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Simulation and Analysis of Wind Turbine Variable Pitch Torque and Control System Chaofeng Li, Honggang Li, Xuejun Tao, Ruijie Zhao, Delin Liu XJ Group Corporation XuChang, China [email protected] Abstract—This paper establishes a variable pitch system working force mathematical model by analyzing variable pitch wind turbine blade stress , and designs its closed-loop PID controllers combined with the actual pitch system. a fuzzy adaptive PID loop control is introduced in the variable pitch system position loop , compares with simulation torque curves which were produced by the fuzzy adaptive PID algorithm and traditional PID algorithm in the process of feathering wind turbine and adjusting pitch in the power generation used real wind turbine parameters, and shows the feasibility and superiority of Fuzzy adaptive PID algorithm. Keywords-blade disturbance torque; fuzzy adaptive PID; simulation I. PID PID II. A. . [1] 1 2 2 m b m b m a 0.5* * sin 2 cos * a a ( ) c dT a l dr f f l ω β φ ρ = ° ® ° = ¯ 1 a m : f m f b B. [2] Schmitz 1 ) sin( 2 1 1 I I w w = Δ w 1 w 3 w w δ I 1 I ε l d 1 8 e=C - [ sinI+C ]tan(I -I)F r Bl π 2 1 1 I =tan xbe Ybe V V R ω 0 V Pr M P S Pr F Q F Z F N F p a β B F α rel V φ rel V α 1266 978-1-4244-8165-1/11/$26.00 ©2011 IEEE

[IEEE 2011 International Conference on Electrical and Control Engineering (ICECE) - Yichang, China (2011.09.16-2011.09.18)] 2011 International Conference on Electrical and Control

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Simulation and Analysis of Wind Turbine Variable Pitch Torque and Control System

Chaofeng Li, Honggang Li, Xuejun Tao, Ruijie Zhao, Delin Liu XJ Group Corporation

XuChang, China [email protected]

Abstract—This paper establishes a variable pitch system working force mathematical model by analyzing variable pitch wind turbine blade stress , and designs its closed-loop PID controllers combined with the actual pitch system. a fuzzy adaptive PID loop control is introduced in the variable pitch system position loop , compares with simulation torque curves which were produced by the fuzzy adaptive PID algorithm and traditional PID algorithm in the process of feathering wind turbine and adjusting pitch in the power generation used real wind turbine parameters, and shows the feasibility and superiority of Fuzzy adaptive PID algorithm.

Keywords-blade disturbance torque; fuzzy adaptive PID; simulation

I.

PIDPID

II.

A.

.[1]

1

2 2m b

m b m

a0.5* * sin2 cos *a

a ( )

cdT a l dr

f f l

ω β φ ρ= ∗ ∗ ∗ ∗ ∗

= − 1

am : fm

fb

B.

[2]

Schmitz 1

)sin(2 11 IIww −=Δ

w1w

3wwδ

I

1I ε

l d 18e=C - [ sinI+C ]tan(I -I)FrBlπ

2

11I =tan xbe

Ybe

VV

0V

PrM

PS

PrF QF

ZF

NF

pa

β

BF

αrelV

φrelV α

1266978-1-4244-8165-1/11/$26.00 ©2011 IEEE

Cl ;Cd Ir ;l B

;v1 F ; Vxbe

Vybe Cl Cd i Cl

Cd[5]

2

a b

( cos sin )2

a ( )

a l d r a

a

dT C C V ldr

f f l

ρα α α= +

= − 3

Cl

Vr a

l fa

Bladeaxis

Rotor axis

AF

MT

aa 2v

rvUv

α Planeof rotor

TM

liftM

C.

[3] 2 2a

a

ada 2r m rT C V l dr

ρ= − (4)

Cm

D.

III.

m

( )s(J s+b)

e

t m

Ls R I V K s

K I T

θθ

+ = −= −

(5)

5

Jm b Kt Ke L R

IV. PID PID [4] rin

k yout k6

( ) ( ) ( )( ) ( ) ( ) ( ) ( )

( ) ( ) ( )

k k

1 1

2 1 2

in out

p i

d

e r y k

u k u k k e k e k ke k

k e k e k e k

= −

= − + − − +

+ − − + −

(6)

PID

V. PID PID

[5] eecPID

[6]

[-3,3], Kp

[-480,480],ki [-6,6],kd [-3,3], 47

[NB NM NS ZO PS PM PB] [7]Kp Ki

Kd 1 e

NB NM NS ZO PS PM PB NB PB PB PM PM PS ZO ZO NM PB PB PM PS PS ZO NS NS PB PM PM PS ZO NS NS ZO PM PM PS ZO NS NM NM PS PS PS ZO NS NS NM NB PM PS ZO NS NM NM NM NB PB ZO ZO NM NM NM NB NB

1267

NB NM NS ZO PS PM PB NB NB NB NM NM NS ZO ZO NM NB NB NM NS NS ZO ZO NS NB NM NS NS ZO PS PS ZO NM NM NS ZO PS PM PM PS NS NS ZO PS PS PM PB PM ZO ZO PS PS PM PB PB PB ZO ZO PS PM PM PB PB

NB NM NS ZO PS PM PB NB PS NS NB NB NB NM PS NM PS NS NB NM NM NS ZO NS ZO NS NM NM NS NS ZO ZO ZO NS NS NS NS NS ZO PS ZO ZO ZO ZO ZO ZO ZO PM PB NS PS PS PS PS PB PB PB PM PM PM PS PS PB

VI. Matlab Simulink S

4

kg. /s2) 0.0295

(H) 2.051

( ) 0.68

0.29

0.57

0.93

V 213.04

A 89

26576.8/15

(m) 40.25

(m) 1.21

NACA63

° 4

° 3

m 80 ° 0

A.

P I D

7 158 0

100 0.1 0

120 0.1 1

PID 5 55 0.6s PID

PID5

0.6 PID PID

PID

B.

[8,9]

6 24m/s10°/s

9.5Nm19Nm

6

1268

6 ADLC1.1

VII.

PIDPID

REFERENCES [1] Mate Jelavi´c,Vlaho Petrovi´c, Nedjeljko Peri´c. Estimation based

Individual Pitch Control of Wind Turbine[J] ISSN 0005 -1144 ATKAFF 51(2),181–192(2010)

[2] Siegfried Heier . Wind Energy Conversion Systems[M].2006 John Wiley & Sons . ltd :77—79.

[3] Yi Ning, Honggang Li etc. Modeling and Simulation of Wind Rotor for Variable-speed Wind Turbine[J].Acta Energiae Solaries Sinica,2011.

[4] Yaonan Wang. Intelligent Control System.Changsha: Hunan University Press,1996,37~50.

[5] Ying Qiao , Zongxiang Lu etc. Integration Monitoring Platform research of Wind farm[J].Power system Protection and Control 2011 , 39(6):117-123.

[6] Aiguo Zhang,Junfeng Han,Cheng Jiang. power flow controller of adaptive neural network-based PI control[J]. Power system Protection and Control 2010,38(22):15-19,24.

[7] Hui Zhao, Baofa Zhang, Chao Lu. Brushless doubly-fed wind generator fuzzy power factor control and simulation[J]. Power system Protection and Control 2010,38(20):96-101.

[8] Shan Yi, Zhenfeng Zheng. variable pitch wind turbine emergency feathering torque analysis and calculation [J]. Wind Power, 1993(2):21—25.

[9] Xiaowu Chen. Wind turbine emergency feathering test and research[J]. Wind Power, 1992(2):21—26

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