Articles | Volume 5, issue 2
Wind Energ. Sci., 5, 601–621, 2020
https://doi.org/10.5194/wes-5-601-2020

Special issue: Wind Energy Science Conference 2019

Wind Energ. Sci., 5, 601–621, 2020
https://doi.org/10.5194/wes-5-601-2020
Research article
26 May 2020
Research article | 26 May 2020

Analysing uncertainties in offshore wind farm power output using measure–correlate–predict methodologies

Michael Denis Mifsud et al.

Viewed

Total article views: 1,685 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,103 549 33 1,685 31 29
  • HTML: 1,103
  • PDF: 549
  • XML: 33
  • Total: 1,685
  • BibTeX: 31
  • EndNote: 29
Views and downloads (calculated since 02 Dec 2019)
Cumulative views and downloads (calculated since 02 Dec 2019)

Viewed (geographical distribution)

Total article views: 1,344 (including HTML, PDF, and XML) Thereof 1,278 with geography defined and 66 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 Aug 2022
Download
Short summary
In offshore wind, it is important to have an accurate wind resource assessment. Measure–correlate–predict (MCP) is a statistical method used in the assessment of the wind resource at a candidate site. Being a statistical method, it is subject to uncertainty, resulting in an uncertainty in the power output from the wind farm. This study involves the use of wind data from the island of Malta and uses a hypothetical wind farm to establish the best MCP methodology for the wind resource assessment.