52 citations as recorded by crossref.

1. Development of a novel analytical wake model behind HAWT by considering the nacelle effect R. Mirsane et al. 10.1016/j.enconman.2023.118031
2. Towards multi-fidelity deep learning of wind turbine wakes S. Pawar et al. 10.1016/j.renene.2022.10.013
3. Research on the dynamic characteristics of wind turbine gearboxes under the spatiotemporal inhomogeneous in the wake X. Zhu et al. 10.1016/j.measurement.2023.113704
4. Analytical solution for the cumulative wake of wind turbines in wind farms M. Bastankhah et al. 10.1017/jfm.2020.1037
5. Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows S. Letizia & G. Iungo 10.1063/5.0076739
6. A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. 10.1016/j.rser.2024.114279
7. Curled-Skewed Wakes behind Yawed Wind Turbines Subject to Veered Inflow M. Mohammadi et al. 10.3390/en15239135
8. Time-Averaged Wind Turbine Wake Flow Field Prediction Using Autoencoder Convolutional Neural Networks Z. Zhang et al. 10.3390/en15010041
9. Wind Tunnel Study on the Tip Speed Ratio’s Impact on a Wind Turbine Wake Development I. Neunaber et al. 10.3390/en15228607
10. Characterization of wind turbine flow through nacelle-mounted lidars: a review S. Letizia et al. 10.3389/fmech.2023.1261017
11. The impact of the atmospheric boundary layer on the asymmetric wake profile: A bivariate analysis M. Barasa et al. 10.1016/j.seta.2022.102563
12. Two three-dimensional super-Gaussian wake models for hilly terrain L. Dai et al. 10.1063/5.0174297
13. Theoretical modelling of the three-dimensional wake of vertical axis turbines P. Ouro & M. Lazennec 10.1017/flo.2021.4
14. A Comparative Analysis of Actuator-Based Turbine Structure Parametrizations for High-Fidelity Modeling of Utility-Scale Wind Turbines under Neutral Atmospheric Conditions C. Santoni et al. 10.3390/en17030753
15. Comparison of modular analytical wake models to the Lillgrund wind plant N. Hamilton et al. 10.1063/5.0018695
16. A physics-based model for wind turbine wake expansion in the atmospheric boundary layer D. Vahidi & F. Porté-Agel 10.1017/jfm.2022.443
17. Evaluation of a lattice Boltzmann-based wind-turbine actuator line model against a Navier-Stokes approach H. Schottenhamml et al. 10.1088/1742-6596/2265/2/022027
18. Large-eddy simulation of upwind-hill effects on wind-turbine wakes and power performance Z. Zhang et al. 10.1016/j.energy.2024.130823
19. FarmConners wind farm flow control benchmark – Part 1: Blind test results T. Göçmen et al. 10.5194/wes-7-1791-2022
20. Derivation and verification of three-dimensional wake model of multiple wind turbines based on super-Gaussian function S. Zhang et al. 10.1016/j.renene.2023.118968
21. Derivation and Verification of Gaussian Terrain Wake Model Based on Wind Field Experiment W. Liu et al. 10.3390/pr10122731
22. A new 3D asymmetric double-Gaussian wake analytical model for horizontal-axis wind turbines Y. Liu et al. 10.1016/j.jweia.2024.105685
23. An adaptation of the super-Gaussian wake model for yawed wind turbines F. Blondel et al. 10.1088/1742-6596/1618/6/062031
24. Bayesian uncertainty quantification framework for wake model calibration and validation with historical wind farm power data F. Aerts et al. 10.1002/we.2841
25. 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
26. The area localized coupled model for analytical mean flow prediction in arbitrary wind farm geometries G. Starke et al. 10.1063/5.0042573
27. The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study P. Yang & H. Najafi 10.1115/1.4052775
28. Decentralized yaw optimization for maximizing wind farm production based on deep reinforcement learning Z. Deng et al. 10.1016/j.enconman.2023.117031
29. Can wind turbine farms increase settlement of particulate matters during dust events? M. Mataji et al. 10.1063/5.0129481
30. Analytical Descriptions of Swirling Wake Profiles W. Schutz & J. Naughton 10.1088/1742-6596/2505/1/012021
31. A physically interpretable data-driven surrogate model for wake steering B. Sengers et al. 10.5194/wes-7-1455-2022
32. Brief communication: A momentum-conserving superposition method applied to the super-Gaussian wind turbine wake model F. Blondel 10.5194/wes-8-141-2023
33. Quantification of three-dimensional added turbulence intensity for the horizontal-axis wind turbine considering the wake anisotropy S. Zhang et al. 10.1016/j.energy.2024.130843
34. A vortex sheet based analytical model of the curled wake behind yawed wind turbines M. Bastankhah et al. 10.1017/jfm.2021.1010
35. Quantification of 3D spatiotemporal inhomogeneity for wake characteristics with validations from field measurement and wind tunnel test X. Gao et al. 10.1016/j.energy.2022.124277
36. Large-Scale Wind Turbine’s Load Characteristics Excited by the Wind and Grid in Complex Terrain: A Review W. Li et al. 10.3390/su142417051
37. Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model Z. Deng et al. 10.3390/en16093932
38. Quantifying and clustering the wake-induced perturbations within a wind farm for load analysis A. Lovera et al. 10.1088/1742-6596/2505/1/012011
39. Breakdown of the velocity and turbulence in the wake of a wind turbine – Part 2: Analytical modelling E. Jézéquel et al. 10.5194/wes-9-119-2024
40. FarmConners market showcase results: wind farm flow control considering electricity prices K. Kölle et al. 10.5194/wes-7-2181-2022
41. 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
42. Prediction of multiple-wake velocity and wind power using a cosine-shaped wake model Z. Zhang & P. Huang 10.1016/j.renene.2023.119418
43. LiDAR and SCADA data processing for interacting wind turbine wakes with comparison to analytical wake models A. Hegazy et al. 10.1016/j.renene.2021.09.019
44. A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines E. Mahmoodi et al. 10.3390/en16155710
45. Flow in a large wind field with multiple actuators in the presence of constant vorticity S. Basu et al. 10.1063/5.0104902
46. Discussion on the spatial-temporal inhomogeneity characteristic of horizontal-axis wind turbine's wake and improvement of four typical wake models S. Zhang et al. 10.1016/j.jweia.2023.105368
47. A Meandering-Capturing Wake Model Coupled to Rotor-Based Flow-Sensing for Operational Wind Farm Flow Prediction M. Lejeune et al. 10.3389/fenrg.2022.884068
48. Validation of Meso-Wake Models for Array Efficiency Prediction Using Operational Data from Five Offshore Wind Farms J. Rodrigo et al. 10.1088/1742-6596/1618/6/062044
49. Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2 P. Fleming et al. 10.5194/wes-5-945-2020
50. Wake Statistics of Different-Scale Wind Turbines under Turbulent Boundary Layer Inflow X. Yang et al. 10.3390/en13113004
51. A new wake‐merging method for wind‐farm power prediction in the presence of heterogeneous background velocity fields L. Lanzilao & J. Meyers 10.1002/we.2669
52. Review on Small Horizontal-Axis Wind Turbines K. Ismail et al. 10.1007/s13369-023-08314-6