175 citations as recorded by crossref.

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20. Wind tunnel testing of wake steering with dynamic wind direction changes F. Campagnolo et al. 10.5194/wes-5-1273-2020
21. Analysis of control-oriented wake modeling tools using lidar field results J. Annoni et al. 10.5194/wes-3-819-2018
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24. On the Robustness of Active Wake Control to Wind Turbine Downtime S. Kanev 10.3390/en12163152
25. On the load impact of dynamic wind farm wake mixing strategies J. Frederik & J. van Wingerden 10.1016/j.renene.2022.05.110
26. FarmConners wind farm flow control benchmark – Part 1: Blind test results T. Göçmen et al. 10.5194/wes-7-1791-2022
27. Dynamic wake steering and its impact on wind farm power production and yaw actuator duty S. Kanev 10.1016/j.renene.2019.06.122
28. A review of applications of artificial intelligent algorithms in wind farms Y. Wang et al. 10.1007/s10462-019-09768-7
29. Real-time optimization of wind farms using modifier adaptation and machine learning L. Andersson & L. Imsland 10.5194/wes-5-885-2020
30. Analysis of Wind Farms under Different Yaw Angles and Wind Speeds R. Das & Y. Shen 10.3390/en16134953
31. Wind farm optimization by active yaw control strategy using machine learning approach T. Qureshi & V. Warudkar 10.1080/15435075.2024.2322972
32. Error analysis of low-fidelity models for wake steering based on field measurements S. Letizia et al. 10.1088/1742-6596/2767/4/042029
33. Experimental investigation of wind turbine wake and load dynamics during yaw maneuvers S. Macrí et al. 10.5194/wes-6-585-2021
34. Wind Farm Modeling with Interpretable Physics-Informed Machine Learning M. Howland & J. Dabiri 10.3390/en12142716
35. Exploring the complexities associated with full-scale wind plant wake mitigation control experiments J. Duncan Jr. et al. 10.5194/wes-5-469-2020
36. Experimental investigation and analytical modelling of active yaw control for wind farm power optimization H. Zong & F. Porté-Agel 10.1016/j.renene.2021.02.059
37. A yawed wake model to predict the velocity distribution of curled wake cross-section for wind turbines Q. Yang et al. 10.1016/j.oceaneng.2024.116911
38. Control Co-Design of Wind Turbines L. Pao et al. 10.1146/annurev-control-061423-101708
39. 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
40. Coupled modeling of wake steering and platform offsets for floating wind arrays E. Lozon et al. 10.1088/1742-6596/2767/6/062035
41. Collective wind farm operation based on a predictive model increases utility-scale energy production M. Howland et al. 10.1038/s41560-022-01085-8
42. Expert Elicitation on Wind Farm Control J. van Wingerden et al. 10.1088/1742-6596/1618/2/022025
43. Data-driven optimisation of wind farm layout and wake steering with large-eddy simulations N. Bempedelis et al. 10.5194/wes-9-869-2024
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. A Study of the Impact of Pitch Misalignment on Wind Turbine Performance D. Astolfi 10.3390/machines7010008
46. Wake steering of wind turbine in the presence of a two-dimensional hill A. Mishra et al. 10.1063/5.0185842
47. 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
48. Initial results from a field campaign of wake steering applied at a commercial wind farm – Part 1 P. Fleming et al. 10.5194/wes-4-273-2019
49. Identification of wind turbine clusters for effective real time yaw control optimization F. Bernardoni et al. 10.1063/5.0036640
50. Joint state-parameter estimation for a control-oriented LES wind farm model B. Doekemeijer et al. 10.1088/1742-6596/1037/3/032013
51. 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
52. 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
53. Dynamic wake tracking using a cost-effective LiDAR and Kalman filtering: Design, simulation and full-scale validation W. Lio et al. 10.1016/j.renene.2021.03.081
54. Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms B. Doekemeijer et al. 10.3390/en15061964
55. On the importance of wind predictions in wake steering optimization E. Kadoche et al. 10.5194/wes-9-1577-2024
56. Wind Farm Power Optimization and Fault Ride-Through under Inter-Turn Short-Circuit Fault K. Ma et al. 10.3390/en14113072
57. Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer W. Shaw et al. 10.5194/wes-7-2307-2022
58. Study of wind farm control potential based on SCADA data J. Schreiber et al. 10.1088/1742-6596/1037/3/032012
59. Digital twin of wind farms via physics-informed deep learning J. Zhang & X. Zhao 10.1016/j.enconman.2023.117507
60. A study on the dynamic characteristics of alternative arrangements of floating wind farms with varying hub heights X. Xu et al. 10.1016/j.engstruct.2024.118857
61. Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
62. 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
63. Coplanar lidar measurement of a single wind energy converter wake in distinct atmospheric stability regimes at the Perdigão 2017 experiment N. Wildmann et al. 10.1088/1742-6596/1037/5/052006
64. Turbulence and Control of Wind Farms C. Shapiro et al. 10.1146/annurev-control-070221-114032
65. Stochastic Dynamical Modeling of Wind Farm Turbulence A. Bhatt et al. 10.3390/en16196908
66. Field Validation of Wake Steering Control with Wind Direction Variability E. Simley et al. 10.1088/1742-6596/1452/1/012012
67. Analysis of Wind-Turbine Main Bearing Loads Due to Constant Yaw Misalignments over a 20 Years Timespan M. Cardaun et al. 10.3390/en12091768
68. Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence N. Bodini et al. 10.1088/1742-6596/1452/1/012023
69. Wind Farm Loads under Wake Redirection Control S. Kanev et al. 10.3390/en13164088
70. On wind farm wake mixing strategies using dynamic individual pitch control J. Frederik et al. 10.1088/1742-6596/1618/2/022050
71. Fast yaw optimization for wind plant wake steering using Boolean yaw angles A. Stanley et al. 10.5194/wes-7-741-2022
72. Wind direction estimation using SCADA data with consensus-based optimization J. Annoni et al. 10.5194/wes-4-355-2019
73. Maximization of the Power Production of an Offshore Wind Farm R. Balakrishnan & S. Hur 10.3390/app12084013
74. Predicting the benefit of wake steering on the annual energy production of a wind farm using large eddy simulations and Gaussian process regression D. Hoek et al. 10.1088/1742-6596/1618/2/022024
75. Addressing deep array effects and impacts to wake steering with the cumulative-curl wake model C. Bay et al. 10.5194/wes-8-401-2023
76. Investigation into the shape of a wake of a yawed full-scale turbine P. Fleming et al. 10.1088/1742-6596/1037/3/032010
77. Wake steering optimization under uncertainty J. Quick et al. 10.5194/wes-5-413-2020
78. The Yawing Behavior of Horizontal-Axis Wind Turbines: A Numerical and Experimental Analysis F. Castellani et al. 10.3390/machines7010015
79. Design and analysis of a wake model for spatially heterogeneous flow A. Farrell et al. 10.5194/wes-6-737-2021
80. Loads assessment of a fixed‐bottom offshore wind farm with wake steering K. Shaler et al. 10.1002/we.2756
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86. Periodic dynamic induction control of wind farms: proving the potential in simulations and wind tunnel experiments J. Frederik et al. 10.5194/wes-5-245-2020
87. 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
88. Wind Turbine Power Curve Upgrades: Part II D. Astolfi & F. Castellani 10.3390/en12081503
89. Real-time identification of clusters of turbines F. Bernardoni et al. 10.1088/1742-6596/1618/2/022032
90. Wake Management in Wind Farms: An Adaptive Control Approach H. Dhiman et al. 10.3390/en12071247
91. Wake steering of multirotor wind turbines G. Speakman et al. 10.1002/we.2633
92. Impacts of wind field characteristics and non-steady deterministic wind events on time-varying main-bearing loads E. Hart et al. 10.5194/wes-7-1209-2022
93. An active power control approach for wake-induced load alleviation in a fully developed wind farm boundary layer M. Vali et al. 10.5194/wes-4-139-2019
94. A Study of the Near Wake Deformation of the X‐Rotor Vertical‐Axis Wind Turbine With Pitched Blades D. Bensason et al. 10.1002/we.2944
95. Influence of atmospheric conditions on the power production of utility-scale wind turbines in yaw misalignment M. Howland et al. 10.1063/5.0023746
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97. Wind turbine drivetrains: state-of-the-art technologies and future development trends A. Nejad et al. 10.5194/wes-7-387-2022
98. 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
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100. 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
101. Design and analysis of a wake steering controller with wind direction variability E. Simley et al. 10.5194/wes-5-451-2020
102. Model‐free closed‐loop wind farm control using reinforcement learning with recursive least squares J. Liew et al. 10.1002/we.2852
103. A General Method For The Diagnosis Of Wind Turbine Systematic Yaw Error Based Solely On SCADA Data D. Astolfi et al. 10.1088/1742-6596/2767/4/042007
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108. Wind tunnel experiments on wind turbine wakes in yaw: redefining the wake width J. Schottler et al. 10.5194/wes-3-257-2018
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128. Lidar measurements of yawed-wind-turbine wakes: characterization and validation of analytical models P. Brugger et al. 10.5194/wes-5-1253-2020
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138. Development of engineering cost models for integrated design optimization of onshore and offshore wind farms K. Yilmazlar et al. 10.1088/1742-6596/2265/4/042042
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154. Observability of the ambient conditions in model‐based estimation for wind farm control: A focus on static models B. Doekemeijer & J. van Wingerden 10.1002/we.2495
155. Field investigation on the influence of yaw misalignment on the propagation of wind turbine wakes M. Bromm et al. 10.1002/we.2210
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169. Lidar-based closed-loop wake redirection in high-fidelity simulation S. Raach et al. 10.1088/1742-6596/1037/3/032016
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