Articles | Volume 7, issue 6
Research article
08 Dec 2022
Research article |  | 08 Dec 2022

Predicting power ramps from joint distributions of future wind speeds

Thomas Muschinski, Moritz N. Lang, Georg J. Mayr, Jakob W. Messner, Achim Zeileis, and Thorsten Simon


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2022-48', Anonymous Referee #1, 30 Jun 2022
    • AC2: 'Reply on RC1', Thomas Muschinski, 17 Aug 2022
  • CC1: 'Comment on wes-2022-48', Jethro Browell, 01 Jul 2022
    • AC1: 'Reply on CC1', Thomas Muschinski, 07 Jul 2022
      • CC2: 'Reply on AC1', Jethro Browell, 07 Jul 2022
  • RC2: 'Comment on wes-2022-48', Anonymous Referee #2, 16 Jul 2022
    • AC3: 'Reply on RC2', Thomas Muschinski, 17 Aug 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Thomas Muschinski on behalf of the Authors (17 Aug 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (17 Aug 2022) by Raúl Bayoán Cal
RR by Anonymous Referee #2 (30 Aug 2022)
RR by Anonymous Referee #1 (10 Oct 2022)
ED: Publish as is (20 Oct 2022) by Raúl Bayoán Cal
ED: Publish as is (23 Oct 2022) by Joachim Peinke (Chief editor)
AR by Thomas Muschinski on behalf of the Authors (24 Oct 2022)  Manuscript 
Short summary
The power generated by offshore wind farms can vary greatly within a couple of hours, and failing to anticipate these ramp events can lead to costly imbalances in the electrical grid. A novel multivariate Gaussian regression model helps us to forecast not just the means and variances of the next day's hourly wind speeds, but also their corresponding correlations. This information is used to generate more realistic scenarios of power production and accurate estimates for ramp probabilities.
Final-revised paper