59 citations as recorded by crossref.

1. Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm T. Duc et al. 10.5194/wes-4-287-2019
2. 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
3. Adjoint-based model predictive control for optimal energy extraction in waked wind farms M. Vali et al. 10.1016/j.conengprac.2018.11.005
4. 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
5. 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
6. Wind Turbine Power Curve Upgrades: Part II D. Astolfi & F. Castellani 10.3390/en12081503
7. Wake Management in Wind Farms: An Adaptive Control Approach H. Dhiman et al. 10.3390/en12071247
8. Effects of axial induction control on wind farm energy production - A field test D. van der Hoek et al. 10.1016/j.renene.2019.03.117
9. 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
10. A review of full-scale wind-field measurements of the wind-turbine wake effect and a measurement of the wake-interaction effect H. Sun et al. 10.1016/j.rser.2020.110042
11. A Study of the Impact of Pitch Misalignment on Wind Turbine Performance D. Astolfi 10.3390/machines7010008
12. Validation of a lookup-table approach to modeling turbine fatigue loads in wind farms under active wake control H. Mendez Reyes et al. 10.5194/wes-4-549-2019
13. 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
14. Joint state-parameter estimation for a control-oriented LES wind farm model B. Doekemeijer et al. 10.1088/1742-6596/1037/3/032013
15. Online model calibration for a simplified LES model in pursuit of real-time closed-loop wind farm control B. Doekemeijer et al. 10.5194/wes-3-749-2018
16. Experimental characterisation of the wake behind paired vertical-axis wind turbines A. Vergaerde et al. 10.1016/j.jweia.2020.104353
17. A Study on the Effect of Closed-Loop Wind Farm Control on Power and Tower Load in Derating the TSO Command Condition H. Kim et al. 10.3390/en12102004
18. Modulation of turbulence scales passing through the rotor of a wind turbine N. Tobin & L. Chamorro 10.1080/14685248.2018.1547387
19. Design and analysis of a wake steering controller with wind direction variability E. Simley et al. 10.5194/wes-5-451-2020
20. A point vortex transportation model for yawed wind turbine wakes H. Zong & F. Porté-Agel 10.1017/jfm.2020.123
21. Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization 10.3390/en11010177
22. Wind farm power optimization through wake steering M. Howland et al. 10.1073/pnas.1903680116
23. The helix approach: Using dynamic individual pitch control to enhance wake mixing in wind farms J. Frederik et al. 10.1002/we.2513
24. Mechanical behaviour of wind turbines operating above design conditions F. Castellani et al. 10.1016/j.prostr.2020.02.045
25. Study of wind farm control potential based on SCADA data J. Schreiber et al. 10.1088/1742-6596/1037/3/032012
26. Optimising yaw control at wind farm level E. Bossanyi 10.1088/1742-6596/1222/1/012023
27. Analysis of control-oriented wake modeling tools using lidar field results J. Annoni et al. 10.5194/wes-3-819-2018
28. Robust active wake control in consideration of wind direction variability and uncertainty A. Rott et al. 10.5194/wes-3-869-2018
29. Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms T. Ahmad et al. 10.3390/en12071266
30. 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
31. Improving wind farm flow models by learning from operational data J. Schreiber et al. 10.5194/wes-5-647-2020
32. On the Robustness of Active Wake Control to Wind Turbine Downtime S. Kanev 10.3390/en12163152
33. 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
34. Wind tunnel experiments on wind turbine wakes in yaw: redefining the wake width J. Schottler et al. 10.5194/wes-3-257-2018
35. Field investigation on the influence of yaw misalignment on the propagation of wind turbine wakes M. Bromm et al. 10.1002/we.2210
36. Wind Turbine Yaw Control Optimization and Its Impact on Performance D. Astolfi et al. 10.3390/machines7020041
37. Field Validation of Wake Steering Control with Wind Direction Variability E. Simley et al. 10.1088/1742-6596/1452/1/012012
38. Analysis of Wind-Turbine Main Bearing Loads Due to Constant Yaw Misalignments over a 20 Years Timespan M. Cardaun et al. 10.3390/en12091768
39. Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence N. Bodini et al. 10.1088/1742-6596/1452/1/012023
40. Dynamic wake steering and its impact on wind farm power production and yaw actuator duty S. Kanev 10.1016/j.renene.2019.06.122
41. Numerical and Experimental Methods for the Assessment of Wind Turbine Control Upgrades D. Astolfi et al. 10.3390/app8122639
42. Wind direction estimation using SCADA data with consensus-based optimization J. Annoni et al. 10.5194/wes-4-355-2019
43. LSTM-NN Yaw Control of Wind Turbines Based on Upstream Wind Information W. Chen et al. 10.3390/en13061482
44. U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence N. Bodini et al. 10.1029/2019GL082636
45. A review of applications of artificial intelligent algorithms in wind farms Y. Wang et al. 10.1007/s10462-019-09768-7
46. Investigation into the shape of a wake of a yawed full-scale turbine P. Fleming et al. 10.1088/1742-6596/1037/3/032010
47. Wake steering optimization under uncertainty J. Quick et al. 10.5194/wes-5-413-2020
48. Real-time optimization of wind farms using modifier adaptation and machine learning L. Andersson & L. Imsland 10.5194/wes-5-885-2020
49. Field testing of a local wind inflow estimator and wake detector J. Schreiber et al. 10.5194/wes-5-867-2020
50. The Yawing Behavior of Horizontal-Axis Wind Turbines: A Numerical and Experimental Analysis F. Castellani et al. 10.3390/machines7010015
51. Wind Farm Modeling with Interpretable Physics-Informed Machine Learning M. Howland & J. Dabiri 10.3390/en12142716
52. A simulation study demonstrating the importance of large-scale trailing vortices in wake steering P. Fleming et al. 10.5194/wes-3-243-2018
53. Large-eddy simulation study of wind farm active power control with a coordinated load distribution M. Vali et al. 10.1088/1742-6596/1037/3/032018
54. Lidar-based closed-loop wake redirection in high-fidelity simulation S. Raach et al. 10.1088/1742-6596/1037/3/032016
55. Exploring the complexities associated with full-scale wind plant wake mitigation control experiments J. Duncan Jr. et al. 10.5194/wes-5-469-2020
56. Lidar assisted wake redirection in wind farms: A data driven approach H. Dhiman et al. 10.1016/j.renene.2020.01.027
57. An Application of Nested Control Synthesis for Wind Farms L. Buccafusca et al. 10.1016/j.ifacol.2019.12.158
58. Data-Driven Methods for the Analysis of Wind Turbine Yaw Control Optimization D. Astolfi et al. 10.1115/1.4047413
59. Full-Scale Field Test of Wake Steering P. Fleming et al. 10.1088/1742-6596/854/1/012013