Abstract
The present work proposes an experimental methodology to characterize the unsteady properties of a wind turbine wake, called meandering, and particularly its ability to follow the large-scale motions induced by large turbulent eddies contained in the approach flow. The measurements were made in an atmospheric boundary layer wind tunnel. The wind turbine model is based on the actuator disc concept. One part of the work has been dedicated to the development of a methodology for horizontal wake tracking by mean of a transverse hot wire rake, whose dynamic response is adequate for spectral analysis. Spectral coherence analysis shows that the horizontal position of the wake correlates well with the upstream transverse velocity, especially for wavelength larger than three times the diameter of the disc but less so for smaller scales. Therefore, it is concluded that the wake is actually a rather passive tracer of the large surrounding turbulent structures. The influence of the rotor size and downstream distance on the wake meandering is studied. The fluctuations of the lateral force and the yawing torque affecting the wind turbine model are also measured and correlated with the wake meandering. Two approach flow configurations are then tested: an undisturbed incoming flow (modelled atmospheric boundary layer) and a disturbed incoming flow, with a wind turbine model located upstream. Results showed that the meandering process is amplified by the presence of the upstream wake. It is shown that the coherence between the lateral force fluctuations and the horizontal wake position is significant up to length scales larger than twice the wind turbine model diameter. This leads to the conclusion that the lateral force is a better candidate than the upstream transverse velocity to predict in real time the meandering process, for either undisturbed (wake free) or disturbed incoming atmospheric flows.
Similar content being viewed by others
Abbreviations
- a :
-
Axial induction factor
- Δy :
-
Transverse spacing between the probes that constitute the hot wire rake
- α :
-
Power law exponent
- C T :
-
Thrust coefficient
- D :
-
Disc diameter
- Du i :
-
Local velocity deficit at the ith probe position
- f :
-
Frequency
- H hub :
-
Disc “hub height”
- I u :
-
Turbulent intensity for the axial velocity component defined as I u = σ u /U
- I w :
-
Turbulent intensity for the vertical velocity component defined as I w = σ w /U
- L :
-
Streamwise distance between the disc and the hot wire rake
- L ux :
-
Integral scale for the axial velocity component
- L wx :
-
Integral scale for the vertical velocity component
- u, v, w :
-
Instantaneous wind velocity along x, y and z axis respectively
- u*:
-
Friction velocity
- U :
-
Time-averaged velocity
- U ∞ :
-
Upstream time-averaged velocity at hub height
- v upstream :
-
Upstream transverse velocity fluctuation
- v downstream :
-
Downstream transverse velocity fluctuation
- y wake :
-
Transverse wake position fluctuation
- z 0 :
-
Roughness length
References
Ainslie JP (1988) Calculating the flow field in the wake of wind turbines. J Wind Eng Ind Aerodyn 27:213–224
Aubrun S, Devinant P, España G (2007) Physical modelling of the far wake from wind turbines. Application to wind turbine interactions. In: Proceedings of the European wind energy conference, Milan, Italy
Aubrun S, Loyer S, Hancock PE, Hayden P (2013) Wind turbine wake properties: comparison between a non-rotating simplified wind turbine model and a rotating model. J Wind Eng Ind Aerodyn 120:1–8
Bingöl F, Mann J, Larsen GC (2010) Light detection and ranging measurements of wake dynamics. Part 1: one-dimensional scanning. Wind Energy 13:51–61
Cannon S, Champagne F, Glezer A (1993) Observations of large-scale structures in wakes behind axisymmetric bodies. Exp Fluids 14(6):447–450
Chamorro LP, Hill C, Morton S, Ellis C, Arndt REA, Sotiropoulos F (2013) On the interaction between open channel flow and an axial-flow turbine. J Fluid Mech 716:658–670
Cholbrock AK, Fleming PA, Fingersh LJ, Wright AD, Schlipf D, Haizman F, Belen F (2013) Field testing LiDAR based feed-forward controls on the NREL controls advanced research turbine. Conference Paper NREL/CP-5000-57339
Counihan J (1975) Adiabatic atmospheric boundary layers: a review and analysis of data from the period 1880–1972. Atmos Environ 9:871–905
Davoust S, Jehu A, Bouillet M, Bardon M, Vercherin B, Scholbrock A, Fleming P, Wright A (2014) Assessment and optimization of LiDAR measurement availability for wind turbine control. In: Scientific. Proceedings of EWEA Conference March 10–13, 2014, Barcelona, Spain
Engineering Sciences Data Unit (1985) Characteristics of atmospheric turbulence near the ground. Item No. 85020
España G, Aubrun S, Loyer S, Devinant P (2011) Spatial study of the wake meandering using modelled wind turbines in a wind tunnel. Wind Energy 14:923–937
España 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 Eng Ind Aerodyn 101:24–33
Felli M, Camussi R, Di Felice F (2011) Mechanisms of evolution of the propeller wake in the transition and far fields. J Fluid Mech 682:5–53
Frandsen S, Barthelmie R, Pryor S, Rathmann O, Larsen S, Højstrup J, Thøgersen M (2006) Analytical modelling of wind Speed deficit in large offshore wind farms. Wind Energy 9:39–53
Hancock PE, Pascheke F (2014) Wind tunnel simulation of the wake of a large wind turbine in a stable boundary layer: part 2 the wake flow. Bound Layer Meteorol 151:23–37
Hu H, Yang Z, Sarkar P (2012) Dynamic wind loads and wake characteristics of a wind turbine model in an atmospheric boundary layer wind. Exp Fluids 52:1277–1294
Iungo GV, Viola F, Camarri S, Porté-Agel F, Gallaire F (2013) Linear stability analysis on wind turbine wakes performed on wind tunnel measurements. J Fluid Mech 737:499–526
Jensen NO (1983) A note on wind generator interaction. Risø Report M-2411
Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layer flows, their structure and measurements. Oxford University Press, Oxford
Larsen GC, Madsen HA, Thomsen K, Larsen TJ (2008) Wake meandering—a pragmatic approach. Wind Energy 11:377–395
Larsen TJ, Madsen HA, Larsen GC, Hansen KS (2013) Validation of the dynamic wake meander model for loads and power production in the Egmond aan Zee wind farm. Wind Energy 16(4):605–624
Medici D, Alfredsson PH (2006) Measurements on a wind turbine wake: 3D effects and bluff body vortex shedding. Wind Energy 9:219–236
Snyder WH (1981) Guideline for fluid modelling of atmospheric diffusion. US Environmental Protection Agency. Report EPA-600/8-81-009
Taylor GJ, Milborrow DJ, McIntosh DN, Swift-Hook DT (1985) Wake measurements on the Nibe windmills. In: Proceedings of the 7th British wind energy association conference March 27–29 1985, Oxford
Trujillo JJ, Kühn M (2009) Adaptation of a lagrangian dispersion model for wind turbine wake meandering. In: Proceedings of the EWEA conference, March 16–19, Marseille, France
Trujillo JJ, Bingöl F, Larsen GC, Mann J (2011) Light detection and ranging measurements on wake dynamics, part II: two-dimensional Scanning. Wind Energy 14:61–75
VDI guideline 3783/12 (2000) Physical modelling of flow and dispersion processes in the atmospheric boundary layer—application for wind tunnels. Beuth Verlag, Berlin
Zhang W, Markfort CD, Porté-Agel F (2012) Near-wake flow structure downwind of a wind turbine in a turbulent boundary layer. Exp Fluids 52:1219–1235
Zhang W, Markfort CD, Porté-Agel F (2013) Wind turbine wakes in a convective boundary layer: wind tunnel study. Bound Layer Meteorol 146:161–179
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Muller, YA., Aubrun, S. & Masson, C. Determination of real-time predictors of the wind turbine wake meandering. Exp Fluids 56, 53 (2015). https://doi.org/10.1007/s00348-015-1923-9
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s00348-015-1923-9