126 citations as recorded by crossref.

1. From wind conditions to operational strategy: optimal planning of wind turbine damage progression over its lifetime N. Requate et al. 10.5194/wes-8-1727-2023
2. Wind-farm power prediction using a turbulence-optimized Gaussian wake model N. Zehtabiyan-Rezaie et al. 10.1016/j.weer.2024.100007
3. Sensitivity analysis of computational domain height for semi-infinite and finite-sized wind farms W. Chanprasert et al. 10.1088/1742-6596/3016/1/012052
4. Experimental comparison of induction control methods for wind farm power maximization on a scaled two-turbine setup D. Van Der Hoek et al. 10.1088/1742-6596/2767/9/092064
5. Wake characteristics and scalar transport equation for energy recovery analysis under different tip speed ratio conditions Q. Tang et al. 10.1016/j.renene.2025.124409
6. A Data-Driven Model Predictive Control for Wind Farm Power Maximization M. Kim et al. 10.1109/ACCESS.2024.3420872
7. Grand challenges of wind energy science – meeting the needs and services of the power system M. O'Malley et al. 10.5194/wes-9-2087-2024
8. The Influence of Floating Turbine Dynamics on the Helix Wake Mixing Method D. Van Den Berg et al. 10.1088/1742-6596/2767/3/032012
9. Evolution of eddy viscosity in the wake of a wind turbine R. Scott et al. 10.5194/wes-8-449-2023
10. Floating Platform and Mooring Line Optimization for Wake Loss Mitigation in Offshore Wind Farms Through Wake Mixing Strategy G. Lazzerini et al. 10.3390/en18112813
11. Exploring cooperation between wind farms: a wake steering optimization study of the Belgian offshore wind farm cluster B. Foloppe et al. 10.1088/1742-6596/2505/1/012055
12. Tailoring anisotropic synthetic inflow turbulence generator for wind turbine wake simulations N. Ali et al. 10.1063/5.0217802
13. On the power and control of a misaligned rotor – beyond the cosine law S. Tamaro et al. 10.5194/wes-9-1547-2024
14. Synchronized Dynamic Induction Control: An Experimental Investigation A. Van Vondelen et al. 10.1088/1742-6596/2767/3/032027
15. Recovering Corrupted Data in Wind Farm Measurements: A Matrix Completion Approach M. Silei et al. 10.3390/en16041674
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. 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
18. Integrated Design and Experimental Validation of a Fixed-Pitch Rotor for Wind Tunnel Testing A. Fontanella et al. 10.3390/en16052205
19. Physics informed neural networks for wind field modeling in wind farms P. Cobelli et al. 10.1088/1742-6596/2505/1/012051
20. Fluid-Dynamic Mechanisms Underlying Wind Turbine Wake Control with Strouhal-Timed Actuation L. Cheung et al. 10.3390/en17040865
21. Brief communication: An elliptical parameterisation of the wind direction rose E. Hart 10.5194/wes-10-1821-2025
22. Wake asymmetry of yaw state wind turbines induced by interference with wind towers K. Shibuya & T. Uchida 10.1016/j.energy.2023.128091
23. Integer programming for optimal yaw control of wind farms F. Bestehorn et al. 10.5194/wes-10-1637-2025
24. The dynamic coupling between the pulse wake mixing strategy and floating wind turbines D. van den Berg et al. 10.5194/wes-8-849-2023
25. Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures L. Cheung et al. 10.5194/wes-10-1403-2025
26. Combining wake redirection and derating strategies in a load-constrained wind farm power maximization A. Croce et al. 10.5194/wes-9-1211-2024
27. Dynamic interaction of inflow and rotor time scales and impact on single turbine wake recovery S. Andersen et al. 10.1088/1742-6596/2767/9/092002
28. Mimicking the Helix with a porous disc for wind tunnel testing B. De Vos et al. 10.1088/1742-6596/2767/9/092063
29. Prediction and Mitigation of Wind Farm Blockage Losses Considering Mesoscale Atmospheric Response L. Legris et al. 10.3390/en16010386
30. On the importance of wind predictions in wake steering optimization E. Kadoche et al. 10.5194/wes-9-1577-2024
31. Wind Tunnel Testing of Combined Derating and Wake Steering F. Campagnolo et al. 10.1016/j.ifacol.2023.10.1034
32. Control-oriented modelling of wind direction variability S. Dallas et al. 10.5194/wes-9-841-2024
33. Dynamic wake conditions tailored by an active grid in the wind tunnel D. Onnen et al. 10.1088/1742-6596/2767/4/042038
34. Wake Mixing Control For Floating Wind Farms: Analysis of the Implementation of the Helix Wake Mixing Strategy on the IEA 15-MW Floating Wind Turbine D. van den Berg et al. 10.1109/MCS.2024.3432341
35. Analysis of wake recovery effects using small-diameter-ratio wind turbines for vertically staggered wind farms H. Yang et al. 10.1063/5.0191884
36. The value of wake steering wind farm flow control in US energy markets E. Simley et al. 10.5194/wes-9-219-2024
37. Large eddy simulation and linear stability analysis of active sway control for wind turbine array wake Z. Li et al. 10.1063/5.0216602
38. Evaluating the potential of a wake steering co-design for wind farm layout optimization through a tailored genetic algorithm M. Baricchio et al. 10.5194/wes-9-2113-2024
39. Inverse reinforcement learning for objective discovery in collective behavior of artificial swimmers D. Wälchli et al. 10.1103/646f-dt2k
40. Investigation of far-wake models coupled with yaw-induction control for power optimization K. Heck et al. 10.1088/1742-6596/2767/9/092103
41. Modelling of Wind Turbines as Porous Disks for Wind Farm Flow Studies M. Catania et al. 10.1088/1742-6596/2767/5/052049
42. Structural motion control of waked floating offshore wind farms H. del Pozo Gonzalez et al. 10.1016/j.oceaneng.2024.116709
43. Simulating the helix wake within an actuator disk framework: verification against discrete-blade type simulations M. Coquelet et al. 10.1088/1742-6596/2505/1/012017
44. Wind pattern clustering of high frequent field measurements for dynamic wind farm flow control M. Becker et al. 10.1088/1742-6596/2767/3/032028
45. A control-oriented load surrogate model based on sector-averaged inflow quantities: capturing damage for unwaked, waked, wake-steering and curtailed wind turbines A. Guilloré et al. 10.1088/1742-6596/2767/3/032019
46. Experimental investigation of blade tip vortex behavior in the wake of asymmetric rotors A. Abraham & T. Leweke 10.1007/s00348-023-03646-3
47. Offshore wind turbine tower design and optimization: A review and AI-driven future directions J. Alves Ribeiro et al. 10.1016/j.apenergy.2025.126294
48. Advancements in Wind Farm Control: Modelling and Multi-Objective Optimization Through Yaw-Based Wake Steering T. Lucas Frutuoso et al. 10.3390/en18092247
49. Influence of platform motion on the energy production of a floating wind farm M. De Pascali et al. 10.1088/1742-6596/2767/9/092046
50. 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
51. Assessment of loads and power generation for a wind farm utilizing Helix control strategy M. Mohammadi et al. 10.1088/1742-6596/3016/1/012022
52. 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
53. Wake development in floating wind turbines: new insights and an open dataset from wind tunnel experiments A. Fontanella et al. 10.5194/wes-10-1369-2025
54. Scalable SCADA-Based Calibration for Analytical Wake Models Across an Offshore Cluster D. Binsbergen et al. 10.1088/1742-6596/2745/1/012014
55. 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
56. 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
57. A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models D. Millstein et al. 10.1038/s41597-023-02804-w
58. 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
59. LES-based validation of a dynamic wind farm flow model under unsteady inflow and yaw misalignment J. Bohrer et al. 10.1088/1742-6596/2767/3/032041
60. Control co-design of a large offshore wind farm considering the effect of wind extractability M. Pahus et al. 10.1088/1742-6596/2767/9/092026
61. Stochastic Dynamical Modeling of Wind Farm Turbulence A. Bhatt et al. 10.3390/en16196908
62. Design of a robotic platform for hybrid wind tunnel experiments of floating wind farms A. Fontanella et al. 10.1088/1742-6596/2767/4/042008
63. Phase Synchronization for Helix Enhanced Wake Mixing in Downstream Wind Turbines A. van Vondelen et al. 10.1016/j.ifacol.2023.10.1039
64. Potential of Wake Scaling Techniques for Vertical-Axis Wind Turbine Wake Prediction D. Vahidi & F. Porté-Agel 10.3390/en17174527
65. Modular deep learning approach for wind farm power forecasting and wake loss prediction S. Ally et al. 10.5194/wes-10-779-2025
66. A multi-fidelity approach for wind farm simulations and comparison with field data W. Yu et al. 10.1088/1742-6596/2767/5/052039
67. 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
68. Validation of induction/steering reserve-boosting active power control by a wind tunnel experiment with dynamic wind direction changes S. Tamaro et al. 10.1088/1742-6596/2767/9/092067
69. Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon 10.5194/wes-9-495-2024
70. A Supervisory Control Framework for Fatigue-Aware Wake Steering in Wind Farms Y. Shen et al. 10.3390/en18133452
71. Evaluation of wind resource uncertainty on energy production estimates for offshore wind farms K. Klemmer et al. 10.1063/5.0166830
72. On the performance of the helix wind farm control approach in the conventionally neutral atmospheric boundary layer E. Taschner et al. 10.1088/1742-6596/2505/1/012006
73. Deep Reinforcement Learning Applied to Wake Steering C. Ros Perez et al. 10.1002/adts.202500199
74. Unified momentum model for rotor aerodynamics across operating regimes J. Liew et al. 10.1038/s41467-024-50756-5
75. On the impact of different static induction control strategies on a wind turbine wake M. Zúñiga Inestroza et al. 10.1088/1742-6596/2767/9/092082
76. Surrogate Modeling and Aeroelastic Analysis of a Wind Turbine with Down-Regulation, Power Boosting, and IBC Capabilities V. Pettas & P. Cheng 10.3390/en17061284
77. Experimental and numerical investigation on the potential of wake mixing by dynamic yaw for wind farm power optimization F. Mühle et al. 10.1088/1742-6596/2767/9/092068
78. Maximizing wind farm power output with the helix approach: Experimental validation and wake analysis using tomographic particle image velocimetry D. van der Hoek et al. 10.1002/we.2896
79. Increased power gains from wake steering control using preview wind direction information B. Sengers et al. 10.5194/wes-8-1693-2023
80. Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability N. Zehtabiyan-Rezaie et al. 10.1103/PRXEnergy.2.013009
81. Study on the yaw-based wake steering control considering dynamic flow characteristics for wind farm power improvement X. Yu et al. 10.1088/1742-6596/2505/1/012010
82. Comparison of helix and wake steering control for varying turbine spacing and wind direction E. Taschner et al. 10.1088/1742-6596/2767/3/032023
83. Improving Floating Offshore Wind Farm Flow Control With Scalable Model-Based Deep Reinforcement Learning M. Mei et al. 10.1109/TASE.2025.3585016
84. Comparison of steady-state analytical wake models implemented in wind farm analysis software R. Mudafort et al. 10.1088/1742-6596/2767/5/052066
85. Wind Farm Power Maximisation via Wake Steering: A Gaussian Process‐Based Yaw‐Dependent Parameter Tuning Approach F. Gori et al. 10.1002/we.2953
86. Overview of preparation for the American WAKE ExperimeNt (AWAKEN) P. Moriarty et al. 10.1063/5.0141683
87. Optimal control of wind farm power output with delay compensated nested-loop extreme seeking control Z. Wu & Y. Li 10.1063/5.0134878
88. Self-consistent model for active control of wind turbine wakes Z. Li & X. Yang 10.1017/jfm.2025.10263
89. Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
90. Deep reinforcement learning-driven wind farm flow control considering dynamic wind H. Wang et al. 10.1016/j.enconman.2025.119888
91. A blind test on wind turbine wake modelling: Benchmark results and Phase II announcement I. Chondromatidis et al. 10.1088/1742-6596/3016/1/012035
92. The rotor as a sensor – observing shear and veer from the operational data of a large wind turbine M. Bertelè et al. 10.5194/wes-9-1419-2024
93. Modern Strategies for Controlling Wind Power Plants: Technologies, Challenges and Prospects N. Kurylko & R. Fedoryshyn 10.23939/jeecs2024.01.056
94. Field validation of a yaw misalignment observer for wind farm control M. Bertelè et al. 10.1088/1742-6596/2767/9/092013
95. Evolution and instability of the tip vortices behind a yawed wind turbine C. Li et al. 10.1017/jfm.2025.10389
96. Large-Eddy Simulation of Wind Turbine Wakes in Forest Terrain Y. Li et al. 10.3390/su15065139
97. The wind farm as a sensor: learning and explaining orographic and plant-induced flow heterogeneities from operational data R. Braunbehrens et al. 10.5194/wes-8-691-2023
98. Wind farm power optimization using system identification Y. Zhu et al. 10.1016/j.compchemeng.2024.108877
99. On the robustness of a blade-load-based wind speed estimator to dynamic pitch control strategies M. Coquelet et al. 10.5194/wes-9-1923-2024
100. Field measurement and analysis of near-ground wind field characteristics and wind pressure on tracking photovoltaic panels T. Bao et al. 10.1016/j.energy.2025.135400
101. Resolvent-based motion-to-wake modelling of wind turbine wakes under dynamic rotor motion Z. Li & X. Yang 10.1017/jfm.2023.1097
102. 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
103. Exploring the Power & Loads Paradigm: Tocha Farm Case Study T. Lucas Frutuoso et al. 10.1088/1742-6596/2767/9/092102
104. Positive effect of wind farm control on energy production and revenue in European markets F. Wasilczuk et al. 10.1016/j.energy.2025.136159
105. Characterization of wind turbine flow through nacelle-mounted lidars: a review S. Letizia et al. 10.3389/fmech.2023.1261017
106. Multi-row extremum seeking for wind farm power maximization M. Rotea et al. 10.1088/1742-6596/2767/3/032043
107. Wake turbulence modeling in stratified atmospheric flows using a novel k−ℓ model K. Klemmer & M. Howland 10.1063/5.0249278
108. Towards real-time optimal control of wind farms using large-eddy simulations N. Janssens & J. Meyers 10.5194/wes-9-65-2024
109. Dynamic individual pitch control for wake mitigation: Why does the helix handedness in the wake matter? M. Coquelet et al. 10.1088/1742-6596/2767/9/092084
110. Winds of Progress: An In-Depth Exploration of Offshore, Floating, and Onshore Wind Turbines as Cornerstones for Sustainable Energy Generation and Environmental Stewardship S. Khan Afridi et al. 10.1109/ACCESS.2024.3397243
111. Wake dynamics of wind turbines in unsteady streamwise flow conditions N. Wei et al. 10.1017/jfm.2024.999
112. Considerations for the global commercialization of floating offshore wind energy A. Robertson et al. 10.1038/s44359-025-00093-7
113. Aerodynamic effects of leading-edge erosion in wind farm flow modeling J. Visbech et al. 10.5194/wes-9-1811-2024
114. Reinforcement learning for wind-farm flow control: Current state and future actions M. Abkar et al. 10.1016/j.taml.2023.100475
115. A meso–micro atmospheric perturbation model for wind farm blockage K. Devesse et al. 10.1017/jfm.2024.868
116. Secondary flows in the actuator-disk simulation of wind-turbine wakes N. Zehtabiyan-Rezaie et al. 10.1063/5.0203068
117. Model predictive control of wakes for wind farm power tracking A. Sterle et al. 10.1088/1742-6596/2767/3/032005
118. Understanding wind farm power densities R. Stevens 10.1017/jfm.2023.113
119. Wind plant wake losses: Disconnect between turbine actuation and control of plant wakes with engineering wake models R. Scott et al. 10.1063/5.0207013
120. Wind tunnel investigations of an individual pitch control strategy for wind farm power optimization F. Mühle et al. 10.5194/wes-9-1251-2024
121. 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
122. A new coupling of a GPU‐resident large‐eddy simulation code with a multiphysics wind turbine simulation tool E. Taschner et al. 10.1002/we.2844
123. FarmConners wind farm flow control benchmark – Part 1: Blind test results T. Göçmen et al. 10.5194/wes-7-1791-2022
124. FarmConners market showcase results: wind farm flow control considering electricity prices K. Kölle et al. 10.5194/wes-7-2181-2022
125. Wind tunnel investigation of the aerodynamic response of two 15 MW floating wind turbines A. Fontanella et al. 10.5194/wes-7-1711-2022
126. A Probabilistic Learning Approach Applied to the Optimization of Wake Steering in Wind Farms J. Almeida & F. Rochinha 10.1115/1.4054501