61 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. Wind energy-harvesting technologies and recent research progresses in wind farm control models B. Desalegn et al. 10.3389/fenrg.2023.1124203
4. Vertical wake deflection for floating wind turbines by differential ballast control E. Nanos et al. 10.5194/wes-7-1641-2022
5. Active Wake Steering Control Data-Driven Design for a Wind Farm Benchmark S. Simani et al. 10.1016/j.ifacol.2023.10.1504
6. Loads assessment of a fixed‐bottom offshore wind farm with wake steering K. Shaler et al. 10.1002/we.2756
7. 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
8. Identification of wind turbine clusters for effective real time yaw control optimization F. Bernardoni et al. 10.1063/5.0036640
9. Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model Z. Deng et al. 10.3390/en16093932
10. 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
11. Data–Driven Wake Steering Control for a Simulated Wind Farm Model S. Simani et al. 10.31875/2409-9694.2023.10.02
12. Wake steering of multirotor wind turbines G. Speakman et al. 10.1002/we.2633
13. A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. 10.1016/j.rser.2024.114279
14. Enabling control co-design of the next generation of wind power plants A. Stanley et al. 10.5194/wes-8-1341-2023
15. Wind plant power maximization via extremum seeking yaw control: A wind tunnel experiment D. Kumar et al. 10.1002/we.2799
16. Maximization of the Power Production of an Offshore Wind Farm R. Balakrishnan & S. Hur 10.3390/app12084013
17. Design of the American Wake Experiment (AWAKEN) field campaign M. Debnath et al. 10.1088/1742-6596/2265/2/022058
18. Region-based convolutional neural network for wind turbine wake characterization from scanning lidars J. Aird et al. 10.1088/1742-6596/2265/3/032077
19. 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
20. Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
21. 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
22. 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
23. Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon 10.5194/wes-9-495-2024
24. Further calibration and validation of FLORIS with wind tunnel data F. Campagnolo et al. 10.1088/1742-6596/2265/2/022019
25. 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
26. 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
27. Serial-Refine Method for Fast Wake-Steering Yaw Optimization P. Fleming et al. 10.1088/1742-6596/2265/3/032109
28. Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
29. 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
30. Three-dimensional yaw wake model development with validations from wind tunnel experiments R. He et al. 10.1016/j.energy.2023.128402
31. On the Load Impact of Dynamic Wind Farm Wake Mixing Strategies J. Frederik & J. van Wingerden 10.2139/ssrn.3910237
32. Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms B. Doekemeijer et al. 10.3390/en15061964
33. Dynamic wind farm flow control using free-vortex wake models M. van den Broek et al. 10.5194/wes-9-721-2024
34. 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
35. Wind Tunnel Testing of Yaw by Individual Pitch Control Applied to Wake Steering F. Campagnolo et al. 10.3389/fenrg.2022.883889
36. 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
37. 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
38. Model predictive control of wakes for wind farm power tracking A. Sterle et al. 10.1088/1742-6596/2767/3/032005
39. A physically interpretable data-driven surrogate model for wake steering B. Sengers et al. 10.5194/wes-7-1455-2022
40. 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
41. Quantification of wake shape modulation and deflection for tilt and yaw misaligned wind turbines J. Bossuyt et al. 10.1017/jfm.2021.237
42. 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
43. 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
44. Can wind turbine farms increase settlement of particulate matters during dust events? M. Mataji et al. 10.1063/5.0129481
45. The value of wake steering wind farm flow control in US energy markets E. Simley et al. 10.5194/wes-9-219-2024
46. Experimental investigation of wind turbine wake and load dynamics during yaw maneuvers S. Macrí et al. 10.5194/wes-6-585-2021
47. Wind Farm Loads under Wake Redirection Control S. Kanev et al. 10.3390/en13164088
48. Wake position tracking using dynamic wake meandering model and rotor loads L. Dong et al. 10.1063/5.0032917
49. How generalizable is a machine-learning approach for modeling hub-height turbulence intensity? N. Bodini et al. 10.1088/1742-6596/2265/2/022028
50. Control-oriented model for secondary effects of wake steering J. King et al. 10.5194/wes-6-701-2021
51. Turbine power loss during yaw-misaligned free field tests at different atmospheric conditions P. Hulsman et al. 10.1088/1742-6596/2265/3/032074
52. Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
53. Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
54. Blade planform design optimization to enhance turbine wake control J. Allen et al. 10.1002/we.2699
55. Stochastic Dynamical Modeling of Wind Farm Turbulence A. Bhatt et al. 10.3390/en16196908
56. 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
57. On the load impact of dynamic wind farm wake mixing strategies J. Frederik & J. van Wingerden 10.1016/j.renene.2022.05.110
58. Decentralized yaw optimization for maximizing wind farm production based on deep reinforcement learning Z. Deng et al. 10.1016/j.enconman.2023.117031
59. Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
60. 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
61. Wind Farm Power Maximization through Wake Steering with a New Multiple Wake Model for Prediction of Turbulence Intensity G. Qian & T. Ishihara 10.1016/j.energy.2020.119680