174 citations as recorded by crossref.

1. A Numerical Investigation of the Influence of the Wake for Mixed Layout Wind Turbines in Wind Farms Using FLORIS W. Tian et al. 10.3390/jmse12101714
2. 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
3. Blade planform design optimization to enhance turbine wake control J. Allen et al. 10.1002/we.2699
4. Large eddy simulations of curled wakes from tilted wind turbines H. Johlas et al. 10.1016/j.renene.2022.02.018
5. Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
6. Adjoint-based model predictive control for optimal energy extraction in waked wind farms M. Vali et al. 10.1016/j.conengprac.2018.11.005
7. Bi-fidelity modeling of uncertain and partially unknown systems using DeepONets S. De et al. 10.1007/s00466-023-02272-4
8. 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
9. A Machine Learning Method for Modeling Wind Farm Fatigue Load Y. Miao et al. 10.3390/app12157392
10. Ensemble-Based Flow Field Estimation Using the Dynamic Wind Farm Model FLORIDyn M. Becker et al. 10.3390/en15228589
11. 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
12. Wind plants can impact long-term local atmospheric conditions N. Bodini et al. 10.1038/s41598-021-02089-2
13. Multiobjective model predictive control design for wind turbines and farms L. Buccafusca & C. Beck 10.1063/5.0039707
14. 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
15. Joint optimization of wind farm layout considering optimal control K. Chen et al. 10.1016/j.renene.2021.10.032
16. Floating Offshore Wind Farm Control via Turbine Repositioning: Unlocking the Potential Unique to Floating Offshore Wind Y. Niu et al. 10.1109/MCS.2024.3432342
17. A point vortex transportation model for yawed wind turbine wakes H. Zong & F. Porté-Agel 10.1017/jfm.2020.123
18. Adaptation of Engineering Wake Models using Gaussian Process Regression and High-Fidelity Simulation Data L. Andersson et al. 10.1088/1742-6596/1618/2/022043
19. The helix approach: Using dynamic individual pitch control to enhance wake mixing in wind farms J. Frederik et al. 10.1002/we.2513
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
22. MARLYC: Multi-Agent Reinforcement Learning Yaw Control E. Kadoche et al. 10.1016/j.renene.2023.119129
23. Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
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
81. Optimization of wind farm power output using wake redirection control R. Balakrishnan et al. 10.1016/j.renene.2024.121357
82. Lidar assisted wake redirection in wind farms: A data driven approach H. Dhiman et al. 10.1016/j.renene.2020.01.027
83. An efficient solution for large offshore wind farm power optimization with the Porté-Agel wake model: Optimality and efficiency Z. Huang & W. Wu 10.1016/j.energy.2024.132444
84. Evaluation of the potential for wake steering for U.S. land-based wind power plants D. Bensason et al. 10.1063/5.0039325
85. 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
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
96. 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
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
99. Wind Tunnel Testing of Yaw by Individual Pitch Control Applied to Wake Steering F. Campagnolo et al. 10.3389/fenrg.2022.883889
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
104. Mechanical behaviour of wind turbines operating above design conditions F. Castellani et al. 10.1016/j.prostr.2020.02.045
105. Optimising yaw control at wind farm level E. Bossanyi 10.1088/1742-6596/1222/1/012023
106. Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms T. Ahmad et al. 10.3390/en12071266
107. Improving wind farm flow models by learning from operational data J. Schreiber et al. 10.5194/wes-5-647-2020
108. Wind tunnel experiments on wind turbine wakes in yaw: redefining the wake width J. Schottler et al. 10.5194/wes-3-257-2018
109. Wind Turbine Yaw Control Optimization and Its Impact on Performance D. Astolfi et al. 10.3390/machines7020041
110. A wind tunnel study on cyclic yaw control: Power performance and wake characteristics G. Duan et al. 10.1016/j.enconman.2023.117445
111. A new method to characterize the curled wake shape under yaw misalignment B. Sengers et al. 10.1088/1742-6596/1618/6/062050
112. Enabling control co-design of the next generation of wind power plants A. Stanley et al. 10.5194/wes-8-1341-2023
113. Turbine power loss during yaw-misaligned free field tests at different atmospheric conditions P. Hulsman et al. 10.1088/1742-6596/2265/3/032074
114. Numerical and Experimental Methods for the Assessment of Wind Turbine Control Upgrades D. Astolfi et al. 10.3390/app8122639
115. Tilted wind turbines in farm configuration for improved global efficiency F. Trigaux et al. 10.1088/1742-6596/1618/6/062035
116. Floating platform effects on power generation in spar and semisubmersible wind turbines H. Johlas et al. 10.1002/we.2608
117. U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence N. Bodini et al. 10.1029/2019GL082636
118. 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
119. On the power and control of a misaligned rotor – beyond the cosine law S. Tamaro et al. 10.5194/wes-9-1547-2024
120. Sensitivity analysis of wake steering optimisation for wind farm power maximisation F. Gori et al. 10.5194/wes-8-1425-2023
121. Active Cluster Wake Mixing J. Gutknecht et al. 10.1088/1742-6596/2767/9/092052
122. Sensitivity and Uncertainty of the FLORIS Model Applied on the Lillgrund Wind Farm M. van Beek et al. 10.3390/en14051293
123. A physically interpretable data-driven surrogate model for wake steering B. Sengers et al. 10.5194/wes-7-1455-2022
124. Quantification of wake shape modulation and deflection for tilt and yaw misaligned wind turbines J. Bossuyt et al. 10.1017/jfm.2021.237
125. A simulation study demonstrating the importance of large-scale trailing vortices in wake steering P. Fleming et al. 10.5194/wes-3-243-2018
126. 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
127. An Application of Nested Control Synthesis for Wind Farms L. Buccafusca et al. 10.1016/j.ifacol.2019.12.158
128. Lidar measurements of yawed-wind-turbine wakes: characterization and validation of analytical models P. Brugger et al. 10.5194/wes-5-1253-2020
129. Control-oriented modelling of wind direction variability S. Dallas et al. 10.5194/wes-9-841-2024
130. A Review of Recent Advancements in Offshore Wind Turbine Technology T. Asim et al. 10.3390/en15020579
131. Region-based convolutional neural network for wind turbine wake characterization from scanning lidars J. Aird et al. 10.1088/1742-6596/2265/3/032077
132. A Tutorial on the Control of Floating Offshore Wind Turbines: Stability Challenges and Opportunities for Power Capture D. Stockhouse et al. 10.1109/MCS.2024.3433208
133. The revised FLORIDyn model: implementation of heterogeneous flow and the Gaussian wake M. Becker et al. 10.5194/wes-7-2163-2022
134. Closely spaced corotating helical vortices: General solutions A. Castillo-Castellanos et al. 10.1103/PhysRevFluids.6.114701
135. 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
136. Wind turbine power modelling and optimization using artificial neural network with wind field experimental data H. Sun et al. 10.1016/j.apenergy.2020.115880
137. 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
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
139. Experimental characterisation of the wake behind paired vertical-axis wind turbines A. Vergaerde et al. 10.1016/j.jweia.2020.104353
140. 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
141. 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
142. Wind farm flow control oriented to electricity markets and grid integration: Initial perspective analysis I. Eguinoa et al. 10.1002/adc2.80
143. Modulation of turbulence scales passing through the rotor of a wind turbine N. Tobin & L. Chamorro 10.1080/14685248.2018.1547387
144. Wind farm yaw control set-point optimization under model parameter uncertainty M. Howland 10.1063/5.0051071
145. 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
146. Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization W. Munters & J. Meyers 10.3390/en11010177
147. Wind farm power optimization through wake steering M. Howland et al. 10.1073/pnas.1903680116
148. Wind turbine power performance characterization through aeroelastic simulations and virtual nacelle lidar measurements A. Sebastiani et al. 10.1088/1742-6596/2265/2/022059
149. Synchronized optimization of wind farm start-stop and yaw control based on 3D wake model Q. Wang et al. 10.1016/j.renene.2024.120044
150. Wind Farm Power Maximisation via Wake Steering: A Gaussian Process‐Based Yaw‐Dependent Parameter Tuning Approach F. Gori et al. 10.1002/we.2953
151. Robust active wake control in consideration of wind direction variability and uncertainty A. Rott et al. 10.5194/wes-3-869-2018
152. 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
153. Toward flow control: An assessment of the curled wake model in the FLORIS framework C. Bay et al. 10.1088/1742-6596/1618/2/022033
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
156. Optimal closed-loop wake steering – Part 1: Conventionally neutral atmospheric boundary layer conditions M. Howland et al. 10.5194/wes-5-1315-2020
157. MARLYC: Multi-Agent Reinforcement Learning Yaw Control E. KADOCHE et al. 10.2139/ssrn.4507479
158. LSTM-NN Yaw Control of Wind Turbines Based on Upstream Wind Information W. Chen et al. 10.3390/en13061482
159. Experimental results of wake steering using fixed angles P. Fleming et al. 10.5194/wes-6-1521-2021
160. A dynamic model of wind turbine yaw for active farm control G. Starke et al. 10.1002/we.2884
161. A fast-running physics-based wake model for a semi-infinite wind farm M. Bastankhah et al. 10.1017/jfm.2024.282
162. On the wake deflection of vertical axis wind turbines by pitched blades M. Huang et al. 10.1002/we.2803
163. Wind farm control ‐ Part I: A review on control system concepts and structures L. Andersson et al. 10.1049/rpg2.12160
164. Quantitative evaluation of yaw-misalignment and aerodynamic wake induced fatigue loads of offshore Wind turbines J. Sun et al. 10.1016/j.renene.2022.08.137
165. Effect of yaw on wake and load characteristics of two tandem offshore wind turbines under neutral atmospheric boundary layer conditions L. Ju et al. 10.1063/5.0235036
166. Field testing of a local wind inflow estimator and wake detector J. Schreiber et al. 10.5194/wes-5-867-2020
167. Influence of Wake Model Superposition and Secondary Steering on Model-Based Wake Steering Control with SCADA Data Assimilation M. Howland & J. Dabiri 10.3390/en14010052
168. Lidar-based closed-loop wake redirection in high-fidelity simulation S. Raach et al. 10.1088/1742-6596/1037/3/032016
169. Atmospheric dispersion of chemical, biological, and radiological hazardous pollutants: Informing risk assessment for public safety X. Zhang & J. Wang 10.1016/j.jnlssr.2022.09.001
170. Experimental and numerical study of the wake deflections of scaled vertical axis wind turbine models M. Huang et al. 10.1088/1742-6596/2505/1/012019
171. Grand challenges in the digitalisation of wind energy A. Clifton et al. 10.5194/wes-8-947-2023
172. Data-Driven Methods for the Analysis of Wind Turbine Yaw Control Optimization D. Astolfi et al. 10.1115/1.4047413
173. 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
174. Full-Scale Field Test of Wake Steering P. Fleming et al. 10.1088/1742-6596/854/1/012013