IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v256y2026ipfs0960148125020737.html

Wake characteristics and scalar transport equation for energy recovery analysis under different tip speed ratio conditions

Author

Listed:
  • Tang, Qinghong
  • Sun, Yifan
  • Wu, Yuxin
  • Zhao, Mengshang
  • Li, Changhua
  • Duan, Peiyao
  • Lyu, Junfu

Abstract

To analyze the quantitative characterization of energy recovery, a quantitative method of scalar transport equation is employed to characterize the process of wake energy exchange in wakes. The computational fluid dynamics with parameterized method actuator line model is performed to study wake features under various tip speed ratio conditions. Large velocity deficit and significant turbulence intensity appear under high tip speed ratio condition and velocity rapidly recovers in wakes. More intense vorticity and stronger vortex are induced after blade tip and nacelle on high tip speed ratio than low condition. The scalar transport equation was embedded into computational fluid dynamics solver to label the deficit energy and its recovery during solution. The solved scalar can reflect the energy state in wake and reveal the process of energy recovery quantitatively. Pearson correlation coefficient is 0.962 between scalar transport method and kinetic method. The wake energy recovers to approximately 60 % of the inflow energy at 8 rotor diameters downstream. The scalar transport method can calculate wake recovery rate quantitatively and reflect the spatial details of wake energy exchange intuitively. The scalar transport equation method can be used to improve power output by optimization of wind turbine layout or operating strategies. https://github.com/CAME-THU/Scalar-Transport-Model.git.

Suggested Citation

  • Tang, Qinghong & Sun, Yifan & Wu, Yuxin & Zhao, Mengshang & Li, Changhua & Duan, Peiyao & Lyu, Junfu, 2026. "Wake characteristics and scalar transport equation for energy recovery analysis under different tip speed ratio conditions," Renewable Energy, Elsevier, vol. 256(PF).
  • Handle: RePEc:eee:renene:v:256:y:2026:i:pf:s0960148125020737
    DOI: 10.1016/j.renene.2025.124409
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148125020737
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2025.124409?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Gao, Zhiteng & Li, Ye & Wang, Tongguang & Shen, Wenzhong & Zheng, Xiaobo & Pröbsting, Stefan & Li, Deshun & Li, Rennian, 2021. "Modelling the nacelle wake of a horizontal-axis wind turbine under different yaw conditions," Renewable Energy, Elsevier, vol. 172(C), pages 263-275.
    2. Liu, Jie & Feng, Lele & Wu, Yuxin & Feng, Renhai & Chen, Shukuan & Zhao, Dongqiang, 2024. "Numerical investigation on H2S formation in a pulverized coal-fired boiler using recycled flue gas as near-wall air," Energy, Elsevier, vol. 313(C).
    3. Yu, An & Tang, Yibo & Tang, Qinghong & Cai, Jianguo & Zhao, Lei & Ge, Xinfeng, 2022. "Energy analysis of Francis turbine for various mass flow rate conditions based on entropy production theory," Renewable Energy, Elsevier, vol. 183(C), pages 447-458.
    4. Sarlak, H. & Meneveau, C. & Sørensen, J.N., 2015. "Role of subgrid-scale modeling in large eddy simulation of wind turbine wake interactions," Renewable Energy, Elsevier, vol. 77(C), pages 386-399.
    5. Amiri, Mojtaba Maali & Shadman, Milad & Estefen, Segen F., 2024. "A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    6. Han, Cong & Banerjee, Arindam, 2024. "Near wake evolution of a tidal stream turbine due to asymmetric sheared turbulent inflow with different integral length scales," Renewable Energy, Elsevier, vol. 237(PD).
    7. Sedaghatizadeh, Nima & Arjomandi, Maziar & Kelso, Richard & Cazzolato, Benjamin & Ghayesh, Mergen H., 2018. "Modelling of wind turbine wake using large eddy simulation," Renewable Energy, Elsevier, vol. 115(C), pages 1166-1176.
    8. Xu, Zongyuan & Gao, Xiaoxia & Zhu, Yuting & Gong, Xiaoyu & Han, Zhonghe & Zhu, Xiaoxun & Wang, Yu & Zhao, Wensheng, 2025. "Wake characteristics of wind turbine in anisotropic terrain based on field experiment combined with LES," Renewable Energy, Elsevier, vol. 252(C).
    9. Florian Ries & Yongxiang Li & Dario Klingenberg & Kaushal Nishad & Johannes Janicka & Amsini Sadiki, 2018. "Near-Wall Thermal Processes in an Inclined Impinging Jet: Analysis of Heat Transport and Entropy Generation Mechanisms," Energies, MDPI, vol. 11(6), pages 1-23, May.
    10. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Experimental investigation of the performance and wake effect of a small-scale wind turbine in a wind tunnel," Energy, Elsevier, vol. 166(C), pages 819-833.
    11. Bayron, Paul & Kelso, Richard & Chin, Rey, 2024. "Experimental investigation of tip-speed-ratio influence on horizontal-axis wind turbine wake dynamics," Renewable Energy, Elsevier, vol. 225(C).
    12. Yu-Ting Wu & Chang-Yu Lin & Che-Ming Hsu, 2020. "An Experimental Investigation of Wake Characteristics and Power Generation Efficiency of a Small Wind Turbine under Different Tip Speed Ratios," Energies, MDPI, vol. 13(8), pages 1-19, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Arabgolarcheh, Alireza & Rouhollahi, Amirhossein & Benini, Ernesto, 2023. "Analysis of middle-to-far wake behind floating offshore wind turbines in the presence of multiple platform motions," Renewable Energy, Elsevier, vol. 208(C), pages 546-560.
    2. Gao, Zhiteng & Li, Ye & Wang, Tongguang & Shen, Wenzhong & Zheng, Xiaobo & Pröbsting, Stefan & Li, Deshun & Li, Rennian, 2021. "Modelling the nacelle wake of a horizontal-axis wind turbine under different yaw conditions," Renewable Energy, Elsevier, vol. 172(C), pages 263-275.
    3. Wen, Jiahao & Zhou, Lei & Zhang, Hongfu, 2023. "Mode interpretation of blade number effects on wake dynamics of small-scale horizontal axis wind turbine," Energy, Elsevier, vol. 263(PA).
    4. Amiri, Mojtaba Maali & Shadman, Milad & Estefen, Segen F., 2024. "A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    5. Meng, Haoran & Ma, Zhe & Dou, Bingzheng & Zeng, Pan & Lei, Liping, 2020. "Investigation on the performance of a novel forward-folding rotor used in a downwind horizontal-axis turbine," Energy, Elsevier, vol. 190(C).
    6. Fei Zhao & Yihan Gao & Tengyuan Wang & Jinsha Yuan & Xiaoxia Gao, 2020. "Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements," Sustainability, MDPI, vol. 12(6), pages 1-14, March.
    7. Liu, Songyang & Xin, Zhiqiang & Wang, Lei & Xu, Yanming & Cai, Zhiming, 2025. "Fluid–structure interaction simulation of the effect of static yaw control on the aerodynamic responses and wake characteristics of floating offshore wind turbines," Energy, Elsevier, vol. 330(C).
    8. Fan, Shuanglong & Liu, Zhenqing, 2025. "Investigation of fully coupled wind field simulations in complex terrain wind farms considering automatic upwind control of turbines," Renewable Energy, Elsevier, vol. 239(C).
    9. Shen, Wen Zhong & Lin, Jian Wei & Jiang, Yu Hang & Feng, Ju & Cheng, Li & Zhu, Wei Jun, 2023. "A novel yaw wake model for wind farm control applications," Renewable Energy, Elsevier, vol. 218(C).
    10. Ti, Zilong & Deng, Xiao Wei & Yang, Hongxing, 2020. "Wake modeling of wind turbines using machine learning," Applied Energy, Elsevier, vol. 257(C).
    11. Salim Abdullah Bazher & Juyeol Park & Jungkeun Oh & Daewon Seo, 2024. "Numerical Investigation of Wake Characteristics for Scaled 20 kW Wind Turbine Models with Various Size Factors," Energies, MDPI, vol. 17(17), pages 1-27, September.
    12. Wei Zhang & Huiren Zhu & Guangchao Li, 2020. "Experimental Study of Heat Transfer on the Internal Surfaces of a Double-Wall Structure with Pin Fin Array," Energies, MDPI, vol. 13(24), pages 1-17, December.
    13. Sun, Haiying & Yang, Hongxing, 2020. "Numerical investigation of the average wind speed of a single wind turbine and development of a novel three-dimensional multiple wind turbine wake model," Renewable Energy, Elsevier, vol. 147(P1), pages 192-203.
    14. Rezaeiha, Abdolrahim & Micallef, Daniel, 2021. "Wake interactions of two tandem floating offshore wind turbines: CFD analysis using actuator disc model," Renewable Energy, Elsevier, vol. 179(C), pages 859-876.
    15. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Mori, Naoya, 2017. "Investigation of wake characteristics of a Horizontal Axis Wind Turbine in vertical axis direction with field experiments," Energy, Elsevier, vol. 141(C), pages 262-272.
    16. Sarlak, H. & Nishino, T. & Martínez-Tossas, L.A. & Meneveau, C. & Sørensen, J.N., 2016. "Assessment of blockage effects on the wake characteristics and power of wind turbines," Renewable Energy, Elsevier, vol. 93(C), pages 340-352.
    17. Ruoping Chu & Kai Wang, 2025. "CFD in Urban Wind Resource Assessments: A Review," Energies, MDPI, vol. 18(10), pages 1-21, May.
    18. Wang, Mingwei & Zhang, Mingming & Qin, Caiyan & Sun, Haiying & Deng, Xiaowei, 2026. "A data-driven double-Gaussian wake model reflecting the wake evolution process," Renewable Energy, Elsevier, vol. 257(C).
    19. Deskos, Georgios & Laizet, Sylvain & Piggott, Matthew D., 2019. "Turbulence-resolving simulations of wind turbine wakes," Renewable Energy, Elsevier, vol. 134(C), pages 989-1002.
    20. Hoseinzadeh, Siamak & Astiaso Garcia, Davide & Huang, Lizhen, 2023. "Grid-connected renewable energy systems flexibility in Norway islands’ Decarbonization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:256:y:2026:i:pf:s0960148125020737. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.