Articles | Volume 3, issue 1
Wind Energ. Sci., 3, 371–393, 2018
https://doi.org/10.5194/wes-3-371-2018
Wind Energ. Sci., 3, 371–393, 2018
https://doi.org/10.5194/wes-3-371-2018

Research article 14 Jun 2018

Research article | 14 Jun 2018

Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing

Rochelle P. Worsnop et al.

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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 Rochelle Worsnop on behalf of the Authors (16 Apr 2018)  Author's response    Manuscript
ED: Publish subject to technical corrections (23 May 2018) by Jakob Mann
ED: Publish as is (29 May 2018) by Joachim Peinke(Chief Editor)
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Short summary
This paper uses four statistical methods to generate probabilistic wind speed and power ramp forecasts from the High Resolution Rapid Refresh model. The results show that these methods can provide necessary uncertainty information of power ramp forecasts. These probabilistic forecasts can aid in decisions regarding power production and grid integration of wind power.