Articles | Volume 7, issue 6
https://doi.org/10.5194/wes-7-2469-2022
© 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-7-2469-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Dec 2022
Research article |
| 15 Dec 2022
| 15 Dec 2022
Comparison of large eddy simulations against measurements from the Lillgrund offshore wind farm
Mechanical Engineering, KU Leuven, Celestijnenlaan 300, 3001 Leuven, Belgium
Elliot Simon
DTU Wind and Energy Systems, Technical University of Denmark, Frederiksborgvej 399,
4000 Roskilde, Denmark
Athanasios Vitsas
Mechanical Engineering, KU Leuven, Celestijnenlaan 300, 3001 Leuven, Belgium
Bart Blockmans
Mechanical Engineering, KU Leuven, Celestijnenlaan 300, 3001 Leuven, Belgium
Gunner C. Larsen
DTU Wind and Energy Systems, Technical University of Denmark, Frederiksborgvej 399,
4000 Roskilde, Denmark
Johan Meyers
Mechanical Engineering, KU Leuven, Celestijnenlaan 300, 3001 Leuven, Belgium
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Cited
14 citations as recorded by crossref.
- Aeroelastic simulations of the DTU 10 MW turbine using tight coupling integration techniques K. Ntrelia et al. 10.1088/1742-6596/2767/2/022051
- Wake Effect Quantification using SCADA Data and LES Modelling of an Operational Offshore Wind Farm W. Chanprasert et al. 10.1088/1742-6596/2767/9/092012
- Assessing the Internal Variability of Large-Eddy Simulations for Microscale Pollutant Dispersion Prediction in an Idealized Urban Environment E. Lumet et al. 10.1007/s10546-023-00853-7
- Flexible multi-fidelity framework for load estimation of wind farms through graph neural networks and transfer learning G. Duthé et al. 10.1017/dce.2024.35
- How Fast is Fast Enough? Industry Perspectives on the Use of Large-eddy Simulation in Wind Energy H. Asmuth et al. 10.1088/1742-6596/2505/1/012001
- Large-eddy simulation of aerosol concentrations in a realistic urban environment: Model validation and transport mechanism Y. Du et al. 10.1016/j.envpol.2024.124475
- 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
- Wind turbine power curve modelling under wake conditions using measurements from a spinner-mounted lidar A. Sebastiani et al. 10.1016/j.apenergy.2024.122985
- Extending the dynamic wake meandering model in HAWC2Farm: a comparison with field measurements at the Lillgrund wind farm J. Liew et al. 10.5194/wes-8-1387-2023
- A data-driven reduced-order model for rotor optimization N. Peters et al. 10.5194/wes-8-1201-2023
- Sensitivity of Lillgrund Wind Farm Power Performance to Turbine Controller N. Troldborg & S. Andersen 10.1088/1742-6596/2505/1/012025
- Using observational mean‐flow data to drive large‐eddy simulations of a diurnal cycle at the SWiFT site D. Allaerts et al. 10.1002/we.2811
- An aeroelastic coupling of an actuator sector model with OpenFAST in atmospheric flows M. Mohammadi et al. 10.1088/1742-6596/2767/2/022037
- Comparison of large eddy simulations against measurements from the Lillgrund offshore wind farm I. Sood et al. 10.5194/wes-7-2469-2022
13 citations as recorded by crossref.
- Aeroelastic simulations of the DTU 10 MW turbine using tight coupling integration techniques K. Ntrelia et al. 10.1088/1742-6596/2767/2/022051
- Wake Effect Quantification using SCADA Data and LES Modelling of an Operational Offshore Wind Farm W. Chanprasert et al. 10.1088/1742-6596/2767/9/092012
- Assessing the Internal Variability of Large-Eddy Simulations for Microscale Pollutant Dispersion Prediction in an Idealized Urban Environment E. Lumet et al. 10.1007/s10546-023-00853-7
- Flexible multi-fidelity framework for load estimation of wind farms through graph neural networks and transfer learning G. Duthé et al. 10.1017/dce.2024.35
- How Fast is Fast Enough? Industry Perspectives on the Use of Large-eddy Simulation in Wind Energy H. Asmuth et al. 10.1088/1742-6596/2505/1/012001
- Large-eddy simulation of aerosol concentrations in a realistic urban environment: Model validation and transport mechanism Y. Du et al. 10.1016/j.envpol.2024.124475
- 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
- Wind turbine power curve modelling under wake conditions using measurements from a spinner-mounted lidar A. Sebastiani et al. 10.1016/j.apenergy.2024.122985
- Extending the dynamic wake meandering model in HAWC2Farm: a comparison with field measurements at the Lillgrund wind farm J. Liew et al. 10.5194/wes-8-1387-2023
- A data-driven reduced-order model for rotor optimization N. Peters et al. 10.5194/wes-8-1201-2023
- Sensitivity of Lillgrund Wind Farm Power Performance to Turbine Controller N. Troldborg & S. Andersen 10.1088/1742-6596/2505/1/012025
- Using observational mean‐flow data to drive large‐eddy simulations of a diurnal cycle at the SWiFT site D. Allaerts et al. 10.1002/we.2811
- An aeroelastic coupling of an actuator sector model with OpenFAST in atmospheric flows M. Mohammadi et al. 10.1088/1742-6596/2767/2/022037
1 citations as recorded by crossref.
Latest update: 30 Dec 2024
Short summary
In this work, we conduct a validation study to compare a numerical solver against measurements obtained from the offshore Lillgrund wind farm. By reusing a previously developed inflow turbulent dataset, the atmospheric conditions at the wind farm were recreated, and the general performance trends of the turbines were captured well. The work increases the reliability of numerical wind farm solvers while highlighting the challenges of accurately representing large wind farms using such solvers.
In this work, we conduct a validation study to compare a numerical solver against measurements...
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