Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-28T13:22:04.210Z Has data issue: false hasContentIssue false

Similarity of wake meandering for different wind turbine designs for different scales

Published online by Cambridge University Press:  06 March 2018

Daniel Foti
Affiliation:
Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
Xiaolei Yang
Affiliation:
Department of Civil Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY 11794, USA
Fotis Sotiropoulos*
Affiliation:
Department of Civil Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY 11794, USA
*
Email address for correspondence: [email protected]

Abstract

The wake meandering characteristics of four different wind turbine designs with diameters ranging from a few centimetres (wind tunnel scale) to a hundred metres (utility scale) are investigated using large-eddy simulation with the turbine blades and nacelle parametrised using a new actuator surface model. Different velocity fields and meandering behaviours are observed at near-wake locations. At far-wake locations, on the other hand, the mean velocity deficit profiles begin to collapse when scaled by the centreline velocity deficit based on the incoming wind speed at turbine hub height, suggesting far-wake similarity across scales. The turbine-added turbulence kinetic energy profiles are shown to also nearly collapse with each other in the far wake when normalised using a velocity scale defined by the thrust on the turbine rotor. Moreover, we show that at far-wake locations, the simulated flow fields for all four turbine designs exhibit similar wake meandering characteristics in terms of (1) a Strouhal number independent of rotor designs of different sizes and (2) the distributions of wake meandering wavelengths and amplitudes when normalised by the rotor diameter and a length scale defined by the turbine thrust respectively.

Type
JFM Papers
Copyright
© 2018 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

Abkar, M. & Dabiri, J. O. 2017 Self-similarity and flow characteristics of vertical-axis wind turbine wakes: an LES study. J. Turbul. 18 (4), 373389.CrossRefGoogle Scholar
Aitken, M. L., Banta, R. M., Pichugina, Y. L. & Lundquist, J. K. 2014 Quantifying wind turbine wake characteristics from scanning remote sensor data. J. Atmos. Ocean. Technol. 31 (4), 765787.CrossRefGoogle Scholar
Berg, J., Bryant, J., LeBlanc, B., Maniaci, D., Naughton, B., Paquette, J., Resor, B., White, J. & Kroeker, D. 2014 Scaled wind farm technology facility overview. In 32nd ASME Wind Energy Symposium, vol. 1088. AIAA.Google Scholar
Bisset, D. K., Antonia, R. A. & Browne, L. W. B. 1990 Spatial organization of large structures in the turbulent far wake of a cylinder. J. Fluid Mech. 218, 439461.CrossRefGoogle Scholar
Bottasso, C. L., Campagnolo, F. & Petrović, V. 2014 Wind tunnel testing of scaled wind turbine models: beyond aerodynamics. J. Wind Engng Ind. Aerodyn. 127, 1128.CrossRefGoogle Scholar
Campagnolo, F.2013 Wind tunnel testing of scaled wind turbine models: aerodynamics and beyond. PhD thesis, Politecnico Di Milano.Google Scholar
Chamorro, L. P., Hill, C., Morton, S., Ellis, C., Arndt, R. E. A. & Sotiropoulos, F. 2013 On the interaction between a turbulent open channel flow and an axial-flow turbine. J. Fluid Mech. 716, 658670.CrossRefGoogle Scholar
Chrisohoides, A. & Sotiropoulos, F. 2003 Experimental visualization of Lagrangian coherent structures in aperiodic flows. Phys. Fluids 15 (3), L25L28.CrossRefGoogle Scholar
Davies, M. E. 1976 A comparison of the wake structure of a stationary and oscillating bluff body, using a conditional averaging technique. J. Fluid Mech. 75 (02), 209231.CrossRefGoogle Scholar
Du, Z. & Selig, M. S.1998 A 3-d stall-delay model for horizontal axis wind turbine performance prediction. ASME Wind Energy Symposium at Reno, NV, USA, 12–15 January 1998, Paper 21.Google Scholar
Foti, D., Yang, X., Campagnolo, F., Maniaci, D. & Sotiropoulos, F. 2017 On the use of spires for generating inflow conditions with energetic coherent structures in large eddy simulation. J. Turbul. 18 (7), 611633.CrossRefGoogle Scholar
Foti, D., Yang, X., Campagnolo, F., Maniaci, D. & Sotiropolos, F.2018 On the wake meandering of a model wind turbine operating in two different regimes. arXiv:1802.03836 [physics.flu-dyn] (Submitted to Phys. Rev. Fluids).CrossRefGoogle 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.CrossRefGoogle 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), 251265.CrossRefGoogle 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
Hong, J., Toloui, M., Chamorro, L. P., Guala, M., Howard, K., Riley, S., Tucker, J. & Sotiropoulos, F. 2014 Natural snowfall reveals large-scale flow structures in the wake of a 2.5-MW wind turbine. Nat. Commun. 5, 4216.CrossRefGoogle ScholarPubMed
Howard, K. B., Hu, J. S., Chamorro, L. P. & Guala, M. 2015a Characterizing the response of a wind turbine model under complex inflow conditions. Wind Energy 18 (4), 729743.CrossRefGoogle Scholar
Howard, K. B., Singh, A., Sotiropoulos, F. & Guala, M. 2015b On the statistics of wind turbine wake meandering: an experimental investigation. Phys. Fluids 27 (7), 075103.CrossRefGoogle 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
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
Jensen, N. O. 1983 A Note on Wind Generator Interaction. Risø National Laboratory.Google Scholar
Kang, S., Lightbody, A., Hill, C. & Sotiropoulos, F. 2011 High-resolution numerical simulation of turbulence in natural waterways. Adv. Water Resour. 34 (1), 98113.CrossRefGoogle 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, 376403.CrossRefGoogle Scholar
Mann, J. 1998 Wind field simulation. Prob. Engng Mech. 13 (4), 269282.CrossRefGoogle Scholar
Medici, D. & Alfredsson, P. H. 2008 Measurements behind model wind turbines: further evidence of wake meandering. Wind Energy 11 (2), 211217.CrossRefGoogle Scholar
Mikkelsen, R., Sørensen, J. N. & Troldborg, N. 2007 Prescribed wind shear modelling combined with the actuator line technique. In Conference Proceedings of the 2007 European Wind Energy Conference and Exhibition.Google Scholar
Okulov, V. L., Naumov, I. V., Mikkelsen, R. F., Kabardin, I. K. & Sørensen, J. N. 2014 A regular Strouhal number for large-scale instability in the far wake of a rotor. J. Fluid Mech. 747, 369380.CrossRefGoogle Scholar
Okulov, V. L. & Sørensen, J. N. 2007 Stability of helical tip vortices in a rotor far wake. J. Fluid Mech. 576, 125.CrossRefGoogle Scholar
Pao, L. Y. & Johnson, K. E. 2009 A tutorial on the dynamics and control of wind turbines and wind farms. In 2009 American Control Conference, pp. 20762089. IEEE.CrossRefGoogle Scholar
Rethore, P.-E., Bechmann, A., Sørensen, N. N., Frandsen, S. T., Mann, J., Jørgensen, H. E., Rathmann, O. & Larsen, S. E. 2007 A CFD model of the wake of an offshore wind farm: using a prescribed wake inflow. J. Phys. Conf. Ser. 75, 012047.CrossRefGoogle Scholar
Schlichting, H. & Gersten, K. 2000 Boundary-Layer Theory. Springer.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
Simms, D., Schreck, S., Hand, M. & Fingersh, L. J.2001 NREL unsteady aerodynamics experiment in the NASA-Ames wind tunnel: a comparison of predictions to measurements. Tech. Rep. National Renewable Energy Lab., Golden, CO (US).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
Snel, H., Schepers, J. G. & Montgomerie, B. 2007 The MEXICO project (model experiments in controlled conditions): the database and first results of data processing and interpretation. J. Phys. Conf. Ser. 75, 012014.CrossRefGoogle Scholar
Sørensen, J. N. & Shen, W. Z. 2002 Numerical modeling of wind turbine wakes. Trans. ASME J. Fluids Engng 124 (2), 393399.CrossRefGoogle Scholar
Troldborg, N., Larsen, G. C., Madsen, H. A., Hansen, K. S., Sørensen, J. N. & Mikkelsen, R. 2011 Numerical simulations of wake interaction between two wind turbines at various inflow conditions. Wind Energy 14 (7), 859876.CrossRefGoogle Scholar
Troldborg, N., Sørensen, J. N. & Mikkelsen, R. 2007 Actuator line simulation of wake of wind turbine operating in turbulent inflow. J. Phys. Conf. Ser. 75, 012063.CrossRefGoogle Scholar
Troldborg, N., Sorensen, J. N. & Mikkelsen, R. 2010 Numerical simulations of wake characteristics of a wind turbine in uniform inflow. Wind Energy 13 (1), 8699.CrossRefGoogle Scholar
Uhlmann, M. 2005 An immersed boundary method with direct forcing for the simulation of particulate flows. J. Comput. Phys. 209 (2), 448476.CrossRefGoogle Scholar
Whale, J., Anderson, C. G., Bareiss, R. & Wagner, S. 2000 An experimental and numerical study of the vortex structure in the wake of a wind turbine. J. Wind Engng Ind. Aerodyn. 84 (1), 121.CrossRefGoogle Scholar
Yang, X., Hong, J., Barone, M. & Sotiropoulos, F. 2016 Coherent dynamics in the rotor tip shear layer of utility-scale wind turbines. J. Fluid Mech. 804, 90115.CrossRefGoogle Scholar
Yang, X., Howard, K. B., Guala, M. & Sotiropoulos, F. 2015a 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. 2018 A new class of actuator surface models for wind turbines. Wind Energy doi:10.1002/we.2162.CrossRefGoogle Scholar
Yang, X., Sotiropoulos, F., Conzemius, R. J., Wachtler, J. N. & Strong, M. B. 2015b 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