80 citations as recorded by crossref.

1. Design and analysis of a wake model for spatially heterogeneous flow A. Farrell et al. 10.5194/wes-6-737-2021
2. Wind farm control ‐ Part I: A review on control system concepts and structures L. Andersson et al. 10.1049/rpg2.12160
3. Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control Y. Wang & Z. Liu 10.1016/j.energy.2025.136266
4. Wind energy-harvesting technologies and recent research progresses in wind farm control models B. Desalegn et al. 10.3389/fenrg.2023.1124203
5. Effectiveness of cooperative yaw control based on reinforcement learning for in-line multiple wind turbines L. Wang et al. 10.1016/j.conengprac.2024.106124
6. Vertical wake deflection for floating wind turbines by differential ballast control E. Nanos et al. 10.5194/wes-7-1641-2022
7. Active Wake Steering Control Data-Driven Design for a Wind Farm Benchmark S. Simani et al. 10.1016/j.ifacol.2023.10.1504
8. Loads assessment of a fixed‐bottom offshore wind farm with wake steering K. Shaler et al. 10.1002/we.2756
9. Artificial intelligence-aided wind plant optimization for nationwide evaluation of land use and economic benefits of wake steering D. Harrison-Atlas et al. 10.1038/s41560-024-01516-8
10. Identification of wind turbine clusters for effective real time yaw control optimization F. Bernardoni et al. 10.1063/5.0036640
11. Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model Z. Deng et al. 10.3390/en16093932
12. An open-source framework for the development, deployment and testing of wind farm control strategies C. Sucameli et al. 10.1088/1742-6596/2767/9/092043
13. Data–Driven Wake Steering Control for a Simulated Wind Farm Model S. Simani et al. 10.31875/2409-9694.2023.10.02
14. Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm D. van Binsbergen et al. 10.5194/wes-9-1507-2024
15. Wake steering of multirotor wind turbines G. Speakman et al. 10.1002/we.2633
16. A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. 10.1016/j.rser.2024.114279
17. Enabling control co-design of the next generation of wind power plants A. Stanley et al. 10.5194/wes-8-1341-2023
18. Wind plant power maximization via extremum seeking yaw control: A wind tunnel experiment D. Kumar et al. 10.1002/we.2799
19. The impact of coherent large-scale vortices generated by helix active wake control on the recovery process of wind turbine wakes J. Gutknecht et al. 10.1063/5.0278687
20. Maximization of the Power Production of an Offshore Wind Farm R. Balakrishnan & S. Hur 10.3390/app12084013
21. Design of the American Wake Experiment (AWAKEN) field campaign M. Debnath et al. 10.1088/1742-6596/2265/2/022058
22. Region-based convolutional neural network for wind turbine wake characterization from scanning lidars J. Aird et al. 10.1088/1742-6596/2265/3/032077
23. A machine learning-based fatigue loads and power prediction method for wind turbines under yaw control R. He et al. 10.1016/j.apenergy.2022.120013
24. Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
25. Investigating the impact of atmospheric conditions on wake-steering performance at a commercial wind plant E. Simley et al. 10.1088/1742-6596/2265/3/032097
26. Impact of the wake deficit model on wind farm yield: A study of yaw-based control optimization B. Rak & R. Santos Pereira 10.1016/j.jweia.2021.104827
27. Wake Recovery Enhancement with Helix Active Wake Control: Vortex Structures in a Porous Disk Wake Observed in PIV Experiments J. Gutknecht et al. 10.1088/1742-6596/3016/1/012030
28. Overview of preparation for the American WAKE ExperimeNt (AWAKEN) P. Moriarty et al. 10.1063/5.0141683
29. Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon 10.5194/wes-9-495-2024
30. Further calibration and validation of FLORIS with wind tunnel data F. Campagnolo et al. 10.1088/1742-6596/2265/2/022019
31. Lifetime fatigue response due to wake steering on a pair of utility-scale wind turbines S. Dana et al. 10.1088/1742-6596/2265/2/022106
32. Koopman Model Predictive Control for Wind Farm Yield Optimization with Combined Thrust and Yaw Control A. Dittmer et al. 10.1016/j.ifacol.2023.10.1037
33. Serial-Refine Method for Fast Wake-Steering Yaw Optimization P. Fleming et al. 10.1088/1742-6596/2265/3/032109
34. Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
35. Validation of an interpretable data-driven wake model using lidar measurements from a field wake steering experiment B. Sengers et al. 10.5194/wes-8-747-2023
36. Modular deep learning approach for wind farm power forecasting and wake loss prediction S. Ally et al. 10.5194/wes-10-779-2025
37. Three-dimensional yaw wake model development with validations from wind tunnel experiments R. He et al. 10.1016/j.energy.2023.128402
38. On the Load Impact of Dynamic Wind Farm Wake Mixing Strategies J. Frederik & J. van Wingerden 10.2139/ssrn.3910237
39. Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms B. Doekemeijer et al. 10.3390/en15061964
40. Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
41. Are steady-state wake models and lookup tables sufficient to design profitable wake steering strategies? A Large Eddy Simulation investigation M. Lejeune et al. 10.1088/1742-6596/2767/9/092075
42. Wind Tunnel Testing of Yaw by Individual Pitch Control Applied to Wake Steering F. Campagnolo et al. 10.3389/fenrg.2022.883889
43. 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
44. Field experiment for open-loop yaw-based wake steering at a commercial onshore wind farm in Italy B. Doekemeijer et al. 10.5194/wes-6-159-2021
45. Model predictive control of wakes for wind farm power tracking A. Sterle et al. 10.1088/1742-6596/2767/3/032005
46. A physically interpretable data-driven surrogate model for wake steering B. Sengers et al. 10.5194/wes-7-1455-2022
47. Modeling Annual Electricity Production and Levelized Cost of Energy from the US East Coast Offshore Wind Energy Lease Areas R. Barthelmie et al. 10.3390/en16124550
48. Effect of Atmospheric Stability on Meandering and Wake Characteristics in Wind Turbine Fluid Dynamics B. Løvøy Alvestad et al. 10.3390/app14178025
49. Quantification of wake shape modulation and deflection for tilt and yaw misaligned wind turbines J. Bossuyt et al. 10.1017/jfm.2021.237
50. Adjoint optimisation for wind farm flow control with a free-vortex wake model M. van den Broek et al. 10.1016/j.renene.2022.10.120
51. 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
52. Can wind turbine farms increase settlement of particulate matters during dust events? M. Mataji et al. 10.1063/5.0129481
53. The value of wake steering wind farm flow control in US energy markets E. Simley et al. 10.5194/wes-9-219-2024
54. Experimental investigation of wind turbine wake and load dynamics during yaw maneuvers S. Macrí et al. 10.5194/wes-6-585-2021
55. Wind Farm Loads under Wake Redirection Control S. Kanev et al. 10.3390/en13164088
56. Wake position tracking using dynamic wake meandering model and rotor loads L. Dong et al. 10.1063/5.0032917
57. How generalizable is a machine-learning approach for modeling hub-height turbulence intensity? N. Bodini et al. 10.1088/1742-6596/2265/2/022028
58. Control-oriented model for secondary effects of wake steering J. King et al. 10.5194/wes-6-701-2021
59. Positive effect of wind farm control on energy production and revenue in European markets F. Wasilczuk et al. 10.1016/j.energy.2025.136159
60. Uncertainty of toggling in wake steering experiments under diurnal cycle atmospheric conditions: an LES study E. Hodgson et al. 10.1088/1742-6596/3016/1/012026
61. Synergizing Helix Active Wake Mixing with Dynamic Yawing: An Exploration Study using Porous Discs in a Wind Tunnel J. Gutknecht et al. 10.1088/1742-6596/3016/1/012014
62. Turbine power loss during yaw-misaligned free field tests at different atmospheric conditions P. Hulsman et al. 10.1088/1742-6596/2265/3/032074
63. A Supervisory Control Framework for Fatigue-Aware Wake Steering in Wind Farms Y. Shen et al. 10.3390/en18133452
64. Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
65. Load assessment of a wind farm considering negative and positive yaw misalignment for wake steering R. Thedin et al. 10.5194/wes-10-1033-2025
66. Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
67. A dynamic open-source model to investigate wake dynamics in response to wind farm flow control strategies M. Becker et al. 10.5194/wes-10-1055-2025
68. Blade planform design optimization to enhance turbine wake control J. Allen et al. 10.1002/we.2699
69. Stochastic Dynamical Modeling of Wind Farm Turbulence A. Bhatt et al. 10.3390/en16196908
70. Free-vortex models for wind turbine wakes under yaw misalignment – a validation study on far-wake effects M. van den Broek et al. 10.5194/wes-8-1909-2023
71. On the load impact of dynamic wind farm wake mixing strategies J. Frederik & J. van Wingerden 10.1016/j.renene.2022.05.110
72. Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons K. Shaler et al. 10.5194/wes-9-1451-2024
73. Decentralized yaw optimization for maximizing wind farm production based on deep reinforcement learning Z. Deng et al. 10.1016/j.enconman.2023.117031
74. Data-driven wind farm flow control and challenges towards field implementation: A review T. Göçmen et al. 10.1016/j.rser.2025.115605
75. A low-computational physics-guided deep learning model for wind farm flow control under time-varying wind conditions S. He et al. 10.1016/j.energy.2025.137048
76. Development and validation of a hybrid data-driven model-based wake steering controller and its application at a utility-scale wind plant P. Bachant et al. 10.5194/wes-9-2235-2024
77. Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
78. Analytical solutions for yawed wind-turbine wakes with application to wind-farm power optimization by active yaw control Z. Zhang et al. 10.1016/j.oceaneng.2024.117691
79. Comparison of wind farm control strategies under realistic offshore wind conditions: turbine quantities of interest J. Frederik et al. 10.5194/wes-10-755-2025
80. Combined wake control of aligned wind turbines for power optimization based on a 3D wake model considering secondary wake steering Y. Liu et al. 10.1016/j.energy.2024.132900