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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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Discussion papers
https://doi.org/10.5194/wes-2019-65
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-2019-65
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 02 Oct 2019

Submitted as: research article | 02 Oct 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Wind Energy Science (WES).

Analytical model for the power-yaw sensitivity of wind turbines operating in full wake

Jaime Liew1, Albert M. Urbán1, and Søren Juhl Andersen2 Jaime Liew et al.
  • 1Department of Wind Energy, Technical University of Denmark (DTU), Frederiksborgvej 399, 4000 Roskilde, Denmark
  • 2Department of Wind Energy, Technical University of Denmark (DTU), Anker Engelunds Vej 1, 2800 Lyngby, Denmark

Abstract. Wind turbines are designed to align themselves with the incoming wind direction. However, turbines often experience unintentional yaw misalignment, which can significantly reduce the power production. The unintentional yaw misalignment increase for turbines operating in wake of upstream turbines. Here, the combined effects of wakes and yaw misalignment are investigated with the resulting reduction in power production. A model is developed, which considers the trajectory of each turbine blade element as it passes through the waked wind field in order to determine a power-yaw loss coefficient. The simple model is verified using the HAWC2 aeroelastic code, where wake flow fields have been generated using both medium and high-fidelity computational fluid dynamics simulations. It is demonstrated that the spatial variation of the incoming wind field, due to the presence of wake(s), plays a significant role in the power loss due to yaw misalignment. Results show that disregarding these effects on the power-yaw loss coefficient can yield a 3.5 % overestimation in the power production of a turbine misaligned by 30°. The presented analysis and model is relevant to low-fidelity wind farm optimization tools, which aim to capture the effects of wake effects and yaw misalignment as well as uncertainty on power output.

Jaime Liew et al.
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Latest update: 21 Oct 2019
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Short summary
In wind farms, the interaction between neighboring turbines can cause notable power losses. The focus of the paper is on how the combination of turbine yaw misalignment and wake effects influences the power loss in a wind turbine. The results of the paper show a more notable power loss due to turbine misalignment when turbines are closely spaced. The presented conclusions enable better predictions of a turbine's power production, which can assist the wind farm design process.
In wind farms, the interaction between neighboring turbines can cause notable power losses. The...
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