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.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Michael Mifsud on behalf of the Authors (22 Feb 2020)  Author's response    Manuscript
ED: Publish as is (09 Apr 2020) by Zhen Gao
ED: Publish as is (11 Apr 2020) by Jakob Mann(Chief Editor)
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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.