We present two intelligent controllers for large and flexible wind turbines operating in high-speed winds, a Fuzzy-P + I and an adaptive neuro-fuzzy controller. The control objective is to regulate the rotor speed at the given rated power in region 3 (full load) via collective blade pitch angle. The modeled turbine is a three-bladed, upwind machine with a flexible blade and tower. We use the particle swarm optimization method in off-line training for our adaptive neuro-fuzzy controller. Numerical simulations are performed using wind inflow step change with a set of input–output data of a nonlinear wind turbine model. We compare the performance of the proposed controllers with the baseline PI-controller. Simulation results confirm successful performance of the proposed controllers.

References

References
2.
Kos
,
J. M.
, 1978, “
On Line Control of a Large Horizontal Axis Energy Conversion System and Its Performance in a Turbulent Wind Environment
,”
Proceedings of the 13th Intersociety Energy Conversion Engineering Conference
, pp.
2064
2073
.
3.
Wasynczuk
,
O.
,
Man
,
D. T.
, and
Sullivan
,
J. P.
, 1981, “
Dynamic Behavior of a Class of Wind Turbine Generators During Random Wind Fluctuations
,”
IEEE Trans. Power Appar. Syst.
,
100
, pp.
2837
2845
.
4.
Liebst
,
B. S.
, 1985, “
A Pitch Control System for the KaMeWa Wind Turbine
,”
ASME J. Dyn. Syst., Meas., Control
,
107
, pp.
47
52
.
5.
Mattson
,
S. E.
, 1984, “
Modeling and Control of Large Horizontal Axis Wind Power Plants
,” Ph.D. thesis, Department of Automatic Control, Lund Institute of Technology, Lund, Sweden.
6.
Bossanyi
,
E. A.
, 1987, “
Adaptive Pitch Control for a 250 kW Wind Turbine
,”
Proceedings of the 9th British Wind Energy Conference
,
Edinburgh, Scotland
, pp.
85
92
.
7.
Freeman
,
J. B.
, and
Balas
,
M. J.
, 1999, “
An Investigation of Variable Speed Horizontal-Axis Wind Turbines Using Direct Model Reference Adaptive Control
,”
Proceeding AIAA/ASME Wind Energy Symposium
, pp.
66
76
, January 1999.
8.
Johnson
,
K. E.
,
Pao
,
L. Y.
,
Balas
,
M. J.
,
Kulkami
,
V.
, and
Fingersh
,
L. J.
, 2004, “
Stability Analysis of an Adaptive Torque Controller for Variable Speed Wind Turbines
,”
Proceedings of the IEEE Conference Decision and Control
, pp.
4087
4094
.
9.
Frost
,
S. A.
,
Balas
,
M. J.
, and
Wright
,
A. D.
, 2009, “
Direct Adaptive Control of a Utility-Scale Wind Turbine for Speed Regulation
,”
Int. J. Robust Nonlinear Control
,
19
(
1
), pp.
59
71
.
10.
Cutululis
,
N. A.
,
Ceanga
,
E.
,
Hansen
,
A. D.
, and
Srensen
,
P.
, 2006, “
Robust Multi-Model Control of an Autonomous Wind Power System
,”
Wind Energy
,
9
(
5
), pp.
399
419
.
11.
Wright
,
A. D.
, 2004, “
Modern Control Design for Flexible Wind Turbines
,” NREL Report No. TP-500-35816, National Renewable Energy Laboratory.
12.
Song
,
Y. D.
,
Dhinakaran
,
B.
, and
Bao
,
X. Y.
, 2000, “
Variable Speed Control of Wind Turbines Using Non-Linear and Adaptive Algorithms
,”
J. Wind Eng. Ind. Aerodyn.
,
85
(
3
), pp.
293
308
.
13.
Boukhezzar
,
B.
,
Siguerdidjane
,
H.
, and
Hand
,
M. M.
, 2006, “
Nonlinear Control of Variable-Speed Wind Turbines for Generator Torque Limiting and Power Optimization
,”
ASME J. Sol. Energy Eng.
,
128
(
4
), pp.
516
530
.
14.
Kumar
,
A.
, and
Stol
,
K.
, 2008, “
Simulating MIMO Feedback Linearization Control of Wind Turbines Using FAST
,”
Proceedings of AIAA/ASME Wind Energy Symposium
, January 2008.
15.
Kumar
,
A.
, and
Stol
,
K.
, 2009, “
Scheduled Model Predictive Control of a Wind Turbine
,”
Proceedings of AIAA/ASME Wind Energy Symposium
, January 2009.
16.
Igbal
,
M. T.
,
Coonick
,
A. H.
, and
Freris
,
L. L.
, 1994, “
Dynamic Control Options for Variable Speed Wind Turbines
,”
Wind Eng.
,
18
(
1
), pp.
1
12
.
17.
Wu
,
K. C.
, and
R.
De La Guardia
, 1996, “
Effects of Controls on Fatigue Loads in Two-Bladed Teetered Rotor Wind Turbines
,”
ASME J. Sol. Energy Eng.
,
118
(
4
), pp.
228
234
.
18.
Gao
,
F.
,
Xu
,
D.
, and
Lv
,
Y.
, 2008, “
Pitch-Control for Large-Scale Wind Turbines Based on Feed Forward Fuzzy-PI
,”
Proceedings of the 7th World Congress on Intelligent Control and Automation
,
Chongqing, China
, June 2008.
19.
Zhang
,
X.
,
Zhang
,
X.
,
Zhou
,
P.
, and
Cheng
,
J.
, 2009, “
Fuzzy Control Used in Variable Speed Wind Turbine
,”
Proceedings of IEEE International Conference on Automation and Logistics
,
Shenyang, China
.
20.
Lin
,
W. M.
,
Hong
,
C. M.
, and
Cheng
,
F. S.
, 2010, “
Fuzzy Neural Networks Output Maximization Control for Sensorless Wind Energy Conversion System
,”
Energy
,
35
(
2
), pp.
592
601
.
21.
Jafarian
,
M.
, and
Ranibar
,
A. M.
, 2010, “
Fuzzy Modeling Techniques and Artificial Neural Networks to Estimate Annual Energy Output of a Wind Turbine
,”
Renewable Energy
,
35
(
9
), pp.
2008
2014
.
22.
Ayoubi
,
M. A.
, and
Tai
,
L.-C.
, 2010, “
An Adaptive Neuro-Fuzzy Controller for a Wind Turbine Operating in Region 3
,” IMECHE2010-40970, International Mechanical Engineering Congress & Exposition, Vancouver, British Columbia, Canada.
23.
Fuzzy Logic Toolbox User’s Guide—Version 2, 2009, The Mathworks, Inc., Natick, MA.
24.
Sharma
,
K. D.
,
Chatterjee
,
A.
, and
Rakshit
,
A.
, 2009, “
A Hybrid Approach for Design of Stable Adaptive Fuzzy Controllers Employing Lyapunov Theory and Particle Swarm Optimization
,”
IEEE Trans. Fuzzy Syst.
,
17
(
2
), pp.
329
342
.
25.
Passino
,
K. M.
, and
Yurkovich
,
S.
, 1997,
Fuzzy Control
,
Addison-Wesley Longman, Inc.
,
Reading, MA
.
26.
Kandel
,
A.
, and
Langholz
,
G.
, 1994,
Fuzzy Control Systems
,
CRC Press, Inc.
, Chaps. >1, 2, and 20.
27.
Jang
,
J. -S. R. R.
, 1993, “
ANFIS: Adaptive-Network-Based Fuzzy Inference Systems
,”
IEEE Trans. Syst., Man, Cybern.
,
23
, pp.
665
685
.
28.
Jang
,
J.-S. R.
,
Sun
,
C.-T.
, and
Mizutani
,
E.
, 1997,
Neuro-Fuzzy and Soft Computing
,
Prentice-Hall
,
Englewood Cliffs, NJ
, pp.
335
360
.
29.
Mann
,
G. K. I.
,
Hu
,
B.-G.
, and
Gosine
,
R. G.
, 1999, “
Analysis of Direct Action Fuzzy PID Controller Structures
,”
IEEE Trans. Syst., Man, Cybern., Part B: Cybern.
,
29
(
3
), pp.
371
388
.
30.
Juang
,
C.-F.
, 2004, “
A Hybrid of Genetic Algorithm and Particle Swarm Optimization for Recurrent Network Design
,”
IEEE Trans. Syst., Man, Cybern., Part B: Cybern.
,
34
(
2
), pp.
997
1006
.
31.
Clerc
,
M.
, and
Kennedy
,
J.
, 2002, “
The Particle Swarm-Explosion, Stability, and Convergence in a Multidimensional Complex Space
,”
IEEE Trans. Evol. Comput.
,
6
(
1
), pp.
58
73
.
32.
Kennedy
,
J.
, and
Eberhart
,
R. C.
, 1995,
“Particle Swarm Optimization,” Proceedings of the 1995 IEEE ICEC
, Perth, Australia, pp.
1942
1948
.
33.
Eberhart
,
R. C.
, and
Kennedy
,
J.
, 1995, “
A New Optimizer Using Particle Swarm Theory
,”
Sixth International Symposium on Micro Machine and Human Science
, Nagoya, Japan, pp.
39
43
.
34.
Kennedy
,
J.
,
Eberhart
,
R. C.
, and
Shi
,
Y.
, 2001,
Swarm Intelligence
,
Academic Press
, pp.
287
324
.
35.
Eberhart
,
R. C.
, and
Shi
,
Y.
, 2000, “
Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization
,”
Proceedings of the 1995 ICEC.
37.
Wright
,
A. D.
, and
Fingersh
,
L. J.
, 2008, “
Advanced Control Design For Wind Turbines. Part I: Control Design, Implementation, and Initial Tests
,” NREL Report No. TP-500-42437, National Renewable Energy Laboratory.
You do not currently have access to this content.