Articles | Volume 6, issue 2
https://doi.org/10.5194/wes-6-555-2021
© Author(s) 2021. 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-6-555-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Apr 2021
Research article |
| 22 Apr 2021
| 22 Apr 2021
The curled wake model: a three-dimensional and extremely fast steady-state wake solver for wind plant flows
Luis A. Martínez-Tossas
CORRESPONDING AUTHOR
National Renewable Energy Laboratory, Golden, CO, USA
Jennifer King
National Renewable Energy Laboratory, Golden, CO, USA
Eliot Quon
National Renewable Energy Laboratory, Golden, CO, USA
Christopher J. Bay
National Renewable Energy Laboratory, Golden, CO, USA
Rafael Mudafort
National Renewable Energy Laboratory, Golden, CO, USA
Nicholas Hamilton
National Renewable Energy Laboratory, Golden, CO, USA
Michael F. Howland
Graduate Aerospace Laboratories (GALCIT), California Institute of Technology, Pasadena, CA 91125, USA
Paul A. Fleming
National Renewable Energy Laboratory, Golden, CO, USA
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Cited
38 citations as recorded by crossref.
- Enabling control co-design of the next generation of wind power plants A. Stanley et al.
- Toward ultra-efficient high-fidelity predictions of wind turbine wakes: Augmenting the accuracy of engineering models with machine learning C. Santoni et al.
- Unified momentum model for rotor aerodynamics across operating regimes J. Liew et al.
- A time‐varying formulation of the curled wake model within the FAST.Farm framework E. Branlard et al.
- Wind plant wake losses: Disconnect between turbine actuation and control of plant wakes with engineering wake models R. Scott et al.
- Modular deep learning approach for wind farm power forecasting and wake loss prediction S. Ally et al.
- Adaptive Multitask Neural Network for High-Fidelity Wake Flow Modeling of Wind Farms D. Zhang et al.
- Momentum deficit and wake-added turbulence kinetic energy budgets in the stratified atmospheric boundary layer K. Klemmer & M. Howland
- Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows S. Letizia & G. Iungo
- Machine learning enables national assessment of wind plant controls with implications for land use D. Harrison‐Atlas et al.
- Evolution of eddy viscosity in the wake of a wind turbine R. Scott et al.
- A three-dimensional, analytical wind turbine wake model: Flow acceleration, empirical correlations, and continuity Z. Sadek et al.
- Can wind turbine farms increase settlement of particulate matters during dust events? M. Mataji et al.
- Investigation of far-wake models coupled with yaw-induction control for power optimization K. Heck et al.
- Investigating Turbulent Dynamics in the Nocturnal Boundary Layer: A Large Eddy Simulation Study of the South Fork Wind Farm A. Ayouche et al.
- Wake turbulence modeling in stratified atmospheric flows using a novel k−ℓ model K. Klemmer & M. Howland
- Dynamic wind farm wake modeling based on a Bilateral Convolutional Neural Network and high-fidelity LES data R. Li et al.
- Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models S. Anagnostopoulos et al.
- Surrogate-assisted power optimization framework for heterogeneous Wind farms under turbine upgrade scenarios C. Zhao et al.
- Structural motion control of waked floating offshore wind farms H. del Pozo Gonzalez et al.
- Modelling the induction, thrust and power of a yaw-misaligned actuator disk K. Heck et al.
- The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study P. Yang & H. Najafi
- Multicluster Distributed Optimization Strategy for Turbine Wake Environment Z. Yu et al.
- Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions M. Howland et al.
- On the power and control of a misaligned rotor – beyond the cosine law S. Tamaro et al.
- Data-driven wake model parameter estimation to analyze effects of wake superposition M. LoCascio et al.
- A vortex sheet based analytical model of the curled wake behind yawed wind turbines M. Bastankhah et al.
- A Tutorial on the Control of Floating Offshore Wind Turbines: Stability Challenges and Opportunities for Power Capture D. Stockhouse et al.
- Faster wind farm AEP calculations with CFD using a generalized wind turbine model M. van der Laan et al.
- Load assessment of a wind farm considering negative and positive yaw misalignment for wake steering R. Thedin et al.
- Collective wind farm operation based on a predictive model increases utility-scale energy production M. Howland et al.
- Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations T. Chatterjee et al.
- Modification of wind turbine wakes by large-scale, convective atmospheric boundary layer structures L. Cheung et al.
- FlowFormer: Toward a foundation model for full-flow-field wind farm wake modeling R. Li et al.
- FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models M. LoCascio et al.
- Model‐free closed‐loop wind farm control using reinforcement learning with recursive least squares J. Liew et al.
- A data-driven machine learning approach for yaw control applications of wind farms C. Santoni et al.
- A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines E. Mahmoodi et al.
38 citations as recorded by crossref.
- Enabling control co-design of the next generation of wind power plants A. Stanley et al.
- Toward ultra-efficient high-fidelity predictions of wind turbine wakes: Augmenting the accuracy of engineering models with machine learning C. Santoni et al.
- Unified momentum model for rotor aerodynamics across operating regimes J. Liew et al.
- A time‐varying formulation of the curled wake model within the FAST.Farm framework E. Branlard et al.
- Wind plant wake losses: Disconnect between turbine actuation and control of plant wakes with engineering wake models R. Scott et al.
- Modular deep learning approach for wind farm power forecasting and wake loss prediction S. Ally et al.
- Adaptive Multitask Neural Network for High-Fidelity Wake Flow Modeling of Wind Farms D. Zhang et al.
- Momentum deficit and wake-added turbulence kinetic energy budgets in the stratified atmospheric boundary layer K. Klemmer & M. Howland
- Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows S. Letizia & G. Iungo
- Machine learning enables national assessment of wind plant controls with implications for land use D. Harrison‐Atlas et al.
- Evolution of eddy viscosity in the wake of a wind turbine R. Scott et al.
- A three-dimensional, analytical wind turbine wake model: Flow acceleration, empirical correlations, and continuity Z. Sadek et al.
- Can wind turbine farms increase settlement of particulate matters during dust events? M. Mataji et al.
- Investigation of far-wake models coupled with yaw-induction control for power optimization K. Heck et al.
- Investigating Turbulent Dynamics in the Nocturnal Boundary Layer: A Large Eddy Simulation Study of the South Fork Wind Farm A. Ayouche et al.
- Wake turbulence modeling in stratified atmospheric flows using a novel k−ℓ model K. Klemmer & M. Howland
- Dynamic wind farm wake modeling based on a Bilateral Convolutional Neural Network and high-fidelity LES data R. Li et al.
- Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models S. Anagnostopoulos et al.
- Surrogate-assisted power optimization framework for heterogeneous Wind farms under turbine upgrade scenarios C. Zhao et al.
- Structural motion control of waked floating offshore wind farms H. del Pozo Gonzalez et al.
- Modelling the induction, thrust and power of a yaw-misaligned actuator disk K. Heck et al.
- The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study P. Yang & H. Najafi
- Multicluster Distributed Optimization Strategy for Turbine Wake Environment Z. Yu et al.
- Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions M. Howland et al.
- On the power and control of a misaligned rotor – beyond the cosine law S. Tamaro et al.
- Data-driven wake model parameter estimation to analyze effects of wake superposition M. LoCascio et al.
- A vortex sheet based analytical model of the curled wake behind yawed wind turbines M. Bastankhah et al.
- A Tutorial on the Control of Floating Offshore Wind Turbines: Stability Challenges and Opportunities for Power Capture D. Stockhouse et al.
- Faster wind farm AEP calculations with CFD using a generalized wind turbine model M. van der Laan et al.
- Load assessment of a wind farm considering negative and positive yaw misalignment for wake steering R. Thedin et al.
- Collective wind farm operation based on a predictive model increases utility-scale energy production M. Howland et al.
- Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations T. Chatterjee et al.
- Modification of wind turbine wakes by large-scale, convective atmospheric boundary layer structures L. Cheung et al.
- FlowFormer: Toward a foundation model for full-flow-field wind farm wake modeling R. Li et al.
- FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models M. LoCascio et al.
- Model‐free closed‐loop wind farm control using reinforcement learning with recursive least squares J. Liew et al.
- A data-driven machine learning approach for yaw control applications of wind farms C. Santoni et al.
- A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines E. Mahmoodi et al.
Saved (final revised paper)
Latest update: 28 Apr 2026
Short summary
In this paper a three-dimensional steady-state solver for flow through a wind farm is developed and validated. The computational cost of the solver is on the order of seconds for large wind farms. The model is validated using high-fidelity simulations and SCADA.
In this paper a three-dimensional steady-state solver for flow through a wind farm is developed...
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