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Impacts of inflow turbulence on the flow past a permeable disk

Published online by Cambridge University Press:  13 November 2024

Yunliang Li
Affiliation:
The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, PR China School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, PR China
Fengshun Zhang
Affiliation:
The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, PR China School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, PR China
Zhaobin Li
Affiliation:
The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, PR China School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, PR China
Xiaolei Yang*
Affiliation:
The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, PR China School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, PR China
*
Email address for correspondence: [email protected]

Abstract

A permeable disk serves as a simplified model for the conversion of wind energy by a horizontal axis wind turbine. In this study, we investigate how inflow turbulence intensity (TI), $I_\infty$, and inflow turbulence integral length scale, $L_\infty$, influence the flow recovery in the wake, the capability of a permeable disk in extracting turbulence kinetic energy (TKE) of the incoming flow, and the statistics of wake-added turbulence using large-eddy simulation. The simulated inflows include various TIs (i.e. $I_\infty =2.5\,\%$$25\,\%$) and integral length scales (i.e. $L_\infty / D =0.5$$2.0$) for two thrust coefficients. Simulation results show that both inflow TI and integral length scale influence flow recovery via enhanced ejections and sweeps across the wake boundary, with the former strongly affecting the position where the wake starts to recover and the latter mainly on the recovery rate. Moreover, it is shown that increasing $I_\infty$ and $L_\infty$ increases the TKE extraction by the disk, occurring mainly at scales ($s$) greater than $0.5D$ and frequencies depending on the inflow integral length scale. As for the wake-added TKE, the inflow TI mainly affects its intensity, while the inflow integral length scale affects both its intensity and the sensitive frequencies, with the spectral distributions in scale space ($s$) being similar and the peak located around $s/D=1.0$ for the considered inflows.

Type
JFM Papers
Copyright
© The Author(s), 2024. Published by Cambridge University Press.

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References

Abkar, M. & Porté-Agel, F. 2015 Influence of atmospheric stability on wind-turbine wakes: a large-eddy simulation study. Phys. Fluids 27 (3), 035104.CrossRefGoogle Scholar
Barlas, E., Buckingham, S. & van Beeck, J.P.A.J. 2016 Roughness effects on wind-turbine wake dynamics in a boundary-layer wind tunnel. Boundary-Layer Meteorol. 158, 2742.CrossRefGoogle Scholar
Bastankhah, M. & Porté-Agel, F. 2016 Experimental and theoretical study of wind turbine wakes in yawed conditions. J. Fluid Mech. 806, 506541.CrossRefGoogle Scholar
Blackmore, T., Batten, W.M.J. & Bahaj, A.S. 2014 Influence of turbulence on the wake of a marine current turbine simulator. Proc. R. Soc. A 470 (2170), 20140331.CrossRefGoogle ScholarPubMed
Carbajo Fuertes, F., Markfort, C.D. & Porté-Agel, F. 2018 Wind turbine wake characterization with nacelle-mounted wind lidars for analytical wake model validation. Remote Sens. 10 (5), 668.CrossRefGoogle Scholar
Chamorro, L.P., Guala, M., Arndt, R.E.A. & Sotiropoulos, F. 2012 On the evolution of turbulent scales in the wake of a wind turbine model. J. Turbul. 13, N27.CrossRefGoogle Scholar
Cortina, G., Calaf, M. & Cal, R.B. 2016 Distribution of mean kinetic energy around an isolated wind turbine and a characteristic wind turbine of a very large wind farm. Phys. Rev. Fluids 1 (7), 074402.CrossRefGoogle Scholar
Dong, G., Li, Z., Qin, J. & Yang, X. 2022 How far the wake of a wind farm can persist for? Theor. Appl. Mech. Lett. 12 (1), 100314.CrossRefGoogle Scholar
Dong, G., Qin, J., Li, Z. & Yang, X. 2023 Characteristics of wind turbine wakes for different blade designs. J. Fluid Mech. 965, A15.CrossRefGoogle Scholar
Gambuzza, S. & Ganapathisubramani, B. 2021 The effects of free-stream turbulence on the performance of a model wind turbine. J. Renew. Sustain. Energy 13 (2), 023304.CrossRefGoogle Scholar
Gambuzza, S. & Ganapathisubramani, B. 2023 The influence of free stream turbulence on the development of a wind turbine wake. J. Fluid Mech. 963, A19.CrossRefGoogle Scholar
Ge, L. & Sotiropoulos, F. 2007 A numerical method for solving the 3d unsteady incompressible Navier–Stokes equations in curvilinear domains with complex immersed boundaries. J. Comput. Phys. 225 (2), 17821809.CrossRefGoogle ScholarPubMed
Ge, M., Zhang, S., Meng, H. & Ma, H. 2020 Study on interaction between the wind-turbine wake and the urban district model by large eddy simulation. Renew. Energy 157, 941950.CrossRefGoogle Scholar
George, W.K. 1989 The self-preservation of turbulent flows and its relation to initial conditions and coherent structures. Adv. Turbul. 3973, 39–73.Google Scholar
Germano, M., Piomelli, U., Moin, P. & Cabot, W.H. 1991 A dynamic subgrid-scale eddy viscosity model. Phys. Fluids A 3 (7), 17601765.CrossRefGoogle Scholar
Ghate, A.S., Ghaisas, N., Lele, S.K. & Towne, A. 2018 Interaction of small scale homogenenous isotropic turbulence with an actuator disk. In 2018 Wind Energy Symposium, p. 0753.Google Scholar
He, G., Jin, G. & Yang, Y. 2017 Space-time correlations and dynamic coupling in turbulent flows. Annu. Rev. Fluid Mech. 49, 5170.CrossRefGoogle Scholar
Heisel, M., Hong, J. & Guala, M. 2018 The spectral signature of wind turbine wake meandering: a wind tunnel and field-scale study. Wind Energy 21 (9), 715731.CrossRefGoogle Scholar
Ishihara, T. & Qian, G.-W. 2018 A new Gaussian-based analytical wake model for wind turbines considering ambient turbulence intensities and thrust coefficient effects. J. Wind Engng Ind. Aerodyn. 177, 275292.CrossRefGoogle Scholar
Ivanell, S., Mikkelsen, R., Sørensen, J.N. & Henningson, D. 2010 Stability analysis of the tip vortices of a wind turbine. Wind Energy 13 (8), 705715.CrossRefGoogle Scholar
Jin, Y., Liu, H., Aggarwal, R., Singh, A. & Chamorro, L.P. 2016 Effects of freestream turbulence in a model wind turbine wake. Energies 9 (10), 830.CrossRefGoogle Scholar
Kankanwadi, K.S. & Buxton, O.R.H. 2020 Turbulent entrainment into a cylinder wake from a turbulent background. J. Fluid Mech. 905, A35.CrossRefGoogle Scholar
Knoll, D.A. & Keyes, D.E. 2004 Jacobian-free Newton–Krylov methods: a survey of approaches and applications. J. Comput. Phys. 193 (2), 357397.CrossRefGoogle Scholar
Li, Z., Dong, G. & Yang, X. 2022 Onset of wake meandering for a floating offshore wind turbine under side-to-side motion. J. Fluid Mech. 934, A29.CrossRefGoogle Scholar
Li, Z. & Yang, X. 2021 Large-eddy simulation on the similarity between wakes of wind turbines with different yaw angles. J. Fluid Mech. 921, A11.CrossRefGoogle Scholar
Li, Z. & Yang, X. 2024 Resolvent-based motion-to-wake modelling of wind turbine wakes under dynamic rotor motion. J. Fluid Mech. 980, A48.CrossRefGoogle Scholar
Lissaman, P.B.S. 1979 Energy effectiveness of arbitrary arrays of wind turbines. J. Energy 3 (6), 323328.CrossRefGoogle Scholar
Liu, X., Li, Z., Yang, X., Xu, D., Kang, S. & Khosronejad, A. 2022 Large-eddy simulation of wakes of waked wind turbines. Energies 15 (8), 2899.CrossRefGoogle Scholar
Mann, J. 1998 Wind field simulation. Probab. Engng Mech. 13 (4), 269282.CrossRefGoogle Scholar
Mao, X. & Sørensen, J.N. 2018 Far-wake meandering induced by atmospheric eddies in flow past a wind turbine. J. Fluid Mech. 846, 190209.CrossRefGoogle Scholar
Martinez-Tossas, L.A., Churchfield, M.J., Yilmaz, A.E., Sarlak, H., Johnson, P.L., Sørensen, J.N., Meyers, J. & Meneveau, C. 2018 Comparison of four large-eddy simulation research codes and effects of model coefficient and inflow turbulence in actuator-line-based wind turbine modeling. J. Renew. Sustain. Energy 10 (3), 033301.CrossRefGoogle Scholar
Meneveau, C. 2019 Big wind power: seven questions for turbulence research. J. Turbul. 20 (1), 220.CrossRefGoogle Scholar
Meneveau, C., Lund, T.S. & Cabot, W.H. 1996 A lagrangian dynamic subgrid-scale model of turbulence. J. Fluid Mech. 319, 353385.CrossRefGoogle Scholar
Meyers, J. & Meneveau, C. 2013 Flow visualization using momentum and energy transport tubes and applications to turbulent flow in wind farms. J. Fluid Mech. 715, 335358.CrossRefGoogle Scholar
Saad, Y. 1993 A flexible inner-outer preconditioned GMRES algorithm. SIAM J. Sci. Comput. 14 (2), 461469.CrossRefGoogle Scholar
Sarlak, H., Meneveau, C. & Sørensen, J.N. 2015 Role of subgrid-scale modeling in large eddy simulation of wind turbine wake interactions. Renew. Energy 77, 386399.CrossRefGoogle Scholar
Schlichting, H. & Gersten, K. 2016 Boundary-Layer Theory. Springer.Google Scholar
Sirovich, L. 1987 Turbulence and the dynamics of coherent structures. I. Coherent structures. Q. Appl. Maths 45 (3), 561571.CrossRefGoogle Scholar
Sørensen, J.N. 2011 Aerodynamic aspects of wind energy conversion. Annu. Rev. Fluid Mech. 43, 427448.CrossRefGoogle Scholar
St Martin, C.M., Lundquist, J.K., Clifton, A., Poulos, G.S. & Schreck, S.J. 2016 Wind turbine power production and annual energy production depend on atmospheric stability and turbulence. Wind Energy Sci. 1 (2), 221236.CrossRefGoogle Scholar
Stein, V.P. & Kaltenbach, H.-J. 2019 Non-equilibrium scaling applied to the wake evolution of a model scale wind turbine. Energies 12 (14), 2763.CrossRefGoogle Scholar
Stevens, R.J.A.M. & Meneveau, C. 2017 Flow structure and turbulence in wind farms. Annu. Rev. Fluid Mech. 49, 311339.CrossRefGoogle Scholar
Talavera, M. & Shu, F. 2017 Experimental study of turbulence intensity influence on wind turbine performance and wake recovery in a low-speed wind tunnel. Renew. Energy 109, 363371.CrossRefGoogle Scholar
Vahidi, D. & Porté-Agel, F. 2022 A physics-based model for wind turbine wake expansion in the atmospheric boundary layer. J. Fluid Mech. 943, A49.CrossRefGoogle Scholar
Veers, P., et al. 2019 Grand challenges in the science of wind energy. Science 366 (6464), eaau2027.CrossRefGoogle ScholarPubMed
Vermeer, L.J., Sørensen, J.N. & Crespo, A. 2003 Wind turbine wake aerodynamics. Prog. Aerosp. Sci. 39 (6–7), 467510.CrossRefGoogle Scholar
Wallace, J.M. 2016 Quadrant analysis in turbulence research: history and evolution. Annu. Rev. Fluid Mech. 48, 131158.CrossRefGoogle Scholar
Wallace, J.M., Eckelmann, H. & Brodkey, R.S. 1972 The wall region in turbulent shear flow. J. Fluid Mech. 54 (1), 3948.CrossRefGoogle Scholar
Wang, Z., Dong, G., Li, Z. & Yang, X. 2023 Statistics of wind farm wakes for different layouts and ground roughness. Boundary-Layer Meteorol. 188, 285320.Google Scholar
Wu, Y.-T. & Porté-Agel, F. 2012 Atmospheric turbulence effects on wind-turbine wakes: an LES study. Energies 5 (12), 53405362.CrossRefGoogle Scholar
Yang, X., Howard, K.B., Guala, M. & Sotiropoulos, F. 2015 a Effects of a three-dimensional hill on the wake characteristics of a model wind turbine. Phys. Fluids 27 (2), 025103.CrossRefGoogle Scholar
Yang, X., Kang, S. & Sotiropoulos, F. 2012 Computational study and modeling of turbine spacing effects in infinite aligned wind farms. Phys. Fluids 24 (11), 115107.CrossRefGoogle Scholar
Yang, X. & Sotiropoulos, F. 2013 On the predictive capabilities of les-actuator disk model in simulating turbulence past wind turbines and farms. In 2013 American Control Conference, pp. 2878–2883. IEEE.CrossRefGoogle Scholar
Yang, X. & Sotiropoulos, F. 2018 A new class of actuator surface models for wind turbines. Wind Energy 21 (5), 285302.CrossRefGoogle Scholar
Yang, X. & Sotiropoulos, F. 2019 Wake characteristics of a utility-scale wind turbine under coherent inflow structures and different operating conditions. Phys. Rev. Fluids 4 (2), 024604.CrossRefGoogle Scholar
Yang, X., Sotiropoulos, F., Conzemius, R.J., Wachtler, J.N. & Strong, M.B. 2015 b Large-eddy simulation of turbulent flow past wind turbines/farms: the virtual wind simulator (VWiS). Wind Energy 18 (12), 20252045.CrossRefGoogle Scholar
Zehtabiyan-Rezaie, N. & Abkar, M. 2024 An extended $k$$\varepsilon$ model for wake-flow simulation of wind farms. Renew. Energy 222, 119904.CrossRefGoogle Scholar
Zhang, F., Yang, X. & He, G. 2023 Multiscale analysis of a very long wind turbine wake in an atmospheric boundary layer. Phys. Rev. Fluids 8 (10), 104605.CrossRefGoogle Scholar
Supplementary material: File

Li et al. supplementary movie 1

Contours of filtered instantaneous streamwise velocity fluctuations with the incoming mean streamwise velocity subtracted. The filter width is 0.5D (where D is the diameter of the permeable disk). The thrust coefficient is 0.7. The incoming turbulence intensities are 2.5% and 25%, respectively with the integral length scale 1D.
Download Li et al. supplementary movie 1(File)
File 14 MB
Supplementary material: File

Li et al. supplementary movie 2

Contours of filtered instantaneous streamwise velocity fluctuations with the incoming mean streamwise velocity subtracted. The filter width is 0.5D (where D is the diameter of the permeable disk). The thrust coefficient is 0.7. The incoming integral length scales are 0.5D and 1.5D, respectively, with turbulence intensity 10%.
Download Li et al. supplementary movie 2(File)
File 12.3 MB