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Wind turbine wakes on escarpments: A wind-tunnel study

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  • Dar, Arslan Salim
  • Porté-Agel, Fernando

Abstract

In this study, the wake behind a wind turbine located on an escarpment is investigated using particle-image velocimetry in a wind tunnel. Five different escarpment models are used, which vary in the windward side shape from forward facing steps (FFS) with different curvatures at the leading-edge to sinusoidal ramp shapes with varying slopes. The difference in the base flow (flow without the turbine) resulting from the change in the geometry of the escarpment leads to significant differences in the average and dynamic characteristics of the turbine wake. The relatively high level of turbulence intensity in the base flow induced by the FFS escarpments leads to a faster wake recovery accompanied by higher turbulence kinetic energy, compared with the ramp-shaped ones. The self-similar behavior of the velocity deficit profiles in the far wake is confirmed for all the cases; unlike turbine wakes over flat terrain, the wake growth rate is found to be larger in the vertical direction than in the lateral direction. Meandering of the wake is observed to be higher on the FFS escarpment with an upward wake trajectory, compared to the ramp-shaped one. Finally, an analytical model is assessed to predict the wake velocity deficit of the turbine.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:181:y:2022:i:c:p:1258-1275
    DOI: 10.1016/j.renene.2021.09.102
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    References listed on IDEAS

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    1. Yu-Ting Wu & Fernando Porté-Agel, 2012. "Atmospheric Turbulence Effects on Wind-Turbine Wakes: An LES Study," Energies, MDPI, vol. 5(12), pages 1-23, December.
    2. Han, Xingxing & Liu, Deyou & Xu, Chang & Shen, Wen Zhong, 2018. "Atmospheric stability and topography effects on wind turbine performance and wake properties in complex terrain," Renewable Energy, Elsevier, vol. 126(C), pages 640-651.
    3. Kiran Bhaganagar & Mithu Debnath, 2014. "Implications of Stably Stratified Atmospheric Boundary Layer Turbulence on the Near-Wake Structure of Wind Turbines," Energies, MDPI, vol. 7(9), pages 1-24, September.
    4. David Bastine & Björn Witha & Matthias Wächter & Joachim Peinke, 2015. "Towards a Simplified DynamicWake Model Using POD Analysis," Energies, MDPI, vol. 8(2), pages 1-26, January.
    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. 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.
    7. Fernando Porté-Agel & Yu-Ting Wu & Chang-Hung Chen, 2013. "A Numerical Study of the Effects of Wind Direction on Turbine Wakes and Power Losses in a Large Wind Farm," Energies, MDPI, vol. 6(10), pages 1-17, October.
    8. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    9. 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.
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    Citations

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    Cited by:

    1. Fan, Shuanglong & Liu, Zhenqing, 2023. "Proposal of fully-coupled actuated disk model for wind turbine operation modeling in turbulent flow field due to complex topography," Energy, Elsevier, vol. 284(C).
    2. Wang, Tengyuan & Cai, Chang & Wang, Xinbao & Wang, Zekun & Chen, Yewen & Song, Juanjuan & Xu, Jianzhong & Zhang, Yuning & Li, Qingan, 2023. "A new Gaussian analytical wake model validated by wind tunnel experiment and LiDAR field measurements under different turbulent flow," Energy, Elsevier, vol. 271(C).
    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. Liu, Haixiao & Fu, Jianing & Liang, Zetao & Liang, Zhichang & Zhang, Yuming & Xiao, Zhong, 2022. "A simple method of fast evaluating full-field wake velocities for arbitrary wind turbine arrays on complex terrains," Renewable Energy, Elsevier, vol. 201(P1), pages 961-976.
    5. Zhang, Ziyu & Huang, Peng & Bitsuamlak, Girma & Cao, Shuyang, 2024. "Large-eddy simulation of upwind-hill effects on wind-turbine wakes and power performance," Energy, Elsevier, vol. 294(C).
    6. Dara Vahidi & Fernando Porté-Agel, 2022. "A New Streamwise Scaling for Wind Turbine Wake Modeling in the Atmospheric Boundary Layer," Energies, MDPI, vol. 15(24), pages 1-18, December.
    7. Arslan Salim Dar & Fernando Porté-Agel, 2022. "An Analytical Model for Wind Turbine Wakes under Pressure Gradient," Energies, MDPI, vol. 15(15), pages 1-13, July.

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