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Wind turbine wake models developed at the technical university of Denmark: A review

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Cited by:

  1. Pascasio, Jethro Daniel A. & Esparcia, Eugene A. & Castro, Michael T. & Ocon, Joey D., 2021. "Comparative assessment of solar photovoltaic-wind hybrid energy systems: A case for Philippine off-grid islands," Renewable Energy, Elsevier, vol. 179(C), pages 1589-1607.
  2. Yang, Kun & Deng, Xiaowei & Ti, Zilong & Yang, Shanghui & Huang, Senbin & Wang, Yuhang, 2023. "A data-driven layout optimization framework of large-scale wind farms based on machine learning," Renewable Energy, Elsevier, vol. 218(C).
  3. Thé, Jesse & Yu, Hesheng, 2017. "A critical review on the simulations of wind turbine aerodynamics focusing on hybrid RANS-LES methods," Energy, Elsevier, vol. 138(C), pages 257-289.
  4. Manisha Sawant & Sameer Thakare & A. Prabhakara Rao & Andrés E. Feijóo-Lorenzo & Neeraj Dhanraj Bokde, 2021. "A Review on State-of-the-Art Reviews in Wind-Turbine- and Wind-Farm-Related Topics," Energies, MDPI, vol. 14(8), pages 1-30, April.
  5. Rebecca J. Barthelmie & Kelsey B. Thompson & Sara C. Pryor, 2025. "Factors Impacting Projected Annual Energy Production from Offshore Wind Farms on the US East and West Coasts," Energies, MDPI, vol. 18(15), pages 1-34, July.
  6. Lu, Hongkun & Gao, Xiaoxia & Yu, Jinxiao & Zhao, Qiansheng & Zhu, Xiaoxun & Ma, Wanli & Cao, Jingyuan & Wang, Yu, 2025. "Analysis and prediction of incoming wind speed for turbines in complex wind farm: Accounting for meteorological factors and spatiotemporal characteristics of wind farm," Applied Energy, Elsevier, vol. 381(C).
  7. Ziyu Zhang & Peng Huang & Haocheng Sun, 2020. "A Novel Analytical Wake Model with a Cosine-Shaped Velocity Deficit," Energies, MDPI, vol. 13(13), pages 1-20, June.
  8. Pérez Albornoz, C. & Escalante Soberanis, M.A. & Ramírez Rivera, V. & Rivero, M., 2022. "Review of atmospheric stability estimations for wind power applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
  9. Matthias Ritter & Simone Pieralli & Martin Odening, 2017. "Neighborhood Effects in Wind Farm Performance: A Regression Approach," Energies, MDPI, vol. 10(3), pages 1-16, March.
  10. Jin, Yuqing & Ju, Ping & Rehtanz, Christian & Wu, Feng & Pan, Xueping, 2018. "Equivalent modeling of wind energy conversion considering overall effect of pitch angle controllers in wind farm," Applied Energy, Elsevier, vol. 222(C), pages 485-496.
  11. Dong, Xinghui & Li, Jia & Gao, Di & Zheng, Kai, 2021. "Wind speed modeling for cascade clusters of wind turbines Part 2: Wind speed reduction and aggregation superposition," Energy, Elsevier, vol. 215(PB).
  12. Sebastiani, Alessandro & Peña, Alfredo & Troldborg, Niels, 2023. "Numerical evaluation of multivariate power curves for wind turbines in wakes using nacelle lidars," Renewable Energy, Elsevier, vol. 202(C), pages 419-431.
  13. Yin, Xiuxing & Zhang, Wencan & Jiang, Zhansi & Pan, Li, 2020. "Data-driven multi-objective predictive control of offshore wind farm based on evolutionary optimization," Renewable Energy, Elsevier, vol. 160(C), pages 974-986.
  14. Pollini, Nicolò, 2022. "Topology optimization of wind farm layouts," Renewable Energy, Elsevier, vol. 195(C), pages 1015-1027.
  15. Amin Allah, Veisi & Shafiei Mayam, Mohammad Hossein, 2017. "Large Eddy Simulation of flow around a single and two in-line horizontal-axis wind turbines," Energy, Elsevier, vol. 121(C), pages 533-544.
  16. Yaqing Jin & Huiwen Liu & Rajan Aggarwal & Arvind Singh & Leonardo P. Chamorro, 2016. "Effects of Freestream Turbulence in a Model Wind Turbine Wake," Energies, MDPI, vol. 9(10), pages 1-12, October.
  17. Khadijah Barashid & Amr Munshi & Ahmad Alhindi, 2023. "Wind Farm Power Prediction Considering Layout and Wake Effect: Case Study of Saudi Arabia," Energies, MDPI, vol. 16(2), pages 1-22, January.
  18. Dhiman, Harsh S. & Deb, Dipankar & Foley, Aoife M., 2020. "Bilateral Gaussian Wake Model Formulation for Wind Farms: A Forecasting based approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
  19. Ti, Zilong & Deng, Xiao Wei & Zhang, Mingming, 2021. "Artificial Neural Networks based wake model for power prediction of wind farm," Renewable Energy, Elsevier, vol. 172(C), pages 618-631.
  20. Ge, Mingwei & Wu, Ying & Liu, Yongqian & Li, Qi, 2019. "A two-dimensional model based on the expansion of physical wake boundary for wind-turbine wakes," Applied Energy, Elsevier, vol. 233, pages 975-984.
  21. Kuichao Ma & Jiaxin Zou & Qingyang Fan & Xiaodong Wang & Wei Zhang & Wei Fan, 2024. "Wind Turbine Wake Regulation Method Coupling Actuator Model and Engineering Wake Model," Energies, MDPI, vol. 17(23), pages 1-19, November.
  22. Li, B. & Zhou, D.L. & Wang, Y. & Shuai, Y. & Liu, Q.Z. & Cai, W.H., 2020. "The design of a small lab-scale wind turbine model with high performance similarity to its utility-scale prototype," Renewable Energy, Elsevier, vol. 149(C), pages 435-444.
  23. Böhme, Gustavo S. & Fadigas, Eliane A. & Gimenes, André L.V. & Tassinari, Carlos E.M., 2018. "Wake effect measurement in complex terrain - A case study in Brazilian wind farms," Energy, Elsevier, vol. 161(C), pages 277-283.
  24. Zhang, Ziyu & Huang, Peng, 2023. "Prediction of multiple-wake velocity and wind power using a cosine-shaped wake model," Renewable Energy, Elsevier, vol. 219(P1).
  25. Linlin Tian & Yilei Song & Ning Zhao & Wenzhong Shen & Tongguang Wang, 2019. "AD/RANS Simulations of Wind Turbine Wake Flow Employing the RSM Turbulence Model: Impact of Isotropic and Anisotropic Inflow Conditions," Energies, MDPI, vol. 12(21), pages 1-14, October.
  26. Christy Pérez & Michel Rivero & Mauricio Escalante & Victor Ramirez & Damien Guilbert, 2023. "Influence of Atmospheric Stability on Wind Turbine Energy Production: A Case Study of the Coastal Region of Yucatan," Energies, MDPI, vol. 16(10), pages 1-20, May.
  27. Yutaka Hara & Yoshifumi Jodai & Tomoyuki Okinaga & Masaru Furukawa, 2021. "Numerical Analysis of the Dynamic Interaction between Two Closely Spaced Vertical-Axis Wind Turbines," Energies, MDPI, vol. 14(8), pages 1-23, April.
  28. Jirarote Buranarote & Yutaka Hara & Masaru Furukawa & Yoshifumi Jodai, 2022. "Method to Predict Outputs of Two-Dimensional VAWT Rotors by Using Wake Model Mimicking the CFD-Created Flow Field," Energies, MDPI, vol. 15(14), pages 1-29, July.
  29. Ti, Zilong & Deng, Xiao Wei & Yang, Hongxing, 2020. "Wake modeling of wind turbines using machine learning," Applied Energy, Elsevier, vol. 257(C).
  30. Minh-Quang Tran & Yi-Chen Li & Chen-Yang Lan & Meng-Kun Liu, 2020. "Wind Farm Fault Detection by Monitoring Wind Speed in the Wake Region," Energies, MDPI, vol. 13(24), pages 1-16, December.
  31. Dong, Guodan & Qin, Jianhua & Wu, Chutian & Xu, Chang & Yang, Xiaolei, 2026. "Reinforcement learning-enhanced genetic algorithm for wind farm layout optimization," Renewable Energy, Elsevier, vol. 259(C).
  32. Yutaka Hara & Md. Shameem Moral & Aoi Ide & Yoshifumi Jodai, 2025. "Fast Simulation of the Flow Field in a VAWT Wind Farm Using the Numerical Data Obtained by CFD Analysis for a Single Rotor," Energies, MDPI, vol. 18(1), pages 1-32, January.
  33. Archer, Cristina L. & Vasel-Be-Hagh, Ahmadreza & Yan, Chi & Wu, Sicheng & Pan, Yang & Brodie, Joseph F. & Maguire, A. Eoghan, 2018. "Review and evaluation of wake loss models for wind energy applications," Applied Energy, Elsevier, vol. 226(C), pages 1187-1207.
  34. Dhiman, Harsh S. & Deb, Dipankar & Foley, Aoife M., 2020. "Lidar assisted wake redirection in wind farms: A data driven approach," Renewable Energy, Elsevier, vol. 152(C), pages 484-493.
  35. Keane, Aidan, 2021. "Advancement of an analytical double-Gaussian full wind turbine wake model," Renewable Energy, Elsevier, vol. 171(C), pages 687-708.
  36. Syed Ahmed Kabir, Ijaz Fazil & Safiyullah, Ferozkhan & Ng, E.Y.K. & Tam, Vivian W.Y., 2020. "New analytical wake models based on artificial intelligence and rivalling the benchmark full-rotor CFD predictions under both uniform and ABL inflows," Energy, Elsevier, vol. 193(C).
  37. Tian, Linlin & Song, Yilei & Xiao, Pengcheng & Zhao, Ning & Shen, Wenzhong & Zhu, Chunling, 2022. "A new three-dimensional analytical model for wind turbine wake turbulence intensity predictions," Renewable Energy, Elsevier, vol. 189(C), pages 762-776.
  38. Guido Pantuza, 2025. "Exact Hybrid Approach to the Wind Farm Layout Optimisation Problem," SN Operations Research Forum, Springer, vol. 6(3), pages 1-18, September.
  39. Xiao, Pengcheng & Tian, Linlin & Zhao, Ning & Song, Yilei & Wang, Zhenming & Lu, Xiyun, 2026. "An integrated model for predicting wind turbine wake velocity and turbulence intensity under different atmospheric stability regimes," Renewable Energy, Elsevier, vol. 256(PA).
  40. Zhenzhou Shao & Ying Wu & Li Li & Shuang Han & Yongqian Liu, 2019. "Multiple Wind Turbine Wakes Modeling Considering the Faster Wake Recovery in Overlapped Wakes," Energies, MDPI, vol. 12(4), pages 1-14, February.
  41. Jiufa Cao & Weijun Zhu & Xinbo Wu & Tongguang Wang & Haoran Xu, 2018. "An Aero-acoustic Noise Distribution Prediction Methodology for Offshore Wind Farms," Energies, MDPI, vol. 12(1), pages 1-16, December.
  42. Zehtabiyan-Rezaie, Navid & Abkar, Mahdi, 2024. "An extended k−ɛ model for wake-flow simulation of wind farms," Renewable Energy, Elsevier, vol. 222(C).
  43. Richmond, M. & Sobey, A. & Pandit, R. & Kolios, A., 2020. "Stochastic assessment of aerodynamics within offshore wind farms based on machine-learning," Renewable Energy, Elsevier, vol. 161(C), pages 650-661.
  44. repec:hum:wpaper:sfb649dp2016-012 is not listed on IDEAS
  45. Oscar Saborío-Romano & Ali Bidadfar & Ömer Göksu & Lorenzo Zeni & Nicolaos A. Cutululis, 2019. "Power Oscillation Damping from Offshore Wind Farms Connected to HVDC via Diode Rectifiers," Energies, MDPI, vol. 12(17), pages 1-15, September.
  46. Li, Tian & Yang, Baoshan & Yang, Qingshan & Zhang, Mingming & Hu, Weicheng & Guo, Kunpeng, 2026. "Wind farm layout optimization with multi-type wind turbines for minimizing levelized cost of energy," Renewable Energy, Elsevier, vol. 270(C).
  47. Kyoungboo Yang, 2020. "Determining an Appropriate Parameter of Analytical Wake Models for Energy Capture and Layout Optimization on Wind Farms," Energies, MDPI, vol. 13(3), pages 1-17, February.
  48. Michael F. Howland & John O. Dabiri, 2019. "Wind Farm Modeling with Interpretable Physics-Informed Machine Learning," Energies, MDPI, vol. 12(14), pages 1-21, July.
  49. Bingzheng Dou & Zhanpei Yang & Michele Guala & Timing Qu & Liping Lei & Pan Zeng, 2020. "Comparison of Different Driving Modes for the Wind Turbine Wake in Wind Tunnels," Energies, MDPI, vol. 13(8), pages 1-17, April.
  50. Chen, Jian & Zhang, Yu & Xu, Zhongyun & Li, Chun, 2023. "Flow characteristics analysis and power comparison for two novel types of vertically staggered wind farms," Energy, Elsevier, vol. 263(PE).
  51. Zhang, Lidong & Yang, Shiyu & Wei, Fulong & Zhong, Xiaohui & Hu, Tianyu, 2026. "A new anisotropic three-dimensional Gaussian wake model considering swirling effects for horizontal-axis wind turbine," Energy, Elsevier, vol. 348(C).
  52. Qian, Guo-Wei & Ishihara, Takeshi, 2025. "A novel double-Gaussian full wake model for wind turbines considering dependence on thrust coefficient and ambient turbulence intensity," Applied Energy, Elsevier, vol. 391(C).
  53. Warder, Simon C. & Piggott, Matthew D., 2025. "The future of offshore wind power production: Wake and climate impacts," Applied Energy, Elsevier, vol. 380(C).
  54. Yimei Wang & Yongqian Liu & Li Li & David Infield & Shuang Han, 2018. "Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method," Energies, MDPI, vol. 11(4), pages 1-19, April.
  55. Shabara, Mohamed A. & Abdelkhalik, Ossama, 2023. "Dynamic modeling of the motions of variable-shape wave energy converters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
  56. Adam Rasiński & Ziemowit Malecha, 2025. "Wake Losses, Productivity, and Cost Analysis of a Polish Offshore Wind Farm in the Baltic Sea," Energies, MDPI, vol. 18(15), pages 1-21, August.
  57. Ouro, Pablo & Ghobrial, Mina & Ali, Karim & Stallard, Tim, 2025. "Numerical modelling of offshore wind-farm cluster wakes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 215(C).
  58. Yang, Shanghui & Deng, Xiaowei & Ti, Zilong & Yan, Bowen & Yang, Qingshan, 2022. "Cooperative yaw control of wind farm using a double-layer machine learning framework," Renewable Energy, Elsevier, vol. 193(C), pages 519-537.
  59. Cockcroft, Ross & Thornber, Ben, 2026. "Computational fluid dynamics and digital twins for wind turbines: A review," Applied Energy, Elsevier, vol. 415(C).
  60. He, Ruiyang & Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2022. "Wind tunnel tests for wind turbines: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
  61. Göçmen, Tuhfe & Giebel, Gregor, 2016. "Estimation of turbulence intensity using rotor effective wind speed in Lillgrund and Horns Rev-I offshore wind farms," Renewable Energy, Elsevier, vol. 99(C), pages 524-532.
  62. Ge, Mingwei & Wu, Ying & Liu, Yongqian & Yang, Xiang I.A., 2019. "A two-dimensional Jensen model with a Gaussian-shaped velocity deficit," Renewable Energy, Elsevier, vol. 141(C), pages 46-56.
  63. Cao, Jiufa & Gao, Xiang & Shen, Xiang & Zhong, Wei & Ren, Hehe & Ke, Shitang, 2025. "Impact of hub height for enhanced performance of wind turbines under varying atmospheric stability," Applied Energy, Elsevier, vol. 401(PC).
  64. Wang, Tengyuan & Guo, Naizhi & Jia, Ning & Cai, Chang & Sun, Xiangyu & Gao, Xiaoxia & Wang, Xinbao & Song, Juanjuan & Bai, Jingyan & Zhao, Yingjiu & Yuan, Ling & Li, Qingan, 2026. "A SCADA-informed evaluation method for wake-induced power losses considering the flow heterogeneity within large-scale wind farm," Energy, Elsevier, vol. 353(C).
  65. Li, Xuyang & Qiu, Yingning & Feng, Yanhui & Wang, Zheng, 2021. "Wind turbine power prediction considering wake effects with dual laser beam LiDAR measured yaw misalignment," Applied Energy, Elsevier, vol. 299(C).
  66. Nicolai Radke & Patrick E. M. De Smet & Erika Ábrahám, 2025. "Numerical Modeling and Analysis of Shadow Flicker Using Solar Path Functions for Enhanced Predictive Accuracy," Energies, MDPI, vol. 18(2), pages 1-17, January.
  67. Li, Peiyi & Che, Yanbo & Hua, Anran & Wang, Lei & Zheng, Mengxiang & Guo, Xiaojiang, 2025. "A data-physics hybrid-driven layout optimization framework for large-scale wind farms," Applied Energy, Elsevier, vol. 392(C).
  68. Göçmen, Tuhfe & Liew, Jaime & Kadoche, Elie & Dimitrov, Nikolay & Riva, Riccardo & Andersen, Søren Juhl & Lio, Alan W.H. & Quick, Julian & Réthoré, Pierre-Elouan & Dykes, Katherine, 2025. "Data-driven wind farm flow control and challenges towards field implementation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 216(C).
  69. Dongqin Zhang & Yang Liang & Chao Li & Yiqing Xiao & Gang Hu, 2022. "Applicability of Wake Models to Predictions of Turbine-Induced Velocity Deficit and Wind Farm Power Generation," Energies, MDPI, vol. 15(19), pages 1-26, October.
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  72. Wang, Longyan & Luo, Wei & Xu, Jian & Xie, Junhang & Luo, Zhaohui & Tan, Andy C.C., 2022. "Comparative study of decentralized instantaneous and wind-interval-based controls for in-line two scale wind turbines," Renewable Energy, Elsevier, vol. 189(C), pages 1218-1233.
  73. Hornshøj-Møller, Simon D. & Nielsen, Peter D. & Forooghi, Pourya & Abkar, Mahdi, 2021. "Quantifying structural uncertainties in Reynolds-averaged Navier–Stokes simulations of wind turbine wakes," Renewable Energy, Elsevier, vol. 164(C), pages 1550-1558.
  74. Ulku, I. & Alabas-Uslu, C., 2019. "A new mathematical programming approach to wind farm layout problem under multiple wake effects," Renewable Energy, Elsevier, vol. 136(C), pages 1190-1201.
  75. Lattawan Niyomtham & Charoenporn Lertsathittanakorn & Jompob Waewsak & Yves Gagnon, 2022. "Mesoscale/Microscale and CFD Modeling for Wind Resource Assessment: Application to the Andaman Coast of Southern Thailand," Energies, MDPI, vol. 15(9), pages 1-19, April.
  76. Kuichao Ma & Mohsen Soltani & Amin Hajizadeh & Jiangsheng Zhu & Zhe Chen, 2021. "Wind Farm Power Optimization and Fault Ride-Through under Inter-Turn Short-Circuit Fault," Energies, MDPI, vol. 14(11), pages 1-16, May.
  77. Warder, Simon C. & Piggott, Matthew D., 2025. "Mapping global offshore wind wake losses, layout optimisation potential, and climate change effects," Energy, Elsevier, vol. 331(C).
  78. Huang, Ming & Ferreira, Carlos & Sciacchitano, Andrea & Scarano, Fulvio, 2022. "Wake scaling of actuator discs in different aspect ratios," Renewable Energy, Elsevier, vol. 183(C), pages 866-876.
  79. Dong, Zhikun & Chen, Yaoran & Zhou, Dai & Su, Jie & Han, Zhaolong & Cao, Yong & Bao, Yan & Zhao, Feng & Wang, Rui & Zhao, Yongsheng & Xu, Yuwang, 2022. "The mean wake model and its novel characteristic parameter of H-rotor VAWTs based on random forest method," Energy, Elsevier, vol. 239(PE).
  80. Eidi, Ali & Ghiassi, Reza & Yang, Xiang & Abkar, Mahdi, 2021. "Model-form uncertainty quantification in RANS simulations of wakes and power losses in wind farms," Renewable Energy, Elsevier, vol. 179(C), pages 2212-2223.
  81. Jian Teng & Corey D. Markfort, 2020. "A Calibration Procedure for an Analytical Wake Model Using Wind Farm Operational Data," Energies, MDPI, vol. 13(14), pages 1-19, July.
  82. Huanqiang, Zhang & Xiaoxia, Gao & Hongkun, Lu & Qiansheng, Zhao & Xiaoxun, Zhu & Yu, Wang & Fei, Zhao, 2024. "Investigation of a new 3D wake model of offshore floating wind turbines subjected to the coupling effects of wind and wave," Applied Energy, Elsevier, vol. 365(C).
  83. Seunggun Hyun & Youn Cheol Park, 2024. "Evaluation and Long-Term Prediction of Annual Wind Farm Energy Production," Energies, MDPI, vol. 17(21), pages 1-12, October.
  84. Wen, Xueliang & Yin, Guang & Liu, Tianhui & Ong, Muk Chen & Wang, Chao & Wang, Kai, 2025. "An optimization framework for mooring design of floating offshore wind turbines using a genetic algorithm based on a surrogate model," Renewable Energy, Elsevier, vol. 245(C).
  85. Feng, Dachuan & Li, Larry K.B. & Gupta, Vikrant & Wan, Minping, 2022. "Componentwise influence of upstream turbulence on the far-wake dynamics of wind turbines," Renewable Energy, Elsevier, vol. 200(C), pages 1081-1091.
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