Impact of Inter-Turn Short-Circuit Fault on Wind
Turbine Driven Squirrel-Cage Induction Generator
Systems
Takwa Sellami, Hanen Berriri, Mohamed Faouzi Mimouni, Sana Jelassi,
Moumen Darcherif
To cite this version:
Takwa Sellami, Hanen Berriri, Mohamed Faouzi Mimouni, Sana Jelassi, Moumen Darcherif.
Impact of Inter-Turn Short-Circuit Fault on Wind Turbine Driven Squirrel-Cage Induction Generator Systems. Conférence Internationale en Sciences et Technologies Electriques au Maghreb
CISTEM 2014, Nov 2014, Tunis, Tunisia. <hal-01214863>
HAL Id: hal-01214863
https://hal.archives-ouvertes.fr/hal-01214863
Submitted on 16 Oct 2015
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Impact of Inter-Turn Short-Circuit Fault on Wind Turbine
Driven Squirrel-Cage Induction Generator Systems
T. Sellami, H. Berriri, M.F. Mimouni
The Electrical Engineering Department of Engineering
school of Monastir (ENIM)
Unit of Study of Industrial Systems and Renewable Energy
Monastir, Tunisia
takwa.sellami.enim@gmail.com, hanen.berriri@yahoo.fr,
Mimouni@enim.rnu.tn
Abstract—This study aims to assess the impact of inter-turn
short-circuit in stator windings of squirrel cage induction
generators on variable-speed wind turbine systems. The shortcircuit fault detection is based on a steady-state technique which
is Motor Current Signatures Analysis (MCSA). Thus, theoretical
developments of both healthy and faulty three-phase squirrelcage induction generator of the wind turbine system models in
the abc-reference frame are made to recognize the current
signature variations. Simulation results are carried out to
illustrate the severe consequences of inter-turn short-circuit fault
on the generator signatures and moreover on the whole system.
This work highlights the importance of the existence of a robust
monitoring and diagnosis system for wind turbine systems.
Keywords—stator inter-turn short-circuit, modeling wind
turbine system, healthy mode, faulty mode, Motor Current
Signatures Analysis …
I.
INTRODUCTION
Due to the continuity of environmental degradation
conditions, renewable energy is still an effective way to deal
with energy crisis and global warming [1, 2]. Within this
framework, wind energy capacity has become one of the most
essential energy sources and expected to carry on increasing
around the world [3]. Thus, high-power variable speed wind
turbine systems are ones of most active research fields [4].
Wind turbine systems modeling and control has recieved
considerable attention [5-8]. However, with growing concerns
about a high level of reliability and the continuity of service
and operating flexibility, fault tolerant control has also become
an important issue during the last years [9] and monitoring and
diagnosis are the most important parts of this research area
[10-13]. Indeed, several failures can occur in variable speed
wind turbines system. Among them, failures related to the
power converter such as open-circuit faults [14, 15] and those
concern sensor faults [16, 17] and [18], also failure of gearbox
bearings and torque arms [19], rotor blades [20], etc.
On the other hand, there are failures related to the
generator, such as broken rotor bar [21] or windings inter-turn
fault [22]. In this respect, inter-turn short-circuit in stator
windings is the most common stator fault witch it can progress
to turn-turn or turn-ground short-circuit [23], where moisture,
partial discharge, m-echanical stress and breakdown of the
S. Jelassi, M. Darcherif
School of Electricity, Industrial Production and
Management (EPMI)
Laboratory of Industrial Eco-Innovation and Energy (LR2E)
Paris Grand Ouest
s.jelassi@epmi.fr.
turn-to-turn insulation are the most important causes of this
type of faults [24]. Such faults can damage the machine and
immediately interrupt the wind turbine system. The Power
converter and the transformer can be damaged too [25]. To
avoid these impacts, fast and effective fault detection
technique should be considered [26]. Many methods have
been used for short-circuit fault detection in wind generators
[27, 28]. Motor Current Signatures Analysis (MCSA) is a non
invasive and on-line fault detection method [29, 30].
Analyzing stator current spectra had been fruitfully utilized for
short-circuit fault detection without influencing the system
operation [31].
This paper is structured as follows: In Section II, a
description of the wind turbine system is made. The next
section describes both healthy and faulty squirrel-cage
induction generator models in the abc-reference frame. In
Section IV stator current signatures are analyzed by
considering healthy and faulty operation mode. Conclusions
are presented in the last part.
II.
DESCRIPTION OF THE WIND TURBINE SYSTEM
Despite the sprawling double-fed induction generator, a
three-phase squirrel-cage induction generator (SCIG) is still
widely used within wind turbine plants [32]. The use of SCIG
is advantageous since they are relatively inexpensive, robust,
and require low maintenance. Even for variable-speed
turbines, it is used instead of synchronous generators by the ad
of converters. The basic configuration of a variable-speed
turbine driven SCIG is depicted in Fig. 1. As the rotational
wind turbine speed is low and variable, it must be adjusted to
the suitable electrical frequency by a gearbox. A SCIG is
coupled to the grid through a back-to-back converter driven by
vector oriented control. The back to back converter includes
the stator side converter connected to the stator windings so
that ensures decoupling the electrical and the mechanical
frequencies, and the grid side converter connected to the grid
through the transformer. Both sides are linked by a DC bus.
The DC bus voltage reference and the grid voltage level are
used to establish the current references which determine the
voltages to be applied on the grid side converter. The aim is to
control the DC bus voltage and the reactive power which is
consumed or supplied by the converter of the grid side. In the
stator side converter control, the torque and rotor flux cascade
loops establish the current references which determine the
voltages to be applied. The stator side converter include a
maximal power point tracking algorithm (MPPT). The control
is performed in the synchronous rotating frame, which is
oriented according to the rotor flux.
T
[V s abc ]  V s a V s b V s c  ; [V r abc ]  V r a V r b V r c 
T
[i s abc ]  i s a i s b i s c  ; [i r abc ]  i r a i r b i r c 
ss
Where R s abc , R r abc , L
rr
abc
, L
abc
T
T
M sr ( ) and
,
M rs ( ) are written as follows :
Turbine
Back-to-Back converter
Gearbox
Grid
Transformer
SCIG
Sator side
converter
control
Grid side
converter
control
Figure 1. Overview the SCIG based variable speed wind turbine system
III.
HEALTHY AND INTER-TURN FAULT DYNAMIC
MODELS OF THE SCIG
A. Healthy model
The SCIG equivalent circuit in healthy conditions (no stator
fault) is given in Fig. 2, where s1, s2, and s3 are the stator threephases, rs the stator phase resistance (Ohms), Ls a self
inductances (H), rr the rotor phase resistance (Ohms), Lr a self
inductances (H). The neutral is connected so VNN’=0V.
r s

 R s abc    0
0

r r
0


0  ;  R r abc    0
0
r s 

0
rs
0
0
rr
0
 Ls  l s

 Lss abc    M s
 Ms

Ms
Ls  l s
Ms
Ms 

Ms ;
Ls  l s 
 Lr  l r

 Lrr abc    M r
 Mr

Mr
Lr  l r
Mr
Mr 

Mr ;
Lr  l r 
0

0;
r r 
2
4 

cos(  ) cos(  ) 
 cos( )
3
3


T
4
2 
sr
rs

 M ( )    M ( )   M sr cos(  )
cos( )
cos(  )

3
3 


2

4

cos(  ) cos(  )
cos( ) 

3
3

The SCIG electromagnetic torque Cem is given by equation
(2).
isa
r , L 
s
s
r , L 
r
s1
r , L 
i sb
V sa
V sb
i
V sc
s
c
s2
r
r
Mr
r , L 
r , L 
s
Cem  ( ) p iabc 
2
r , L 
N’
Ms
s
s
s
1
Mr
Ms
r
s3
VNN '
s
a
i sb
isc
d  M sr abc  
d
0
ir a
irb

 iabc 



i r c 
(2)
T
Where J is the moment inertia and p is the pole pair’s
number. The SCIG mechanical angular speed Ω, is got from
the gearbox.
N
The SCIG voltage equations written in its natural reference
frame (abc) are expressed by (1).
d
d
 s
V
   R s  i s    Lss  i s   (  M sr abc  i r abc  )

  abc   abc   abc   abc  dt  abc  dt 

 V r    0   R r  i r    Lrr  d i r   d (  M rs  i s  )
abc 
abc   abc 
 abc   abc   abc  dt  abc  dt 


T
With [iabc ]  i
r
Figure 2. Induction generator equivalent circuit.
With

0


 d  M rs abc 

 

d
r
(1)
B. Faulty model
A stator inter-turn short-circuit fault in stator windings
causes an insulation failure which affects phase windings. This
failure is modeled by an insulation resistance rf. The resistance
value depends on the fault severity. A graver short-circuit fault
of the phase is got when the fault insulation resistance rf
decreases toward zero. This decrease in most materials, from
infinite toward zero is very fast.
Fig. 3 represents the SCIG stator windings with a shortcircuit fault. This fault is occurred in the first phase s1. The
sub-windings (as1) represent the healthy part of the phase
windings s1 and (bs1) represent the faulty one. Ns is the s1 turns
phase number and Nsf is the turns short-circuited number. The
short-circuit report kcc= Nsf / Ns is between 0 and 1.
Ms, and Msr, are the stator mutual inductances (H) and
mutual inductance between stator and rotor phases (H). Mr is
the rotor mutual inductances (H). rs1b and Ls1b present
resistance and self-inductance of the faulty winding. M1a,2 and
M1a,3 present mutual inductances between as1 and the
windings s2 and s3. In addition, M1a,1b, M1b,2 and M1b,3 present
respectively three mutual inductances between bs1 and the
windings as1, s2 and s3. Msr1, Msr2 are the mutual inductances
between as1, bs1 and rotor.
rf
M1a,1b
i
 r1a , L1a 
s

as1
a

bs1r1b , L1b
if
r , L 
r
s1
r
v1b
v1a
Mr
M1a ,2
r , L 
s
i sb
V sa
M1a ,3
isc
V sb
r
s2
Ms
N’
s
r , L 
r
s3
VNN '

Ls  l s

 M  M 1b,2
 Lss abcf    1a ,2
 M 1a ,3  M 1b,3
 Ls  l s  M
1a ,1b
 1b 1b
 Lss abcf  ,
 Lrr abcf 
and
M 1a ,2  M 1b ,2
M 1a ,3  M 1b ,3
Ls  l s
Ms
Ms
s
L  ls
M 1a ,2
M 1a ,3


 L1sb  l1sb  M 1a ,1b 

 M 1b ,2


 M 1b,3

s
s

 L1b  l1b



2
2 

M sr cos( 
)
M sr cos( 
)
 M sr cos( )
3
3 


2 
 M cos(  2 )
M
cos(

)
M
cos(


)
sr
sr
 sr
3
3 
 M sr abcf   

2

2

 M cos( 

) M sr cos( 
)
M sr cos( )
sr


3
3

2
2 
  M sr2 cos( )
 M sr2 cos( 
)  M sr2 cos( 
)
3
3 

0
rs
0
0
r1sb 
r r

0
  Rr    0
  abc  
0
0


(r1sb  rf ) 
0
0
rs
0
0
rr
0
0

0
r r 
r
 Lr  l r

 L abc    M r
 Mr

Mr
L  lr
Mr
rr
N
V sc
 R r abc  ,
 M sr abcf  are written as follows
rs

0
 R s abcf   
0
 s
 r1b
r
Mr
M1b,3
 R s abcf  ,
Where
r , L 
s
r , L 
s
M1b,2
Matrices
r
Mr 
T
rs
sr

M r   M abcf    M abcf 
Lr  l r 
It is admitted that
Figure 3. SCIG equivalent circuit with short-circuit fault.
The SCIG voltage equations under short-circuit fault
conditions are
d
d
 s
V
   R s  i s    Lss  i s   ( M sr abcf  i r abc  )

  abcf   abcf   abc   abcf  dt  abcf  dt 

 V r    0   R r  i r    Lrr  d i r   d ( M rs  i s  )
abc 
abcf   abcf 
 abc   abc   abc  dt  abc  dt 


(3)
r s1b  k cc rs ; l s1b  k cc 2 Ls
Ms 
Ls
L
; Mr 
2
2
M sr 
L L  ; M
s
r
sr1
r
 1  k cc  M s ; M sr2  k cc M sr
M1a,1b  Ls 1  k cc  k cc
M1a,2  M s 1  k cc  ; M1a,3  M s 1  k cc 
M1b,2  M s k cc ; M1b,3  M s k cc
With
T
[V s abcf ]  V s a V s b V s c 0 ; [V r abc ]  V r a V r b V r c 
T
[i s abcf ]  i s a i s b i s c i f  ; [i r abc ]  i r a i r b i r c 
It is admitted that
L1a +l1a +2M1a,1b +L1b +l1b =Ls +ls  Ls
L r =Lr +lr
M sr1 +M sr2 =M sr
M1a,2 +M1b,2 =M1a,3 +M1b,3 =M s
T
T
IV.
SIMULATIONS AND RESULTS
Simulations were carried out for a wind turbine driven
SCIG system. Dynamic models in healthy and faulty modes
were established to study the behavior of the wind turbine
system components signatures. The SCIG parameters are given
in appendix. The simulation results are shown in figures Fig. 4
to Fig. 11 with a stator fault appearing at time t=0.15s.
In the first time, a partially short-circuited turns as 25% of
the phase s1 is applied: parameter kcc=0.25,. The other
parameter rf is fixed to 0Ω as the decrease of this insulation
resistance rf in most materials from infinite toward zero is very
fast. Fig. 4 presents impact of this fault on the three-phase
stator currents (isa, isb, isc), the three-phase rotor currents (ira, irb,
irc) and the stator currents (isd, isq) in the dq-frame. Fault current
if circulating in rf in the abc-frame variations is given too. Fig.
5 shows the short-circuit fault impact on the torque and the
rectifier voltage. Active and reactive powers of the SCIG
signatures are presented too in Fig. 6.
Fault application
isq
isd
Fault application
Time(s)
The detection of inter-turn short-circuit via MCSA is based
on detecting components caused by the induced faulty current
components in the stator windings. This technique uses the
results of spectral analysis of the stator currents. Current
signals are analyzed in the time-domain and the frequencydomain. For frequency-domain study, Fast Fourier Transform
(FFT) analysis is done to correlate the components of current
signatures in order to detect utile frequency components.
Time(s)
Fault application
isb
Irc
isa
isc
Time(s)
isq
isd
Irb
Ira
Time(s)
Time(s)
Time(s)
isa
Irc
isb
Figure 4. Impact of partially short-circuited turns (kcc=0.25) at t= 0.15s on
currents (a) stator currents in the dq-frame (b) Fault current (c) three-phase
stator currents (d) three-phase rotor currents
Irb
isc
Time(s)
Fault application
Fault application
Ira
Irc
Time(s)
Fault application
Figure 7. Impact of 90% short-circuited turns (kcc=0.9) at t= 0.15s on currents
(a) stator currents in the dq-frame (b) Fault current (c) three-phase stator
currents (d) three-phase rotor currents
Time(s)
Time(s)
Fault application
Fault application
Figure 5. Impact of partially short-circuited turns (kcc=0.25) at t= 0.15s on
torque and rectifier voltage
Fault application
Fault application
Time(s)
Time(s)
Figure 8. Impact of 90% short-circuited turns (kcc=0.9) at t= 0.15s on torque
and rectifier voltage
Time(s)
Time(s)
Fault application
Fault application
Figure 6. Impact of partially short-circuited turns (kcc=0.25) at t= 0.15s on
active and reactive power
In the second step, wind power system behavior is observed
when increasing the severity of the fault to 90% short-circuited
turns. Fig. 7 shows inpact of the high number of short-circuited
turns on the three-phase stator currents (isa, isb, isc), the threephase rotor currents (ira, irb, irc), the stator currents (isd, isq) in
the dq-frame and the fault current if circulating in rf. Fig. 8 and
Fig. 9 show the fault impact on the torque and the rectifier
voltage and on the active and reactive powers of the SCIG
signatures, respectively.
When the severity of short-circuit fault exceeds a certain
level, the imbalance of phase currents (especially isa) becomes
significant. Torque ripples appear too. In addition, the active
and reactive powers are disturbed. These disturbed signals
transmitted from the SCIG to the rectifier affect the rectifier
voltage signatures. Then the inverter and control equipment
signals are troubled too.
Time(s)
Time(s)
Figure 9. Impact of 90% short-circuited turns (kcc=0.9) at t= 0.15s on active and
reactive power
Fig.10 presents phase current isa spectral distribution in the
healthy mode. Fig. 11 and Fig. 12 present isa spectral
signatures in the faulty mode. Fig. 11 treats the case of 25%
short-circuited turns of the phase s1 and Fig. 12 deals with 90%
short-circuited turns. The component 170 Hz is present under
normal operations (healthy case) and abnormal ones (faulty
case). It cannot be utilized as an indicator for short-circuit fault.
Fig. 11 shows that 330 Hz component is a good indicator for
25% short-circuited turns fault. Moreover, the highest
magnitude, non fundamental frequency component, appears at
the 330 Hz frequency. Fig. 12 indicates that 430 Hz component
is the good indicator for 90% short circuited turns fault and its
corresponding magnitude is the highest one in the spectral.
isa(A)
isa(A)
170 Hz
170 Hz
f(Hz)
f(Hz)
330 Hz
f(Hz)
f(Hz)
Figure 10. Phase current spectral signatures healthy case with zoom at the
sideband [0...400Hz]
I.
Figure 11. Phase current spectral signatures faulty cases Faulty case (kcc=0.25)
with zoom at the sideband [200...400Hz]
isa(A)
CONCLUSIONS
In this paper inter-turn short-circuit fault in stator
windings is detected by a Motor Current Signatures Analysis
(MCSA) method. The first objective of this work is the
establishment of sufficiently accurate models to determine the
behavior of different wind turbine components variables in the
healthy case. The second objective is the detection of shortcircuit fault by analyzing generator current signatures. The
technique utilized in this paper has shown its effectiveness.
Furthermore wind turbine generator faults detection by
vibration analysis will be the objective of a next work.
170 Hz
f(Hz)
APPENDIX
The SCIG used is characterized by 11kW power, stator
turns number  =48, rotor turns number  =32, J=0.1
s
r
Kg.m², f=0.003 N.m.s, The load current I
current I
s
s
0=
4A and the rated
430 Hz
n =11.32A.
TABLE I.
PARAMETRES OF THE SCIG.
P
rs
rr
Ls
Lr
ls
lr
2
1.5(Ω)
0.7(Ω)
0.28(H)
0.28(H)
0.011(H)
0.0075(H)
f(Hz)
Figure 11. Phase current spectral signatures faulty cases Faulty case
(kcc=0.9) with zoom at the sideband [300...450Hz]
The machine is supplied by an equilibrated three-phase
sinusoidal voltage source defined by

V s a  V 2 cos(2 freq )

2
 s
V b  V 2 cos(2 freq  ( ))
3

4
 s
V c  V 2 cos(2 freq  ( 3 ))
With V  380V and freq  50Hz .
The simulation is effected with MATLAB-Simulink with a
calculation step equal to Te = 100 μs.
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