Preprints
https://doi.org/10.5194/wes-2025-163
https://doi.org/10.5194/wes-2025-163
16 Sep 2025
 | 16 Sep 2025
Status: this preprint is currently under review for the journal WES.

Comparison of three DWM-based wake models at below-rated wind speeds

Øyvind Waage Hanssen-Bauer, Paula Doubrawa, Helge Aa. Madsen, Henrik Asmuth, Jason Jonkman, Gunner C. Larsen, Stefan Ivanell, and Roy Stenbro

Abstract. Wind turbine wake models are essential tools for predicting power losses and structural loads in wind farms. Among them, the dynamic wake meandering (DWM) model, included as a recommended approach in the International Electrotechnical Commission design standard, is a widely used engineering-fidelity method that balances accuracy and computational cost. This study compares the performance of three DWM-based wake model implementations (from the Technical University of Denmark, the National Renewable Energy Laboratory, and the Institute for Energy Technology) under below-rated wind speed conditions. Model predictions of wake flow, power output, and structural loads for a four-turbine row are evaluated across different ambient turbulence levels and wind-direction misalignments, and compared against high-fidelity large-eddy simulation results. All three models captured the overall wake evolution and mean turbine performance with reasonable accuracy; predicted time-averaged thrust and power were typically within 5–10 % of the large-eddy simulation benchmark. However, notable differences emerged in wake structure and unsteady load predictions, with discrepancies increasing for turbines further downstream. These differences highlight the importance of modelling choices such as wake summation and turbulence treatment, which strongly influence power-deficit and fatigue-load predictions. Comparison with large-eddy simulations reveals the strengths and weaknesses of each approach, indicating where improvements are needed. In general, the findings suggest directions for refining DWM models and improving their fidelity, ultimately enabling more robust wake predictions for wind farm design and operation.

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Øyvind Waage Hanssen-Bauer, Paula Doubrawa, Helge Aa. Madsen, Henrik Asmuth, Jason Jonkman, Gunner C. Larsen, Stefan Ivanell, and Roy Stenbro

Status: open (until 14 Oct 2025)

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Øyvind Waage Hanssen-Bauer, Paula Doubrawa, Helge Aa. Madsen, Henrik Asmuth, Jason Jonkman, Gunner C. Larsen, Stefan Ivanell, and Roy Stenbro
Øyvind Waage Hanssen-Bauer, Paula Doubrawa, Helge Aa. Madsen, Henrik Asmuth, Jason Jonkman, Gunner C. Larsen, Stefan Ivanell, and Roy Stenbro
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Short summary
We studied how different industry-oriented computer models predict the behavior of winds behind turbines in a wind farm. These "wakes" reduce energy output and can affect turbines further down the row. By comparing these three models with more detailed simulations, we found they agree well on overall power but differ in how they capture turbulence and wear on machines. Our results show where the models need improvement to make wind farm computer models more accurate and reliable in the future.
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