Articles | Volume 5, issue 1
https://doi.org/10.5194/wes-5-237-2020
© Author(s) 2020. 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-5-237-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Brief communication
| 
14 Feb 2020
Brief communication |
| 14 Feb 2020
| 14 Feb 2020
Brief communication: A double-Gaussian wake model
Johannes Schreiber
Wind Energy Institute, Technische Universität München, 85748
Garching bei München, Germany
Amr Balbaa
Wind Energy Institute, Technische Universität München, 85748
Garching bei München, Germany
Wind Energy Institute, Technische Universität München, 85748
Garching bei München, Germany
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Cited
50 citations as recorded by crossref.
- The impact of the atmospheric boundary layer on the asymmetric wake profile: A bivariate analysis M. Barasa et al. https://doi.org/10.1016/j.seta.2022.102563
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- Anisotropic double‐Gaussian analytical wake model for an isolated horizontal‐axis wind turbine Q. Soesanto et al. https://doi.org/10.1002/ese3.1120
- A vortex sheet based analytical model of the curled wake behind yawed wind turbines M. Bastankhah et al. https://doi.org/10.1017/jfm.2021.1010
- Development and validation of a three-dimensional wind-turbine wake model based on high-order Gaussian function H. Wei et al. https://doi.org/10.1016/j.oceaneng.2024.119133
- Applicability of Wake Models to Predictions of Turbine-Induced Velocity Deficit and Wind Farm Power Generation D. Zhang et al. https://doi.org/10.3390/en15197431
- A new wake‐merging method for wind‐farm power prediction in the presence of heterogeneous background velocity fields L. Lanzilao & J. Meyers https://doi.org/10.1002/we.2669
- Modelling turbulence in axisymmetric wakes: an application to wind turbine wakes M. Bastankhah et al. https://doi.org/10.1017/jfm.2024.664
- A pressure-corrected double-Gaussian analytical wake model for wind turbines B. Li et al. https://doi.org/10.1063/5.0288010
- A novel three-dimensional yaw wake analytical model and experimental validation using particle image velocimetry P. Zhou et al. https://doi.org/10.1016/j.energy.2025.139885
- Large-eddy simulation and analytical modeling study of the wake of a wind turbine behind an abrupt rough-to-smooth surface roughness transition N. Kethavath et al. https://doi.org/10.1063/5.0129022
- A double-Gaussian wake model considering yaw misalignment Q. Soesanto et al. https://doi.org/10.61435/ijred.2025.60690
- An efficient turbulent wake generator for wind turbine load response including steered wakes D. Major et al. https://doi.org/10.1088/1742-6596/3224/3/032101
- Curled-Skewed Wakes behind Yawed Wind Turbines Subject to Veered Inflow M. Mohammadi et al. https://doi.org/10.3390/en15239135
- Rapid Estimation Model for Wake Disturbances in Offshore Floating Wind Turbines L. Zhao et al. https://doi.org/10.3390/jmse12040647
- Symbolic regression-enhanced dynamic wake meandering: fast and physically consistent wind turbine wake modelling D. Wang et al. https://doi.org/10.1017/jfm.2025.10947
- Evaluation of Gaussian wake models under different atmospheric stability conditions: Comparison with large eddy simulation results M. Krutova et al. https://doi.org/10.1088/1742-6596/1669/1/012016
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- An alternative form of the super-Gaussian wind turbine wake model F. Blondel & M. Cathelain https://doi.org/10.5194/wes-5-1225-2020
- A Meandering-Capturing Wake Model Coupled to Rotor-Based Flow-Sensing for Operational Wind Farm Flow Prediction M. Lejeune et al. https://doi.org/10.3389/fenrg.2022.884068
- Further improvements to the double-Gaussian wake model C. Zengler et al. https://doi.org/10.1088/1742-6596/2767/9/092066
- The Impact of the Atmospheric Boundary Layer on the Radial Wake Profile: A Bivariate Analysis M. Barasa et al. https://doi.org/10.2139/ssrn.4021939
- A linear wake expansion function for the double‐Gaussian analytical wake model Q. Soesanto et al. https://doi.org/10.1002/ese3.1427
- Leading effect for wind turbine wake models I. Neunaber et al. https://doi.org/10.1016/j.renene.2023.119935
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- A new 3D asymmetric double-Gaussian wake analytical model for horizontal-axis wind turbines Y. Liu et al. https://doi.org/10.1016/j.jweia.2024.105685
- A novel engineering wake model for helix-actuated wind turbine wakes T. Dammann et al. https://doi.org/10.1016/j.apenergy.2026.127808
- Discovering an interpretable mathematical expression for a full wind-turbine wake with artificial intelligence enhanced symbolic regression D. Wang et al. https://doi.org/10.1063/5.0221611
- Extension and validation of an operational dynamic wake model to yawed configurations M. Lejeune et al. https://doi.org/10.1088/1742-6596/2265/2/022018
- Analytical Descriptions of Swirling Wake Profiles W. Schutz & J. Naughton https://doi.org/10.1088/1742-6596/2505/1/012021
- The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study P. Yang & H. Najafi https://doi.org/10.1115/1.4052775
- Advances and Challenges in Analytical Wake Modelling for Offshore Wind Farm Layout Optimization H. Liu et al. https://doi.org/10.3390/en19040982
- On the impact of aeroelastic bend-twist coupling on the flow structures in the near and far wake of a modern, highly flexible wind turbine rotor G. Cipriani et al. https://doi.org/10.1088/1742-6596/3224/4/042053
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- Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows S. Letizia & G. Iungo https://doi.org/10.1063/5.0076739
- Bayesian uncertainty quantification framework for wake model calibration and validation with historical wind farm power data F. Aerts et al. https://doi.org/10.1002/we.2841
- Wind turbine wakes modeling and applications: Past, present, and future L. Wang et al. https://doi.org/10.1016/j.oceaneng.2024.118508
- A data-driven double-Gaussian wake model reflecting the wake evolution process M. Wang et al. https://doi.org/10.1016/j.renene.2025.124804
- A new anisotropic three-dimensional Gaussian wake model considering swirling effects for horizontal-axis wind turbine L. Zhang et al. https://doi.org/10.1016/j.energy.2026.140395
- A novel three-dimensional dynamic full-wake model for offshore floating wind turbines Q. Wang et al. https://doi.org/10.1080/15435075.2026.2673151
- A non-symmetric Gaussian wake model for lateral wake-to-wake interactions A. Vad et al. https://doi.org/10.1088/1742-6596/2505/1/012046
- A novel double-Gaussian full wake model for wind turbines considering dependence on thrust coefficient and ambient turbulence intensity G. Qian & T. Ishihara https://doi.org/10.1016/j.apenergy.2025.125859
- Polarization Characteristics of Electromagnetic Wave Sensing in Confined Space Based on Hybrid Algorithm H. Zhang & P. Singh https://doi.org/10.1155/2022/1724428
50 citations as recorded by crossref.
- The impact of the atmospheric boundary layer on the asymmetric wake profile: A bivariate analysis M. Barasa et al. https://doi.org/10.1016/j.seta.2022.102563
- Advancement of an analytical double-Gaussian full wind turbine wake model A. Keane https://doi.org/10.1016/j.renene.2021.02.078
- Design, steady performance and wake characterization of a scaled wind turbine with pitch, torque and yaw actuation E. Nanos et al. https://doi.org/10.5194/wes-7-1263-2022
- An advanced three-dimensional analytical model for wind turbine near and far wake predictions L. Tian et al. https://doi.org/10.1016/j.renene.2024.120035
- Analytical solution for the cumulative wake of wind turbines in wind farms M. Bastankhah et al. https://doi.org/10.1017/jfm.2020.1037
- A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. https://doi.org/10.1016/j.rser.2024.114279
- A physics-based model for wind turbine wake expansion in the atmospheric boundary layer D. Vahidi & F. Porté-Agel https://doi.org/10.1017/jfm.2022.443
- A fast-running physics-based wake model for a semi-infinite wind farm M. Bastankhah et al. https://doi.org/10.1017/jfm.2024.282
- Anisotropic double‐Gaussian analytical wake model for an isolated horizontal‐axis wind turbine Q. Soesanto et al. https://doi.org/10.1002/ese3.1120
- A vortex sheet based analytical model of the curled wake behind yawed wind turbines M. Bastankhah et al. https://doi.org/10.1017/jfm.2021.1010
- Development and validation of a three-dimensional wind-turbine wake model based on high-order Gaussian function H. Wei et al. https://doi.org/10.1016/j.oceaneng.2024.119133
- Applicability of Wake Models to Predictions of Turbine-Induced Velocity Deficit and Wind Farm Power Generation D. Zhang et al. https://doi.org/10.3390/en15197431
- A new wake‐merging method for wind‐farm power prediction in the presence of heterogeneous background velocity fields L. Lanzilao & J. Meyers https://doi.org/10.1002/we.2669
- Modelling turbulence in axisymmetric wakes: an application to wind turbine wakes M. Bastankhah et al. https://doi.org/10.1017/jfm.2024.664
- A pressure-corrected double-Gaussian analytical wake model for wind turbines B. Li et al. https://doi.org/10.1063/5.0288010
- A novel three-dimensional yaw wake analytical model and experimental validation using particle image velocimetry P. Zhou et al. https://doi.org/10.1016/j.energy.2025.139885
- Large-eddy simulation and analytical modeling study of the wake of a wind turbine behind an abrupt rough-to-smooth surface roughness transition N. Kethavath et al. https://doi.org/10.1063/5.0129022
- A double-Gaussian wake model considering yaw misalignment Q. Soesanto et al. https://doi.org/10.61435/ijred.2025.60690
- An efficient turbulent wake generator for wind turbine load response including steered wakes D. Major et al. https://doi.org/10.1088/1742-6596/3224/3/032101
- Curled-Skewed Wakes behind Yawed Wind Turbines Subject to Veered Inflow M. Mohammadi et al. https://doi.org/10.3390/en15239135
- Rapid Estimation Model for Wake Disturbances in Offshore Floating Wind Turbines L. Zhao et al. https://doi.org/10.3390/jmse12040647
- Symbolic regression-enhanced dynamic wake meandering: fast and physically consistent wind turbine wake modelling D. Wang et al. https://doi.org/10.1017/jfm.2025.10947
- Evaluation of Gaussian wake models under different atmospheric stability conditions: Comparison with large eddy simulation results M. Krutova et al. https://doi.org/10.1088/1742-6596/1669/1/012016
- A diffusion-based wind turbine wake model K. Ali et al. https://doi.org/10.1017/jfm.2024.1077
- An alternative form of the super-Gaussian wind turbine wake model F. Blondel & M. Cathelain https://doi.org/10.5194/wes-5-1225-2020
- A Meandering-Capturing Wake Model Coupled to Rotor-Based Flow-Sensing for Operational Wind Farm Flow Prediction M. Lejeune et al. https://doi.org/10.3389/fenrg.2022.884068
- Further improvements to the double-Gaussian wake model C. Zengler et al. https://doi.org/10.1088/1742-6596/2767/9/092066
- The Impact of the Atmospheric Boundary Layer on the Radial Wake Profile: A Bivariate Analysis M. Barasa et al. https://doi.org/10.2139/ssrn.4021939
- A linear wake expansion function for the double‐Gaussian analytical wake model Q. Soesanto et al. https://doi.org/10.1002/ese3.1427
- Leading effect for wind turbine wake models I. Neunaber et al. https://doi.org/10.1016/j.renene.2023.119935
- Two Three-Dimensional Super-Gaussian Wake Models for Wind Turbine Wakes Z. Luo et al. https://doi.org/10.1061/JLEED9.EYENG-5350
- A new 3D asymmetric double-Gaussian wake analytical model for horizontal-axis wind turbines Y. Liu et al. https://doi.org/10.1016/j.jweia.2024.105685
- A novel engineering wake model for helix-actuated wind turbine wakes T. Dammann et al. https://doi.org/10.1016/j.apenergy.2026.127808
- Discovering an interpretable mathematical expression for a full wind-turbine wake with artificial intelligence enhanced symbolic regression D. Wang et al. https://doi.org/10.1063/5.0221611
- Extension and validation of an operational dynamic wake model to yawed configurations M. Lejeune et al. https://doi.org/10.1088/1742-6596/2265/2/022018
- Analytical Descriptions of Swirling Wake Profiles W. Schutz & J. Naughton https://doi.org/10.1088/1742-6596/2505/1/012021
- The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study P. Yang & H. Najafi https://doi.org/10.1115/1.4052775
- Advances and Challenges in Analytical Wake Modelling for Offshore Wind Farm Layout Optimization H. Liu et al. https://doi.org/10.3390/en19040982
- On the impact of aeroelastic bend-twist coupling on the flow structures in the near and far wake of a modern, highly flexible wind turbine rotor G. Cipriani et al. https://doi.org/10.1088/1742-6596/3224/4/042053
- Large-eddy simulation of an atmospheric bore and associated gravity wave effects on wind farm performance in the southern Great Plains A. Wise et al. https://doi.org/10.5194/wes-10-1007-2025
- A new analytical wind turbine wake model considering the effects of coriolis force and yawed conditions R. Snaiki & S. Makki https://doi.org/10.1016/j.jweia.2024.105767
- Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows S. Letizia & G. Iungo https://doi.org/10.1063/5.0076739
- Bayesian uncertainty quantification framework for wake model calibration and validation with historical wind farm power data F. Aerts et al. https://doi.org/10.1002/we.2841
- Wind turbine wakes modeling and applications: Past, present, and future L. Wang et al. https://doi.org/10.1016/j.oceaneng.2024.118508
- A data-driven double-Gaussian wake model reflecting the wake evolution process M. Wang et al. https://doi.org/10.1016/j.renene.2025.124804
- A new anisotropic three-dimensional Gaussian wake model considering swirling effects for horizontal-axis wind turbine L. Zhang et al. https://doi.org/10.1016/j.energy.2026.140395
- A novel three-dimensional dynamic full-wake model for offshore floating wind turbines Q. Wang et al. https://doi.org/10.1080/15435075.2026.2673151
- A non-symmetric Gaussian wake model for lateral wake-to-wake interactions A. Vad et al. https://doi.org/10.1088/1742-6596/2505/1/012046
- A novel double-Gaussian full wake model for wind turbines considering dependence on thrust coefficient and ambient turbulence intensity G. Qian & T. Ishihara https://doi.org/10.1016/j.apenergy.2025.125859
- Polarization Characteristics of Electromagnetic Wave Sensing in Confined Space Based on Hybrid Algorithm H. Zhang & P. Singh https://doi.org/10.1155/2022/1724428
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Short summary
An analytical wake model with a double-Gaussian velocity distribution is used to improve on a similar formulation by Keane et al (2016). The choice of a double-Gaussian shape function is motivated by the behavior of the near-wake region that is observed in numerical simulations and experimental measurements. The model is calibrated and validated using large eddy simulations replicating scaled wind turbine experiments, yielding improved results with respect to a classical single-Gaussian profile.
An analytical wake model with a double-Gaussian velocity distribution is used to improve on a...
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