Articles | Volume 7, issue 3
https://doi.org/10.5194/wes-7-1241-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-7-1241-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Jun 2022
Research article |
| 20 Jun 2022
| 20 Jun 2022
Offshore wind farm cluster wakes as observed by long-range-scanning wind lidar measurements and mesoscale modeling
Beatriz Cañadillas
CORRESPONDING AUTHOR
Institute of Flight Guidance, Technische Universität Braunschweig, Braunschweig, Germany
Renewables, UL International GmbH, Oldenburg, Germany
Maximilian Beckenbauer
Institute of Flight Guidance, Technische Universität Braunschweig, Braunschweig, Germany
Juan J. Trujillo
Renewables, UL International GmbH, Oldenburg, Germany
Martin Dörenkämper
Fraunhofer Institute for Wind Energy Systems, Oldenburg, Germany
Richard Foreman
Renewables, UL International GmbH, Oldenburg, Germany
Thomas Neumann
Renewables, UL International GmbH, Oldenburg, Germany
Astrid Lampert
Institute of Flight Guidance, Technische Universität Braunschweig, Braunschweig, Germany
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Cited
36 citations as recorded by crossref.
- Evaluation of Engineering Models for Large‐Scale Cluster Wakes With the Help of In Situ Airborne Measurements K. zum Berge et al. 10.1002/we.2942
- Power Production, Inter- and Intra-Array Wake Losses from the U.S. East Coast Offshore Wind Energy Lease Areas S. Pryor & R. Barthelmie 10.3390/en17051063
- Statistics of Wind Farm Wakes for Different Layouts and Ground Roughness Z. Wang et al. 10.1007/s10546-023-00814-0
- Overview of preparation for the American WAKE ExperimeNt (AWAKEN) P. Moriarty et al. 10.1063/5.0141683
- Reconstruction of dynamic wind turbine wake flow fields from virtual Lidar measurements via physics-informed neural networks J. Zhang & X. Zhao 10.1088/1742-6596/2767/9/092017
- Parametric Analysis of Inter-Farm Wake Interactions in Offshore Wind Farm Projects Along the US East Coast A. Moura & R. Rodrigues 10.1088/1742-6596/3016/1/012049
- Multi-model approach for wind resource assessment B. Sengers et al. 10.1088/1742-6596/2767/9/092024
- An investigation of spatial wind direction variability and its consideration in engineering models A. von Brandis et al. 10.5194/wes-8-589-2023
- Mesoscale impact of the sea surface on the performance of offshore wind farms C. Wu et al. 10.1016/j.jclepro.2022.133741
- Collocating wind data: A case study on the verification of the CERRA dataset F. Rouholahnejad et al. 10.1088/1742-6596/2875/1/012016
- Revealing inflow and wake conditions of a 6 MW floating turbine N. Angelou et al. 10.5194/wes-8-1511-2023
- Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN A. Abraham et al. 10.1088/1742-6596/2767/9/092037
- Wake field prediction of a wind farm based on a physics-informed neural network with different spatiotemporal prediction performance improvement strategies J. Song et al. 10.1016/j.taml.2025.100577
- System impacts of wind energy developments: Key research challenges and opportunities R. McKenna et al. 10.1016/j.joule.2024.11.016
- Meteorological measurements affected by wind farm cluster wakes: How to deal with waked wind in AEP assessments? M. Mayol et al. 10.1088/1742-6596/2767/9/092051
- Long-Distance Wind Farm Wake Modelling Using Convolutional Neural Networks F. Weilmann Rasmussen & P. Réthoré 10.1088/1742-6596/3016/1/012019
- Brief communication: A simple axial induction modification to the Weather Research and Forecasting Fitch wind farm parameterization L. Vollmer et al. 10.5194/wes-9-1689-2024
- In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes A. Lampert et al. 10.5194/essd-16-4777-2024
- Wind shadows impact planning of large offshore wind farms S. Pryor & R. Barthelmie 10.1016/j.apenergy.2024.122755
- Multiscale analysis of a very long wind turbine wake in an atmospheric boundary layer F. Zhang et al. 10.1103/PhysRevFluids.8.104605
- Gone with the wind? Wind farm-induced wakes and regulatory gaps E. Finserås et al. 10.1016/j.marpol.2023.105897
- Numerical Investigations of Precise Wind Field in Main Landing Area during the Landing Phase of “Shen Zhou” Series Spacecraft Mission Y. Song et al. 10.3390/aerospace10010037
- Detection of Atmospheric Wind Speed by Lidar Based on Quadrichannel Mach–Zehnder Interferometer J. Li et al. 10.3390/photonics10070726
- Power quality assessment in different wind power plant models considering wind turbine wake effects M. Khatamiaghda et al. 10.1093/ce/zkad033
- From macro to micro: A multi-scale method for assessing coastal wind energy potential in China L. Deng et al. 10.1016/j.apenergy.2025.125729
- Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm D. van Binsbergen et al. 10.5194/wes-9-1507-2024
- Benchmarking Engineering Wake Models for Assessing Wind Farm Wakes Interaction R. Rodrigues & A. Moura 10.1088/1742-6596/3016/1/012045
- Simulations suggest offshore wind farms modify low-level jets D. Quint et al. 10.5194/wes-10-117-2025
- Study of aerodynamic performance and wake effects for offshore wind farm cluster J. Cao et al. 10.1016/j.oceaneng.2023.114639
- The Atmospheric Stability Dependence of Far Wakes on the Power Output of Downstream Wind Farms R. Foreman et al. 10.3390/en17020488
- Mapping global offshore wind wake losses, layout optimisation potential, and climate change effects S. Warder & M. Piggott 10.1016/j.energy.2025.136573
- Alignment calibration and correction for offshore wind measurements using scanning lidars K. Gramitzky et al. 10.1088/1742-6596/2767/4/042014
- Characterization of local wind profiles: a random forest approach for enhanced wind profile extrapolation F. Rouholahnejad & J. Gottschall 10.5194/wes-10-143-2025
- Triple-lidar measurements of wind across a virtual rotor plane over a sea surface M. Nafisifard et al. 10.1088/1742-6596/2626/1/012022
- Offshore wakes measured by an adaptive dual-Doppler scanning lidar system T. Hildebrand et al. 10.1088/1742-6596/3025/1/012005
- Cross‐Border Cooperation to Mitigate Wake Losses in Offshore Wind Energy: A 2050 Case Study for the North Sea F. Fliegner et al. 10.1155/er/2518424
36 citations as recorded by crossref.
- Evaluation of Engineering Models for Large‐Scale Cluster Wakes With the Help of In Situ Airborne Measurements K. zum Berge et al. 10.1002/we.2942
- Power Production, Inter- and Intra-Array Wake Losses from the U.S. East Coast Offshore Wind Energy Lease Areas S. Pryor & R. Barthelmie 10.3390/en17051063
- Statistics of Wind Farm Wakes for Different Layouts and Ground Roughness Z. Wang et al. 10.1007/s10546-023-00814-0
- Overview of preparation for the American WAKE ExperimeNt (AWAKEN) P. Moriarty et al. 10.1063/5.0141683
- Reconstruction of dynamic wind turbine wake flow fields from virtual Lidar measurements via physics-informed neural networks J. Zhang & X. Zhao 10.1088/1742-6596/2767/9/092017
- Parametric Analysis of Inter-Farm Wake Interactions in Offshore Wind Farm Projects Along the US East Coast A. Moura & R. Rodrigues 10.1088/1742-6596/3016/1/012049
- Multi-model approach for wind resource assessment B. Sengers et al. 10.1088/1742-6596/2767/9/092024
- An investigation of spatial wind direction variability and its consideration in engineering models A. von Brandis et al. 10.5194/wes-8-589-2023
- Mesoscale impact of the sea surface on the performance of offshore wind farms C. Wu et al. 10.1016/j.jclepro.2022.133741
- Collocating wind data: A case study on the verification of the CERRA dataset F. Rouholahnejad et al. 10.1088/1742-6596/2875/1/012016
- Revealing inflow and wake conditions of a 6 MW floating turbine N. Angelou et al. 10.5194/wes-8-1511-2023
- Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN A. Abraham et al. 10.1088/1742-6596/2767/9/092037
- Wake field prediction of a wind farm based on a physics-informed neural network with different spatiotemporal prediction performance improvement strategies J. Song et al. 10.1016/j.taml.2025.100577
- System impacts of wind energy developments: Key research challenges and opportunities R. McKenna et al. 10.1016/j.joule.2024.11.016
- Meteorological measurements affected by wind farm cluster wakes: How to deal with waked wind in AEP assessments? M. Mayol et al. 10.1088/1742-6596/2767/9/092051
- Long-Distance Wind Farm Wake Modelling Using Convolutional Neural Networks F. Weilmann Rasmussen & P. Réthoré 10.1088/1742-6596/3016/1/012019
- Brief communication: A simple axial induction modification to the Weather Research and Forecasting Fitch wind farm parameterization L. Vollmer et al. 10.5194/wes-9-1689-2024
- In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes A. Lampert et al. 10.5194/essd-16-4777-2024
- Wind shadows impact planning of large offshore wind farms S. Pryor & R. Barthelmie 10.1016/j.apenergy.2024.122755
- Multiscale analysis of a very long wind turbine wake in an atmospheric boundary layer F. Zhang et al. 10.1103/PhysRevFluids.8.104605
- Gone with the wind? Wind farm-induced wakes and regulatory gaps E. Finserås et al. 10.1016/j.marpol.2023.105897
- Numerical Investigations of Precise Wind Field in Main Landing Area during the Landing Phase of “Shen Zhou” Series Spacecraft Mission Y. Song et al. 10.3390/aerospace10010037
- Detection of Atmospheric Wind Speed by Lidar Based on Quadrichannel Mach–Zehnder Interferometer J. Li et al. 10.3390/photonics10070726
- Power quality assessment in different wind power plant models considering wind turbine wake effects M. Khatamiaghda et al. 10.1093/ce/zkad033
- From macro to micro: A multi-scale method for assessing coastal wind energy potential in China L. Deng et al. 10.1016/j.apenergy.2025.125729
- Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm D. van Binsbergen et al. 10.5194/wes-9-1507-2024
- Benchmarking Engineering Wake Models for Assessing Wind Farm Wakes Interaction R. Rodrigues & A. Moura 10.1088/1742-6596/3016/1/012045
- Simulations suggest offshore wind farms modify low-level jets D. Quint et al. 10.5194/wes-10-117-2025
- Study of aerodynamic performance and wake effects for offshore wind farm cluster J. Cao et al. 10.1016/j.oceaneng.2023.114639
- The Atmospheric Stability Dependence of Far Wakes on the Power Output of Downstream Wind Farms R. Foreman et al. 10.3390/en17020488
- Mapping global offshore wind wake losses, layout optimisation potential, and climate change effects S. Warder & M. Piggott 10.1016/j.energy.2025.136573
- Alignment calibration and correction for offshore wind measurements using scanning lidars K. Gramitzky et al. 10.1088/1742-6596/2767/4/042014
- Characterization of local wind profiles: a random forest approach for enhanced wind profile extrapolation F. Rouholahnejad & J. Gottschall 10.5194/wes-10-143-2025
- Triple-lidar measurements of wind across a virtual rotor plane over a sea surface M. Nafisifard et al. 10.1088/1742-6596/2626/1/012022
- Offshore wakes measured by an adaptive dual-Doppler scanning lidar system T. Hildebrand et al. 10.1088/1742-6596/3025/1/012005
- Cross‐Border Cooperation to Mitigate Wake Losses in Offshore Wind Energy: A 2050 Case Study for the North Sea F. Fliegner et al. 10.1155/er/2518424
Latest update: 28 Jun 2025
Short summary
Scanning lidar measurements combined with meteorological sensors and mesoscale simulations reveal the strong directional and stability dependence of the wake strength in the direct vicinity of wind farm clusters.
Scanning lidar measurements combined with meteorological sensors and mesoscale simulations...
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