Frequency regulation of wind turbines can improve the stability of the power system. However, it would cause generator torque fluctuation, increasing the risk of fatigue load. Previous research works were restricted to inertial and droop responses. Less attention has been paid to striking a balance between frequency regulation and fatigue load. To overcome these, a hybrid control strategy is proposed to consider both frequency response characteristic and fatigue load mitigation. First, a small signal linearization model is built to reveal the impact of the correlation mechanism of frequency regulation on drive train torque load. Second, a multivariable cost function is constructed to optimize the proportional integral (PI) controller, which combines the total fluctuation with the dispersion of the fatigue load and frequency. Then, a hybrid controller based on PI control optimized by particle swarm optimization algorithm and active disturbance rejection control is designed to restrain rapid frequency changes as well as fatigue torque fluctuation simultaneously. Several experiments are performed to verify the significance of the proposed method under different scenarios. Compared with the existing methods, the proposed hybrid control exhibits superiority in improving frequency response and fatigue load mitigation.

1.
P.
Veers
,
K.
Dykes
,
E.
Lantz
et al, “
Grand challenges in the science of wind energy
,”
Science
366
,
443
(
2019
).
2.
G.
Zhang
,
W.
Hu
,
D.
Cao
,
W.
Liu
,
R.
Huang
,
Q.
Huang
,
Z.
Chen
, and
F.
Blaabjerg
, “
Data-driven optimal energy management for a wind-solar-diesel-battery-reverse osmosis hybrid energy system using a deep reinforcement learning approach
,”
Energy Convers. Manage.
129
,
227
(
2021
).
3.
J.
K
.
Kambrath
,
M. S. U.
Khan
,
Y.
Wang
,
A. I.
, and
Maswood
,
Y. J.
Yoon
, “A novel control technique to reduce the effects of torsional interaction in wind turbine system,”
IEEE J. Emerg. Sel. Top. Power Electron.
7
,
2090
2105
(
2019
).
4.
M. F. M.
Arani
and
Y. A.-R. I.
Mohamed
, “
Dynamic droop control for wind turbines participating in primary frequency regulation in microgrids
,”
IEEE Trans. Smart Grid
9
,
5742
5751
(
2018
).
5.
X.
Zhang
,
W.
He
, and
J.
Hu
, “
Impact of inertia control of DFIG-based WT on torsional vibration in drivetrain
,”
IEEE Trans. Sustainable Energy
11
,
2525
2534
(
2020
).
6.
S.
Kim
,
D.
Kim
, and
B.
Kim
, “
Effect of multiple load reduction control systems on the ultimate load and fatigue load of 4 MW class wind turbine
,”
J. Renewable Sustainable Energy
12
,
053306
(
2020
).
7.
A. B. T.
Attya
and
J. L.
Dominguez-García
, “
Insights on the provision of frequency support by wind power and the impact on energy systems
,”
IEEE Trans. Sustainable Energy
9
,
719
728
(
2018
).
8.
M.
Garmroodi
,
G.
Verbič
, and
D. J.
Hill
, “
Frequency support from wind turbine generators with a time-variable droop characteristic
,”
IEEE Trans. Sustainable Energy
9
,
676
684
(
2018
).
9.
J.
Han
, “
From PID to active disturbance rejection control
,”
IEEE Trans. Ind. Electron.
56
,
900
906
(
2009
).
10.
Y.
Zuo
,
J.
Mei
,
C.
Jiang
,
X.
Yuan
,
S.
Xie
, and
C. H. T.
Lee
, “
Linear active disturbance rejection controllers for PMSM speed regulation system considering the speed filter
,”
IEEE Trans. Power Electron.
36
,
14579
14592
(
2021
).
11.
S.
Jain
and
Y. V.
Hote
, “
Design of improved nonlinear active disturbance rejection controller for hybrid microgrid with communication delay
,”
IEEE Trans. Sustainable Energy
13
,
1101
1111
(
2022
).
12.
J.
Heidary
,
M.
Gheisarnejad
, and
M. H.
Khooban
, “
Stability enhancement and energy management of ac-dc microgrid based on active disturbance rejection control
,”
Electr. Power Syst. Res.
217
,
109105
(
2023
).
13.
K.
Sharma
,
A. K.
Yadav
, and
B. B.
Sharma
, “Hybrid cyber-attack compensation of sustainable microgrid using active disturbance rejection control strategy,”
Proc. Royal Soc. A Mathem. Phys. Engin. Sci.
479
,
2279
(
2023
).
14.
J.
Yang
,
S.
Zheng
,
D.
Song
,
M.
Su
,
X.
Yang
, and
Y. H.
Joo
, “
Comprehensive optimization for fatigue loads of wind turbines in complex-terrain wind farms
,”
IEEE Trans. Sustainable Energy
12
,
909
919
(
2021
).
15.
A.
Lasheen
and
A. L.
Elshafei
, “
Wind-turbine collective-pitch control via a fuzzy predictive algorithm
,”
Renewable Energy
87
,
298
306
(
2016
).
16.
A.
Lasheen
,
M.
Elnaggar
, and
H.
Yassin
, “
Adaptive control design and implementation for collective pitch in wind energy conversion systems
,”
ISA Trans.
102
,
251
263
(
2020
).
17.
A.
Lasheen
,
M. S.
Saad
,
H. M.
Emara
, and
A. L.
Elshafei
, “
Continuous-time tube-based explicit model predictive control for collective pitching of wind turbines
,”
Energy
118
,
1222
1233
(
2017
).
18.
J.
Li
and
S.
Wang
, “
Dual multivariable model-free adaptive individual pitch control for load reduction in wind turbines with actuator faults
,”
Renewable Energy
174
,
293
304
(
2021
).
19.
D.
Ossmann
,
P.
Seiler
,
C.
Milliren
, and
A.
Danker
, “
Field testing of multi-variable individual pitch control on a utility-scale wind turbine
,”
Renewable Energy
170
,
1245
1256
(
2021
).
20.
D.
Collet
,
M.
Alamir
,
D.
Di Domenico
, and
G.
Sabiron
, “
Data-driven fatigue-oriented MPC applied to wind turbines Individual Pitch Control
,”
Renewable Energy
170
,
1008
1019
(
2021
).
21.
M.
Wipfler
,
R.
Bauer
,
N.
Dourdoumas
, and
W.
Rossegger
, “
Control methods for torsional vibration damping of a drive train based on the example of an engine test bed
,”
e i Elektrotech. Informationstech.
133
,
142
152
(
2016
).
22.
J.
Darrow
,
K.
Johnson
, and
A.
Wright
, “
Design of a tower and drive train damping controller for the three-bladed controls advanced research turbine operating in design-driving load cases
,”
Wind Energy
14
,
571
601
(
2011
).
23.
Y.
Wang
,
Y.
Guo
,
D.
Zhang
,
H.
Liu
, and
R.
Song
, “
Analysis and mitigation of the drive train fatigue load for wind turbine with inertial control
,”
Int. J. Electr. Power Energy Syst.
136
,
107698
(
2022
).
24.
L.
Ren
,
C.
Mao
,
Z.
Song
, and
F.
Liu
, “
Study on active disturbance rejection control with actuator saturation to reduce the load of a driving chain in wind turbines
,”
Renewable Energy
133
,
268
274
(
2019
).
25.
E.
Mohammadi
,
R.
Fadaeinedjad
, and
G.
Moschopoulos
, “
Implementation of internal model based control and individual pitch control to reduce fatigue loads and tower vibrations in wind turbines
,”
J. Sound Vib.
421
,
132
152
(
2018
).
26.
Y.
Liu
,
Y.
Wang
,
X.
Wang
,
J.
Zhu
, and
W. H.
Lio
, “
Active power dispatch for supporting grid frequency regulation in wind farms considering fatigue load
,”
Energies
12
,
1508
(
2019
).
27.
T.
Gentils
,
L.
Wang
, and
A.
Kolios
, “
Integrated structural optimisation of offshore wind turbine support structures based on finite element analysis and genetic algorithm
,”
Appl. Energy
199
,
187
204
(
2017
).
28.
A.
Boujleben
,
A.
Ibrahimbegovic
, and
E.
Lefrancois
, “
An efficient computational model for fluid-structure interaction in application to large overall motion of wind turbine with flexible blades
,”
Appl. Math. Modell.
77
,
392
407
(
2020
).
29.
J. D.
Grunnet
,
M.
Soltani
,
T.
Knudsen
,
M. N.
Kragelund
, and
T.
Bak
, “
Aeolus toolbox for dynamics wind farm model, simulation and control
,” in
European Wind Energy Conference and Exhibition, EWEC 2010: Conference Proceedings
,
2010
.
30.
H.
Zhao
,
Q.
Wu
,
S.
Huang
,
M.
Shahidehpour
,
Q.
Guo
, and
H.
Sun
, “
Fatigue load sensitivity-based optimal active power dispatch for wind farms
,”
IEEE Trans. Sustainable Energy
8
,
1247
1259
(
2017
).
31.
A.
Fernández-Guillamón
,
A.
Vigueras-Rodríguez
,
E.
Gómez-Lázaro
, and
Á.
Molina-García
, “
Fast power reserve emulation strategy for VSWT supporting frequency control in multi-area power systems
,”
Energies
11
,
2775
(
2018
).
32.
B.
Liu
,
J.
Zhao
,
Q.
Huang
,
F.
Milano
, and
W.
Hu
, “
Robust nonlinear controller to damp drivetrain torsional oscillation of wind turbine generators
,”
IEEE Trans. Sustainable Energy
12
,
1336
1346
(
2021
).
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