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Study of the flow fields over simplified topographies with different roughness conditions using large eddy simulations

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  • Liu, Zhenqing
  • Diao, Zheng
  • Ishihara, Takeshi

Abstract

The parameters influencing the wind turbine fatigue load calculations, such as two-point correlations Ruu, power spectrum density Su, turbulent length scale Lu, skewness Sku, and kurtosis Kuu of the wind are examined. Four simplified topographies, i.e., a 3D hill with smooth ground (3Ds), a 3D hill with rough ground (3Dr), a 2D ridge with smooth ground (2Ds), and a 2D ridge with rough ground (2Dr) are considered to investigate the influence from the shape of the topography and the ground roughness conditions. Ruu was found to vary considerably for different hill shapes and ground roughness conditions. Sku and Kuu peaked in the shear layer region in the smooth cases, but not in the rough cases. Su exhibited concentration in the wake in the 3Ds, 3Dr, and 2Ds cases, but not in the 2Dr case. In addition, a prominent increase in Lux was observed just above the summit of the smooth 3D hill. The flow fields were further visualized using the enstrophy and Q-criteria. Coherent turbulent structures were observed to exist in the wake in the 3Ds, 3Dr, and 2Ds cases, whereas the flow was highly mixed in the wake in the 2Dr case.

Suggested Citation

  • Liu, Zhenqing & Diao, Zheng & Ishihara, Takeshi, 2019. "Study of the flow fields over simplified topographies with different roughness conditions using large eddy simulations," Renewable Energy, Elsevier, vol. 136(C), pages 968-992.
  • Handle: RePEc:eee:renene:v:136:y:2019:i:c:p:968-992
    DOI: 10.1016/j.renene.2019.01.032
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    References listed on IDEAS

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    1. Dhunny, A.Z. & Lollchund, M.R. & Rughooputh, S.D.D.V., 2017. "Wind energy evaluation for a highly complex terrain using Computational Fluid Dynamics (CFD)," Renewable Energy, Elsevier, vol. 101(C), pages 1-9.
    2. Celik, Ali Naci, 2004. "A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey," Renewable Energy, Elsevier, vol. 29(4), pages 593-604.
    3. Argüeso, D. & Businger, S., 2018. "Wind power characteristics of Oahu, Hawaii," Renewable Energy, Elsevier, vol. 128(PA), pages 324-336.
    4. Bashirzadeh Tabrizi, Amir & Whale, Jonathan & Lyons, Thomas & Urmee, Tania & Peinke, Joachim, 2017. "Modelling the structural loading of a small wind turbine at a highly turbulent site via modifications to the Kaimal turbulence spectra," Renewable Energy, Elsevier, vol. 105(C), pages 288-300.
    5. Kim, Yong-Hwan & Lim, Hee-Chang, 2017. "Effect of island topography and surface roughness on the estimation of annual energy production of offshore wind farms," Renewable Energy, Elsevier, vol. 103(C), pages 106-114.
    6. Bilal, Muhammad & Birkelund, Yngve & Homola, Matthew & Virk, Muhammad Shakeel, 2016. "Wind over complex terrain – Microscale modelling with two types of mesoscale winds at Nygårdsfjell," Renewable Energy, Elsevier, vol. 99(C), pages 647-653.
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    1. Hu, Weicheng & Yang, Qingshan & Chen, Hua-Peng & Yuan, Ziting & Li, Chen & Shao, Shuai & Zhang, Jian, 2021. "Wind field characteristics over hilly and complex terrain in turbulent boundary layers," Energy, Elsevier, vol. 224(C).

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