Articles | Volume 3, issue 2
Wind Energ. Sci., 3, 667–680, 2018
https://doi.org/10.5194/wes-3-667-2018
Wind Energ. Sci., 3, 667–680, 2018
https://doi.org/10.5194/wes-3-667-2018

Research article 09 Oct 2018

Research article | 09 Oct 2018

Probabilistic forecasting of wind power production losses in cold climates: a case study

Jennie Molinder et al.

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Jennie Molinder on behalf of the Authors (09 May 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (30 May 2018) by Jakob Mann
RR by Anonymous Referee #1 (18 Jun 2018)
ED: Publish subject to minor revisions (review by editor) (28 Jun 2018) by Jakob Mann
AR by Jennie Molinder on behalf of the Authors (29 Jun 2018)  Author's response    Manuscript
ED: Publish subject to minor revisions (review by editor) (16 Jul 2018) by Jakob Mann
ED: Publish as is (12 Sep 2018) by Jakob Mann
ED: Publish as is (12 Sep 2018) by Jakob Mann(Chief Editor)
Download
Short summary
This study shows that using probabilistic forecasting can improve next-day production forecasts for wind energy in cold climates. Wind turbines can suffer from severe production losses due to icing on the turbine blades. Short-range forecasts including the icing-related production losses are therefore valuable when planning for next-day energy production. Probabilistic forecasting can also provide a likelihood for icing and icing-related production losses.