Comparison of Smart Rotor Blade Concepts for Large Offshore Wind Turbines
B.A.H. Marrant and Th. van Holten
Delft University of Technology, Faculty of Aerospace Engineering
Kluyverweg 1, 2629 HS Delft, The Netherlands
Tel.: +31 (0)15 27 85171
Fax.: +31 (0)15 27 83444
E-mail: B.Marrant@lr.tudelft.nl
Keywords: offshore, wind turbines, fatigue loads, smart materials, active rotor control
Abstract
This paper provides the results of a comparison of four different smart structure concepts to obtain active rotor control on
large offshore wind turbines. The concepts are active trailing-edge flap control, micro-electro-mechanical tab control,
camber control with inflatable structures and active blade twist control. The different smart rotor blade concepts are
compared with each other based on their potential to reduce fatigue loads for particular dimensions, their aerodynamic
efficiency, bandwidth and complexity.
Introduction
The aim of the research project on smart dynamic rotor control for large offshore wind turbines is to develop new
technology capable of considerably reducing the extreme and fatigue loads on wind turbines – in particular on very large
wind turbines for offshore application – and thereby to reduce the costs of wind turbines. A second aim is to reduce
maintenance requirements and improve reliability by applying condition-monitoring techniques.
The way to achieve this is to implement recent advances in control theory, sensor- and actuator technology, smart
structures, etc. taking into account the special requirements and conditions of offshore wind turbines. The FLEXHATprogram performed in the Netherlands some years ago has shown that “smart” control methods may have a significant effect
on the various loads [1]. The purpose of the former project was to decrease loads in the drive train and the rotor blades by
using passive tip control and flexibilities in the rotor system. Unfortunately, the techniques used within the FLEXHAT
configuration were not suitable for incorporation into very large wind turbines. Therefore, different solutions need to be
developed.
In a preliminary study [2,3] on smart dynamic rotor control for large offshore wind turbines different concepts have already
been investigated in wind energy and helicopter literature. Helicopter literature has also been studied because of its close
relation to the field of wind turbines. Moreover, smart dynamic rotor control for the purpose of e.g. vibration reduction is a
relatively new concept in wind energy whereas this topic has been the subject of study for many years in the field of
helicopters [4],[10].
The two approaches which will be used to reduce the structural loads on wind turbines are the reduction of the fluctuations
of aerodynamic loads and the active/passive damping of structural modes [5]. In the preliminary study a list of control
devices for rotor blades was made which could be used to control the extreme and fatigue loads. This list included trailingedge flap control (possibly combined with leading-edge flap control), Micro-Electro-Mechanical tab control, active twist
control, part-span and full-span pitch control and camber control. This study focused mainly on the feasibility of smart
materials as a means to actuate the devices. These concepts have already been presented in reference [6].
This paper will continue the previous work with the purpose to make a ranking of devices for the purpose of smart dynamic
rotor control. The most promising devices are considered to be trailing-edge flaps and Micro-Electro-Mechanical tabs
because of their relative simplicity and their potential. On top of these two devices active twist and variable camber with the
use of inflatable structures are also included. The actuators which are considered in this paper are mainly smart material
actuators based on piezoelectric materials. The different concepts that result from the devices and actuators are compared
with each other based on their potential to reduce aerodynamic loads, their aerodynamic efficiency, bandwidth and
complexity.
Approach to compare the smart blade concepts
The four smart blade concepts which were mentioned before will be compared with each other based on their ability to
reduce fatigue loads during normal operation of the wind turbine. The fatigue loads are used as a basis to compare the
concepts because wind turbine designs are often governed by fatigue [12] and because none of the smart blade concepts
mentioned previously will have the power to reduce the extreme loads completely. The fatigue load case during normal
power production (DLC 1.2), as described in the IEC standard [7], has been used as a basis for the comparison because this
will be the phase during which the smart blade will be operating most of its time. This means that normal power production
with the occurrence of an emergency, start up, normal shut down and stand still load cases have not been considered.
The fatigue load calculations for the conventional blade and the smart blade concepts have been performed for wind turbine
class I B because this involves a high reference wind speed average over 10 minutes (V ref = 50 m/s) and a medium
turbulence intensity at 15 m/s (Iref = 0.14) which is considered to be representative for offshore wind conditions.
The turbulence model which has been used is a three-dimensional, one component model, which means that the wind speed
varies over the rotor disc area in time. The method to simulate turbulence makes use of Fourier series to create a number of
correlated time series from the longitudinal velocity component spectrum (S1(f)) and a coherence function. The turbulence
spectrum used for the analysis is the Kaimal spectrum:
S1  f  
where
4 12 L1 Vhub
1  6 f L1
(1)
Vhub 
53
1=Iref(0.75Vhub+5.6):
is the longitudinal turbulence standard deviation with Iref=0.14
is the longitudinal velocity integral scale, where L1=8.11
is the wind speed at hub height
is the frequency in Hertz
L1:
Vhub:
f:
0.7 z z  60m
1  
42m z  60m
is the longitudinal turbulence scale parameter
The following exponential coherence model (Coh(r,f)) is used in conjunction with the Kaimal autospectrum to account for
the spatial correlation of the longitudinal wind speed component:
Cohr , f   exp  12

 f  r Vhub 2  0.12 r
2
L1  

(2)
where r is the magnitude of the projection of the separation vector between the two points on to a plane normal to the
average wind direction.
20
18
V [m/s]
16
14
12
10
8
160
140
120
100
80
60
40
z [m]
20
-60
-40
-20
0
20
40
60
y [m]
Figure 1: Turbulence for a wind speed of 13 m/s over the height (z) and the width (y)
An example of the turbulence at a wind speed of 13 m/s at time t=0 can be seen in figure 1 where the total grid spans 60 m x
60 m, the grid interspacing is 4 m and the hub height is 91.4 m. The turbulence was rotationally sampled by selecting wind
speeds out of the complete wind field at points in space and time corresponding to positions of the rotating blade of a
horizontal axis wind turbine. Correlated time series were generated in 60 equally spaced points on the rotor blade and linear
interpolation has been used when the point on the blade was in between the grid points.
The deterministic part of the wind field only consisted of wind shear where the longitudinal wind speed is given by the
following power law:
V z   Vhub z z hub 
0, 2
(3)
The fatigue loads for the different smart rotor blade concepts are compared making use of a benchmark wind turbine. For
this purpose an offshore wind turbine derived from the DOWEC (Dutch Offshore Wind Energy Converter) wind turbine
study [9] is used since this involves a horizontal axis (HAWT), upwind, pitch-regulated, variable speed turbine which has
the size and characteristics of a wind turbine this research is intended for. A drawing of the original DOWEC design can be
seen in figure 2 and some characteristic data of this benchmark turbine are presented in table 1.
Cut-in wind speed Vin
Cut-out wind speed Vout
Rated wind speed Vr
Tip speed ratio r
Hub height zhub (above the water)
Rotor diameter D
Rated power Pr
Figure 2: DOWEC wind turbine
3.0 m/s
25 m/s
12 m/s
7.4
91.4 m
120 m
6.0 MW
Table 1: Characteristic data of the benchmark wind
turbine
For the calculations of the loads the Windsim [18] package has been used with a few alterations in order to be able to
calculate the aerodynamic loading due to a distributed wind field. This package uses BEM theory for the calculations of the
aerodynamic loads in which the wake is approximated as constant over the rotor disc area. The smart rotor blade concepts
were compared by calculating their fatigue damage relative to the conventional blade. As a first approximation the dynamics
of the blade are neglected and only the variable aerodynamic loading due to the variable wind field is considered. The
maximum load alleviation capacity of the smart structures has been used in the analysis where it has been assumed that the
smart rotor blade knows exactly what the wind field looks like at every time step, moreover as a first approximation the
smart blade is assumed to react instantaneously to the load change. Making these assumptions has the inherent advantage
that the controller can be left out of the analysis which leads to a more straightforward comparison of the smart rotor blade
concepts. This way a first estimate can be made of the minimum required dimensions, deflections and deflection rates for
the different smart structure concepts.
The smart rotor blade concepts which are able to alter the aerodynamic blade loads can be divided into two categories:
blades which are able to actively change the airfoil’s camber thereby shifting the cl- curve up- or downward and blades
which are able to change the local angle-of-attack in order to obtain changes in lift coefficient. Trailing-edge flaps, MEMtabs and variable camber control belong to the first category whereas active twist control belongs to the second.
7
1.4
V = 13 m/s
x 10
Muu
1.3
mean
1.2
1
M
uu
[Nm]
1.1
0.9
0.8
0.7
0.6
420
425
430
435
t [s]
Figure 3: Variation of aerodynamic blade root bending moment due to a varying wind field and steady aerodynamic
blade root bending moment at a wind speed of 13 m/s
The steady condition of the wind turbine rotor for a uniform wind speed and uniform wake was determined for each wind
speed in the operational envelope after which the variations in the aerodynamic blade root loads due to the varying wind
field were calculated. The variations of the aerodynamic blade root bending moment for the benchmark turbine for a wind
speed at the hub of 13 m/s can be seen in figure 3 as well as the steady aerodynamic blade root moment which was
determined for uniform wind flow conditions. This is the blade root bending moment with respect to the blade chord
reference system. In the ideal case the smart blade should return the blade root bending moments to the mean value. Since
the potential of the smart blade is depending on the concept and smart structure length the aerodynamic bending moments
will be returned more or less to the mean bending moment. Figure 4 gives the aerodynamic blade root bending moment for
the conventional blade and the reduced blade root bending moments when a smart blade is used. In this example the smart
blade is able to change the camber of the blade with maximum changes in the lift coefficient of cl = ± 0.4. The length of the
smart structure is 33% of the total blade and is located outer part of the blade (near the blade tip). As can be seen from the
figure the amplitudes of the aerodynamic blade root loads have been reduced significantly for the smart rotor blade
compared to the conventional blade. The calculation of the blade loads have been done for time intervals exceeding 10
minutes. The same calculations have been done for different changes in lift coefficient and twist and percentages of the rotor
blade containing the smart structure.
7
1.4
x 10
V = 13 m/s, smart length = 33%,  c l = 0.4
Muu
Muu,smart, fmax = 
1.3
1.2
1
M
uu
[Nm]
1.1
0.9
0.8
0.7
0.6
420
425
430
435
t [s]
Figure 4: Variation of the aerodynamic blade root bending moment for the conventional and the smart blade due to
a varying wind field at a wind speed of 13 m/s
A smart blade which has the ability to react instantaneously to load changes because of its infinite bandwidth is not realistic.
A way to account for this limited bandwidth of the smart rotor blade concepts is by cutting-off of the maximum frequency
of the Fast Fourier Transform of the blade root bending moments of this smart rotor blade in figure 4.
7
1.4
x 10
V = 13 m/s, smart length = 33%,  c l = 0.4
Muu
Muu,smart, fmax = 
1.3
Muu,smart, fmax = 1Hz
1.2
1
M
uu
[Nm]
1.1
0.9
0.8
0.7
0.6
420
425
430
435
t [s]
Figure 5: Variation of the aerodynamic blade root bending moment for the conventional and the smart blade with
and without limited bandwidth due to a varying wind field at a wind speed of 13 m/s
The result can be seen in figure 5 where the smart rotor blade concept is now limited to a bandwidth of 1Hz. It can be seen
that the fluctuations in aerodynamic blade root bending of the smart rotor blade with limited bandwidth are still much
smaller than that of the conventional blade but there are more fluctuations with respect to the smart rotor blade with infinite
bandwidth. In figure 6 the power spectrum of the aerodynamic blade root bending moments for a wind speed of 13 m/s can
be seen for a) the conventional blade and b) the smart rotor blade. The dashed lines represent the 1P, 2P, 3P and 4P
frequencies. It can clearly be seen that there is a large reduction in fatigue loads when a smart rotor blade is used at its
maximum performance.
V = 13 m/s
16
16
10
15
15
10
10
14
14
10
10
13
13
10
PSD [(Nm)2]
PSD [(Nm)2]
10
12
10
11
10
12
10
11
10
10
10
10
10
9
9
10
10
8
10
V= 13m/s, smart length = 33 %,  c l = 0.4
10
8
0.2356
0.4711
0.7067
f [Hz]
a)
0.9422
10
0.2356
0.4711
0.7067
f [Hz]
b)
0.9422
Figure 6: Power spectral density of the a) aerodynamic moment of the blade, b) aerodynamic and smart structure
moment
Once the aerodynamic blade root bending moments of the conventional and smart structure blade were determined for the
varying wind conditions they were converted to both compressive and tensile stresses in the blade root structure. Thereafter
the rainflow counting method [11], was used to determine the number of cycles at each stress amplitude and mean stress
value combination. The fatigue damage at each wind speed was then determined with the Palmgren-Miner rule for the
conventional rotor blade and the different smart rotor blade concepts with varying smart structure lengths:
d i, j 
ni , j
(4)
N i, j
where di,j is the fatigue damage, ni,j is the number of cycles at a particular stress amplitude and mean stress combination as
determined with the Rainflow counting method and Ni,j is the number of allowable cycles before the structure will fail for
each stress amplitude i and mean stress j combination. When the damage d is equal to 1, the structure is at the end of its life.
The number of allowable cycles N for the case of mean tensile stress [12] for composites can be calculated with:







N 

  1   mean  
 tu 
 tu  
 
10
(5)
where tu is the ultimate tensile stress,  is the stress amplitude and mean is the mean stress. In the case of mean
compressive stress tu is replaced with -cu in the mean term. The values of tu and cu for a glass/polyester ply are used with
50% fibre volume fraction unidirectional fibres running in the longitudinal direction, because this is the most popular
composite material to build blades with [12]. Then all the damages for each wind speed have been summed up. In order to
make a direct comparison with the conventional blade the ratio of the damage for the smart rotor blade and the conventional
blade is used at each wind speed. In order to obtain an overall relative damage factor, the relative damages for each smart
blade concept at each wind speed are summed up taking into account the amount of time the wind turbine is operating at that
particular wind speed:
K   k
k
d k , smart
(6)
d k ,conv
where K is the overall relative damage factor, k is the wind speed, dk,smart is the total damage of the smart blade, dk,conv is the
damage of the conventional blade and k is the fraction of time the wind turbine is operating at a particular wind speed k as
determined with a Rayleigh wind speed distribution. Therefore the different smart blade concepts can be compared using
their overall relative damage factor for both tension and compression (see equation (5) and its counterpart for compression).
Since the structure gets more damage in case of a mean compressive stress, only the overall relative damage factors for
mean compressive stress will be considered. However, the overall relative damage factors for compressive and tensile mean
stress are very close to each other for the material under consideration.
Smart rotor blade concepts
The concepts considered for active load control on wind turbines are active trailing-edge flaps, MEM-tabs, inflatable
structures for active camber control and active blade twist. As mentioned before, they are able to control the effective airfoil
camber or the local blade pitch. Since these devices mainly influence the lift forces and not as much the drag, their strength
lies in the possibility to change the out-of-plane bending moments of the blades. Devices which can have an influence on the
in-plane blade bending moments will probably need to be of non-aerodynamic origin. The actuators which have been
considered for the previous devices are piezoelectric actuators. Piezo-electric materials are able to provide excitations at
very high frequencies, much higher than required for load alleviation purposes on large wind turbines, however because of
the difference in dimensions (and inertia) of the different smart blade concepts there will be a difference in maximum
frequency which can be obtained with the piezoelectric actuators. Piezoelectric materials are able to exhibit maximum
strains around 2000 [25].
When active trailing-edge flaps, see figure 8, are considered for active load control two possible concepts can be mentioned:
active trailing-edge flaps with a physical hinge to make flap deflections possible and smart structure trailing-edge flaps
based on bender elements.
Figure 7: Trailing-edge flap concepts
Active trailing-edge flaps with a hinge are a classic approach and are commonly used both on helicopters and airplanes.
They can be actuated using a piezoelectric stack actuator in combination with an LL-amplifier [10] or with classic electroactuators. Piezoelectric stack actuators consist of several layers of piezoelectric sheet material where normal strain is used as
driver. Stacks are capable of delivering large forces but only small displacements. Therefore they need to be amplified with
an LL-amplifier.
Figure 8: Stack actuator with LL-amplification
Trailing-edge flap control with piezoelectric stack actuators has been proven on a full scale helicopter rotor with flap
deflections of -10 to +8 . The smart structure trailing-edge flap can be thought of as a unimorph or bimorph actuator, see
figure 9, which could be used as a retrofit on existing rotor blades without the need to make many changes to the structure of
the blade. Unimorphs and bimorphs are bender actuators. A bender actuator is obtained when two layers are operated such
that one extends and the other contracts. These actuators can give large displacements but only relatively small forces. The
Riso-B1-18 airfoil makes use of such a trailing-edge flap to obtain lift control [14]. The performance of these actuators can
be improved when holding them under compression as has been shown on UAV’s [26]. In reference [4,6] lift control and
moment control were considered for trailing-edge flaps. With direct lift control the change in effective camber leads to a
change in lift. In the case of moment control, the blade root is considered to be soft. Therefore the change in effective
camber results in a twist of the blade which indirectly leads to a change in lift. Since wind turbine rotor blades exhibit
relatively large torsion stiffness, direct lift control is considered to be the logic option for wind turbines. Typical possible
changes in lift coefficient are in the order of cl=0.4 and even maxima of cl=0.5 have been found in literature
[14,15,17]. The aerodynamic efficiency which is characterised by the lift over drag ratio is hardly influenced at small
angles-of-attack when the trailing-edge flap is deflected. Active trailing-edge flaps have relatively fast response times,
especially when the total trailing-edge flap is divided into separate segments, therefore reducing its inertia and making it
more fail-safe. The response times of trailing-edge flaps will be slower than MEM-tabs but faster than active blade twist. A
disadvantage of active trailing-edge flaps is that they usually give rise to acoustic problems.
Figure 3: Unimorph and bimorph bender elements
Micro-electro-mechanical (MEM) translational tabs were proposed for active load control by D. Yen and C.P. van Dam
[8,20], see figure 10. MEM-tabs are derived from Guerney flaps which were introduced by Liebeck in 1978 [21]. They are
installed near the trailing-edge of the rotor blade for maximum effect on the Kutta condition. When moving the location of
the MEM-tab in the direction of the leading-edge it becomes less effective but for tab-locations up to 95% chord its
effectiveness can be guaranteed [16]. When moving the tab-location further in the direction of the leading-edge, the tab will
lose its effect due to reattachment of the flow behind the tab. The MEM-tab deploys approximately normal to the surface
and has a maximum translation in the order of the boundary layer thickness, 1-2% of the chord. Figure 10 only shows a
MEM-tab which is deployed on the upper surface in order to reduce the lift, but the same device can also be placed at the
trailing-edge of the bottom surface to increase the lift. Another possibility to reduce the lift is to locate the tab near the onset
of pressure recovery in order to induce flow separation. When the upper and lower tab are both installed near the trailingedge, typical increases in lift coefficient which have been found in literature [13,15,16,20] are cl=0.3 for a tab height-tochord ratio ht/c=1% with maximum increases of cl=+0.4 for a ht/c=2% and when the upper tab is located at the onset of
pressure recovery even values of cl=-0.55 have been found. The lift over drag ratios of airfoils with MEM-tabs decrease
with respect to the base airfoil for lift coefficients up to the base airfoil maximum lift coefficient, above this maximum lift
coefficient it may exceed the lift over drag ratios of the base airfoil. Therefore smart blades with MEM tabs will have a
negative influence on the power production since lower lift over drag values are encountered [22]. For the current generation
of airfoils it will not be easy to implement these devices at the trailing-edge because the volume available to install the
MEM tabs is limited. This means that when MEM-tabs are to be used in smart rotor blades, airfoils with an increased
trailing-edge thickness should be designed to include these tabs. Another possibility to overcome this problem would be the
use of rotational tabs instead of translational tabs. In case of a rotational tab, the tab would be hinged at the airfoil skin
making it possible to take a position perpendicular to the surface as well as tangential to the surface when it is not deployed.
and from the Because of the minute size of these devices, much faster response times will be achieved than with any other
concept mentioned in this paper. According to the specifications in reference [20] these MEM-tabs could even have a
maximum frequency in the order of 70 Hz when magnetic actuation is used. However, magnetic actuation has only been
proven in a laboratory environment which means that the maximum obtainable frequency will be much lower. MEM-tabs
can be actuated using classic electro-actuators or smart material actuators based on piezoelectric materials.
Figure 4: MEM-tabs
Another means of controlling the airfoil lift is the use of camber control, see figure 11. Changing the airfoil camber with the
use of smart material fibres embedded in the skin is not possible as has been shown in reference [4,6] since there are no
smart materials on the market which are able to exhibit such large strains (in the order of 98000). Therefore another set-up
is proposed being active camber control with the use of inflatables. Inflatables have found an increasing amount of
applications, e.g. in the military and space applications where these structures need to stay operational in a harsh
environment. In this case several separate air chambers on the “top” or the “bottom” surface of the airfoil are inflated which
push a flexible rubber skin more outward, thus increasing/decreasing the camber of the airfoil. Using many air chambers
provides the stiffness of the flexible outer skin. The air chambers can be inflated or deflated with a piston like arrangement
as in a car engine or with an air pressure vessel which is held under pressure with an air-pump. This might involve a
complex system and leakage may be one of the biggest problems. Instead of air, viscid fluids might also be used to ensure
maximum rigidity but this has a negative effect on the weight. The changes in lift coefficient as well as the maximum
frequency which can be obtained with this concept are assumed to be comparable with trailing-edge flaps as given above. In
the case that the outer skin does not get any bubbles, a clear advantage would be the smoother surface skin which would
reduce the acoustical problems encountered with trailing-edge flaps.
Figure 5: Camber control with inflatable structures
Active blade twist, see figure 12, can be accomplished with the use of piezo-fibre composites when the orientation of the
smart fibres is 45 with respect to the direction of the main spar of the blade such that actuation of the active fibres produces
a shear deformation of the blade. Active fibre composites are developed at the Active Materials and Structures Lab at MIT.
This type of device has uniaxially aligned piezoceramic fibres surrounded by a polymer matrix and can include inactive
glass fibres for increased structural strength. Interdigitated electrodes deliver the electric field required to activate the
piezoelectric effect in the fibres as seen in figure 13.
Figure 6: Active blade twist
Therefore they are called Inter-Digitated Electrode Fibre Composites (IDEPFC) [23]. Active fibre composites offer many
advantages with respect to their monolithic counterparts [24]. The multiphase construction yields a more robust actuator
which can be added to a lay-up as an active layer along with the conventional fibre-reinforced laminae. Also the flexible
nature of the polymer matrix allows the material to more easily conform to the curved surfaces such as in airfoils. Moreover
the polymer matrix protects the active piezoelectric fibres which have a brittle nature. The strain required to obtain a twist of
4 at the tip has been determined to be in the order of 800 for a wind turbine blade of 60 meters with a chord of 3.4 meters
and a t/c ratio of 28%. This amount of strain is still feasible for piezoelectric materials. However this was determined for a
straight blade, for a tapered blade the strains will consequently be higher. The inherent problem with active blade twist is
that the complete blade must be made with active fibre composites. This will lead to huge costs because of the large amount
of costly piezoelectric materials and to an increase in blade weight since led is one of the components in piezoelectric
materials. The same concept has already applied on helicopter rotor blades [10]. However, the control forces to obtain active
twist will be much higher for wind turbine blades with respect to the helicopter rotor blades because of the much larger t/c
ratio of typical wind turbine airfoils. Because of this and the relatively large inertia active blade twist will show the slowest
response times with respect to the other concepts mentioned in the paper. A clear advantage of this concept is that a smooth
rotor blade is obtained which does not change the aerodynamic behaviour of the original blade design.
Figure 7: Inter-Digitated Electrode Piezoelectric Fibre Composite
Comparison of smart rotor blade concepts
The smart rotor blade concepts can be compared with each other based on their overall relative damage factor K. This factor
K gives the fatigue damage of a smart rotor blade concept as a fraction of the fatigue damage of the conventional blade
without smart structures during normal power production. When the smart structure length of the rotor blade is 0% the blade
becomes the conventional blade and K goes to 1. The smart rotor blade concepts are compared in figure 14 for actuators
with an infinite bandwidth, i.e. they are able to react instantaneously to load changes, and for different smart structure
lengths in span wise direction where the smart structure always starts from the blade tip. Before attaching too much
importance to the overall relative damage factor K it must be emphasised that the smart rotor blade concepts in the analysis
are able to react infinitely fast to the load changes and know these load changes before they even occur. Therefore the
reduction in damage with respect to the conventional blade has hardly any significance, only the relative differences
between the concepts are important.
0
10
c l = 0.4
 = 2deg
Overall relative damage factor [-]
-1
10
 = 4deg
c l = -0.55 - 0.3
-2
10
c l = 0.5
c l = -0.55 - 0.4
-3
10
c l = 0.3
-4
10
-5
10
0
20
40
60
Smart length [%]
80
100
Figure 8: Comparison of smart rotor blade concepts with infinite bandwidth
From figure 14 it can be seen that the fatigue loads can be reduced more when the smart structure length is increasing but
smart structure lengths exceeding 30% become less effective in reducing fatigue loads. Trailing-edge flap control or camber
control (both cl=0.4) reduce the fatigue loads more than MEM-tab control when the upper and lower tab are both located
near the trailing-edge (cl=0.3) for a tab height over chord ratio: ht/c=1%. In case that the upper tab is located near the
onset of pressure recovery to induce flow separation downstream of the tab (cl=-0.55 - +0.3) nearly the same reductions in
fatigue are obtained as for the trailing-edge flap and camber control concept up to 30% smart structure length. For larger
smart structure lengths the trailing-edge flap and camber control concept become more effective in reducing the loads.
When a larger MEM-tab (ht/c= 2%) at the lower surface is used (cl=-0.55 – +0.4) the reduction in loads are the same as for
the smaller pressure tab (ht/c=1% and cl=-0.55 - +0.3) for all smart structure lengths but the larger tab will lead to larger
drag and thereby reducing the aerodynamic efficiency. When the trailing-edge flap control and camber control are pushed to
their extremes (cl=0.5) the largest load reductions can be seen. However this will also lead to larger drags due to flow
separation. In case of active twist control, the complete blade is twisted which means that the smart structure length is equal
to 100%.
From figure 14 it can be concluded that active twist control (tip angles: =2 and =4) is not an efficient way to
reduce loads since the same load reduction can be obtained with trailing-edge flap control/camber control (cl=0.4) and
MEM-tab control (cl=-0.55 - +0.3) but this with only 17% smart structure length instead of 100% for the =2 and 35%
smart structure length instead of 100% for the =4 active twist concept.
The smart rotor blade concepts are compared in figure 15 for actuators with a finite bandwidth, i.e. they know the load
changes before they occur but cannot react infinitely fast to these changes, and for different smart structure lengths in span
wise direction. It can be seen in the figure the damage reductions by the smart rotor blades become less than for the case
where the smart rotor blades have infinite bandwidth leading to more realistic reductions in fatigue damage. Taking time
delays due to the controller and the unsteady aerodynamics will improve the predictions of the fatigue reduction. Since the
bandwidth of the different smart rotor blade concepts are not very well known, some numbers have been assumed while
keeping their relative reaction quickness into account. MEM-tabs are considered to be twice as fast as active trailing-edge
flaps/active camber control and four times as fast as active twist. Although active trailing-edge flaps/active camber control
(cl=0.4, fmax=1Hz) is slower than MEM-tab control (cl=0.3,fmax=2Hz), it gives the largest reduction in fatigue loads.
Only MEM-tabs with a larger tab at the lower surface (cl=-0.55 - +0.3,fmax=2Hz) can keep up with the active trailing-edge
flap/active camber control concept up to 15% smart structure length.
0
10
 c l = 0.3, fmax = 2Hz
Overall relative damage factor [-]
 c l = 0.4, fmax = 1Hz
 c l = -0.55 - 0.3, fmax = 2 Hz
 = 2deg, fmax = 0.5 Hz
-1
10
-2
10
0
10
20
30
40
50
60
Smart length [%]
70
80
90
100
Figure 9: Comparison of smart rotor blade concepts with limited bandwidth
Conclusions
From the preceding analysis it can be stated that active trailing-edge flap control/active camber control (cl=0.4) is about
twice as effective as MEM-tab control (cl=0.3). Only MEM-tabs with a larger tab at the lower surface (cl=-0.55 +0.3,fmax=2Hz) can keep up with the active trailing-edge flap/active camber control concept up to 15% smart structure
length. For active trailing-edge flaps, active camber control and MEM tabs, smart structure lengths of 30% are most
efficient for the reduction of fatigue loads. Although active twist control is feasible, it is expensive, results in heavier blades
and is a very inefficient way to reduce fatigue loads. Since active camber control with inflatable structures is a relatively
new concept in wind energy this will need to be investigated further.
Acknowledgements
This research is supported by the Technology Foundation STW, applied science division of NWO and the technology
programme of the Ministry of Economic Affairs. I also want to thank ir. W.A.A.M. Bierbooms for the use of the Windsim
package.
References
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
[26]
G.A.M. van Kuik, J.W.M. Dekker, The FLEXHAT program, technology development and testing of flexible rotor
systems with fast passive pitch control, Journal of Wind Engineering and Industrial Aerodynamics, 39 (1992) 435448
B.A.H. Marrant, K. Hinnen, Th. Van Holten, G.A.M. van Kuik, Smart Dynamic Rotor Control of Large Offshore
Wind Turbines, Inventory of Present Techniques, Duwind 2002.011, May 2002
B.A.H. Marrant, Th. Van Holten, G.A.M. van Kuik, Smart Dynamic Rotor Control of Large Offshore Wind
Turbines,
Inventory of Rotor Design Options and Possible Load Reductions, Duwind 2002.012, May 2002
F.K. Straub, A feasibility study of using smart materials for rotor control, Smart Material Structures 5, 1-10, 1996
M. Geyler, Advanced Pitch Control for Wind Turbines, Duwind 2001.001, January 2001
B.A.H. Marrant and Th. van Holten, Smart Dynamic Rotor Control on Large Offshore Wind Turbines, Napels, April,
2003, Naples, Campania, Italy
IEC 61400-1 Ed.3, Wind Turbines, PART 1: Design Requirements, 25 May 2006
D.T. Yen, C.P. van Dam, R.L. Smith and S.D. Collins, Active load control for wind turbine blades using mem
translational tabs, AIAA 2001-0031, Wind Energy 2001, January 2001, Reno CA
H.J.T.Kooijman, C. Lindenburg, D. Winkelaar, E.L. van der Hooft, DOWEC 6 MW pre-design: Aeroelastic
modelling of the DOWEC 6 MW pre-design in PHATAS, DOWEC-F1W2-HJK-01-046/9, September 2000
I. Chopra, A. Gessow, Recent Progress on the Development of a Smart Rotor System, 26th European Rotorcraft
Forum, September 26-29 2000, The Hague, The Netherlands
International Energy Agency, International Recommended Practices for Wind Energy Conversion Systems Testing:
(3) Fatigue Characteristics, 1984
T. Burton, D. Sharpe, N. Jenkins, E. Bossanyi, Wind Energy handbook, ISBN 0 471 48997 2, John Wiley and Sons,
Ltd, 2001
J.R. Zayas, Active Aerodynamic Load Control For Wind Turbine Blades, EWEC, Athens, Greece, 2006
N. Troldborg, Computational Study of the Riso-B1-18 airfoil with a hinged flap providing variable trailing-edge
geometry, Wind Engineering, Vol. 29, No. 2, 2005
W.A. Timmer, R.P.J.O.M. Rooij, Summary of the Delft University Wind Turbine Dedicated Airfoils, AIAA-20030352
K.J. Standish, C.P. van Dam, Computational Analysis of a Microtab-Based Aerodynamic Load Control System for
Rotor Blades, Journal of the American Helicopter Society
I. Abott, A. Von Doenhoff, Theory of Wing Sections, Dover publications, Inc. New York, 1958
WINDSIM: http://www.duwind.tudelft.nl/Website%20WINDSIM/main.htm
D.T. Yen, C.P. van Dam, R.L. Smith and S.D. Collins, Active load control for wind turbine blades using mem
translational tabs, AIAA 2001-0031, Wind Energy 2001, January 2001, Reno CA
D.T. Yen, C.P. van Dam, F. Bräuchle, R.L. Smith and S.D. Collins, Active Load Control and Lift Enhancement
Using MEM Translational Tabs, AIAA 2000-2242, Fluids 2000, 19-22 June 2000, Denver CO
R.H. Liebeck, Design of Subsonic Airfoils for High Lift, Journal of Aircraft, Vol. 15, (9), September 1978, pp. 547561
W.A. Timmer, R.P.J.O.M. Rooij, Design of Airfoils for Wind Turbine Blades, Delft University of Technology, The
Netherlands, 3 May, 2004
R.C. Derham, N.W. Hagood, Rotor Design Using Smart Materials to Actively Twist Blades, AHS 52 nd Annual
Forum, Washington D.C., June 4-6, 1996
R.B. Williams, D.J. Innman, An Overview of Composite Actuators with Piezoceramic Fibres, Centre for Intelligent
Material Systems and Structures, Department of Mechanical Engineeering, Virginia
B. Enenkel, V. Klöppel, D. Preißler, Full Scale Rotor with Piezoelectric Actuated Blade Flaps, 28th European
Rotorcraft Forum, September 17-19, 2002, Bristol United Kingdom
R. Vos, “Post-Buckled Precompressed elements: a new class of control actuators for morphing wing UAV’s”, Master
thesis, TU Delft, 2005