46 citations as recorded by crossref.

1. Sensitivity and Uncertainty of the FLORIS Model Applied on the Lillgrund Wind Farm M. van Beek et al. 10.3390/en14051293
2. How realistic are the wakes of scaled wind turbine models? C. Wang et al. 10.5194/wes-6-961-2021
3. Real-time optimization of wind farms using modifier adaptation and machine learning L. Andersson & L. Imsland 10.5194/wes-5-885-2020
4. Blind test comparison on the wake behind a yawed wind turbine F. Mühle et al. 10.5194/wes-3-883-2018
5. Optimal yaw strategy for optimized power and load in various wake situations A. Urbán et al. 10.1088/1742-6596/1102/1/012019
6. Design and analysis of a wake steering controller with wind direction variability E. Simley et al. 10.5194/wes-5-451-2020
7. Influence of Wake Model Superposition and Secondary Steering on Model-Based Wake Steering Control with SCADA Data Assimilation M. Howland & J. Dabiri 10.3390/en14010052
8. Power increases using wind direction spatial filtering for wind farm control: Evaluation using FLORIS, modified for dynamic settings M. Sinner et al. 10.1063/5.0039899
9. Exploring the complexities associated with full-scale wind plant wake mitigation control experiments J. Duncan Jr. et al. 10.5194/wes-5-469-2020
10. Optimizing wind farm control through wake steering using surrogate models based on high-fidelity simulations P. Hulsman et al. 10.5194/wes-5-309-2020
11. Parametric dependencies of the yawed wind‐turbine wake development E. Kleusberg et al. 10.1002/we.2395
12. Wind tunnel experiments on wind turbine wakes in yaw: effects of inflow turbulence and shear J. Bartl et al. 10.5194/wes-3-329-2018
13. 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
14. Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
15. The curled wake model: a three-dimensional and extremely fast steady-state wake solver for wind plant flows L. Martínez-Tossas et al. 10.5194/wes-6-555-2021
16. Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
17. A new method for simulating multiple wind turbine wakes under yawed conditions D. Wei et al. 10.1016/j.oceaneng.2021.109832
18. Control-oriented model for secondary effects of wake steering J. King et al. 10.5194/wes-6-701-2021
19. Influence of atmospheric stability on wind farm performance in complex terrain W. Radünz et al. 10.1016/j.apenergy.2020.116149
20. Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
21. Development of a curled wake of a yawed wind turbine under turbulent and sheared inflow P. Hulsman et al. 10.5194/wes-7-237-2022
22. An adaptation of the super-Gaussian wake model for yawed wind turbines F. Blondel et al. 10.1088/1742-6596/1618/6/062031
23. The aerodynamics of the curled wake: a simplified model in view of flow control L. Martínez-Tossas et al. 10.5194/wes-4-127-2019
24. Near-wake structure of full-scale vertical-axis wind turbines N. Wei et al. 10.1017/jfm.2020.578
25. Machine learning enables national assessment of wind plant controls with implications for land use D. Harrison‐Atlas et al. 10.1002/we.2689
26. Results from a wake-steering experiment at a commercial wind plant: investigating the wind speed dependence of wake-steering performance E. Simley et al. 10.5194/wes-6-1427-2021
27. Influence of atmospheric conditions on the power production of utility-scale wind turbines in yaw misalignment M. Howland et al. 10.1063/5.0023746
28. Grand challenges in the science of wind energy P. Veers et al. 10.1126/science.aau2027
29. A low-fidelity dynamic wind farm model for simulating time-varying wind conditions and floating platform motion A. Kheirabadi & R. Nagamune 10.1016/j.oceaneng.2021.109313
30. Power Maximization and Fatigue-Load Mitigation in a Wind-turbine Array by Active Yaw Control: an LES Study M. Lin & F. Porté-Agel 10.1088/1742-6596/1618/4/042036
31. Analytical model for the power–yaw sensitivity of wind turbines operating in full wake J. Liew et al. 10.5194/wes-5-427-2020
32. Wind farm power optimization through wake steering M. Howland et al. 10.1073/pnas.1903680116
33. Analysis of control-oriented wake modeling tools using lidar field results J. Annoni et al. 10.5194/wes-3-819-2018
34. Engineering models for turbine wake velocity deficit and wake deflection. A new proposed approach for onshore and offshore applications R. Ruisi & E. Bossanyi 10.1088/1742-6596/1222/1/012004
35. Improving wind farm flow models by learning from operational data J. Schreiber et al. 10.5194/wes-5-647-2020
36. Blade planform design optimization to enhance turbine wake control J. Allen et al. 10.1002/we.2699
37. Toward flow control: An assessment of the curled wake model in the FLORIS framework C. Bay et al. 10.1088/1742-6596/1618/2/022033
38. Real-time relocation of floating offshore wind turbine platforms for wind farm efficiency maximization: An assessment of feasibility and steady-state potential A. Kheirabadi & R. Nagamune 10.1016/j.oceaneng.2020.107445
39. Field Validation of Wake Steering Control with Wind Direction Variability E. Simley et al. 10.1088/1742-6596/1452/1/012012
40. Wind farm power optimization via yaw angle control: A wind tunnel study M. Bastankhah & F. Porté-Agel 10.1063/1.5077038
41. Optimal closed-loop wake steering – Part 1: Conventionally neutral atmospheric boundary layer conditions M. Howland et al. 10.5194/wes-5-1315-2020
42. Wind-Turbine and Wind-Farm Flows: A Review F. Porté-Agel et al. 10.1007/s10546-019-00473-0
43. Wake steering of multirotor wind turbines G. Speakman et al. 10.1002/we.2633
44. A quantitative review of wind farm control with the objective of wind farm power maximization A. Kheirabadi & R. Nagamune 10.1016/j.jweia.2019.06.015
45. A new method to characterize the curled wake shape under yaw misalignment B. Sengers et al. 10.1088/1742-6596/1618/6/062050
46. Modelling Yawed Wind Turbine Wakes: Extension of a Gaussian-Based Wake Model D. Wei et al. 10.3390/en14154494