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.

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Fig. 4

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

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Fig. 3

Drone instrumented with FRAP

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Fig. 2

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

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Fig. 1

Immersed wind turbine model in ETH micrositing tool [26]

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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.

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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)

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Fig. 5

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

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Fig. 6

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

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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.

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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.

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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.

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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.

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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.




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