0
Research Papers

Drone-Based Experimental Investigation of Three-Dimensional Flow Structure of a Multi-Megawatt Wind Turbine in Complex Terrain

[+] Author and Article Information
B. Subramanian

Laboratory for Energy Conversion,
Department of Mechanical and Process Engineering,
ETH Zürich,
Zürich 8092, Switzerland
e-mail: subramanian@lec.mavt.ethz.ch

N. Chokani

Laboratory for Energy Conversion,
Department of Mechanical and Process Engineering,
ETH Zürich,
Zürich 8092, Switzerland

R. S. Abhari

Laboratory for Energy Conversion,
Department of Mechanical and Process Engineering,
ETH Zürich,
Zürich 8092, Switzerland

1Corresponding author.

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received June 25, 2014; final manuscript received June 24, 2015; published online July 23, 2015. Assoc. Editor: Yves Gagnon.

J. Sol. Energy Eng 137(5), 051007 (Jul 23, 2015) (10 pages) Paper No: SOL-14-1189; doi: 10.1115/1.4031038 History: Received June 25, 2014

The aerodynamic characteristics of wakes in complex terrain have a profound impact on the energy yield of wind farms and on the fatigue loads on wind turbines in the wind farm. In order to detail the spatial variations of the wind speed, wind direction, and turbulent kinetic energy (TKE) in the near-wake, comprehensive drone-based measurements at a multi-megawatt (MW) wind turbine that is located in complex terrain have been conducted. A short-time Fourier transform (STFT)-based analysis method is used to derive time-localized TKE along the drone's trajectory. In upstream and in the near-wake, the vertical profiles of wind speed, wind direction, and TKE are detailed. There is an increase in the TKE from upstream to downstream of the wind turbine, and whereas, the characteristic microscale length scales increase with increasing height above the ground upstream of the turbine, in the near-wake the microscale lengths are of constant, smaller magnitude. The first-ever measurements of the pressure field across a multi-MW wind turbines rotor plane and of the tip vortices in the near-wake are also reported. It is shown that the pitch between subsequent tip vortices, which are shed from the wind turbines blades, increases in the near-wake as the wake evolves. These details of the near-wake can have an important effect on the subsequent evolution of the wake and must be incorporated into the three-dimensional (3D) field wake models that are currently under intensive development.

FIGURES IN THIS ARTICLE
<>
Copyright © 2015 by ASME
Your Session has timed out. Please sign back in to continue.

References

Global Wind Energy Council Report, 2012, http://www.gwec.net/publications/global-wind-report-2
Sanderse, B. , 2009, “Aerodynamics of Wind Turbine Wakes,” Energy Research Center of the Netherlands, Report No. ECN-E-09-016.
Kocer, G. , Mansour, M. , Chokani, N. , Abhari, R. S. , and Müller, M. , 2011, “Full-Scale Wind Turbine Near-Wake Measurements Using an Instrumented Uninhabited Aerial Vehicle,” ASME J. Sol. Energy Eng., 133(4), p. 041011. [CrossRef]
Mansour, M. , Kocer, G. , Lenherr, C. , Chokani, N. , and Abhari, R. S. , 2011, “Full Scale Wind Turbine Flow Field Measurements Using a 7-Sensor Fast Response Probe,” ASME J. Eng. Gas Turbines Power, 133(8), p. 081601. [CrossRef]
Clive, P. J. M. , 2008, “LIDAR and Resource Assessment for Wind Power Applications: The State of the Art,” Proc. SPIE, 7111, p. 711107.
Käsler, Y. , Rahm, S. , Simmet, R. , and Kühn, M. , 2010, “Wake Measurements of a Multi-MW Wind Turbine With Coherent Long-Range Pulsed Doppler Wind Lidar,” J. Atmos. Oceanic Technol., 27(9), pp. 1529–1532. [CrossRef]
Bingöl, F. , Mann, J. , and Larsen, G. C. , 2009, “Light Detection and Ranging Measurements of Wake Dynamics Part 1: One Dimensional Scanning,” Wind Energy, 13(1), pp. 51–61. [CrossRef]
Trujillo, J. J. , Bingöl, F. , Larsen, G. C. , Mann, J. , and Kühn, M. , 2011, “Light-Detection and Ranging Measurements of Wake Dynamics. Part II: Two-Dimensional Scanning,” Wind Energy, 14(1), pp. 61–75. [CrossRef]
Ebert, P. R. , and Wood, D. H. , 1997, “The Near Wake of a Model Horizontal-Axis Wind Turbine—I. Experimental Arrangements and Initial Results,” Renewable Energy, 12(3), pp. 225–243. [CrossRef]
Haans, W. , Sant, T. , van Kuik, G. , and van Bussel, G. , 2008, “HAWT Near-Wake Aerodynamics, Part I: Axial Flow Conditions,” Wind Energy, 11(3), pp. 245–264. [CrossRef]
Whale, J. , Anderson, C. G. , Bareiss, R. , and Wagner, S. , 2000, “An Experimental and Numerical Study of the Vortex Structure in the Wake of a Wind Turbine,” J. Eng. Ind. Aerodyn., 84(1), pp. 1–21. [CrossRef]
Vermeer, L. , Sørensen, J. , and Crespo, A. , 2003, “Wind Turbine Wake Aerodynamics,” Prog. Aerosp. Sci., 39(6–7), pp. 467–510. [CrossRef]
Helmis, C. G. , Papadopoulos, K. H. , Asimakopoulos, D. N. , Papageorgas, P. G. , and Soilemes, A. T. , 1995, “An Experimental Study of the Near-Wake Structure of a Wind Turbine Operating Over Complex Terrain,” J. Sol. Energy, 54(6), pp. 413–428. [CrossRef]
Elliott, D. L. , and Barnard, J. C. , 1990, “Observations of Wind Turbine Wakes and Surface Roughness Effects on Wind Flow Variability,” Sol. Energy, 45(5), pp. 265–283. [CrossRef]
Papadopoulos, K. H. , Helmis, C. G. , Soilemes, A. T. , Papageorgas, P. G. , and Asimakopoulos, D. N. , 1995, “Study of the Turbulent Characteristics of the Near-Wake Field of a Medium-Sized Wind Turbine Operating in High Wind Conditions,” Sol. Energy, 55(1), pp. 61–72. [CrossRef]
Zambrano, T. G. , and Gyatt, G. W. , 1983, “Wake Structure Measurements at the MOD-2 Cluster Test Facility at Goodnoe Hills, Washington,” IEE Proc., 130(9), pp. 562–565.
Högström, U. , Asimakopoulos, D. N. , Kambezidis, H. , Helmis, C. G. , and Smedman, A. , 1988, “A Field Study of the Wake Behind a 2 MW Wind Turbine,” Atmos. Environ., 22(4), pp. 803–820. [CrossRef]
Kambezidis, H. D. , Asimakopoulos, D. N. , and Helmis, C. G. , 1990, “Wake Measurements Behind a Horizontal-Axis 50 kW Wind Turbine,” Sol. Wind Technol., 7(2–3), pp. 177–184. [CrossRef]
Rhyne, R. H. , and Steiner, R. , 1964, “Power Spectral Measurement of Atmospheric Turbulence in Severe Storms and Cumulus Clouds,” NASA Technical Note, NASA TN D-2469.
Burns, A. , 1964, “Power Spectra of Low level Atmospheric Turbulence Measured From an Aircraft,” Aeronautical Research Council, C. P. No. 733.
Lenschow, D. H. , and Sun, J. , 2007, “The Spectral Composition of Fluxes and Variances Over Land and Sea Out to the Mesoscale,” Boundary Layer Meteorol., 125(1), pp. 63–84. [CrossRef]
Lovejoy, S. , Tuck, A. F. , Schertzer, D. , and Hovde, S. J. , 2009, “Reinterpreting Aircraft Measurement in Anisotropic Scaling Turbulence,” Atmos. Chem. Phys., 9(14), pp. 5007–5025. [CrossRef]
Schlipf, D. , Trabucchi, D. , Bischoff, O. , Hofsäss, M. , Mann, J. , Mikkelsen, T. , Rettenmeier, A. , Trujillo, J. J. , and Kühn, M. , 2010, “Testing of Frozen Turbulence Hypothesis for Wind Turbine Applications With a Scanning LIDAR System,” International Symposium for the Advancement of Boundary Layer Remote Sensing, Paris, France.
Giebel, G. , Schmidt Paulsen, U. , Bange, J. , la Cour-Harbo, A. , Reuder, J. , Mayer, S. , van der Kroonenberg, A. , and Mølgaard, J. , 2012, “Autonomous Aerial Sensors for Wind Power Meteorology—A Pre-Project,” Final Project Report, Risø-R-1798(EN).
Wildmann, N. , Hofsäss, M. , Weimer, F. , Joos, A. , and Bange, J. , 2014, “MASC—A Small Remotely Piloted Aircraft (RPA) for Wind Energy Research,” Adv. Sci. Res., 11(1), pp. 55–61. [CrossRef]
Jafari, S. , Chokani, N. , and Abhari, R. S. , 2014, “Simulation of Wake Interactions in Wind Farms Using an Immersed Wind Turbine Model,” ASME J. Turbomach., 136(6), p. 061018. [CrossRef]
Kupferschmied, K. , Köppel, P. , Roduner, C. , and Gyarmathy, G. , 2000, “On the Development and Application of the Fast-Response Aerodynamic Probe System in Turbomachines—Part 1: The Measurement System,” ASME J. Turbomach., 122(3), pp. 505–516. [CrossRef]
Mueller, M. , and Drouin, A. , 2007, “Paparazzi—The Free Autopilot. Build Your Own UAV,” 24th Chaos Communication Congress, Berliner Congress Center, Dec. 27–30.
Chao, H. , Coopmans, C. , Di, L. , and Chen, Y. Q. , 2010, “A Comparative Evaluation of Low-Cost IMUs for Unmanned Autonomous Systems,” IEEE 2010 International Conference on Multisensor Fusion and Integration for Intelligent Systems, University of Utah, Salt Lake City, UT, Sept. 5–7, pp. 211–216.
Behr, T. , Kalfas, A. I. , and Abhari, R. S. , 2006, “A Probabilistic Uncertainty Evaluation Method for Turbomachinery Probe Measurements,” The XVIIIth Bi-Annual Symposium on Measuring Techniques in Transonic and Supersonic Flows in Cascades and Turbomachines, Thessaloniki, Greece, pp. 1–21.
Norris, J. D. , and Chokani, N. , 2001, “Identification of Nonlinear Interactions in Hypersonic Boundary Layers Using STFT,” AIAA Paper No. 2001-0207.
Jafari, S. , Chokani, N. , and Abhari, R. S. , 2011, “An Immersed Boundary Method for Simulation of Wind Flow Over Complex Terrain,” ASME J. Sol. Energy Eng., 134(1), p. 011006. [CrossRef]
Subramanian, B. , Chokani, N. , and Abhari, R. S. , 2012, “Full-Scale HAWT: Structure of Near-Wake Turbulence Measured With Instrumented UAV,” Euromech Colloquium 528.
Kocer, G. , Chokani, N. , and Abhari, R. S. , 2012, “Wake Structure of a 2 MW Wind Turbine Measured Using an Instrumented UAV,” AIAA Paper No. 2012-0231.
Dubovikov, M. M. , and Tatarskii, V. I. , 1987, “The Calculation of the Asymptotics of the Spectrum of Locally Isotropic Turbulence in the Viscous Range,” Zh. Eksp. Teor. Fiz., 93, pp. 1992–2001 [English translation by the American Institute of Physics, Sov. Phys. JETP 66(6), 1136–1141 (1988)].
Kaimal, J. C. , and Finnigan, J. J. , 1994, Atmospheric Boundary Layer Flows—Their Structure and Measurement, Oxford University Press, New York.
Subramanian, B. , Chokani, N. , and Abhari, R. S. , 2015, “Experimental Analysis of Wakes in a Utility Scale Wind Farm,” J. Wind Eng. Ind. Aerodyn., 138(2015), pp. 61–68. [CrossRef]
Wood, D. H. , 1994, “Simple Equations for Helical Vortex Wakes,” J. Aircr., 31(4), pp. 994–995. [CrossRef]

Figures

Grahic Jump Location
Fig. 4

A typical autonomous drone trajectory for measurements in the near-wake

Grahic Jump Location
Fig. 3

Drone instrumented with FRAP

Grahic Jump Location
Fig. 2

Elevation map of Mont Crosin wind farm. The circle symbols show the locations of the wind turbines.

Grahic Jump Location
Fig. 1

Immersed wind turbine model in ETH micrositing tool [26]

Grahic Jump Location
Fig. 11

PSD in wake (at X/D = 1.5) and in upstream (at X/D = −1) for (a) (Z − ZHH)/D = 0.5, (b) (Z − ZHH)/D = 0.25, and (c) (Z − ZHH)/D = −0.4. The y-abscissa shows the product of the frequency and the power spectrum density.

Grahic Jump Location
Fig. 5

Comparison of LIDAR measured line-of-sight wind speed component to drone measurements

Grahic Jump Location
Fig. 6

Vertical profiles of mean flow properties measured upstream and downstream of the turbine: (a) wind speed; (b) wind direction; and (c) TKE

Grahic Jump Location
Fig. 7

Streamwise variation of static pressure across wind turbine rotor. The measurements are at radial spans of r/D = 0.4 and 0.6. The pressure is normalized relative to reference based on the SCADA 10-min averages.

Grahic Jump Location
Fig. 8

Hub height, streamwise evolutions of wind speed, and TKE at (a) Y/D = 0, (b) Y/D = −0.4, and (c) Y/D = −0.6. The measurements are derived from trajectories that are flown parallel and into the upstream wind direction.

Grahic Jump Location
Fig. 9

Drone trajectory, flow properties—wind speed, TKE, wind direction, power spectra, and differential static pressure—along a trajectory passing through shear layer (wake boundary)

Grahic Jump Location
Fig. 10

PSD measured upstream of the turbine at heights of 70 m, 130 m, 180 m, and 250 m AGL. The y-abscissa shows the product of the frequency and the power spectrum density.

Grahic Jump Location
Fig. 12

Spanwise profiles of the hub height FRAP air speed upstream and at X/D = 0.3, 0.4, 0.6, and 1.0. The distinctive sharp peaks and elevated broadband levels are signatures, respectively, of the tip vortices and the nacelle wake.

Grahic Jump Location
Fig. 13

(a) Representative streamwise profile of hub height FRAP air speed at Y/D = 0.6. The distinctive peaks identify the location of the tip vortices. (b) Comparison of measured and predicted vortex pitches.

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In