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High-resolution numerical simulation of the performance of vertical axis wind turbines in urban area: Part II, array of vertical axis wind turbines between buildings

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  • Xu, Wenhao
  • Li, Ye
  • Li, Gaohua
  • Li, Shoutu
  • Zhang, Chen
  • Wang, Fuxin

Abstract

Vertical axis wind turbines can harvest wind energy from every direction, and they are suitable for the complex flow conditions in urban areas. The flow field around buildings consists some high speed regions, and the blockage effect can provide higher wind velocity. Meanwhile, they can be installed at a certain altitude with no interference to pedestrians and vehicles. In this paper, we investigate the characteristics of wind turbines in an array by arranging them between two buildings. For this aim, a high-resolution numerical simulation method is adopted to simulate the accurate flow field and force coefficients. The high-resolution numerical simulation method is composed of adaptive mesh refinement and overset grid techniques. Firstly, there are two array types with wind turbines uniformly arranged in a line, which is perpendicular to the free stream. The result shows that array type A with asymmetric wake achieves a greater mean power coefficient. It reveals that the wake matching phenomenon of array type B causes a loss of wind energy between each couple. Secondly, five column positions between the two buildings are arranged in different positions. The five positions correspond to different flow conditions, and they belong to three typical processes: contraction acceleration process, uniform velocity process, and expansion deceleration process. When mounting array type A in contraction acceleration or expansion deceleration regions, the velocity profile is non-uniform along with the array. The power coefficients of wind turbines in one array are significantly different from each other. The array in the contraction acceleration region reaches the maximum mean power coefficient. Thirdly, in order to evaluate the influence of wind directions in urban area, there are four cases with different wind directions. The simulation results show that the array at α∞=15∘ obtains the maximum mean power coefficient. In summary, the mean output power of the wind turbine array in urban areas is always greater than that of a single wind turbine.

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  • Xu, Wenhao & Li, Ye & Li, Gaohua & Li, Shoutu & Zhang, Chen & Wang, Fuxin, 2021. "High-resolution numerical simulation of the performance of vertical axis wind turbines in urban area: Part II, array of vertical axis wind turbines between buildings," Renewable Energy, Elsevier, vol. 176(C), pages 25-39.
    • Handle: RePEc:eee:renene:v:176:y:2021:i:c:p:25-39
    DOI: 10.1016/j.renene.2021.05.011
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    Cited by:

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    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. Luca Salvadori & Annalisa Di Bernardino & Giorgio Querzoli & Simone Ferrari, 2021. "A Novel Automatic Method for the Urban Canyon Parametrization Needed by Turbulence Numerical Simulations for Wind Energy Potential Assessment," Energies, MDPI, vol. 14(16), pages 1-22, August.
    7. Meng, Fantai & Sergiienko, Nataliia & Ding, Boyin & Zhou, Binzhen & Silva, Leandro Souza Pinheiro Da & Cazzolato, Benjamin & Li, Ye, 2023. "Co-located offshore wind–wave energy systems: Can motion suppression and reliable power generation be achieved simultaneously?," Applied Energy, Elsevier, vol. 331(C).
    8. Zhang, Lijun & Li, Ye & Xu, Wenhao & Gao, Zhiteng & Fang, Long & Li, Rongfu & Ding, Boyin & Zhao, Bin & Leng, Jun & He, Fenglan, 2022. "Systematic analysis of performance and cost of two floating offshore wind turbines with significant interactions," Applied Energy, Elsevier, vol. 321(C).
    9. Ogliari, Emanuele & Guilizzoni, Manfredo & Giglio, Alessandro & Pretto, Silvia, 2021. "Wind power 24-h ahead forecast by an artificial neural network and an hybrid model: Comparison of the predictive performance," Renewable Energy, Elsevier, vol. 178(C), pages 1466-1474.
    10. Xu, Wenhao & Li, Gaohua & Zheng, Xiaobo & Li, Ye & Li, Shoutu & Zhang, Chen & Wang, Fuxin, 2021. "High-resolution numerical simulation of the performance of vertical axis wind turbines in urban area: Part I, wind turbines on the side of single building," Renewable Energy, Elsevier, vol. 177(C), pages 461-474.
    11. Yadav, Sandeep & Veeravalli, Srinivas V. & Singh, Sidh Nath, 2024. "Effect of rotor spacing, overlapping and non-overlapping, on the performance of a coupled counter-rotating twin-rotor VAWT using CFD," Renewable Energy, Elsevier, vol. 221(C).

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