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Thomas Hahm and Jürgen Kröning, TÜV Nord e.V., Hamburg,
Germany
Many companies throughout the world have been applying their skills and
expertise to the development of renewable energy sources. The number of
companies involved in the production of clean and sustainable energy will
undoubtedly increase in the near future due in part to a commitment to
the Kyoto Protocol (1997), which calls for sweeping reductions in man-made
green-house gas emissions, and in part to an increased awareness of the
environment.
One of the most abundant sources of renewable energy is wind, and technology
exists today for the efficient extraction of energy from wind for power
generation. The efficiency of wind power is tied to a number of factors,
one of which is the positioning of wind turbines near other wind turbines
or structures. Decreased distances give rise to wake effects for the downstream
units, which can lead to changeable wind loads, reduced energy yield,
and vibration induced fatigue on the rotors and potentially on nearby
power lines.
One popular operation concept for wind turbines allows for adjustments
in the blade pitch to deliver a reasonably constant power output when
there are variations in the wind speed. The wake behind these so-called
“pitch-regulated” wind turbines depends on a number of parameters,
such as blade geometry, pitch angle, and rotor speed on the hardware side
and wind velocity, turbulence characteristics, and wind gradients on the
environmental side. The large number of governing parameters makes it
difficult to judge whether wake influences will lead to loads not considered
during the original construction process. In a recent series of simulations
at TÜV Nord e.V., FLUENT has been used to examine the wakes behind
wind turbines of this type on the basis of their geometry and operating
characteristics.
TÜV Nord e.V. is one of Germany’s Technical Inspection Agencies
and has the goal of protecting humanity, the environment, and property
against detrimental effects caused by technical installations and systems
of every kind. To this end, it promotes the economic installation or manufacture
and use of technical equipment, production, and operating facilities.
In a typical simulation, approximately 650 data points are used to create
the geometry of a single rotor blade. A fine grid on the whole rotor surface
is used to create a volume mesh of about 750,000 cells that gradually
coarsens as the distance from the blades increases. The dimensions of
the flow domain are adjusted to suit the needs of the specific problem.
Downstream distances of six to ten times the rotor diameter have been
modeled so far. The multiple reference frames (MRF) model is used to account
for the rotation of the blades. Blade pitch, wind speed and direction,
turbulence intensity and length scale, and rotor speed are input for each
simulation.
Velocity contours behind one turbine show the wake effect on a second,
smaller turbine
The geometry (front) and typical surface mesh (back) of a turbine rotor
and hub
To validate the CFD model, wake measurements behind a 55 kW pitch-regulated
turbine were taken from the literature [Ref. 1]. Despite some inconsistencies
in the measured wind velocities, good agreement between the measurements
and calculated values was obtained. In addition, calculations presented
in Reference 1, based on a simpler model that did not use the blade geometry,
were not able to predict flow details that were captured by the 3D FLUENT
runs. In particular, the enhancement of wind velocity at the edges of
the wake could only be predicted by the CFD calculations, even though
the magnitude of the enhancement was larger than the measured value.
Once the model was validated, it was used for several investigations
of wake effects. On the previous page, one wind turbine is shown operating
in the wake of a second, larger turbine. A wind velocity of 12.5 m/sec,
with a turbulence intensity of 13%, was imposed upstream of the front
turbine. Filled contours of constant mean velocity in the plane of the
smaller turbine, four diameters behind the front turbine, show that the
velocity field is nonuniform and not centered on the hub. Line contours
in the plane containing the two turbines illustrate the decay in the wake
as a function of distance behind the turbine. These results were used
to help analyze the special wake loads experienced by the rear turbine.
Velocity magnitude slightly downstream of the rotor plane
Velocity magnitude in the wake of a wind turbine
In another example, the excitation of vibrations in a power line was
studied. Wind speeds in the range of 1 to 7 m/s and normal to the direction
of the power line are most likely to cause these vibrations [Ref. 2].
If there is a considerable shift in the wind speeds due to wake loadings
on the power line, the installation of vibration dampers on the power
lines might be indicated. In the case studied, where the power line runs
25m above the ground, well below the turbine hub, the wake passes over
the power line without causing any interference.
Currently, there is little data available for the turbulence intensity
in the vicinity of installed wind turbines, and this point requires further
investigation. Today, different empirical models are used to predict
turbulence intensity in the wake of wind turbines [Ref. 3, 4]. Since
these models only predict single averaged values along the wake axis
and differ from one another, they cannot be used to validate the CFD calculations.
The distribution of turbulence intensity computed by FLUENT in the wake
region is in reasonably good agreement with theory. Absolute values,
however, fall well below measured turbulence intensities due to effects
not captured in the current model (e.g. tip vortices and wake meandering).
Nonetheless, the flexibility and increased rigor of the CFD calculations,
when compared to the simpler models, suggests that this methodology can
offer improved insight into the efficient production of wind energy in
the years to come.
In summary, given the rotor geometry and operating characteristics, CFD
calculations are able to predict the wind velocities inside the wake of
a wind turbine. Specific operating conditions, such as pitch angle and
rotor speed, can easily be analyzed. Three-dimensional simulations of
wind turbines can also be extended to include landscape topography (see
Article 3) and other objects located in or near the wake.
Path lines through the turbine colored by velocity magnitude
References :
1. Beyer, H.G. et. al.; Messungen von Windgeschwindigkeit und Turbulenz
in der Nachlaufströmung eines 55 kW Windenergiekonverters mit variabler
Drehzahl (Measurement of windspeed profiles and turbulence in the flow
after a 55 kW wind energy converter with variable speed); DEWEK ’92,
Deutsche Windenergie-Konferenz 1992; Wilhelmshaven 1993.
2. Degener, T.; Kießling, F.; Tzschoppe, J.; Mindestabstand zwischen
Windenergieanlagen und Freileitungen (Minimum distance between wind energy
plants and overhead lines); Elektrizitätswirtschaft Jg. 98 (1999),
No. 7, p. 32-35.
3. Dekker, J.W.M.; Pierik, J.T.G. (Eds); European Wind Turbine Standards
II; Petten, The Netherlands: ECN Solar & Wind Energy, 1998.
4. Frandsen, St.; Thogersen, L.; Integrated Fatigue Loading for Wind
Turbines in Wind Farms by Combining Ambient Turbulence and Wakes; Wind
Engineering, Vol. 23, No. 6, 1999.
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