Wind Energy Science
Wind Energy Science
WES
Articles | Volume 5, issue 1
Articles | Volume 5, issue 1
https://doi.org/10.5194/wes-5-199-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-5-199-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 5, issue 1
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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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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