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Frontiers of Mechanical Engineering

ISSN 2095-0233

ISSN 2095-0241(Online)

CN 11-5984/TH

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Front. Mech. Eng.    2017, Vol. 12 Issue (3) : 367-376    https://doi.org/10.1007/s11465-017-0429-y
RESEARCH ARTICLE
Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator
Xueping PAN, Ping JU(), Feng WU, Yuqing JIN
College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
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Abstract

A new hierarchical parameter estimation method for doubly fed induction generator (DFIG) and drive train system in a wind turbine generator (WTG) is proposed in this paper. Firstly, the parameters of the DFIG and the drive train are estimated locally under different types of disturbances. Secondly, a coordination estimation method is further applied to identify the parameters of the DFIG and the drive train simultaneously with the purpose of attaining the global optimal estimation results. The main benefit of the proposed scheme is the improved estimation accuracy. Estimation results confirm the applicability of the proposed estimation technique.
Keywords wind turbine generator      DFIG      drive train system      hierarchical parameter estimation method      trajectory sensitivity technique     
Corresponding Author(s): Ping JU   
Just Accepted Date: 16 March 2017   Online First Date: 30 March 2017    Issue Date: 04 August 2017
 Cite this article:   
Xueping PAN,Ping JU,Feng WU, et al. Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator[J]. Front. Mech. Eng., 2017, 12(3): 367-376.
 URL:  
https://academic.hep.com.cn/fme/EN/10.1007/s11465-017-0429-y
https://academic.hep.com.cn/fme/EN/Y2017/V12/I3/367
Fig.1  A DFIG-based wind farm integrated single machine infinite bus system in MATLAB 2010b Demo
l=s±jw z/% f/Hz Participation factors Dominate states
l1,2=?83.24±j601.29 13.71 95.70 P_ids=0.61, P_iqs=0.66 Stator electrical
l3,4=?18.39±j109.89 16.50 17.49 P_x1=0.26, P_x3=0.38 Rotor side control
l5,6=?21.26±j24.64 65.32 3.92 P_vDC=0.66, P_x5=0.66 Converter and grid side control
l7,8=?0.18±j0.96 18.95 0.15 P_sr=0.51, P_xb=0.52 Drive train and pitch control
l9,10=?27.09±j0.84 99.95 0.13 P_x2=0.53, P_x4=0.52 Rotor side inner current control
l11=?193.89 100.00 ? P_E′q=0.77 Rotor q-axis electrical
l12=?114.60 100.00 ? P_E′d=0.74 Rotor d-axis electrical
l13=?60.00 100.00 ? P_b=0.91 Pitch control
l14=?3.33 100.00 ? P_x6=1.00 Grid side d-axis inner current control
l15=?100.00 100.00 P_x7=1.00 Grid side q-axis inner current control
Tab.1  Eigenvalues and participation factors obtained by linearizing the DFIG model
Fig.2  The disturbed trajectories of DFIG active power and reactive power
Fig.3  The gust wind and the disturbed trajectories of DFIG active power and reactive power
Fig.4  The architecture of the proposed hierarchical parameter estimation method
Component Parameters Pe Qe Vs is
DFIG Ls 1.0029 0.6579 0.0142 0.5464
Lr 0.6740 0.5992 0.0174 0.4067
Lm 0.1897 0.3147 0.0087 0.1348
Rs 0.1865 0.1865 0.0038 0.0960
Rr 0.0330 0.0610 0.0016 0.0170
Drive train H 0.0072 0.0072 0.0001 0.0059
Dsh 0.0295 0.0293 0.0005 0.0251
Tab.2  Trajectory sensitivity value within 0.5s time window after the disturbance cleared
Fig.5  Qe trajectory sensitivity curves under Disturbance 1: (a) Rs and Rr; (b) Ls, Lm and Lr; (c) H and Dsh
Parameters Actual value Search range Initial estimation Estimation Error/%
Ls 0.1710 [0.0171, 0.8550] 0.2354 0.2124 24.2105
Lr 0.1560 [0.0156, 0.7800] 0.0521 0.1067 ?31.6020
Lm 2.9000 [0.2900, 10.0000] 5.3029 3.1770 9.5517
Rs 0.0076 [0, 0.0380] 0.0322 0.0080 5.2632
Rr 0.0050 [0, 0.0250] 0.0091 0.0053 6.0000
Ls+Lr 0.3270 ? 0.2875 0.3191 ?2.4159
Tab.3  Local estimation values of DFIG parameters
Fig.6  Qe trajectory sensitivity curves under Disturbance 2: (a) Rs and Rr; (b) Ls , Lm and Lr; (c) H and Dsh
Component Parameters Pe Qe Vs is
DFIG Ls 1.9549 5.3796 0.0070 1.9803
Lr 0.0360 0.0957 0.0002 0.0363
Lm 34.6466 75.5961 0.0319 34.8192
Rs 24.3083 52.1723 0.0221 24.4280
Rr 37.0584 80.2866 0.0338 37.2423
Drive train H 645.6709 1219.6450 0.6127 648.4093
Dsh 290.5878 629.3274 0.2660 292.0274
Tab.4  Trajectory sensitivity in 20 s time window after disturbance (×10?4)
Parameters Actual value Search range Initial estimation Estimation Error/%
H 5.0400 [0.5040, 10.0000] 10.0000 5.0468 0.1349
Dsh 0.0100 [0, 0.1000] 0.10000 0.0087 13.0000
Tab.5  Local estimation values of drive train parameters
Component Parameter Actual value Decomposition Coordination Error/%
1st round 2nd round 3rd round 4th round
DFIG Ls 0.1710 0.2124 0.2073 0.1787 0.1712 0.1170
Lr 0.1560 0.1067 0.1159 0.1445 0.1536 ?1.5385
Lm 2.9000 3.1770 3.1497 2.9601 2.9053 0.1827
Rs 0.0076 0.0080 0.0094 0.0070 0.0073 3.9473
Rr 0.0050 0.0053 0.0049 0.0054 0.0059 18.0000
Ls+Lr 0.3270 0.3191 0.3232 0.3232 0.3248 ?0.6728
Drive train H 5.0400 5.0468 5.0446 5.0397 5.0401 0.0020
Dsh 0.0100 0.0087 0.0103 0.0103 0.0097 ?3.0000
Tab.6  Estimation results by coordination method
d, q Direct and quadrature axes
r, s Rotor and stator variables
ydr, yqr d- and q-axis components of rotor flux
Lss, Lrs Stator, rotor self-inductance
Lm Magnetizing inductance
Rs, Rr Stator, rotor resistance
ws Synchronous angle speed
wt Wind turbine angle speed
s r Rotor slip
Xs Stator reactance
X′ s Stator transient reactance
E′ d, E′ q d- and q-axis component of voltages behind the transient reactance
T′ 0 Rotor circuit time constant
vds, vqs d- and q-axis component of stator voltages
vdr, vqr d- and q-axis component of rotor voltages
i s Stator currents
ids, iqs d- and q-axis component of stator currents
idr, iqr d- and q-axis component of rotor currents
vdg, vqg d- and q-axis component of voltages of the grid side converter
idg, iqg d- and q-axis component of currents of the grid side converter
Ht, Hg The inertia constant of the turbine and the generator
D sh Damping factor
Tm, Te Mechanical and electrical torque
r Air density
R Wind turbine blade radius
V w Wind speed
C p Power coefficient
C f Blade design constant coefficient;
λ Blade tip speed ratio, λ =ωtR/Vw
b Pitch angle
x b Intermediate variables related to pitch controller
v DC Capacitor voltage
Pm, Pe Mechanical and electrical powers
ζ Mode damping coefficient
f Mode oscillation frequency
Sθi Trajectory sensitivity of qi
k Number of parameters
N Number of sampling within the period of interest t0≤ t≤tN
Aθi Value of trajectory sensitivity of the ith parameter θi,
n Total number of sample points
  
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