Articles | Volume 5, issue 4
https://doi.org/10.5194/wes-5-1551-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/wes-5-1551-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Integrated wind farm layout and control optimization
Wind Energy Department, Technical University of Denmark,
Frederiksborgvej 399, 4000 Roskilde, Denmark
Gunner C. Larsen
Wind Energy Department, Technical University of Denmark,
Frederiksborgvej 399, 4000 Roskilde, Denmark
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Total article views: 4,469 (including HTML, PDF, and XML)
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Cited
19 citations as recorded by crossref.
- Investigations into deep Reinforcement Learning for wind farm set-point optimisation H. Sheehan et al. https://doi.org/10.1016/j.eswa.2025.127627
- Wind farm flow control: prospects and challenges J. Meyers et al. https://doi.org/10.5194/wes-7-2271-2022
- Speeding up large-wind-farm layout optimization using gradients, parallelization, and a heuristic algorithm for the initial layout R. Valotta Rodrigues et al. https://doi.org/10.5194/wes-9-321-2024
- Koopman Model Predictive Control for Wind Farm Yield Optimization with Combined Thrust and Yaw Control A. Dittmer et al. https://doi.org/10.1016/j.ifacol.2023.10.1037
- Advances in Wind Farm Layout Optimization: Wind Direction Robustness and Wake Induced Asymmetric Thrust Load C. Croonenbroeck & D. Hennecke https://doi.org/10.21926/jept.2104044
- Three-dimensionality of flow through an array of cylinders F. He & C. Ren https://doi.org/10.1063/5.0313182
- Evaluating the potential of a wake steering co-design for wind farm layout optimization through a tailored genetic algorithm M. Baricchio et al. https://doi.org/10.5194/wes-9-2113-2024
- Streaming dynamic mode decomposition for short‐term forecasting in wind farms J. Liew et al. https://doi.org/10.1002/we.2694
- A Meso-Microscale Coupled Wind Farm Parameterization B. Du et al. https://doi.org/10.1007/s10546-025-00928-7
- Real‐time rotor effective wind speed estimation based on actuator disc theory: Design and full‐scale experimental validation A. Lio et al. https://doi.org/10.1002/we.2858
- Tip Speed Ratio Optimization: More Energy Production with Reduced Rotor Speed A. Hosseini et al. https://doi.org/10.3390/wind2040036
- Impact of atmospheric stability and turbulence on wind turbine wake characteristics: a nacelle lidar study J. Menken & N. Wildmann https://doi.org/10.5194/wes-11-2783-2026
- Towards holistic wind farm design optimization: an integrated multidisciplinary approach N. Italiano et al. https://doi.org/10.1088/1742-6596/3224/3/032082
- Enhanced Modeling of Joint Yaw and Axial Induction Control Using Blade Element Momentum Methods J. Liew et al. https://doi.org/10.1088/1742-6596/2767/3/032018
- Joint optimization of wind farm layout considering optimal control K. Chen et al. https://doi.org/10.1016/j.renene.2021.10.032
- Probabilistic surrogates for flow control using combined control strategies C. Debusscher et al. https://doi.org/10.1088/1742-6596/2265/3/032110
- Advancing wind turbines through control co-design: An integrative review S. Bayat et al. https://doi.org/10.1016/j.apenergy.2026.127951
- Full-scale validation of optimal axial induction control of a row of turbines at Lillgrund wind farm E. Bossanyi et al. https://doi.org/10.1088/1742-6596/2505/1/012042
- Beyond a single solution: Multimodal wind farm layout optimization via cluster annealing elite search Y. Chen et al. https://doi.org/10.1016/j.apenergy.2026.127852
19 citations as recorded by crossref.
- Investigations into deep Reinforcement Learning for wind farm set-point optimisation H. Sheehan et al. https://doi.org/10.1016/j.eswa.2025.127627
- Wind farm flow control: prospects and challenges J. Meyers et al. https://doi.org/10.5194/wes-7-2271-2022
- Speeding up large-wind-farm layout optimization using gradients, parallelization, and a heuristic algorithm for the initial layout R. Valotta Rodrigues et al. https://doi.org/10.5194/wes-9-321-2024
- Koopman Model Predictive Control for Wind Farm Yield Optimization with Combined Thrust and Yaw Control A. Dittmer et al. https://doi.org/10.1016/j.ifacol.2023.10.1037
- Advances in Wind Farm Layout Optimization: Wind Direction Robustness and Wake Induced Asymmetric Thrust Load C. Croonenbroeck & D. Hennecke https://doi.org/10.21926/jept.2104044
- Three-dimensionality of flow through an array of cylinders F. He & C. Ren https://doi.org/10.1063/5.0313182
- Evaluating the potential of a wake steering co-design for wind farm layout optimization through a tailored genetic algorithm M. Baricchio et al. https://doi.org/10.5194/wes-9-2113-2024
- Streaming dynamic mode decomposition for short‐term forecasting in wind farms J. Liew et al. https://doi.org/10.1002/we.2694
- A Meso-Microscale Coupled Wind Farm Parameterization B. Du et al. https://doi.org/10.1007/s10546-025-00928-7
- Real‐time rotor effective wind speed estimation based on actuator disc theory: Design and full‐scale experimental validation A. Lio et al. https://doi.org/10.1002/we.2858
- Tip Speed Ratio Optimization: More Energy Production with Reduced Rotor Speed A. Hosseini et al. https://doi.org/10.3390/wind2040036
- Impact of atmospheric stability and turbulence on wind turbine wake characteristics: a nacelle lidar study J. Menken & N. Wildmann https://doi.org/10.5194/wes-11-2783-2026
- Towards holistic wind farm design optimization: an integrated multidisciplinary approach N. Italiano et al. https://doi.org/10.1088/1742-6596/3224/3/032082
- Enhanced Modeling of Joint Yaw and Axial Induction Control Using Blade Element Momentum Methods J. Liew et al. https://doi.org/10.1088/1742-6596/2767/3/032018
- Joint optimization of wind farm layout considering optimal control K. Chen et al. https://doi.org/10.1016/j.renene.2021.10.032
- Probabilistic surrogates for flow control using combined control strategies C. Debusscher et al. https://doi.org/10.1088/1742-6596/2265/3/032110
- Advancing wind turbines through control co-design: An integrative review S. Bayat et al. https://doi.org/10.1016/j.apenergy.2026.127951
- Full-scale validation of optimal axial induction control of a row of turbines at Lillgrund wind farm E. Bossanyi et al. https://doi.org/10.1088/1742-6596/2505/1/012042
- Beyond a single solution: Multimodal wind farm layout optimization via cluster annealing elite search Y. Chen et al. https://doi.org/10.1016/j.apenergy.2026.127852
Saved (final revised paper)
Latest update: 24 Aug 2026
Short summary
In this paper, the influence of optimal wind farm control and optimal wind farm layout is investigated in terms of power production. The capabilities of the developed optimization platform is demonstrated on the Swedish offshore wind farm, Lillgrund. It shows that the expected annual energy production can be increased by 4 % by integrating the wind farm control into the design of the wind farm layout, which is 1.2 % higher than what is achieved by optimizing the layout only.
In this paper, the influence of optimal wind farm control and optimal wind farm layout is...
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