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Mean and turbulent kinetic energy budgets inside and above very large wind farms under conventionally-neutral condition

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  • Abkar, Mahdi
  • Porté-Agel, Fernando

Abstract

In this study, large-eddy simulations (LES) is combined with a turbine model to investigate all the terms in the budgets of mean and turbulent kinetic energy (TKE) inside and above very large wind farms. Emphasis is placed on quantifying the relative contribution of the thermal stratification in the free-atmosphere and wind-turbine spacing on the energy balance. The mean kinetic energy budget through the wind farms indicates that the magnitude of the kinetic energy entrainment form the free atmosphere into the boundary layer increases by increasing the density of the farms and decreasing the static stability in the free atmosphere, leading to larger power output from the wind farms. This entrainment is the only source of kinetic energy to balance that extracted by the turbines inside very large wind farms. In addition, it is shown that the distribution of the kinetic energy flux above the wind turbines, at top-tip level, is quite heterogeneous and its magnitude just behind the wind turbines is much larger due to the strong wind shear at that level. The simulation results also show that increasing the wind-farm density leads to an increase in the boundary-layer height, the ratio of the ageostrophic to the geostrophic velocity component inside the boundary layer, and the potential temperature near the surface. Detailed analysis of the TKE budget through the wind farms reveals also an important effect of the thermal stratification and wind turbine spacing on the magnitude and spatial distribution of the shear production, dissipation rate and transport terms. In particular, the shear production and dissipation rate have a peak at the turbine-top level, where the wind shear is largest, and their magnitude increases as the static stability in the free atmosphere and the wind-turbine spacing decrease.

Suggested Citation

  • Abkar, Mahdi & Porté-Agel, Fernando, 2014. "Mean and turbulent kinetic energy budgets inside and above very large wind farms under conventionally-neutral condition," Renewable Energy, Elsevier, vol. 70(C), pages 142-152.
  • Handle: RePEc:eee:renene:v:70:y:2014:i:c:p:142-152
    DOI: 10.1016/j.renene.2014.03.050
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    References listed on IDEAS

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    1. Mahdi Abkar & Fernando Porté-Agel, 2013. "The Effect of Free-Atmosphere Stratification on Boundary-Layer Flow and Power Output from Very Large Wind Farms," Energies, MDPI, vol. 6(5), pages 1-24, April.
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    Cited by:

    1. 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.
    2. Mahdi Abkar & Jens Nørkær Sørensen & Fernando Porté-Agel, 2018. "An Analytical Model for the Effect of Vertical Wind Veer on Wind Turbine Wakes," Energies, MDPI, vol. 11(7), pages 1-10, July.
    3. Zhang, Zhihao & Yang, Haoran & Zhao, Yongsheng & Han, Zhaolong & Zhou, Dai & Zhang, Jianhua & Tu, Jiahuang & Chen, Mingsheng, 2024. "A novel wake control strategy for a twin-rotor floating wind turbine: Mitigating wake effect," Energy, Elsevier, vol. 287(C).
    4. Ka Ling Wu & Fernando Porté-Agel, 2017. "Flow Adjustment Inside and Around Large Finite-Size Wind Farms," Energies, MDPI, vol. 10(12), pages 1-23, December.
    5. Amin Niayifar & Fernando Porté-Agel, 2016. "Analytical Modeling of Wind Farms: A New Approach for Power Prediction," Energies, MDPI, vol. 9(9), pages 1-13, September.
    6. Liu, Wenyi, 2016. "Design and kinetic analysis of wind turbine blade-hub-tower coupled system," Renewable Energy, Elsevier, vol. 94(C), pages 547-557.
    7. Tristan Revaz & Fernando Porté-Agel, 2021. "Large-Eddy Simulation of Wind Turbine Flows: A New Evaluation of Actuator Disk Models," Energies, MDPI, vol. 14(13), pages 1-22, June.
    8. 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.
    9. Sharma, V. & Cortina, G. & Margairaz, F. & Parlange, M.B. & Calaf, M., 2018. "Evolution of flow characteristics through finite-sized wind farms and influence of turbine arrangement," Renewable Energy, Elsevier, vol. 115(C), pages 1196-1208.
    10. 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.
    11. Jacob R. West & Sanjiva K. Lele, 2020. "Wind Turbine Performance in Very Large Wind Farms: Betz Analysis Revisited," Energies, MDPI, vol. 13(5), pages 1-25, March.
    12. Claire VerHulst & Charles Meneveau, 2015. "Altering Kinetic Energy Entrainment in Large Eddy Simulations of Large Wind Farms Using Unconventional Wind Turbine Actuator Forcing," Energies, MDPI, vol. 8(1), pages 1-17, January.
    13. Yang, Haoze & Ge, Mingwei & Abkar, Mahdi & Yang, Xiang I.A., 2022. "Large-eddy simulation study of wind turbine array above swell sea," Energy, Elsevier, vol. 256(C).
    14. Dar, Arslan Salim & Porté-Agel, Fernando, 2022. "Wind turbine wakes on escarpments: A wind-tunnel study," Renewable Energy, Elsevier, vol. 181(C), pages 1258-1275.
    15. Zehtabiyan-Rezaie, Navid & Abkar, Mahdi, 2024. "An extended k−ɛ model for wake-flow simulation of wind farms," Renewable Energy, Elsevier, vol. 222(C).

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