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Large-Eddy Simulation of Wind Turbine Wakes in Forest Terrain

Author

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  • Yunliang Li

    (The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
    School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Zhaobin Li

    (The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
    School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Zhideng Zhou

    (The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
    School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xiaolei Yang

    (The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
    School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

In this study, large-eddy simulation was employed to investigate the influence of the forest canopy on wind turbine wakes. Nine forest case studies were carried out with different vertical distributions of leaf area density (LAD) and values of leaf area index (LAI). It was found that the wake in forest canopies recovers at a faster rate when compared with the flat terrain. An interesting observation was the significant reduction in turbulence kinetic energy (TKE) in the lower part of the wake above the forest in comparison with the inflow TKE, which occurred for a wide range of turbine downstream positions. The increase of TKE, on the other hand, was mainly located in the region around the top tip. Analyses of the power spectral density showed that the increase in TKE happened at a certain range of frequencies for the forest canopy cases and at all the examined frequencies for the flat case. Wake meandering was also examined and was found to be of a higher amplitude and a lower dominant frequency for the forest cases compared with the flat case. In terms of the influence of forest canopy parameters, the LAI was found to have an impact greater than the vertical distribution of LAD. Specifically, the wake-added TKE and wake-added Reynolds shear stress were found to be approximately the same for cases with the same LAI, regardless of the vertical distribution of LAD.

Suggested Citation

  • Yunliang Li & Zhaobin Li & Zhideng Zhou & Xiaolei Yang, 2023. "Large-Eddy Simulation of Wind Turbine Wakes in Forest Terrain," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5139-:d:1097141
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    References listed on IDEAS

    as
    1. Taiwo Adedipe & Ashvinkumar Chaudhari & Antti Hellsten & Tuomo Kauranne & Heikki Haario, 2022. "Numerical Investigation on the Effects of Forest Heterogeneity on Wind-Turbine Wake," Energies, MDPI, vol. 15(5), pages 1-27, March.
    2. Stevens, Richard J.A.M. & Martínez-Tossas, Luis A. & Meneveau, Charles, 2018. "Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments," Renewable Energy, Elsevier, vol. 116(PA), pages 470-478.
    3. Xu Ning & Decheng Wan, 2019. "LES Study of Wake Meandering in Different Atmospheric Stabilities and Its Effects on Wind Turbine Aerodynamics," Sustainability, MDPI, vol. 11(24), pages 1-26, December.
    4. Lignarolo, L.E.M. & Ragni, D. & Krishnaswami, C. & Chen, Q. & Simão Ferreira, C.J. & van Bussel, G.J.W., 2014. "Experimental analysis of the wake of a horizontal-axis wind-turbine model," Renewable Energy, Elsevier, vol. 70(C), pages 31-46.
    5. Jennifer Marie Rinker & Esperanza Soto Sagredo & Leonardo Bergami, 2021. "The Importance of Wake Meandering on Wind Turbine Fatigue Loads in Wake," Energies, MDPI, vol. 14(21), pages 1-18, November.
    6. Yang, Xiaolei & Pakula, Maggie & Sotiropoulos, Fotis, 2018. "Large-eddy simulation of a utility-scale wind farm in complex terrain," Applied Energy, Elsevier, vol. 229(C), pages 767-777.
    7. Jerry L. Holechek & Hatim M. E. Geli & Mohammed N. Sawalhah & Raul Valdez, 2022. "A Global Assessment: Can Renewable Energy Replace Fossil Fuels by 2050?," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    8. Xiaolei Yang & Fotis Sotiropoulos, 2019. "A Review on the Meandering of Wind Turbine Wakes," Energies, MDPI, vol. 12(24), pages 1-20, December.
    9. Daniela Colafranceschi & Pere Sala & Fabio Manfredi, 2021. "Nature of the Wind, the Culture of the Landscape: Toward an Energy Sustainability Project in Catalonia," Sustainability, MDPI, vol. 13(13), pages 1-23, June.
    10. Yaqing Jin & Huiwen Liu & Rajan Aggarwal & Arvind Singh & Leonardo P. Chamorro, 2016. "Effects of Freestream Turbulence in a Model Wind Turbine Wake," Energies, MDPI, vol. 9(10), pages 1-12, October.
    11. Yang, Di & Meneveau, Charles & Shen, Lian, 2014. "Effect of downwind swells on offshore wind energy harvesting – A large-eddy simulation study," Renewable Energy, Elsevier, vol. 70(C), pages 11-23.
    12. André D. Thess & Philipp Lengsfeld, 2022. "Side Effects of Wind Energy: Review of Three Topics—Status and Open Questions," Sustainability, MDPI, vol. 14(23), pages 1-17, December.
    13. Abedi, Hamidreza & Sarkar, Saptarshi & Johansson, Håkan, 2021. "Numerical modelling of neutral atmospheric boundary layer flow through heterogeneous forest canopies in complex terrain (a case study of a Swedish wind farm)," Renewable Energy, Elsevier, vol. 180(C), pages 806-828.
    14. Zhaobin Li & Xiaolei Yang, 2020. "Evaluation of Actuator Disk Model Relative to Actuator Surface Model for Predicting Utility-Scale Wind Turbine Wakes," Energies, MDPI, vol. 13(14), pages 1-18, July.
    15. Zendehbad, M. & Chokani, N. & Abhari, R.S., 2016. "Impact of forested fetch on energy yield and maintenance of wind turbines," Renewable Energy, Elsevier, vol. 96(PA), pages 548-558.
    16. Shyuan Cheng & Mahmoud Elgendi & Fanghan Lu & Leonardo P. Chamorro, 2021. "On the Wind Turbine Wake and Forest Terrain Interaction," Energies, MDPI, vol. 14(21), pages 1-13, November.
    17. Yang, Xiaolei & Milliren, Christopher & Kistner, Matt & Hogg, Christopher & Marr, Jeff & Shen, Lian & Sotiropoulos, Fotis, 2021. "High-fidelity simulations and field measurements for characterizing wind fields in a utility-scale wind farm," Applied Energy, Elsevier, vol. 281(C).
    18. Victor P. Stein & Hans-Jakob Kaltenbach, 2019. "Non-Equilibrium Scaling Applied to the Wake Evolution of a Model Scale Wind Turbine," Energies, MDPI, vol. 12(14), pages 1-24, July.
    19. Zhaobin Li & Xiaohao Liu & Xiaolei Yang, 2022. "Review of Turbine Parameterization Models for Large-Eddy Simulation of Wind Turbine Wakes," Energies, MDPI, vol. 15(18), pages 1-28, September.
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