Tong W. Wind Power Generation and Wind Turbine Design

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Implementation of The ‘Smart’ Rotor Concept 495

the dSpace™ system. Inputs and outputs for, e.g. setting values and plotting and

recording signals can also be incorporated and linked to Control Desk™, a graphi-

cal user interface (GUI) ( Fig. 20 ). From the dSpace™ hardware, one signal goes

to the pitch system, which consists of a linear motor and two signals go to the high

voltage ampliﬁ er which drives both sets of piezoelectric benders.

Inputs to dSpace™ include: the actual pitch displacement (feedback from the

pitch system), the actual voltage on the piezoelectric benders (output of the ampliﬁ er),

strain at the root of the blade and acceleration of the tip.

A critical part of the blade's design is the dynamics. The ﬁ rst natural vibration

mode should be scaled with respect to two parameters:

The frequencies of the disturbances on the blade. HAWT blades are mainly sub-1.

jected to loads associated with its rotational frequency or multiples of that – 1P, 2P

and 3P. Proximity of vibrational modes will inﬂ uence the dynamic response under

Pitch system

Strain sensor

(PZT patch)

Actuator

Table

Figure 18: Wind tunnel set-up for load alleviation experiments. The airﬂ ow goes

from right-to-left in this picture.

Figure 19: Design of the active control surface.

496 Wind Power Generation and Wind Turbine Design

loading. However, this can also be tuned by changing the frequency spectrum of

the disturbances which is controlled by the pitch system.

The second type of dynamic effects to take into account, is the unsteadiness 2.

of the aerodynamics. This is expressed by the parameter k , called the reduced

frequency:

( 46)

in which Ω is the frequency of the disturbances, V the undisturbed airspeed and b

the half cord of the aerofoil. With it, frequencies of disturbances can be scaled to

the dimensions of the blade and the wind speed. The aerodynamic delay, the phase

between a sine on the ﬂ ap and the resulting lift forces, is dependent on this reduced

frequency [ 112 ].

The blade is designed to match the frequencies that were derived from these

considerations. The target ﬁ rst ﬂ apping frequency was determined to be 19.2 Hz

and in the actual blade the eigenfrequency was 12.5 Hz. This was easily compen-

sated for by changing the airspeed and the frequencies of the disturbances to which

the blade is subjected. The blade was tuned by changing the internal structure, viz. the

number of glass-epoxy plies and the presence of a spar. A spar was added in the tip

because here the actuator slots were cut out. The spar adds additional stiffness and

strength and can be used as mounting point for the actuators.

The blade was produced using vacuum infusion in a closed mould and after

assembly of the sensors and actuators, it was mounted on the pitch system and

connected to the control hardware. Several tests were conducted:

Feedforward on disturbances with a sinusoid signal. •

Feedback control on a sinusoid signal with a strain sensor at the root. •

Feedback control on a spectrum angle of attack disturbances that resembles the •

turbulence that an actual blade experiences.

Feedback control on a step on the angle of attack (simulating gusts or tower •

shadow) .

Figure 20: Set-up of the control system.

Implementation of The ‘Smart’ Rotor Concept 497

5.3 Results and Discussion

The results of the ﬁ rst set are promising. Here the focus will be on the results on

the step experiments. See van Wingerden et al. [ 113 ] for details. In these experi-

ments a step, simulating a gust, was put on the pitch of the blade which triggered

a sudden change in lift. This was ﬁ rstly done without controlling the ﬂ aps and

secondly with feedback control. The results in two cases, a = 6˚ (around maximum

/ C

) and a =10˚ (higher than the static stall angle), can be seen in Figs. 21 and 22 .

A signiﬁ cant reduction in the vibration behavior, as well as a reduction of the ﬁ rst

peak can be observed.

Observing Figs. 21 and 22 and an important conclusion can be drawn: the con-

trol system based on structural response is only partially able to mitigate the

Figure 21: Strain signal at the root as a result of a step on the pitch at 6˚ angle of

attack (close to maximum C

, desired operating point for the DU-

96 aerofoil).

Figure 22: Strain signal at the root as a result of a step on the pitch at 10˚ angle of

attack (higher than the static stall angle).

498 Wind Power Generation and Wind Turbine Design

response to a gust. But it is possible to considerably increase the aerodynamic

damping and to decrease the peak load.

The measuring of inﬂ ow could increase the load alleviation potential of the

concept. Then so-called collocated control [ 114 ] is possible, where a local ﬂ ow

sensor directly coupled to a local control surface keeps the local aerodynamics

constant. However, a global control system must be installed too to make sure that

the ultimate goal on the system, reducing the load ﬂ uctuations, is assured. Keeping

the aerodynamic load at certain stations constant does not assure that, because not

all stations can be controlled and because non-aerodynamic loading on the blade

exist, e.g. wave loading on the tower for offshore turbines. Including inﬂ ow sen-

sors will complicate the control system and it can be questioned whether acting

solely on the structural response is not already sufﬁ cient to attain a satisfying level

of load reduction.

To answer this question, it must be researched which part of the load spectrum

is dominant: are the loads dominated by quasi-static components or is the turbu-

lence exciting the dynamics of the blade? MacMartin [ 114 ] makes the same

distinction: he calls the mitigation of load ﬂ uctuation due to forced excitation

isolation, whereas the suppression of dynamic modes is called active damping. In

the latter case, basing the control system on the structural response, possibly with

feedforward control on deterministic components of turbulence, will sufﬁ ce. For

issues concerning the control algorithms, please refer to [ 115 ].

5.4 Rotating experiments

These control issues are also being addressed in a second series of experiments in

which an actual blades equipped with ﬂ aps is tested on a small turbine. This will

allow for the study of the effect of rotationally induced disturbances, such as yaw

misalignment, as well as the interaction between multiple blades and between the

rotor and the wake. In addition, some design enhancements are made.

Blade design and manufacturing was done similar to the non-rotating experi-

ment, except that the blade was made out of one piece and the dynamic scaling was

performed with respect to the ratio between the rotational and the eigenfrequency,

not the reduced frequency. This was done because from the non-rotating experi-

ment it was concluded that the proximity of natural modes to parts of the distur-

bance spectrum has an inﬂ uence on the dynamics loading of the blade. However, the

reduced frequency for the model is higher than with the reference blade, and thus is

the aerodynamic delay. A photo of the ﬁ nished blades can be seen in Fig. 23 . As you

can see, the blade has twist and tapper, but a straight tip. This is to facilitate the

installation of the actuators.

In this experiment, more attention was given to the dynamic behavior of the

blade. In harmonic analyses, the transfer between ﬂ ap excitation and stresses at

different points on the blade was calculated in order to determine the right place-

ment of sensors. The sensors were placed at locations where the normal stresses

for a given excitation were relatively high and a safe phase margin existed. Both

piezoelectric MFCs as well as strain gages are adhered to the blade. At the center

of the ﬂ aps accelerometers are build in. The accelerometers record both in and out

Implementation of The ‘Smart’ Rotor Concept 499

of plane acceleration and can be used for so-called collocated control as discussed

above. The sensor array measures the structural response of the blade. However,

ﬂ ow measurement devices could be considered in the future.

Also, the actuator design was updated. The Thunder

actuator was placed at

the suction side instead of the center of the proﬁ le to form a hard. In addition, stiff

dissected foam was used to ﬁ ll the remainder of the proﬁ le. High modulus foam

was used to prevent the indentation under the dynamic pressure during operation.

The dissected foam was covered with a thin layer of soft polyether foam, which in

turn was covered with a polypropylene skin (see Fig. 24).

Wind tunnel experiments with the ‘smart’ rotor are scheduled for Fall 2009.

Figure 23: Photo of the ﬁ nished scaled ‘smart’ rotor blade with two actuator slots

in the tip.

Figure 24: Design of the enhanced actuator for the rotating experiments with the

‘smart’ rotor.

500 Wind Power Generation and Wind Turbine Design

6 Conclusions and discussion

6.1 Conclusions on adaptive aerospace structures

The adaptiveness of aerospace structures is advocated with many purposes in mind;

from vibration control to reconﬁ guration. But the underlying idea is the same: to

obtain lighter, better performing structures. Both the smart rotor blade research

for helicopters, as the smart wing research for aeroplanes pose interesting bench-

marks. In rotor blades aerodynamic load control is mostly pursued for vibration

control. The concepts are usually based on hinged ﬂ aps where adaptive materials

are implemented for their high power to weight ratio. Moreover, with piezoelec-

trics very high actuation frequencies are attainable. For vibration control or ﬂ ight

control for helicopters mostly piezoelectrics are proposed. For quasi-static blade

tracking SMAs are referred to.

In smart wing research most research into aerodynamic load control is aimed at

replacing the current control systems or for reconﬁ guration from one ﬂ ight mode

to another. Most concepts for control surfaces are still aimed at mechanisms rather

than integrated structures. In addition compliant mechanisms have been proposed

for morphing surfaces. Actuation of these surfaces does not necessarily have to be

done by means of adaptive materials, but they are mentioned because of their high

power-to-weight ratio. For the smart wind turbine blades, the morphing ﬂ ap or

aileron concepts are mostly interesting.

6.2 Conclusions on adaptive materials

Two adaptive materials are of most interest: piezoelectrics and SMAs. The chal-

lenge with piezoelectrics is to sufﬁ ciently amplify their strain and to take precau-

tions for their brittleness, in the case of PZT. Precompression and applying it in

Thunder-type benders or in mechanisms are good solutions.

The challenges with SMAs are actuation speed and controllability. The band-

width of an SMA actuator could be increased by active cooling and for its control-

lability models exist, but the material behavior is highly non-linear and dependent

on the load history. An issue with SMA material is the fatigue properties of the

material. The advantage of SMA material is that the theoretically attainable band-

width and force–displacement characteristics are very well suited for actuation in

MW-sized HAWT blades.

With all electrically controlled actuators, whether they are electro-mechanical

actuators (EMA) or adaptive materials, an issue is lightning strike.

6.3 Conclusions for wind turbine blades

From a stiffness point of view a rigorous alteration of the blade design proba-

bly not needed, depending on the blade design. Reinforcing and stiffening ele-

ments such as ribs or an additional spar could be placed around the actuator slots.

Thermo plastic materials are favorable for such a blade concept because they allow

Implementation of The ‘Smart’ Rotor Concept 501

for the easy assembly of multi-component designs. In addition, TPCs are to be

preferred for deformable surfaces because many are tougher than thermosets.

Finally it was mentioned that a rib-spar design is also the optimal topology for

transferring loads through the blade.

6.4 Control issues

Load alleviation experiments at the TU Delft, using strain measurements as a feed-

back signal have shown that a signiﬁ cant reduction of the fatigue loads is possible.

But many other signals, including inﬂ ow measurements are possible. Measuring

the inﬂ ow could increase the load alleviation performance of any control system

because then the largest source of ﬂ uctuating loads is known and feedforward

control can be applied to it.

However, before aerodynamic load control on wind turbines can become a real-

ity many hurdles have to be taken. Although the ‘smart’ structures from aerospace

pose an interesting benchmark, the demands for wind turbines are different. Sec-

ondly, there has been a large effort into aero-servo-elastic modeling over the last

few years, but the structural implementation of the spanwise distributed devices

has been relatively ignored. Here some light on the matter has been shed, as well

as on some of the control issues involved.

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