Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-28T14:16:22.941Z Has data issue: false hasContentIssue false
  • English
  • Français

Effect of wind turbine nacelle on turbine wake dynamics in large wind farms

Published online by Cambridge University Press:  18 April 2019

Daniel Foti ,
Xiaolei Yang ,
Lian Shen Open the ORCID record for Lian Shen [Opens in a new window]  and
Fotis Sotiropoulos Open the ORCID record for Fotis Sotiropoulos [Opens in a new window]
Daniel Foti
Affiliation:
Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI 48109, USA
Xiaolei Yang
Affiliation:
Department of Mechanical Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY 11794, USA Department of Civil Engineering, College of Engineering and Applied Science, Stony Brook University, Stony Brook, NY 11794, USA
Lian Shen
Affiliation:
St. Anthony Falls Laboratory, Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
Fotis Sotiropoulos*
Affiliation:
Department of Civil Engineering, College of Engineering and Applied Science, Stony Brook University, Stony Brook, NY 11794, USA
*
†Email address for correspondence: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Wake meandering, a phenomenon of large-scale lateral oscillation of the wake, has significant effects on the velocity deficit and turbulence intensities in wind turbine wakes. Previous studies of a single turbine (Kang et al., J. Fluid. Mech., vol. 774, 2014, pp. 374–403; Foti et al., Phys. Rev. Fluids, vol. 1 (4), 2016, 044407) have shown that the turbine nacelle induces large-scale coherent structures in the near field that can have a significant effect on wake meandering. However, whether nacelle-induced coherent structures at the turbine scale impact the emergent turbine wake dynamics at the wind farm scale is still an open question of both fundamental and practical significance. We take on this question by carrying out large-eddy simulation of atmospheric turbulent flow over the Horns Rev wind farm using actuator surface parameterisations of the turbines without and with the turbine nacelle taken into account. While the computed mean turbine power output and the mean velocity field away from the nacelle wake are similar for both cases, considerable differences are found in the turbine power fluctuations and turbulence intensities. Furthermore, wake meandering amplitude and area defined by wake meanders, which indicates the turbine wake unsteadiness, are larger for the simulations with the turbine nacelle. The wake influenced area computed from the velocity deficit profiles, which describes the spanwise extent of the turbine wakes, and the spanwise growth rate, on the other hand, are smaller for some rows in the simulation with the nacelle model. Our work shows that incorporating the nacelle model in wind farm scale simulations is critical for accurate predictions of quantities that affect the wind farm levelised cost of energy, such as the dynamics of wake meandering and the dynamic loads on downwind turbines.

JFM classification

Wakes/Jets: Wakes
Type
JFM Papers
Information
Journal of Fluid Mechanics , Volume 869 , 25 June 2019 , pp. 1 - 26
Copyright
© 2019 Cambridge University Press 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Archer, C. L., Mirzaeisefat, S. & Lee, S. 2013 Quantifying the sensitivity of wind farm performance to array layout options using large-eddy simulation. Geophys. Res. Lett. 40 (18), 4963–4970.10.1002/grl.50911Google Scholar
Barthelmie, R. J., Frandsen, S. T., Rathmann, O., Hansen, K., Politis, E., Prospathopoulos, J., Cabezon, D., Rados, K., van der Pijl, S., Schepers, J. et al. 2008 Flow and wakes in large wind farms in complex terrain and offshore. In 2008 European Wind Energy Conference and Exhibition, pp. 36–40.Google Scholar
Barthelmie, R. J., Hansen, K., Frandsen, S. T., Rathmann, O., Schepers, J., Schlez, W., Phillips, J., Rados, K., Zervos, A., Politis, E. et al. 2009 Modelling and measuring flow and wind turbine wakes in large wind farms offshore. Wind Energy 12 (5), 431–444.10.1002/we.348Google Scholar
Barthelmie, R. J., Rathmann, O., Frandsen, S. T., Hansen, K., Politis, E., Prospathopoulos, J., Rados, K., Cabezón, D., Schlez, W., Phillips, J. et al. 2007 Modelling and measurements of wakes in large wind farms. J. Phys. Conf. Ser. 75 (1), 012049.10.1088/1742-6596/75/1/012049Google Scholar
Cal, R. B., Lebrón, J., Castillo, L., Kang, H. S. & Meneveau, C. 2010 Experimental study of the horizontally averaged flow structure in a model wind-turbine array boundary layer. J. Renew. Sustain. Ener. 2 (1), 013106.Google Scholar
Calderer, A., Guo, X., Shen, L. & Sotiropoulos, F. 2018 Fluid–structure interaction simulation of floating structures interacting with complex, large-scale ocean waves and atmospheric turbulence with application to floating offshore wind turbines. J. Comput. Phys. 355, 144–175.10.1016/j.jcp.2017.11.006Google Scholar
Chamorro, L., Hill, C., Morton, S., Ellis, C., Arndt, R. & Sotiropoulos, F. 2013 On the interaction between a turbulent open channel flow and an axial-flow turbine. J. Fluid Mech. 716, 658–670.10.1017/jfm.2012.571Google Scholar
Chrisohoides, A. & Sotiropoulos, F. 2003 Experimental visualization of Lagrangian coherent structures in aperiodic flows. Phys. Fluids 15 (3), L25–L28.10.1063/1.1540111Google Scholar
Debnath, M., Santoni, C., Leonardi, S. & Iungo, G. 2017 Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes. Phil. Trans. R. Soc. Lond. A 375 (2091), 20160108.Google Scholar
Eriksson, O., Lindvall, J., Breton, S.-P. & Ivanell, S. 2015 Wake downstream of the Lillgrund wind farm – a comparison between LES using the actuator disc method and a wind farm parametrization in WRF. J. Phys. Conf. Ser. 625 (1), 012028.10.1088/1742-6596/625/1/012028Google Scholar
Fleming, P. A., Gebraad, P. M., Lee, S., van Wingerden, J.-W., Johnson, K., Churchfield, M., Michalakes, J., Spalart, P. & Moriarty, P. 2014 Evaluating techniques for redirecting turbine wakes using SOWFA. Renewable Energy 70, 211–218.10.1016/j.renene.2014.02.015Google Scholar
Foti, D., Yang, X., Campagnolo, F., Maniaci, D. & Sotiropoulos, F. 2018a Wake meandering of a model wind turbine operating in two different regimes. Phys. Rev. Fluids 3 (5), 054607.10.1103/PhysRevFluids.3.054607Google Scholar
Foti, D., Yang, X., Guala, M. & Sotiropoulos, F. 2016 Wake meandering statistics of a model wind turbine: insights gained by large eddy simulations. Phys. Rev. Fluids 1 (4), 044407.10.1103/PhysRevFluids.1.044407Google Scholar
Foti, D., Yang, X. & Sotiropoulos, F. 2017 Uncertainty quantification of infinite aligned wind farm performance using non-intrusive polynomial chaos and a distributed roughness model. Wind Energy 20 (6), 945–958.10.1002/we.2072Google Scholar
Foti, D., Yang, X. & Sotiropoulos, F. 2018b Similarity of wake meandering for different wind turbine designs for different scales. J. Fluid Mech. 842, 5–25.10.1017/jfm.2018.9Google Scholar
Frandsen, S. 1992 On the wind speed reduction in the center of large clusters of wind turbines. J. Wind Engng Ind. Aerodyn. 39 (1), 251–265.10.1016/0167-6105(92)90551-KGoogle 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), 1782–1809.10.1016/j.jcp.2007.02.017Google Scholar
Germano, M., Piomelli, U., Moin, P. & Cabot, W. H. 1991 A dynamic subgrid-scale eddy viscosity model. Phys. Fluids A 3 (7), 1760–1765.10.1063/1.857955Google Scholar
Howard, K. B., Singh, A., Sotiropoulos, F. & Guala, M. 2015 On the statistics of wind turbine wake meandering: an experimental investigation. Phys. Fluids 27 (7), 075103.10.1063/1.4923334Google Scholar
Howland, M. F., Bossuyt, J., Martínez-Tossas, L. A., Meyers, J. & Meneveau, C. 2016 Wake structure in actuator disk models of wind turbines in yaw under uniform inflow conditions. J. Renew. Sustain. Ener. 8 (4), 043301.Google Scholar
Hussain, A. 1986 Coherent structures and turbulence. J. Fluid Mech. 173, 303–356.10.1017/S0022112086001192Google 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, 499–526.10.1017/jfm.2013.569Google Scholar
Jiménez, Á., Crespo, A. & Migoya, E. 2010 Application of a LES technique to characterize the wake deflection of a wind turbine in yaw. Wind Energy 13 (6), 559–572.10.1002/we.380Google Scholar
Kang, S., Lightbody, A., Hill, C. & Sotiropoulos, F. 2011 High-resolution numerical simulation of turbulence in natural waterways. Adv. Water Resour. 34 (1), 98–113.10.1016/j.advwatres.2010.09.018Google Scholar
Kang, S., Yang, X. & Sotiropoulos, F. 2014 On the onset of wake meandering for an axial flow turbine in a turbulent open channel flow. J. Fluid Mech. 744, 376–403.10.1017/jfm.2014.82Google Scholar
Lilly, D. K. 1992 A proposed modification of the Germano subgrid-scale closure method. Phys. Fluids A 4 (3), 633–635.10.1063/1.858280Google Scholar
Lu, H. & Porté-Agel, F. 2011 Large-eddy simulation of a very large wind farm in a stable atmospheric boundary layer. Phys. Fluids 23 (6), 065101.10.1063/1.3589857Google Scholar
Medici, D. & Alfredsson, P. H. 2008 Measurements behind model wind turbines: further evidence of wake meandering. Wind Energy 11 (2), 211–217.10.1002/we.247Google Scholar
Meyers, J. & Meneveau, C. 2010 Large eddy simulations of large wind-turbine arrays in the atmospheric boundary layer. In 48th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, p. 827.Google Scholar
Nilsson, K., Ivanell, S., Hansen, K. S., Mikkelsen, R., Sørensen, J. N., Breton, S.-P. & Henningson, D. 2015 Large-eddy simulations of the Lillgrund wind farm. Wind Energy 18 (3), 449–467.10.1002/we.1707Google Scholar
Okulov, V., Naumov, I., Mikkelsen, R., Kabardin, I. & Sørensen, J. 2014 A regular Strouhal number for large-scale instability in the far wake of a rotor. J. Fluid Mech. 747, 369–380.10.1017/jfm.2014.174Google Scholar
Okulov, V. & Sørensen, J. 2007 Stability of helical tip vortices in a rotor far wake. J. Fluid Mech. 576, 1–25.10.1017/S0022112006004228Google Scholar
Porté-Agel, F., Wu, Y.-T. & Chen, C.-H. 2013 A numerical study of the effects of wind direction on turbine wakes and power losses in a large wind farm. Energies 6 (10), 5297–5313.10.3390/en6105297Google Scholar
Porté-Agel, F., Wu, Y.-T., Lu, H. & Conzemius, R. 2011 Large-eddy simulation of atmospheric boundary layer flow through wind turbines and wind farms. J. Wind Engng Ind. Aerodyn. 99 (4), 154–168.10.1016/j.jweia.2011.01.011Google Scholar
Santoni, C., Carrasquillo, K., Arenas-Navarro, I. & Leonardi, S. 2017 Effect of tower and nacelle on the flow past a wind turbine. Wind Energy 20 (12), 1927–1939.10.1002/we.2130Google Scholar
Schlichting, H. & Gersten, K. 2003 Boundary-Layer Theory. Springer Science & Business Media.Google Scholar
Schümann, H., Pierella, F. & Sætran, L. 2013 Experimental investigation of wind turbine wakes in the wind tunnel. Energy Procedia 35, 285–296.10.1016/j.egypro.2013.07.181Google Scholar
Smagorinsky, J. 1963 General circulation experiments with the primitive equations: I. The basic experiment. Mon. Weath. Rev. 91 (3), 99–164.10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;22.3.CO;2>Google Scholar
Stevens, R., Gayme, D. & Meneveau, C. 2013 Effect of turbine alignment on the average power output of wind-farms. In 2013 International Conference on Aerodynamics of Offshore Wind Energy Systems and Wakes, ICOWES 2013.Google Scholar
Stevens, R., Graham, J. & Meneveau, C. 2014 A concurrent precursor inflow method for large eddy simulations and applications to finite length wind farms. Renewable Energy 68, 46–50.10.1016/j.renene.2014.01.024Google Scholar
Stevens, R., Martínez-Tossas, L. A. & Meneveau, C. 2018 Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments. Renewable Energy 116, 470–478.10.1016/j.renene.2017.08.072Google Scholar
Trujillo, J.-J., Bingöl, F., Larsen, G., Mann, J. & Kühn, M. 2011 Light detection and ranging measurements of wake dynamics. Part II. Two-dimensional scanning. Wind Energy 14 (1), 61–75.10.1002/we.402Google Scholar
Uhlmann, M. 2005 An immersed boundary method with direct forcing for the simulation of particulate flows. J. Comput. Phys. 209 (2), 448–476.10.1016/j.jcp.2005.03.017Google Scholar
VerHulst, C. & Meneveau, C. 2014 Large eddy simulation study of the kinetic energy entrainment by energetic turbulent flow structures in large wind farms. Phys. Fluids 26 (2), 025113.10.1063/1.4865755Google Scholar
Wu, Y.-T. & Porté-Agel, F. 2015 Modeling turbine wakes and power losses within a wind farm using LES: an application to the Horns Rev offshore wind farm. Renewable Energy 75, 945–955.10.1016/j.renene.2014.06.019Google Scholar
Yang, D., Meneveau, C. & Shen, L. 2014a Effect of downwind swells on offshore wind energy harvesting: a large-eddy simulation study. Renewable Energy 70, 11–23.10.1016/j.renene.2014.03.069Google Scholar
Yang, D., Meneveau, C. & Shen, L. 2014b Large-eddy simulation of offshore wind farm. Phys. Fluids 26 (2), 025101.10.1063/1.4863096Google 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), 115107.10.1063/1.4767727Google Scholar
Yang, X., Pakula, M. & Sotiropoulos, F. 2018 Large-eddy simulation of a utility-scale wind farm in complex terrain. Applied Energy 229, 767–777.10.1016/j.apenergy.2018.08.049Google Scholar
Yang, X. & Sotiropoulos, F. 2016 Analytical model for predicting the performance of arbitrary size and layout wind farms. Wind Energy 19 (7), 1239–1248.10.1002/we.1894Google Scholar
Yang, X. & Sotiropoulos, F. 2018 A new class of actuator surface models for wind turbines. Wind Energy 21 (5), 285–302.10.1002/we.2162Google 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), 2025–2045.10.1002/we.1802Google Scholar