Articles | Volume 5, issue 1
https://doi.org/10.5194/wes-5-199-2020
https://doi.org/10.5194/wes-5-199-2020
Research article
 | 
05 Feb 2020
Research article |  | 05 Feb 2020

The Power Curve Working Group's assessment of wind turbine power performance prediction methods

Joseph C. Y. Lee, Peter Stuart, Andrew Clifton, M. Jason Fields, Jordan Perr-Sauer, Lindy Williams, Lee Cameron, Taylor Geer, and Paul Housley

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Joseph C. Y. Lee on behalf of the Authors (10 Dec 2019)  Author's response   Manuscript 
ED: Publish as is (23 Dec 2019) by Alessandro Bianchini
ED: Publish as is (08 Jan 2020) by Jakob Mann (Chief editor)
AR by Joseph C. Y. Lee on behalf of the Authors (14 Jan 2020)
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Short summary
This work summarizes the results of the intelligence-sharing initiative of the Power Curve Working Group. Participants in this share exercise applied a handful of selected power curve modeling correction methods on their power performance test data, and they submitted the results for the coauthors to analyze. In this paper, we describe the share exercise, explain the analysis methodologies, and perform statistical tests to evaluate the correction methods in various inflow conditions.
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