Wind Energy Science
Wind Energy Science
WES
Articles | Volume 8, issue 8
Articles | Volume 8, issue 8
https://doi.org/10.5194/wes-8-1277-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-8-1277-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 8, issue 8
Research article
 | 
17 Aug 2023
Research article |  | 17 Aug 2023

Bayesian method for estimating Weibull parameters for wind resource assessment in a tropical region: a comparison between two-parameter and three-parameter Weibull distributions

Mohammad Golam Mostafa Khan and Mohammed Rafiuddin Ahmed

Viewed

Total article views: 1,760 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,202 508 50 1,760 39 38
  • HTML: 1,202
  • PDF: 508
  • XML: 50
  • Total: 1,760
  • BibTeX: 39
  • EndNote: 38
Views and downloads (calculated since 23 Aug 2022)
Cumulative views and downloads (calculated since 23 Aug 2022)

Viewed (geographical distribution)

Total article views: 1,760 (including HTML, PDF, and XML) Thereof 1,668 with geography defined and 92 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 04 Nov 2024
Download
Short summary
A robust technique for wind resource assessment with a Bayesian approach for estimating Weibull parameters is proposed. Research conducted using seven sites' data in the tropical region from 1° N to 21° S revealed that the three-parameter (3-p) Weibull distribution with a non-zero shift parameter is a better fit for wind data that have a higher percentage of low wind speeds. Wind data with higher wind speeds are a special case of the 3-p distribution. This approach gives accurate results.
Read more
Altmetrics
Final-revised paper
Preprint