This paper proposes a nested-loop extremum seeking control (NLESC) scheme for optimizing the energy capture of wind farm that is formed by a wind turbine array along the prevailing wind direction. It has been shown in earlier work that the axial induction factors of individual wind turbines can be optimized from downstream to upstream units in a sequential manner, which is a spatial domain analogy to the principle of optimality in dynamic programing. Therefore, it is proposed to optimize the turbine operation by a nested-loop optimization framework from the downstream to upstream turbines, based on feedback of the power of the immediate turbine and its downstream units. The extremum seeking control (ESC) based on dither–demodulation scheme is selected as a model-free real-time optimization solution for the individual loops. First, the principle of optimality for optimizing wind farm energy capture is proved for the cascaded wind turbine array based on the disk model. Analysis shows that the optimal torque gain of each turbine in a cascade of turbines is invariant with wind speed if the wind direction does not change. Then, the NLESC scheme is proposed, with the array power coefficient selected as the performance index to be optimized in real-time. As changes of upstream turbine operation affect downstream turbines with significant delays due to wind propagation, a cross-covariance based delay estimate is used to improve the determination of the array power coefficient. The proposed scheme is evaluated with simulation study using a three-turbine wind farm with the simwindfarm simulation platform. Simulation study is performed under both smooth and turbulent winds, and the results indicate the convergence to the actual optimum. Also, simulation under different wind speeds supports the earlier analysis results that the optimal torque gains of the cascaded turbines are invariant to wind speed.

References

1.
Johnson
,
K. E.
,
Fingersh
,
L. J.
,
Balas
,
M. J.
, and
Pao
,
L. Y.
,
2004
, “
Methods for Increasing Region 2 Power Capture on a Variable-Speed Wind Turbine
,”
ASME J. Sol. Energy Eng.
,
126
(
4
), pp.
1092
1100
.
2.
Creaby
,
J.
,
Li
,
Y.
, and
Seem
,
J. E.
,
2009
, “
Maximizing Wind Turbine Energy Capture Using Multivariable Extremum Seeking Control
,”
Wind Eng.
,
33
(
4
), pp.
361
387
.
3.
Bossanyi
,
E. A.
,
2003
, “
Individual Blade Pitch Control for Load Reduction
,”
Wind Energy
,
6
(
2
), pp.
119
128
.
4.
Yang
,
Z.
,
Li
,
Y.
, and
Seem
,
J. E.
,
2012
, “
Individual Pitch Control for Wind Turbine Load Reduction Including Wake Modeling
,”
Wind Eng.
,
35
(
6
), pp.
715
738
.
5.
Yang
,
Z.
,
Li
,
Y.
, and
Seem
,
J. E.
,
2012
, “
Load Reduction of Wind Turbines Under Wake Meandering With Model Predictive Control for Individual Pitching
,”
AIAA
Paper No. 2012-1150.
6.
Soltani
,
M.
,
Knudsen
,
T.
, and
Bak
,
T.
,
2009
, “
Modeling and Simulation of Offshore Wind Farms for Farm Level Control
,”
2009 European Offshore Wind Conference & Exhibition
, Stockholm, Sweden, pp.
1
10
.
7.
Spudić
,
V.
,
Baotić
,
M.
,
Jelavić
,
M.
, and
Perić
,
N.
,
2010
, “
Hierarchical Wind Farm Control for Power/Load Optimization
,” The Science of Making Torque From Wind, pp.
1
8
.
8.
Soleimanzadeh
,
M.
, and
Wisniewski
,
R.
,
2011
, “
Controller Design for a Wind Farm, Considering Both Power and Load Aspects
,”
Mechatronics
,
21
(
4
), pp.
720
727
.
9.
Madjidian
,
D.
, and
Rantzer
,
A.
,
2011
, “
A Stationary Turbine Interaction Model for Control of Wind Farms
,” IFAC 18th World Congress, Milano, Italy, pp.
4921
4926
.
10.
Madjidian
,
D.
,
Martensson
,
K.
, and
Rantzer
,
A.
,
2011
, “
A Distributed Power Coordination Scheme for Fatigue Load Reduction in Wind Farms
,”
2011 American Control Conference
, San Francisco, CA, June 29–July 1, pp.
5219
5224
.
11.
Madjidian
,
D.
,
Kristalny
,
M.
, and
Rantzer
,
A.
,
2013
, “
Dynamic Power Coordination for Load Reduction in Dispatchable Wind Power Plants
,”
2013 European Control Conference
, pp.
3554
3559
.
12.
Kristalny
,
M.
, and
Madjidian
,
D.
,
2011
, “
Decentralized Feedforward Control of Wind Farms: Prospects and Open Problems
,” 50th
IEEE
Conference on Decision and Control and European Control Conference
, Orlando, FL, Dec. 12–15, pp.
3464
3469
.
13.
Bitar
,
E.
, and
Seiler
,
P.
,
2013
, “
Coordinated Control of a Wind Turbine Array for Power Maximization
,”
2013 American Control Conference
, Washington, DC, June 17–19, pp.
2898
2904
.
14.
Johnson
,
K. E.
, and
Thomas
,
N.
,
2009
, “
Wind Farm Control: Addressing the Aerodynamic Interaction Among Wind Turbines
,”
2009 American Control Conference
, St. Louis, MO, June 10–12, pp.
2104
2109
.
15.
Jensen
,
N. O.
,
1983
, “
A Note on Wind Turbine Interaction
,” Risø National Laboratory, DK-4000 Roskilde, Denmark, Report No. Risø-M-2411.
16.
Johnson
,
K. E.
, and
Fritsch
,
G.
,
2012
, “
Assessment of Extremum Seeking Control for Wind Farm Energy Production
,”
Wind Eng.
,
36
(
6
), pp.
701
716
.
17.
Marden
,
J. R.
,
Ruben
,
S. D.
, and
Pao
,
L. Y.
,
2013
, “
A Model-Free Approach to Wind Farm Control Using Game Theoretic Methods
,”
IEEE Trans. Control Syst. Technol.
,
21
(
4
), pp.
1207
1214
.
18.
Corten
,
G. P.
, and
Schaak
,
P.
,
2004
, “
More Power and Less Loads in Wind Farms: ‘Heat and Flux’
,”
2004 European Wind Energy Conference
, London, UK, pp. 1–9.
19.
Park
,
J.
,
Kwon
,
S.
, and
Law
,
K. H.
,
2013
, “
Wind Farm Power Maximization Based on a Cooperative Static Game Approach
,”
Proc. SPIE
,
8688
, p.
86880R
.
20.
Zhao
,
R.
,
Shen
,
W.
,
Knudsen
,
T.
, and
Bak
,
T.
,
2012
, “
Fatigue Distribution Optimization for Offshore Wind Farms Using Intelligent Agent Control
,”
Wind Energy
,
15
(
7
), pp.
927
944
.
21.
Guo
,
Y.
,
Wang
,
W.
,
Tang
,
C.-Y.
,
Jiang
,
J. N.
, and
Ramakumar
,
R. G.
,
2013
, “
Model Predictive and Adaptive Wind Farm Power Control
,”
2013 American Control Conference
, Washington, DC, June 17–19, pp.
2890
2897
.
22.
Seem
,
J. E.
, and
Li
,
Y.
,
2012
, “
Systems and Methods for Optimizing Power Generation in a Wind Farm Turbine Array
,” U.S. Patent No. US2013030011.
23.
Yang
,
Z.
,
Li
,
Y.
, and
Seem
,
J. E.
,
2013
, “
Maximizing Wind Farm Energy Capture Via Nested-Loop Extremum Seeking Control
,”
ASME
Paper No. DSCC2013-3971.
24.
Manwell
,
J. F.
,
McGowan
,
J. G.
, and
Rogers
,
A. L.
,
2010
,
Wind Energy Explained
, 2nd ed.,
Wiley
, Chichester, UK.
25.
Ariyur
,
K. B.
, and
Krstic
,
M.
,
2003
,
Real-Time Optimization by Extremum-Seeking Control
,
Wiley
, Hoboken, NJ.
26.
Munteanu
,
I.
,
Bratcu
,
A. I.
, and
Ceangǎ
,
E.
,
2009
, “
Wind Turbulence Used as Searching Signal for MPPT in Variable-Speed Wind Energy Conversion Systems
,”
Renewable Energy
,
34
(
1
), pp.
322
327
.
27.
Pan
,
T.
,
Ji
,
Z.
, and
Jiang
,
Z.
,
2008
, “
Maximum Power Point Tracking of Wind Energy Conversion Systems Based on Sliding Mode Extremum Seeking Control
,” 2008
IEEE
Energy Conference
, Atlanta, GA, Nov. 17–18, pp.
1
5
.
28.
Hawkins
,
T.
,
White
,
W. N.
,
Hu
,
G.
, and
Sahneh
,
F. D.
,
2011
, “
Region II Wind Power Capture Maximization Using Robust Control and Estimation With Alternating Gradient Search
,”
2011 American Control Conference
(
ACC
), San Francisco, CA, June 29–July 1, pp.
2695
2700
.
29.
Rotea
,
M. A.
,
2000
, “
Analysis of Multivariable Extremum Seeking Algorithms
,”
2000 American Control Conference
, Chicago, IL, June 28–30, pp.
433
437
.
30.
Grunnet
,
J. D.
,
Soltani
,
S. M. N.
,
Knudsen
,
T.
,
Kragelund
,
M. N.
, and
Bak
,
T.
,
2010
, “
AEOLUS Toolbox for Dynamic Wind Farm Model, Simulation and Control
,”
2010 European Wind Energy Conference
, Warsaw, Poland, pp.
1
10
.
31.
Jonkman
,
J.
,
Butterfield
,
S.
,
Musial
,
W.
, and
Scott
,
G.
,
2009
, “
Definition of a 5-MW Reference Wind Turbine for Offshore System Development
,” Report no. NREL/TP-500-38060.
32.
Schepers
,
J. G.
, and
van der Pijl
,
S.
,
2007
, “
Improved Modelling of Wake Aerodynamics and Assessment of New Farm Control Strategies
,”
J. Phys. Conf. Ser.
,
75
(
1
), p.
012039
.
33.
Fleming
,
P.
,
Gebraad
,
P. M. O.
,
Lee
,
S.
,
van Wingerden
,
J. W.
,
Johnson
,
K. E.
,
Churchfield
,
M.
,
Michalakes
,
J.
,
Spalart
,
P.
, and
Moriarty
,
P.
,
2014
, “
Evaluating Techniques for Redirecting Turbine Wake Using SOWFA
,”
Renewable Energy
,
70
, pp.
211
218
.
34.
Fleming
,
P.
,
Gebraad
,
P. M. O.
,
Lee
,
S.
,
van Wingerden
,
J. W.
,
Johnson
,
K. E.
,
Churchfield
,
M.
,
Michalakes
,
J.
,
Spalart
,
P.
, and
Moriarty
,
P.
, “
Simulation Comparison of Wake Mitigation Control Strategies for a Two-Turbine Case
,”
Wind Energy
(published online).
You do not currently have access to this content.