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Figure 6 shows vortex cores and limiting streamlines on
the blade suction surface in the conventional and
optimal cases obtained by the RANS simulations.
Behaviors of separation vortices behind the brim of the
wind-lenses are significantly different between both
cases. In the conventional case, two large-scale
separation vortices are observed behind the brim.
However, only one large-scale separation vortex is
observed in the optimal case. Figure 7 shows
meridional streamlines and meridional velocity
distributions in tangentially-averaged flow fields
obtained by the RANS simulations. As mentioned above,
in the optimal case shown in Figure 7 (b), the
separation region behind the brim is much smaller than
the conventional case and there is no separation inside
the wind-lens. The suppression of the flow separation
behind the brim and inside the wind-lens in the optimal
case may be affected by the divergence angle in the
wind-lens, the brim height and the span-wise
distribution of the blade loading.
In order to achieve higher aerodynamic performance of
the wind-lens turbine, it is important that the design of
the rotor blade is performed coupled with the wind-lens.
These results indicate that the present aerodynamic
optimization for the wind-lens turbine design works well.
Aerodynamic Design Optimization of
Wind-lens Turbine
Nobuhito Oka, Masato Furukawa, Kazutoyo Yamada, Kenta Kawamitsu, Kota Kido and Akihiro Oka Kyushu University, Japan
PO.ID
210
A new type of DAWT called wind-lens turbine shown in Figure 1 was developed in Kyushu University, Japan [1].
The distinctive feature of the wind-lens turbine is a brim
attached at the diffuser exit as shown in Figure 2. The
brim generates separation vortices behind it and the
diffuser creates meridional streamline curvature, so that
a low-pressure field is formed at the diffuser exit. The
low-pressure field draws the upstream wind into the
wind-lens and it generates non-uniform meridional flow
distributions at the rotor. This wind concentration on the
turbine rotor results in the significant enhancement of
the turbine output.
An optimum aerodynamic design method for the new
type of diffuser augmented wind turbine (DAWT) called
wind-lens turbine has been developed. The optimum design method is based on a genetic algorithm (GA)
and a quasi-three-dimensional aerodynamic design
method. The quasi-three-dimensional aerodynamic
design consists of meridional viscous flow calculation
and two-dimensional blade element design.
Aerodynamic performances of optimal and conventional
design cases are obtained from three-dimensional
Reynolds averaged Navier-Stokes (RANS) simulations.
The output power coefficient of the optimal case is
superior to the Betz limit. The numerical results show
that the aerodynamic performance of the wind-lens
turbine is affected by flow separations behind the wind-
lens brim and inside the wind-lens.
Abstracts
Optimum Aerodynamic Design Method
Introduction
Three-Dimensional Flow Field
References
EWEA 2014, Barcelona, Spain: Europes Premier Wind Energy Event
Rotor
Wind-lensHub
Bell-mouth
Diffuser
Brim
Separationvortex
Rotor
Inlet flowdistributions Internal flow field
External flow field
Figure 1: Wind-lens turbine Figure 2: Schematic flow structure
Figure 3: Flow chart of optimum aerodynamic design method
Initial design specificationInitial design specificationInitial design specification
Mutation
Crossover
Optimized design
3-D shape of wind lens turbine& Aerodynamic performance
Result of the calculation Flow rate in wind-lens Inlet flow distribution
Blade loading distribution
3-D blade shape Unit vector normal to
blade camber (nz , nr , n ) Relative flow angle
ConvergenceTwo dimensional blade element designTwo dimensional blade element theory on the
basis of the momentum theorem of ducted turbineDesignation of optional blade loading distribution
Evaluation & Selection
Convergence
Yes
No
Yes
No
Quasi three dimensional aerodynamic design method
Meridional viscous Flow calculationCoupling problem of the internal and external flow fieldAxisymmetric viscous flow calculation on meridional planeBlade force is introduced as body force
Decision of wind-lens meridional shape& Blade loading distribution (r)
Design Specifications
A quasi-three-dimensional aerodynamic design method
has been developed for the wind-lens turbine, which
can take into account the non-uniform meridional flow
distributions [2]. The design method mainly consists of
two parts: meridional viscous flow calculation and two-
dimensional blade element design. The meridional
viscous flow calculation is introduced to obtain the non-
uniform meridional flow distributions of the turbine rotor
inlet. Using the blade loading distribution and the
velocity distribution, the 3-D blade shape is designed by
the two dimensional blade element design method.
Taking into account the blade force, the meridional
viscous flow calculation is performed again. By
repeating the meridional viscous flow calculation and
the two dimensional blade element design, the blade
shape and the flow field are converged [2].
In the present study, a genetic algorithm (GA) has been
applied to the design method. The optimization objects
are the meridional shape of wind-lens and the blade
loading distribution. The same design specifications are
adopted except for the wind-lens shape and blade
loading distribution. A flow chart of the present optimum
design method is shown in Figure 3. The evaluation and
selection model is a Non-dominated Sorting Genetic
Algorithm II (NSGA-II) [3]. The crossover model is a
Real-coded Ensemble Crossover (REX) [4]. In the
optimization procedure, the aerodynamic performances
of each individual are obtained from the meridional
viscous flow calculation.
CW* K
Optimal 0.604 1.01
Conventional 0.474 1.07
Betz limit 0.593 0.66
Table 1 shows the aerodynamic performances obtained
from the RANS simulations at the design operating
condition. The table shows that the output power
coefficient CW* in the optimal case is superior to that in
the other cases. That is also superior to the Betz limit.
As far as the authors know, the optimal design of the
present study is the only one which achieves a higher
output power coefficient than the Betz limit.
0.4
0.5
0.6
0.7
-0.1 0 0.1 0.2
Ra
diu
s r/
D
Axial distance z/D
Conventional
Optimal
0
0.2
0.4
0.6
0.8
1
0 0.5 1 1.5 2
Sp
an
wis
e d
ista
nce
Local load coefficient (r)
Conventional
Optimal
(Hub)
(Tip)
Figure 4: Wind-lens shapes Figure 5: Blade loading distributions
Figure 4 shows the wind-lens shapes in the
conventional and optimal cases. In the optimal case, the
divergence angle of the near the diffuser exit is smaller,
the position of the wind-lens is located more backward
and the height of the wind-lens brim becomes lower
than that in the conventional case. Figure 5 shows the
blade loading distributions in the optimal and
conventional cases. Although a qualitative coincidence
of the blade loading distributions is observed between
the optimal and conventional designs, the blade loading
coefficients from mid-span section to tip section are
significantly different.
Aerodynamic Performance
The aerodynamic performances of the wind-lens turbine
are evaluated by the output power coefficient CW* and
the wind collection coefficient K. The output power
coefficient CW* is defined with the cross-sectional area
of the A* based on the outer diameter of wind-lens as
follows:
(1)
where is the density of air, V is the free-stream wind velocity and W is the wind turbine output power. The
theoretical limitation of the output power coefficient CW*
is CW* =0.593 according to the Betz limit. The wind
collection coefficient K is defined as the ratio of the
cross-sectional averaged velocity at the rotor inlet to
the free-stream velocity V as follows:
(2)
WW
CV A
*3 * 2
vK
V1
v11. Ohya, Y., et al., Development of a shrouded wind turbine with a flanged
diffuser, Journal of Wind Engineering, Vol.96, pp.524-539., 2008
2. Oka, N., et al., Aerodynamic Design for Wind-Lens Turbine Using Optimization Technique, Proceedings of the ASME 2013 FEDSM, Paper No. FEDSM2013-16569., 2013
3. Deb, K., et al., A Fast and Elitist Multiobjective Genetic Algorithm : NSGA-II, IEEE Trans. on evolutional computation, Vol. 6, No. 2, pp.182-197., 2002
4. Kobayashi, S., The frontiers of real-coded genetic algorithms, Journal of the Japanese Society for Artificial Intelligence, Vol24, No.1, pp.147-162., 2009
Table 1: Aerodynamic performances
Trailing vortex
Separation
vortex
CM
0.4132650.3673470.3214290.275510.2295920.1836730.1377550.09183670.04591840
Hn[-]1.0
-1.0
Wind-lens
Flow
Rotation
Trailing vortex
Separation
vortex
CM
0.4132650.3673470.3214290.275510.2295920.1836730.1377550.09183670.04591840
Hn[-]1.0
-1.0
Wind-lens
Flow
Rotation
(a) Conventional
Figure 6: Three-dimensional flow fields
(b) Optimal
Flow
Wind-lens
Rotor
Separation vortex
CM
0.4132650.3673470.3214290.275510.2295920.1836730.1377550.09183670.04591840
vm/Utip[-]0.48
0.00Flow separation
inside the wind-lens
(a) Conventional
Figure 7 : Meridional streamlines and meridional velocity distributions
(b) Optimal