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Resolvent-based motion-to-wake modelling of wind turbine wakes under dynamic rotor motion

Published online by Cambridge University Press:  08 February 2024

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: xyang@imech.ac.cn

Abstract

We propose a linearized deterministic model for predicting coherent structures in the wake of a floating offshore wind turbine subject to platform motions. The model's motion-to-wake predictive capability is achieved through two building blocks: a motion-to-forcing (M2F) part and a forcing-to-wake (F2W) part. The M2F model provides a unified framework to parameterize the effects of arbitrary floating wind turbine motions as unsteady loads of a fixed actuator disk, requiring only the radial distribution of the aerodynamics force coefficient on the blade as input. The F2W model is derived based on a bi-global resolvent model obtained from the linearized Navier–Stokes equations, using the time-averaged wake of a fixed wind turbine as input. In addition to its capability of predicting sensitive frequency ranges, the model excels linear stability analysis by providing spatial modes of the wake response in a motion-specific and phase-resolved manner. The model successfully predicts the wake pulsing mode induced by surge, as well as the similarity and difference of the wake meandering modes caused by sway and yaw. Large-eddy simulations under different inflow turbulence intensities (TIs) and length scales are further conducted to analyse the wake meandering triggered by the simultaneous excitation of free-stream turbulence and sway motion. The results show distinct frequency signatures for the wake dynamics induced by ambient turbulence and sway motion. The inflow TI is found to have a stabilizing effect on the wake, reducing the motion-induced wake responses. Such a stabilizing effect is captured satisfactorily with the proposed model, provided that the effective viscosity is calibrated properly using the data from the fixed turbine wake under the corresponding turbulent inflow.

JFM classification

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

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References

Angelou, N., Mann, J. & Dubreuil-Boisclair, C. 2023 Revealing inflow and wake conditions of a 6 MW floating turbine. Wind Energy Sci. Discuss. 2023, 135.Google Scholar
Barthelmie, R.J., et al. 2009 Modelling and measuring flow and wind turbine wakes in large wind farms offshore. Wind Energy 12 (5), 431444.CrossRefGoogle Scholar
Bayati, I., Belloli, M., Bernini, L. & Zasso, A. 2017 Wind tunnel wake measurements of floating offshore wind turbines. Energy Procedia 137, 214222.CrossRefGoogle Scholar
Belvasi, N., Conan, B., Schliffke, B., Perret, L., Desmond, C., Murphy, J. & Aubrun, S. 2022 Far-wake meandering of a wind turbine model with imposed motions: an experimental S-PIV analysis. Energies 15 (20), 7757.CrossRefGoogle Scholar
Bortolotti, P., Tarres, H.C., Dykes, K.L., Merz, K., Sethuraman, L., Verelst, D. & Zahle, F. 2019 IEA wind TCP task 37: systems engineering in wind energy-WP2. 1 Reference wind turbines. Tech. Rep. National Renewable Energy Lab. (NREL), Golden, CO, USA.CrossRefGoogle Scholar
Chen, G., Liang, X.-F. & Li, X.-B. 2022 Modelling of wake dynamics and instabilities of a floating horizontal-axis wind turbine under surge motion. Energy 239, 122110.CrossRefGoogle Scholar
Del Alamo, J.C. & Jimenez, J. 2006 Linear energy amplification in turbulent channels. J. Fluid Mech. 559, 205213.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
Du, Z. & Selig, M. 1998 A 3-D stall-delay model for horizontal axis wind turbine performance prediction. AIAA Paper AIAA 1998-21.CrossRefGoogle Scholar
Espana, G., Aubrun, S., Loyer, S. & Devinant, P. 2011 Spatial study of the wake meandering using modelled wind turbines in a wind tunnel. Wind Energy 14 (7), 923937.CrossRefGoogle Scholar
Espana, G., Aubrun, S., Loyer, S. & Devinant, P. 2012 Wind tunnel study of the wake meandering downstream of a modelled wind turbine as an effect of large scale turbulent eddies. J. Wind Engng Ind. Aerodyn. 101, 2433.CrossRefGoogle Scholar
Farrugia, R., Sant, T. & Micallef, D. 2016 A study on the aerodynamics of a floating wind turbine rotor. Renew. Energy 86, 770784.CrossRefGoogle Scholar
Feist, C., Sotiropoulos, F. & Guala, M. 2021 A quasi-coupled wind wave experimental framework for testing offshore wind turbine floating systems. Theor. Appl. Mech. Lett., 100294.CrossRefGoogle Scholar
Fontanella, A., Bayati, I., Mikkelsen, R., Belloli, M. & Zasso, A. 2021 Unaflow: a holistic wind tunnel experiment about the aerodynamic response of floating wind turbines under imposed surge motion. Wind Energy Sci. 6 (5), 11691190.CrossRefGoogle Scholar
Fontanella, A., Zasso, A. & Belloli, M. 2022 Wind tunnel investigation of the wake-flow response for a floating turbine subjected to surge motion. J. Phys.: Conf. Ser. 2265, 042023.Google Scholar
Frederik, J.A., Doekemeijer, B.M., Mulders, S.P. & van Wingerden, J.-W. 2020 The helix approach: using dynamic individual pitch control to enhance wake mixing in wind farms. Wind Energy 23 (8), 17391751.CrossRefGoogle Scholar
Fu, S.F., Jin, Y.Q., Zheng, Y. & Chamorro, L.P. 2019 Wake and power fluctuations of a model wind turbine subjected to pitch and roll oscillations. Appl. Energy 253, 113605.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
Garnaud, X., Lesshafft, L., Schmid, P.J. & Huerre, P. 2013 The preferred mode of incompressible jets: linear frequency response analysis. J. Fluid Mech. 716, 189202.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
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
Goit, J.P. & Meyers, J. 2015 Optimal control of energy extraction in wind-farm boundary layers. J. Fluid Mech. 768, 550.CrossRefGoogle Scholar
Gupta, V., Madhusudanan, A., Wan, M., Illingworth, S.J. & Juniper, M.P. 2021 Linear-model-based estimation in wall turbulence: improved stochastic forcing and eddy viscosity terms. J. Fluid Mech. 925, A18.CrossRefGoogle Scholar
Gupta, V. & Wan, M. 2019 Low-order modelling of wake meandering behind turbines. J. Fluid Mech. 877, 534560.CrossRefGoogle 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
Heck, K.S., Johlas, H.M. & Howland, M.F. 2023 Modelling the induction, thrust and power of a yaw-misaligned actuator disk. J. Fluid Mech. 959, A9.CrossRefGoogle Scholar
Ho, C.-M. & Huerre, P. 1984 Perturbed free shear layers. Annu. Rev. Fluid Mech. 16, 365424.CrossRefGoogle Scholar
IEC 2019 Wind Turbines-Part 1: Design Requirements. Standard. International Electrotechnical Commission.Google Scholar
Iungo, G.V., Viola, F., Camarri, S., Porté-Agel, F. & Gallaire, F. 2013 Linear stability analysis of wind turbine wakes performed on wind tunnel measurements. J. Fluid Mech. 737, 499526.CrossRefGoogle Scholar
Jonkman, J. & Musial, W. 2010 Offshore code comparison collaboration (OC3) for IEA task 23 offshore wind technology and deployment. Tech. rep. TP-5000-48191. National Renewable Energy Lab. (NREL), Golden, CO, USA.Google Scholar
Jovanović, M.R. 2021 From bypass transition to flow control and data-driven turbulence modeling: an input–output viewpoint. Annu. Rev. Fluid Mech. 53, 311345.CrossRefGoogle Scholar
Jovanović, M.R. & Bamieh, B. 2005 Componentwise energy amplification in channel flows. J. Fluid Mech. 534, 145183.CrossRefGoogle Scholar
Kaplan, O., Jordan, P., Cavalieri, A.V.G. & Brès, G.A. 2021 Nozzle dynamics and wavepackets in turbulent jets. J. Fluid Mech. 923, A22.CrossRefGoogle Scholar
Kleine, V.G., Franceschini, L., Carmo, B.S., Hanifi, A. & Henningson, D.S. 2022 The stability of wakes of floating wind turbines. Phys. Fluids 34 (7), 074106.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
Kopperstad, K.M., Kumar, R. & Shoele, K. 2020 Aerodynamic characterization of barge and spar type floating offshore wind turbines at different sea states. Wind Energy 23 (11), 20872112.CrossRefGoogle Scholar
Lee, H. & Lee, D.-J. 2019 Effects of platform motions on aerodynamic performance and unsteady wake evolution of a floating offshore wind turbine. Renew. Energy 143, 923.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
Lyu, G., Zhang, H. & Li, J. 2019 Effects of incident wind/wave directions on dynamic response of a spar-type floating offshore wind turbine system. Acta Mechanica Sin. 35, 954963.CrossRefGoogle Scholar
Mann, J. 1994 The spatial structure of neutral atmospheric surface-layer turbulence. J. Fluid Mech. 273, 141–168.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
Martini, E., Rodríguez, D., Towne, A. & Cavalieri, A.V.G. 2021 Efficient computation of global resolvent modes. J. Fluid Mech. 919, A3.CrossRefGoogle Scholar
McKeon, B.J. & Sharma, A.S. 2010 A critical-layer framework for turbulent pipe flow. J. Fluid Mech. 658, 336382.CrossRefGoogle Scholar
Meng, H., Su, H., Guo, J., Qu, T. & Lei, L. 2022 a Experimental investigation on the power and thrust characteristics of a wind turbine model subjected to surge and sway motions. Renew. Energy 181, 13251337.CrossRefGoogle Scholar
Meng, H., Su, H., Qu, T. & Lei, L. 2022 b Wind tunnel study on the wake characteristics of a wind turbine model subjected to surge and sway motions. J. Renew. Sustain. Energy 14 (1), 013307.CrossRefGoogle Scholar
Messmer, T., Hölling, M. & Peinke, J. 2023 Enhanced recovery and non-linear dynamics in the wake of a model floating offshore wind turbine submitted to side-to-side and fore-aft motion. J. Fluid Mech. (submitted) arXiv:2305.12247.Google Scholar
Meyers, J., Bottasso, C., Dykes, K., Fleming, P., Gebraad, P., Giebel, G., Göçmen, T. & van Wingerden, J.-W. 2022 Wind farm flow control: prospects and challenges. Wind Energy Sci. 7 (6), 22712306.CrossRefGoogle Scholar
Morra, P., Semeraro, O., Henningson, D.S. & Cossu, C. 2019 On the relevance of Reynolds stresses in resolvent analyses of turbulent wall-bounded flows. J. Fluid Mech. 867, 969984.CrossRefGoogle Scholar
Nandi, T.N. & Yeo, D.H. 2021 Estimation of integral length scales across the neutral atmospheric boundary layer depth: a large eddy simulation study. J. Wind Engng Ind. Aerodyn. 218, 104715.CrossRefGoogle Scholar
Niayifar, A. & Porté-Agel, F. 2016 Analytical modeling of wind farms: a new approach for power prediction. Energies 9 (9), 741.CrossRefGoogle Scholar
Pickering, E., Rigas, G., Schmidt, O.T., Sipp, D. & Colonius, T. 2021 Optimal eddy viscosity for resolvent-based models of coherent structures in turbulent jets. J. Fluid Mech. 917, A29.CrossRefGoogle Scholar
Porté-Agel, F., Bastankhah, M. & Shamsoddin, S. 2020 Wind-turbine and wind-farm flows: a review. Boundary-Layer Meteorol. 174, 159.CrossRefGoogle ScholarPubMed
Ramos-García, N., González Horcas, S., Pegalajar-Jurado, A., Kontos, S. & Bredmose, H. 2022 Investigation of the floating IEA wind 15-MW RWT using vortex methods. Part II. Wake impact on downstream turbines under turbulent inflow. Wind Energy 25 (8), 14341463.CrossRefGoogle Scholar
Ribeiro, A.F.P., Casalino, D. & Ferreira, C.S. 2023 a Nonlinear inviscid aerodynamics of a wind turbine rotor in surge, sway, and yaw motions using free-wake panel method. Wind Energy Sci. 8 (4), 661675.CrossRefGoogle Scholar
Ribeiro, J.H.M., Yeh, C.-A. & Taira, K. 2023 b Triglobal resolvent analysis of swept-wing wakes. J. Fluid Mech. 954, A42.CrossRefGoogle Scholar
Robertson, A., et al. 2014 Offshore code comparison collaboration continuation within IEA wind task 30: phase II results regarding a floating semisubmersible wind system. In International Conference on Offshore Mechanics and Arctic Engineering, vol. 45547, V09BT09A012. American Society of Mechanical Engineers.Google Scholar
Rockel, S., Camp, E., Schmidt, J., Peinke, J., Cal, R.B. & Hölling, M. 2014 Experimental study on influence of pitch motion on the wake of a floating wind turbine model. Energies 7 (4), 19541985.CrossRefGoogle Scholar
Rockel, S., Peinke, J., Hölling, M. & Cal, R.B. 2017 Dynamic wake development of a floating wind turbine in free pitch motion subjected to turbulent inflow generated with an active grid. Renew. Energy 112, 116.CrossRefGoogle Scholar
Rosenberg, K. & McKeon, B.J. 2019 Computing exact coherent states in channels starting from the laminar profile: a resolvent-based approach. Phys. Rev. E 100 (2), 021101.CrossRefGoogle ScholarPubMed
Saad, Y. 1993 A flexible inner-outer preconditioned GMRES algorithm. SIAM J. Sci. Comput. 14 (2), 461469.CrossRefGoogle Scholar
Schliffke, B., Aubrun, S. & Conan, B. 2020 Wind tunnel study of a “floating” wind turbine's wake in an atmospheric boundary layer with imposed characteristic surge motion. J. Phys.: Conf. Ser. 1618, 062015.Google Scholar
Schliffke, B., Conan, B. & Aubrun, S. 2023 Floating wind turbine motions signature in the far-wake spectral content – a wind tunnel experiment. Wind Energy Sci. Discuss. 2023, 120.Google Scholar
Scott, R., Martínez-Tossas, L., Bossuyt, J., Hamilton, N. & Cal, R.B. 2023 Evolution of eddy viscosity in the wake of a wind turbine. Wind Energy Sci. 8 (3), 449463.CrossRefGoogle Scholar
Sebastian, T. & Lackner, M. 2012 Analysis of the induction and wake evolution of an offshore floating wind turbine. Energies 5 (4), 9681000.CrossRefGoogle Scholar
Shapiro, C.R., Starke, G.M. & Gayme, D.F. 2022 Turbulence and control of wind farms. Annu. Rev. Control Rob. Auton. Syst. 5, 579602.CrossRefGoogle Scholar
Shen, W.Z., Mikkelsen, R., Sørensen, J.N. & Bak, C. 2005 Tip loss corrections for wind turbine computations. Wind Energy 8 (4), 457475.CrossRefGoogle Scholar
Sipp, D., Marquet, O., Meliga, P. & Barbagallo, A. 2010 Dynamics and control of global instabilities in open-flows: a linearized approach. Appl. Mech. Rev. 63 (3), 030801.CrossRefGoogle Scholar
Smagorinsky, J. 1963 General circulation experiments with the primitive equations. I. The basic experiment. Mon. Weath. Rev. 91 (3), 99164.2.3.CO;2>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
Symon, S., Madhusudanan, A., Illingworth, S.J. & Marusic, I. 2023 Use of eddy viscosity in resolvent analysis of turbulent channel flow. Phys. Rev. Fluids 8 (6), 064601.CrossRefGoogle Scholar
Towne, A., Schmidt, O.T. & Colonius, T. 2018 Spectral proper orthogonal decomposition and its relationship to dynamic mode decomposition and resolvent analysis. J. Fluid Mech. 847, 821867.CrossRefGoogle Scholar
Tran, T.T. & Kim, D.-H. 2016 A CFD study into the influence of unsteady aerodynamic interference on wind turbine surge motion. Renew. Energy 90, 204228.CrossRefGoogle Scholar
Trefethen, L.N., Trefethen, A.E., Reddy, S.C. & Driscoll, T.A. 1993 Hydrodynamic stability without eigenvalues. Science 261 (5121), 578584.CrossRefGoogle ScholarPubMed
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
Viola, F., Iungo, G.V., Camarri, S., Porté-Agel, F. & Gallaire, F. 2014 Prediction of the hub vortex instability in a wind turbine wake: stability analysis with eddy-viscosity models calibrated on wind tunnel data. J. Fluid Mech. 750, R1.CrossRefGoogle Scholar
Wei, N.J. & Dabiri, J.O. 2023 Power-generation enhancements and upstream flow properties of turbines in unsteady inflow conditions. J. Fluid Mech. 966, A30.CrossRefGoogle Scholar
Wise, A.S. & Bachynski, E.E. 2020 Wake meandering effects on floating wind turbines. Wind Energy 23 (5), 12661285.CrossRefGoogle Scholar
Wu, T. & He, G. 2023 Composition of resolvents enhanced by random sweeping for large-scale structures in turbulent channel flows. J. Fluid Mech. 956, A31.CrossRefGoogle Scholar
Yang, H., Ge, M., Abkar, M. & Yang, X.I.A. 2022 Large-eddy simulation study of wind turbine array above swell sea. Energy 256, 124674.CrossRefGoogle Scholar
Yang, D., Meneveau, C. & Shen, L. 2014 Effect of downwind swells on offshore wind energy harvesting–a large-eddy simulation study. Renew. Energy 70, 1123.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 A review on the meandering of wind turbine wakes. Energies 12 (24), 4725.CrossRefGoogle Scholar
Yang, X., Sotiropoulos, F., Conzemius, R.J., Wachtler, J.N. & Strong, M.B. 2015 Large-eddy simulation of turbulent flow past wind turbines/farms: the virtual wind simulator (VWiS). Wind Energy 18 (12), 20252045.CrossRefGoogle Scholar
Yang, X., Zhang, X., Li, Z. & He, G.-W. 2009 A smoothing technique for discrete delta functions with application to immersed boundary method in moving boundary simulations. J. Comput. Phys. 228 (20), 78217836.CrossRefGoogle Scholar