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Study on interaction between the wind-turbine wake and the urban district model by large eddy simulation

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  • Ge, Mingwei
  • Zhang, Shuaibin
  • Meng, Hang
  • Ma, Hongliang

Abstract

Urban wind power shows a great potential and plays a significant role for a sustainable city. As a fundamental issue, the interaction between the wind-turbine wake and a building array is studied here via large eddy simulation. The standard actuator disc model is used to model the wind turbine, and 16 cube-shaped buildings are used to represent the urban district. It is found that due to the blocking effect of the downstream urban district, a high-pressure region is formed upstream, which dramatically changes the trajectory of the wind-turbine wake and results in a fast wake recovery. In addition, the wind-turbine wake suppresses the vertical momentum flux and thereby reduces the wind speed in the streamwise streets. At the top region of the urban block below the trajectory of the turbine wake, the turbulence intensity substantially increases at the entrance region of the building array, while the overall turbulence intensity is considerably reduced at the bottom of the block.

Suggested Citation

  • Ge, Mingwei & Zhang, Shuaibin & Meng, Hang & Ma, Hongliang, 2020. "Study on interaction between the wind-turbine wake and the urban district model by large eddy simulation," Renewable Energy, Elsevier, vol. 157(C), pages 941-950.
    • Handle: RePEc:eee:renene:v:157:y:2020:i:c:p:941-950
    DOI: 10.1016/j.renene.2020.04.134
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    References listed on IDEAS

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    Citations

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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. 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.
    4. Isabel Cristina Gil-García & María Socorro García-Cascales & Angel Molina-García, 2022. "Urban Wind: An Alternative for Sustainable Cities," Energies, MDPI, vol. 15(13), pages 1-20, June.
    5. 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.
    6. Li, Li & Wang, Bing & Ge, Mingwei & Huang, Zhi & Li, Xintao & Liu, Yongqian, 2023. "A novel superposition method for streamwise turbulence intensity of wind-turbine wakes," Energy, Elsevier, vol. 276(C).
    7. Angelo Algieri & Pietropaolo Morrone & Sergio Bova, 2020. "Techno-Economic Analysis of Biofuel, Solar and Wind Multi-Source Small-Scale CHP Systems," Energies, MDPI, vol. 13(11), pages 1-21, June.
    8. Yang, Haoze & Ge, Mingwei & Gu, Bo & Du, Bowen & Liu, Yongqian, 2022. "The effect of swell on marine atmospheric boundary layer and the operation of an offshore wind turbine," Energy, Elsevier, vol. 244(PB).
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    13. 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.
    14. 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.
    15. Paxis Marques João Roque & Shyama Pada Chowdhury & Zhongjie Huan, 2021. "Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study," Energies, MDPI, vol. 14(14), pages 1-22, July.

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