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Large-eddy simulation of wind turbines immersed in the wake of a cube-shaped building

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  • Ge, Mingwei
  • Gayme, Dennice F.
  • Meneveau, Charles

Abstract

Motivated by the potential of wind power based electricity generation modules in urban environments, flow properties of wind turbines operating behind a building-like wall-attached cube are investigated through large-eddy simulation. Significant power losses with increased power fluctuations are observed for the first turbine downstream of the cube. Also, the power losses and fluctuations increase with decreasing distance to the cube. However, a faster recovery of the turbine wake is observed, due to not only enhanced turbulent transport but also due to convection associated with the secondary mean flow structure behind the cube. The transport of mass, momentum and energy fluxes shows that turbines at different distances receive mean kinetic energy from different layers of air motion upstream of the cube. Associated transport tubes exhibit deflection towards to the ground behind the first turbine due to the mean flow’s downwash, which can significantly reduce the sheltering effect of turbines at further downstream locations. Therefore, when a second turbine is placed behind the first turbine, the second turbine can produce more power than in the same setting without the cube. The total power output of two turbines behind a cube can be even larger than that without the cube, in certain cases.

Suggested Citation

  • Ge, Mingwei & Gayme, Dennice F. & Meneveau, Charles, 2021. "Large-eddy simulation of wind turbines immersed in the wake of a cube-shaped building," Renewable Energy, Elsevier, vol. 163(C), pages 1063-1077.
    • Handle: RePEc:eee:renene:v:163:y:2021:i:c:p:1063-1077
    DOI: 10.1016/j.renene.2020.08.156
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    References listed on IDEAS

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    Cited by:

    1. Ma, Hongliang & Ge, Mingwei & Wu, Guangxing & Du, Bowen & Liu, Yongqian, 2021. "Formulas of the optimized yaw angles for cooperative control of wind farms with aligned turbines to maximize the power production," Applied Energy, Elsevier, vol. 303(C).
    2. Li, Li & Huang, Zhi & Ge, Mingwei & Zhang, Qiying, 2022. "A novel three-dimensional analytical model of the added streamwise turbulence intensity for wind-turbine wakes," Energy, Elsevier, vol. 238(PB).
    3. Dar, Arslan Salim & Armengol Barcos, Guillem & Porté-Agel, Fernando, 2022. "An experimental investigation of a roof-mounted horizontal-axis wind turbine in an idealized urban environment," Renewable Energy, Elsevier, vol. 193(C), pages 1049-1061.
    4. Zhang, Shuaibin & Du, Bowen & Ge, Mingwei & Zuo, Yingtao, 2022. "Study on the operation of small rooftop wind turbines and its effect on the wind environment in blocks," Renewable Energy, Elsevier, vol. 183(C), pages 708-718.
    5. Fan, Xiantao & Ge, Mingwei & Tan, Wei & Li, Qi, 2021. "Impacts of coexisting buildings and trees on the performance of rooftop wind turbines: An idealized numerical study," Renewable Energy, Elsevier, vol. 177(C), pages 164-180.
    6. Zhang, Huan & Ge, Mingwei & Liu, Yongqian & Yang, Xiang I.A., 2021. "A new coupled model for the equivalent roughness heights of wind farms," Renewable Energy, Elsevier, vol. 171(C), pages 34-46.
    7. 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.

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