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A numerical model for wind turbine wakes based on the vortex filament method

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  • Liu, Weiqi
  • Liu, Weixing
  • Zhang, Liang
  • Sheng, Qihu
  • Zhou, Binzhen

Abstract

A numerical wake model based on the vortex filament method is proposed to predict the velocity deficit in the wake of a horizontal axis wind turbine (HAWT). By solving the evolution of the vortex system behind the wind turbine, the model calculates the distribution of the downstream velocity indirectly with very low computational cost. Instead of the usual scheme of the vortex method, the more efficient and mature blade element momentum (BEM) theory is used for the blade aerodynamics and to initialize the calculation of the vortex system evolution. The model is tested by a published wind tunnel experiment of a miniature wind turbine. The numerical results agree well with the experimental data. It is found that the core growth of the vortex filaments due to turbulence mainly dominate the velocity deficit along the downstream distance in the wake. In addition, the generalization of the model to full-scale wind turbines is discussed and within the framework of the present model, a reasonable conclusion can be obtained: wakes of wind turbines with different scales are similar.

Suggested Citation

  • Liu, Weiqi & Liu, Weixing & Zhang, Liang & Sheng, Qihu & Zhou, Binzhen, 2018. "A numerical model for wind turbine wakes based on the vortex filament method," Energy, Elsevier, vol. 157(C), pages 561-570.
    • Handle: RePEc:eee:energy:v:157:y:2018:i:c:p:561-570
    DOI: 10.1016/j.energy.2018.05.191
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    References listed on IDEAS

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    1. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (Part I: Power performance)," Energy, Elsevier, vol. 113(C), pages 713-722.
    2. Shakoor, Rabia & Hassan, Mohammad Yusri & Raheem, Abdur & Wu, Yuan-Kang, 2016. "Wake effect modeling: A review of wind farm layout optimization using Jensen׳s model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1048-1059.
    3. Zhong, Hongmin & Du, Pingan & Tang, Fangning & Wang, Li, 2015. "Lagrangian dynamic large-eddy simulation of wind turbine near wakes combined with an actuator line method," Applied Energy, Elsevier, vol. 144(C), pages 224-233.
    4. Rajper, Samina & Amin, Imran J., 2012. "Optimization of wind turbine micrositing: A comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5485-5492.
    5. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (part II: Wake characteristics)," Energy, Elsevier, vol. 113(C), pages 1304-1315.
    6. Park, Jinkyoo & Law, Kincho H., 2015. "Layout optimization for maximizing wind farm power production using sequential convex programming," Applied Energy, Elsevier, vol. 151(C), pages 320-334.
    7. Xydis, G. & Koroneos, C. & Loizidou, M., 2009. "Exergy analysis in a wind speed prognostic model as a wind farm sitting selection tool: A case study in Southern Greece," Applied Energy, Elsevier, vol. 86(11), pages 2411-2420, November.
    8. Pinon, Grégory & Mycek, Paul & Germain, Grégory & Rivoalen, Elie, 2012. "Numerical simulation of the wake of marine current turbines with a particle method," Renewable Energy, Elsevier, vol. 46(C), pages 111-126.
    9. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    10. Sebastian, T. & Lackner, M.A., 2012. "Development of a free vortex wake method code for offshore floating wind turbines," Renewable Energy, Elsevier, vol. 46(C), pages 269-275.
    11. Barthelmie, R.J. & Pryor, S.C., 2013. "An overview of data for wake model evaluation in the Virtual Wakes Laboratory," Applied Energy, Elsevier, vol. 104(C), pages 834-844.
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    Cited by:

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    2. Tang, Di & Xu, Min & Mao, Jianfeng & Zhu, Hai, 2020. "Unsteady performances of a parked large-scale wind turbine in the typhoon activity zones," Renewable Energy, Elsevier, vol. 149(C), pages 617-630.
    3. Wu, Baigong & Zhan, Mingjing & Wu, Rujian & Zhang, Xiao, 2023. "The investigation of a coaxial twin-counter-rotating turbine with variable-pitch adaptive blades," Energy, Elsevier, vol. 267(C).
    4. Pavithra Premaratne & Wei Tian & Hui Hu, 2022. "A Proper-Orthogonal-Decomposition (POD) Study of the Wake Characteristics behind a Wind Turbine Model," Energies, MDPI, vol. 15(10), pages 1-22, May.
    5. Liu, Heng-xu & Tian, Yi-nong & Liu, Wei-qi & Jin, Ye-qing & Kong, Fan-kai & Chen, Hai-long & Zhong, Yu-guang, 2023. "Aerodynamic interference characteristics of multiple unit wind turbine based on vortex filament wake model," Energy, Elsevier, vol. 268(C).
    6. Wenbin Su & Hongbo Wei & Penghua Guo & Qiao Hu & Mengyuan Guo & Yuanjie Zhou & Dayu Zhang & Zhufeng Lei & Chaohui Wang, 2021. "Research on Hydraulic Conversion Technology of Small Ocean Current Turbines for Low-Flow Current Energy Generation," Energies, MDPI, vol. 14(20), pages 1-19, October.
    7. Tian, Yinong & Zhong, Yuguang & Liu, Hengxu & Liu, Weiqi & Kong, Fankai & Chen, Hailong, 2024. "A new fast simulation method of wind turbine wake based on annular vortex element," Renewable Energy, Elsevier, vol. 229(C).
    8. Liu, Weiqi & Shi, Jian & Chen, Hailong & Liu, Hengxu & Lin, Zi & Wang, Lingling, 2021. "Lagrangian actuator model for wind turbine wake aerodynamics," Energy, Elsevier, vol. 232(C).
    9. Zheng Yuan & Jin Jiang & Jun Zang & Qihu Sheng & Ke Sun & Xuewei Zhang & Renwei Ji, 2020. "A Fast Two-Dimensional Numerical Method for the Wake Simulation of a Vertical Axis Wind Turbine," Energies, MDPI, vol. 14(1), pages 1-21, December.

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