Articles | Volume 2, issue 1
Wind Energ. Sci., 2, 175–187, 2017
https://doi.org/10.5194/wes-2-175-2017
Wind Energ. Sci., 2, 175–187, 2017
https://doi.org/10.5194/wes-2-175-2017
Research article
28 Mar 2017
Research article | 28 Mar 2017

Monitoring offshore wind farm power performance with SCADA data and an advanced wake model

Niko Mittelmeier et al.

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Latest update: 05 Feb 2023
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Short summary
Efficient detection of wind turbines operating below their expected power output and immediate corrections help maximize asset value. The method presented estimates the environmental conditions from turbine states and uses pre-calculated power lookup tables from a numeric wake model to predict the expected power output. Deviations between the expected and the measured power output are an indication of underperformance. A demonstration of the method's ability to detect underperformance is given.