Abstract —Focusing on the tilt moment and yaw moment caused by asymmetric wind, aerodynamic model for individual pitch control of large-scale wind turbine was established. As the aerodynamic model have characteristics of multiple variables, strong coupling and time-varying. First, we convert it into a linear time-invariant and non-coupled model utilizing a coordinate transformation, and so the controller design was simplified. Finally, take wind shearing as a disturbance and designed two independent PID controllers. The simulation results show that individual pitch control greatly reduced the moment and yaw moment of wind turbine.

Keywords: wind turbine; individual pitch control; coordinate transformation

I. INTRODUCTION

With great development of wind power technology and increase of wind turbine unit capacity, rotor diameter, nacelle weight and tower height of wind turbine increase rapidly. Dynamic load caused by wind turbulence, tower shadow, and rotor unbalance affects large scale wind turbine more and more distinctly, which is an essential factor must be considered.

Now, most of turbines use pitch to control power captured by the rotor. Blade derived and controlled by a servo system according to demand come from main controller according to different operating conditions. A lot of advanced intelligent control algorithms had been used in pitch control.

Even intelligent control algorithms applied, the traditional collective pitch control strategies move the three blades synchronal. However, aerodynamic force on three blades is different, so the rotor of the wind turbine endures unbalanced load all the time. The adjustment of pitch angle has an obvious influence on dynamic load. Dynamic load especially blade With great development of wind power technology and increase of wind turbine unit capacity, rotor diameter, nacelle weight and tower height of wind turbine increase rapidly. Dynamic load caused by wind turbulence, tower shadow, and rotor unbalance affects large scale wind turbine more and more distinctly, which is an essential factor must be considered.

Now, most of turbines use pitch to control power captured by the rotor. Blade derived and controlled by a servo system according to demand come from main controller according to different operating conditions. A lot of advanced intelligent control algorithms had been used in pitch control.

Even intelligent control algorithms applied, the traditional collective pitch control strategies move the three

blades synchronal. However, aerodynamic force on three blades is different, so the rotor of the wind turbine endures unbalanced load all the time. The adjustment of pitch angle has an obvious influence on dynamic load. Dynamic load especially blade root load must be considered during pitch control algorithm design of large scale wind turbine.

At present, electrical servo system and hydraulic servo system are used to drive blade in most of turbine pitch system. Three blades can be controlled independently with three motors or cylinders, which make it possible to decrease the rotor unbalanced load by controlling pitch angle independently. In order to reduce dynamic load of blade root, the following requirements must be satisfied:

1) Try to keep the maximum wind energy using efficiency limited in the permitted range;

2) Try to reduce unbalance load caused by wind rotor itself, wind shear and wind turbulence;

3) Try to keep the power output steadily. In recent years, many experts begin to study on

individual pitch control and load reduction pitch control algorithm. It is an efficient way to realize individual pitch control [1]-[3] according to rotor azimuth. Otherwise it can effectively reduce fatigue load caused by wind shear and tower shadow, but no using for reducing dynamic load caused by wind turbulence and other unbalance. This thesis focus on the closed-loop control method of variable speed turbine pitch control through measurement of blade root load by sensors installed in blades. Because of complexity and unpredictable of wind speed changing, the calculation of dynamic load is very complex. It is difficult to build an accurate mathematical model, so a model free closed-loop control method is selected to control the load.

II. THE ANALYSIS OF BLADE LOAD In order to analyze, blade load can be divided into two

types: the determined load come from stable wind speed and dynamic load produced by turbulence wind speed. So, we use different ways to analyze them [4]-[6]. Determined load is decided by hub height, wind speed, rotor speed, and wind shear force. Dynamic load has a close relationship with rotor azimuth, turbulence wind, and the pitch movement. The only factor can be controlled is pitch movement, a special designed pitch control algorithm can be used to reduce the dynamic load of blades.

The unbalanced load of blade root is mainly considered to deduce in this paper. Blade root load can lead to the broken

Individual Variable Pitch Control of Wind Turbines

Zhao Ximei , Sun XianfengSchool of Electrical Engineering，Shenyang University of technology , Shenyang,110870 China

E-mail: zhaoximei79@yahoo.com.cn

torque to hub and vibrating to main shaft. It plays a dominant influence on blade root, hub and main shaft.

The blade load calculation is a very complex process. For convenient analyses, the load can be divided to aerodynamic load, gravity load, and rotating load. Both gravity load and rotating load depend on turbine structural and rotor speed of wind turbines. The blade root moment is main focus item in this thesis.

III. MODEL FOR INDIVIDUAL PITCH CONTROLLER

Measurement of blade root moment The wind turbine rotor is consisted of three blades. In

order to measure blade root moment, optic stress sensors are installed in each blade root. In high wind speed operate condition of wind turbine, the dynamic blade root moment is affected by wind speed and pitch angle commonly. And also, it should be considered together of all three blades, not any one case blade’s pitch movement. But all the three bladed not all same performance, the rotor unbalance characteristic must be considered. The rotor unbalance can be embodied by different three measured blade moments.

coordinate transformation Two orthogonal unbalance loads is transformed from three

measured blade moment through coordinate transformation theory. One unbalance moment is direct axes and anther one is quadrature axes [7].The conversion function transmitting three blade moments to two direction unbalance load is showed in equation (1)- (2). Md is direct axes unbalance load, Mq is quadrature axes unbalance load. In the same way, the conversion function transmitting three pitch angles to two direction unbalance pitch angle is showed in equation (3)- (4). θd is direct axes unbalance load, θq is quadrature axes unbalance load. And Ψi is the angle between blade i and the direct axis direction.

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32

MMM

MM

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d

ψψψψψψ

(1)

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MM

MMM

33

22

11

3

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1

sincossincossincos

ψψψψψψ

(2)

For the pitch angle:

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θθθ

ψψψψψψ

θθ

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d (3)

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ψψψψψψ

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(4)

Where:

)1(3

2 −+= iiπψψ (5)

For actual wind turbine, each blade pitch signal consists of two parts-one is collective signal θ, the other is independent pitch signal θi. Collective signal θ is determined according to the average wind speed of the hub and independent pitch signal θi is determined as follows: First, measure the Blade root bending moments M1, M2, M3 and transformed them into Md, Mq through (1), second, compare them with 0, the difference is the input signal of the PI controller and output θd, θq, third, transformed into independent pitch signal θ1, θ2, θ3, finally, we can get the pitch signal by sum collective signal θ and independent signal θ1, θ2, θ3. System block diagram is shown in Fig. 1.

Fig.1 Block diagram of wind turbines control system

IV. SIMULATIONS AND DISCUSSIONS In order to verify the feasibility and effectiveness of the

proposed control scheme in the paper, the individual pitch load control algorithm is implemented in MATLAB, and the simulations are made on a 1.5MW variable speed wind turbines model.

The 1.5MW wind turbine control object, consisted of three blades, gearbox, and double fed generator basic drive train etc., and main parameters of rotor diameter is 70.546m, hub center height is 65m, Average wind speed is 14m/s, pitch angle range is 0-90°, the maximum pitch speed is12.5°/s. The simulation results are as follows: Tilt moment curve of collective pitch control is shown in Fig.2. Yaw moment curve of collective pitch control is shown in Fig.3. Tilt moment curve of feedback control is shown in Fig.4. Yaw moment curve of feedback control is shown in Fig.5. It is obviously to see that the individual pitch load controller can mitigate the blade root load, compared with the collective pitch controller.

0 2 4 6 8 101.4

1.6

1.8

2

2.2

2.4

2.6

2.8x 10

5

t

Mya

w

Fig.2 Tilt moment curve of collective pitch control

0 2 4 6 8 10-3

-2

-1

0

1

2

3x 10

4

t

Mya

w

Fig.3 Yaw moment curve of collective pitch control

0 2 4 6 8 10-5

0

5

10x 10

4

t

Mtilt

Fig.4 Tilt moment curve of feedback control

0 2 4 6 8 10-5000

0

5000

10000

15000

20000

t

Myaw

Fig. 5 Yaw moment curve of feedback control

V. CONCLUSION By the process of coordinate transformation and orientation

transfer, the individual pitch close loop control is realized. The Bladed software simulation tools are used to verify it is feasible and effective to reduce dynamic load of wind turbine. Thus, the blade and hub lifetime can be longer, and the whole wind turbine cost can be deduced.

However, the individual pitch load control mostly dependent on load measurement sensor. So the reliable load sensor is the key consideration item during load control.

ACKNOWLEDGMENT

This work is supported by Scientific Research Foundation for Doctors of LiaoNing Province of China (No.20091056). This work is also supported by Scientific Research Foundation of LiaoNing Province Educational Committee (No.L2010400).

REFERENCES

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[3] Zhao Lin, Guo Qingding. “Adjustable-pitch and variable-speed control of wind turbines using nonlinear algorithm.” Proceedings of the Sixth International Conference on Electrical Machines and Systems, pp. 270-273 Vol. 1, 2003

[4] Johnson, Kathryn E. Fingersh, Lee Jay.“ Adaptive pitch control of variable-speed wind turbines,”Journal of Solar Energy Engineering, Transactions of the ASME, Vol. 130, No. 3, pp. 121-127, August 2008

[5] Boukhezzar, B. Lupu, L.; Siguerdidjane, H.; Hand, M. “Multivariable control strategy for variable speed, variable pitch wind turbines,” Renewable Energy, Vol. 32, No. 8, pp. 1273-1287, July 2007

[6] Soliman, M. Malik, O.P.; Westwick, D.T.“Multiple model MIMO predictive control for variable speed variable pitch wind turbines,” 2010 American Control Conference , pp. 2778-2784, 2010

[7] Selvam, K. Kanev, S.; van Wingerden, J.W.; van Engelen, T.; Verhaegen, M. “ Feedback-feedforward individual pitch control for wind turbine load reduction,” International Journal of Robust and Nonlinear Control, Vol. 19, No.1, pp.72-91, 10 Jan. 2009

[8] Bossanyi, E.A.“ Individual blade pitch control for load reduction ,” Wind Energy, Vol. 6, No.2, pp.119-128, April/June 2003