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

Mifsud, Michael Denis; Sant, Tonio; Farrugia, Robert Nicholas

doi:https://doi.org/10.5194/wes-5-601-2020

Articles | Volume 5, issue 2

https://doi.org/10.5194/wes-5-601-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Wind Energy Science Conference 2019

https://doi.org/10.5194/wes-5-601-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 5, issue 2

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, Tonio Sant, and Robert Nicholas Farrugia

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Final revised paper (published on 26 May 2020)
Preprint (discussion started on 02 Dec 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Referee Comment', Anonymous Referee #1, 12 Dec 2019
- AC1: 'Reply to comments of first reviewer', Michael Mifsud, 03 Feb 2020
RC2: 'Good paper, needs some more discussion', Anonymous Referee #2, 06 Jan 2020
- AC2: 'Reply to comments of second reviewer.', Michael Mifsud, 03 Feb 2020

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)

AR by Michael Mifsud on behalf of the Authors (16 Apr 2020)

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.