Articles | Volume 5, issue 3
Wind Energ. Sci., 5, 1225–1236, 2020
https://doi.org/10.5194/wes-5-1225-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Wind Energ. Sci., 5, 1225–1236, 2020
https://doi.org/10.5194/wes-5-1225-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
28 Sep 2020
Research article
| 28 Sep 2020
An alternative form of the super-Gaussian wind turbine wake model
Frédéric Blondel and Marie Cathelain
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Cited
14 citations as recorded by crossref.
- An adaptation of the super-Gaussian wake model for yawed wind turbines F. Blondel et al. 10.1088/1742-6596/1618/6/062031
- Analytical solution for the cumulative wake of wind turbines in wind farms M. Bastankhah et al. 10.1017/jfm.2020.1037
- Theoretical modelling of the three-dimensional wake of vertical axis turbines P. Ouro & M. Lazennec 10.1017/flo.2021.4
- Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows S. Letizia & G. Iungo 10.1063/5.0076739
- The area localized coupled model for analytical mean flow prediction in arbitrary wind farm geometries G. Starke et al. 10.1063/5.0042573
- The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study P. Yang & H. Najafi 10.1115/1.4052775
- Comparison of modular analytical wake models to the Lillgrund wind plant N. Hamilton et al. 10.1063/5.0018695
- Time-Averaged Wind Turbine Wake Flow Field Prediction Using Autoencoder Convolutional Neural Networks Z. Zhang et al. 10.3390/en15010041
- A new wake‐merging method for wind‐farm power prediction in the presence of heterogeneous background velocity fields L. Lanzilao & J. Meyers 10.1002/we.2669
- LiDAR and SCADA data processing for interacting wind turbine wakes with comparison to analytical wake models A. Hegazy et al. 10.1016/j.renene.2021.09.019
- A vortex sheet based analytical model of the curled wake behind yawed wind turbines M. Bastankhah et al. 10.1017/jfm.2021.1010
- Validation of Meso-Wake Models for Array Efficiency Prediction Using Operational Data from Five Offshore Wind Farms J. Rodrigo et al. 10.1088/1742-6596/1618/6/062044
- Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2 P. Fleming et al. 10.5194/wes-5-945-2020
- Wake Statistics of Different-Scale Wind Turbines under Turbulent Boundary Layer Inflow X. Yang et al. 10.3390/en13113004
11 citations as recorded by crossref.
- An adaptation of the super-Gaussian wake model for yawed wind turbines F. Blondel et al. 10.1088/1742-6596/1618/6/062031
- Analytical solution for the cumulative wake of wind turbines in wind farms M. Bastankhah et al. 10.1017/jfm.2020.1037
- Theoretical modelling of the three-dimensional wake of vertical axis turbines P. Ouro & M. Lazennec 10.1017/flo.2021.4
- Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows S. Letizia & G. Iungo 10.1063/5.0076739
- The area localized coupled model for analytical mean flow prediction in arbitrary wind farm geometries G. Starke et al. 10.1063/5.0042573
- The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study P. Yang & H. Najafi 10.1115/1.4052775
- Comparison of modular analytical wake models to the Lillgrund wind plant N. Hamilton et al. 10.1063/5.0018695
- Time-Averaged Wind Turbine Wake Flow Field Prediction Using Autoencoder Convolutional Neural Networks Z. Zhang et al. 10.3390/en15010041
- A new wake‐merging method for wind‐farm power prediction in the presence of heterogeneous background velocity fields L. Lanzilao & J. Meyers 10.1002/we.2669
- LiDAR and SCADA data processing for interacting wind turbine wakes with comparison to analytical wake models A. Hegazy et al. 10.1016/j.renene.2021.09.019
- A vortex sheet based analytical model of the curled wake behind yawed wind turbines M. Bastankhah et al. 10.1017/jfm.2021.1010
3 citations as recorded by crossref.
- Validation of Meso-Wake Models for Array Efficiency Prediction Using Operational Data from Five Offshore Wind Farms J. Rodrigo et al. 10.1088/1742-6596/1618/6/062044
- Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2 P. Fleming et al. 10.5194/wes-5-945-2020
- Wake Statistics of Different-Scale Wind Turbines under Turbulent Boundary Layer Inflow X. Yang et al. 10.3390/en13113004
Latest update: 25 Jun 2022
Short summary
Analytical wind turbine wake models are of high interest for wind farm designers: they provide an estimation of wake losses for a given layout at a low computational cost. Consequently they are heavily used for wind farm design and power production evaluation. While most analytical models focus on far-wake characteristics, we propose an approach that is able to represent both near- and far-wake velocity deficit, enabling the simulation of closely packed wind farms.
Analytical wind turbine wake models are of high interest for wind farm designers: they provide...
