical%20Modelling%20of%20Long-Term%20Wind%20speed%20data%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/13365/ http://pubicon.info/index.php/AJCSIT/article/view/9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|