Electric Power Systems Research 146 (2017) 1–8

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Electric Power Systems Research

journal homepage: www.elsevier.com/locate/epsr

Fault ride through capability improvement of DFIG based wind farm

by fuzzy logic controlled parallel resonance fault current limiter
Gilmanur Rashid a,∗ , Mohd Hasan Ali b
a
ABB Inc., Senatobia, MS 38668, USA
b
Department of Electrical & Computer Engineering, University of Memphis, Memphis, TN 38152, USA

a r t i c l e i n f o a b s t r a c t

Article history: Doubly fed induction generator (DFIG) based wind farms offer some distinct advantages, but their vul-
Received 29 August 2016 nerable nature to grid fault is problematic for the stable operation of power systems with higher wind
Received in revised form 7 January 2017 power penetration. Fault ride through (FRT) capability is a requirement imposed through the grid codes
Accepted 11 January 2017
to ensure stable power system operation. A fuzzy logic controlled parallel resonance fault current lim-
iter (FLC-PRFCL) is proposed to aid the DFIG based wind farms to achieve improved FRT capability. To
Keywords:
check the effectiveness of the proposed FLC-PRFCL, temporary symmetric and asymmetric faults were
Bridge-type fault current limiter (BFCL)
applied to the multi-machine system, to which a DFIG based wind farm is connected. The performance
Doubly fed induction generator (DFIG)
Fault ride through (FRT)
of the proposed FLC-PRFCL was compared with that of the crowbar, the bridge-type fault current lim-
Fuzzy logic controller (FLC) iter (BFCL) and conventional proportional-integral (PI) control based PRFCL (PI-PRFCL). Simulations were
Grid code performed using the Matlab/Simulink software. It was found that the proposed FLC-PRFCL is an effective
Parallel resonance fault current limiter device for FRT capability improvement of the DFIG based wind farm. Moreover, the proposed FLC-PRFCL
(PRFCL) outperforms the crowbar, the BFCL, and the PI-PRFCL.
Proportional-integral (PI) controller © 2017 Elsevier B.V. All rights reserved.
Wind farm

1. Introduction The direct connection of its stator windings to the grid makes it
particularly susceptible to the grid faults. Voltage sag due to the
Environmental concern and the perpetual increase in demand faults within the power system where the farms are connected,
for electricity have necessitated finding alternative energy sources disturbs the air gap flux and affects the DFIG’s energy conversion
and devising methods to utilize existing renewable sources more process. In both the stator and rotor winding, high current results
efficiently. Wind energy is proliferating so quickly, and according in and the dc link faces overvoltage. The rotor side converter (RSC)
to a report, 666.1 GW of electricity is estimated to be produced by can contribute to limit the fault current but it is constrained by
the year 2019 [1]. The rapid growth of electric power generation partial converter rating and the modulation index. Without addi-
from wind is largely credited to the doubly fed induction generator tional support, the RSC loses the current control capability at fault
(DFIG) technology [2]. Ability of the DFIGs to harness more power and, it’s transient current handling capacity is exceeded. Apart from
from wind along with better power quality, variable speed opera- the electrical side, the mechanical part also faces very high stress
tion, enhanced electric power output, extended electro-mechanic at the shaft, bearing and the gearbox due to pulsating torque [6].
efficiency, lower turbine mechanical stress, decoupled control of Traditionally, to protect the DFIGs from the faults, the associated
the active and reactive power [3], and lower converter rating converters were blocked. This lead to the DFIG system disconnec-
(20–30%) have made it a popular choice for erecting new wind tion from the grid. This sort of disconnections were permissible in
farms and upgrading the induction generator based legacy wind traditional wind farm operation. As the contribution of the wind
farms [4]. Also, recent steep price hike of the permanent magnet farms into the grids has swelled, regulators at different parts of the
materials, lead even more attention toward DFIGs [5]. world have imposed grid codes [7] that demand the wind farms
Even though they offer a handful advantages, the DFIG based to have fault ride through (FRT) capability. The FRT implies to stay
wind farms are inculpated for their vulnerable nature to the faults. connected to the grid and support the grid to maintain system sta-
bility during fault events. So it is very important for the DFIG based
wind farm to have improved FRT capability from the standpoint of
∗ Corresponding author. operation as well as regulation.
E-mail addresses: gilmanur.rashid@us.abb.com, gilmaneee@gmail.com The proposed solutions to improve FRT capability of the DFIGs
(G. Rashid). can be designated into two groups. The first group emphasized the

http://dx.doi.org/10.1016/j.epsr.2017.01.018
0378-7796/© 2017 Elsevier B.V. All rights reserved.
2 G. Rashid, M.H. Ali / Electric Power Systems Research 146 (2017) 1–8

use of new converter modeling and control techniques [8,6,9,10],

but these methods are feasible mostly for new installations and
integrations. The second group showed the use of the auxiliary
devices, where the most popular and widely used one is the
crowbar [11,12]. DFIGs are converted to squirrel cage induction
generators by the crowbar activation. This incurs the problem
of reactive power absorption by the DFIGs, and thus it causes
the voltage sag to become even deeper [13]. Although the use
of a series dynamic braking resistor (SDBR) was proposed in
[14,15], but some previous works [3,16] showed the superior-
ity of the bridge-type fault current limiters (BFCL) to the SDBR.
The dynamic voltage restorer (DVR) [17] and series grid side con-
verters [18,19] are proposed but additional converters needed
make them costly. Energy storages like flywheel energy stor-
age (FES) [20], supercapacitor [21], superconducting magnetic
energy storage (SMES) [22] are also proposed to improve the
FRT, but high installation and maintenance cost offset their better
performance.
Power systems have highly nonlinear nature. For this reason,
nonlinear controllers like fuzzy logic, particle swarm optimization,
neural network, and genetic algorithm based controller or their
composite, work better with power systems. Among the nonlin-
ear controllers, fuzzy logic controller (FLC) is a simple but effective
controller [23,22] that efficiently captures the dynamics of power
systems.
The parallel resonance type fault current limiter (PRFCL) is a
new auxiliary device manifesting potential application in power
systems [24]. Day by day it is getting increasing acceptance by the
power researchers. So far the conventional controlled PRFCL has
been applied to the FRT capacity augmentation of DFIG based wind
farm [25,26], however, nonlinear control based approach, such as
Fig. 1. DFIG based wind farm connected to multi-machine power system.
a fuzzy logic controlled PRFCL for FRT capability enhancement is
yet to be reported. Based on this background, a fuzzy logic con-
trolled PRFCL (FLC-PRFCL) is proposed in this work to enhance the 3. Wind farm modeling
FRT capability of the DFIG based wind farm connected to a multi-
machine power system. And this is the main contribution of this A wind farm is composed of many units of turbine-generator
paper. Another salient feature of this work is that, in order to check system. The turbine and the generator are the two key components
the effectiveness of the proposed FLC-PRFCL device in enhancing of a wind farm. Their modeling is as follows.
the FRT capability of the DFIG based wind farms, its performance
is compared with that of the conventional BFCL and the conven- 3.1. Wind turbine modeling
tional proportional-integral control based PRFCL (PI-PRFCL). Both
symmetrical and unsymmetrical temporary faults are considered The wind power harnessed by a wind turbine in the form of
in the studied power network. Simulations are performed by using mechanical power can be calculated by the equation below [28],
the Matlab/Simulink software.
1 3
Pw = AVw Cp (, ˇ) (1)
2
2. Power system model description where Pw is the harnessed wind power,  is the density of air, blade
swept area is A, wind velocity is Vw , and Cp is the Betz constant. Cp
The power system model shown in Fig. 1 is composed of a multi- is given by,
machine main system and a 100 MVA DFIG based wind farm. The C  C5
− C3 ˇ − C4 e− i + C6 
2
wind farm is connected to bus 8 through transformers and a short Cp (, ˇ) = C1 (2)
i
transmission line. In between the wind farm and the short trans-
mission line, an auxiliary device (FLC-PRFCL) is placed to protect ωr R
= (3)
the wind farm from external faults. The wind farm is an aggre- Vw
gated model of 60 individual wind turbine units, where each unit
1 1 0.035
possesses power rating of 1.67 MVA. Actually, an individual wind = − 3 (4)
i  + 0.08ˇ ˇ +1
turbine is scaled up to model the 100 MVA wind farm [27].
The multi-machine power system comprises of two syn- where  is the tip speed ratio and ˇ is the blade pitch angle, ωr
chronous generators (SG1 and SG2) and an infinite bus. They are is the angular mechanical speed and C1 ∼ C6 (C1 = 0.5176, C2 = 116,
connected to each other through transformers and double circuit C3 = 0.4, C4 = 5, C5 = 21, and C6 = 0.0068) are coefficients that define
transmission lines. The transmission line parameters are shown in the turbine characteristic [28].
R + jX(jB/2) form in Fig. 1, where R, X, and B indicates resistance,
reactance, and susceptance, respectively, with two lines per phase. 3.2. Drive train
Various parameters of the generators, governor (GOV), and auto-
matic voltage regulator (AVR) control system model used in this As two mass shaft model [29] is good enough for the dynamic
work are available in [23]. analysis of grid connected wind turbines, it is considered in this
 G. Rashid, M.H. Ali / Electric Power Systems Research 146 (2017) 1–8 3

Fig. 2. Drive train. Fig. 4. GSC controller.

work as shown in Fig. 2. The equations of motion are described as

reduce controller complexity, linear control technique is adopted
follows:
over nonlinear and more complex controllers.
ds
= ωt − ωg (5)
dt
3.5. GSC controller
dωt 1
= (Tt − Ks s ) (6)
dt 2Ht The GSC controller in Fig. 4, takes the dc-link voltage Edc and the
dωg 1 grid side quadrature current Iqg as the inputs. The PI controllers then
= (−Te + Ks s ) (7) produce necessary reference signals to control the IGBT switches
dt 2Hg
at the GSC. A constant dc-link voltage and system required power
where Tt is the mechanical torque referred to the generator side, factor at the generator terminal are ensured by the GSC controller.
Te is the electromagnetic torque, ωt and ωg are the turbine and the The frequency of the carrier waves used at the PWM blocks of both
generator rotational speed, respectively, the shaft stiffness is Ks , the RSC and the GSC controllers are chosen to abate the harmonics.
Ht is the equivalent turbine-blade inertia referred to the genera-
tor side, the generator inertia is Hg , and the angular displacement
4. Fuzzy logic controlled PRFCL
between the ends of the shaft is  s .
The modeling of the proposed FLC-PRFCL is described as follows.
3.3. DFIG modeling

Modeling of the DFIG can be found in many works like [30]. The 4.1. PRFCL configuration
DFIG is modeled here exploiting the Park’s transformation model
[30]. A d–q reference frame revolving at synchronous speed is cho- The per phase diagram of the PRFCL is shown in Fig. 5 [24]. The
sen. For convenience, the stator flux is assumed aligned with the topology comprised of two distinct parts. These parts are described
d-axis so that the stator flux and the reference frame rotate at equal as follows.
speed. These selections facilitate the decoupled control of the gen-
erator electrical torque and the rotor excitation current. A list of 1. Bridge part: Four diodes D1 –D4 , arranged in bridge formation,
used DFIG parameters are available in appendix [31]. build the bridge part. Inside the diode bridge, an IGBT switch
in series with a dc reactor Ldc is placed. Depending on system
3.4. RSC controller requirements, series/parallel combination of IGBTs can be used.
The inherent resistance of the dc reactor is considered by placing
Two identical 2-level, 3-phase full bridge power electronic con- a very small value resistor Rdc in series with the dc reactor. The
verters based on insulated gate bipolar transistors (IGBT) have been free-wheeling diode D5 ensures safe operation of the dc reactor
exploited as the RSC and the grid side converter (GSC). Depending Ldc .
on the reactive power Qt , the generator terminal voltage Vt , and the 2. Resonance part: The shunt resonance part is comprised of a
generator speed ωr , the RSC controller controls the active and reac- capacitor Csh and an inductor Lsh arranged in parallel to each
tive power output as shown in Fig. 3. The proportional-integral (PI) other to form an LC resonance circuit at power line frequency.
controller provides the reference signal for the pulse width mod-
ulation (PWM) block. The PWM block then produces appropriate
signals for the IGBT switches that made up the RSC [15]. In order to

Fig. 3. RSC controller. Fig. 5. Per phase diagram of PRFCL.

4 G. Rashid, M.H. Ali / Electric Power Systems Research 146 (2017) 1–8

1
ZE SM HI

Degree of membership
0.5

Fig. 6. Per phase fuzzy logic based controller for PRFCL.

4.2. PRFCL operation and control 0

0 0.25 0.5 0.75 1
When the system is in normal operation, the IGBT switch ∆V
stays closed and carries the line current fully. For the positive
Fig. 7. Membership function of input V.
and negative half cycle of voltage, the D1 –Ldc –Rdc –D4 path and
D2 –Ldc –Rdc –D3 path carries the line current. But current going into
the dc reactor Ldc , is from the same direction. So current flowing into 1
the dc reactor Ldc is dc current. Ldc is charged up to the peak value ZE MB BI

Degree of membership
of current and the current ripples are smoothed out by it. The turn
on resistance of the IGBT, Rdc , and forward voltage of diode alto-
gether cause some voltage drop. In comparison to the line voltage
drop, this voltage drop is ignorable and has an insignificant effect 0.5
on normal operation. The shunt path impedance is high enough so
that the bridge path conducts the line current entirely, except very
small leakage current through the shunt path. When faults occur,
the line current rise rapidly, but the rate of change di/dt, is sup-
pressed by the dc reactor Ldc . This ensures the safe operation of 0
the IGBT. The per phase controller for the PRFCL is shown in Fig. 6. 0 0.2 0.4 0.6 0.8 1
d
The instantaneous phase voltage of the wind farm terminal Vinst,ϕ
or Vd,ϕ is taken and one-fourth cycle delay is applied to produce
Fig. 8. Membership function of output d.
a quadrature counterpart Vq,ϕ · Vdq,ϕ is then produced defined by

Vdq,ϕ = 2 + V2 ) · V
(Vd,ϕ q,ϕ dq,ϕ is then compared with the reference

voltage Vref . The difference V is fed to the FLC. The FLC output is respectively, for the design of the proposed fuzzy logic controller.
adjusted to produce a duty cycle in between 0.5 and 1 so that very Gaussian membership functions (MFs) for V and d are shown
small value of impedance is not inserted at the fault instant. in Figs. 7 and 8, in which the linguistic variables ZE, SM, HI, MB,
A threshold voltage level Vth = 0.9 pu is compared with Vdq,ϕ to and BI stand for zero, small medium, high, medium big and big,
detect the fault in the system. This signal is used in a selector respectively. Other types of MFs, for example, the triangular and the
that feeds a signal value of 1 to the IGBT gates at normal oper- trapezoidal MFs were also tried in Matlab, but Gaussian MFs gave
ation Vdq,ϕ > Vth and the inverted PWM generator output during the best performance. Also, some adjustments were done to the
the faulty situation (Vdq,ϕ < Vth ). The modified voltage Vdq,ϕ enables Gaussian MFs to get the best system performance. The equation of
quick fault detection. Instead of applying the full impedance value the Gaussian MFs [22]used to determine the grade of membership
of the shunt path (Zsh ) throughout the fault period, a variable value values is as follows:
of impedance Zsh  = d ∗ Z is offered to the system for best compen-
sh (x−c)2
−
sation by the FLC-PRFCL, where d is the duty ratio generated by the f (x; , c) = e 2 2 (9)
FLC block. The duty ratio d is defined as
Toff where  and c defines the width of the bell curve and the center of
d= (8) the peak, respectively.
Tc
where Tc is the period of the PWM generator carrier wave, Toff is the
time the NC-MBFCL bridge IGBT doesn’t conduct. Tc is defined as 4.3.2. Fuzzy rule base
Tc = Toff + Ton or Tc = 1/fc where Ton is the time the NC-MBFCL bridge The very simple design having only one input variable and one
IGBT conducts and fc is the carrier wave frequency of the PWM output variable is the specific feature of the proposed fuzzy con-
generator. The variable value of the shunt impedance makes the troller. The use of single input and single output variable makes
FLC-PRFCL flexible and dynamically responding to the severity level the fuzzy controller very straightforward [23]. The control rules of
of the faults. the proposed controller as shown in Table 1, are determined from
the viewpoint of practical system operation, and also to obtain the
best system performance.
4.3. Fuzzy logic controller design

The fuzzy controller designed to control the FLC-PRFCL is delin-

Table 1
eated below.
Fuzzy rule table.

4.3.1. Fuzzification PCC voltage deviation V Duty cycle d

The difference between the reference voltage and the wind ZE ZE

farm terminal voltage, V, and the duty cycle d of the PWM gen- SM MB
HI BI
erator block at Fig. 6, are chosen as the input and the output,
 G. Rashid, M.H. Ali / Electric Power Systems Research 146 (2017) 1–8 5

4.3.3. Fuzzy inference

Mamdani’s method is used for the inference mechanism that
gives the degree of conformity, Wi , of each fuzzy rule as follows:

Wi = i (V ) (10)

where i is rule number.

4.3.4. Defuzzification
The center of gravity method is a well-known defuzzification Fig. 10. Per phase (a) topology of BFCL and (b) BFCL controller.
procedure. This is implemented to determine the output crispy
value (i.e., the duty cycle, d), given by the expression below,
5. Bridge-type fault current limiter

z · i (z) dz
d=  (11) In order to see the efficacy of the proposed FLC-PRFCL, its per-
i (z) dz
formance is compared with that of the BFCL. Both the BFCL and the
where i (z) is the value of d expressed in terms of linguistic vari- PRFCL share the same bridge part, but the difference is in the shunt
ables in the fuzzy rule table. path. In the BFCL, a resistor and an inductor placed in series are used
as the shunt path as shown in Fig. 10a [33]. The detailed description
on the BFCL technology is given in [33,16,3].
4.4. Influence of operating point on FLC
The operation and control principle is similar to that of a PRFCL.
Also, the BFCL is placed at the same position where the PRFCL was
If the operating point of the wind farm, i.e., wind speed changes,
placed. The BFCL controller is given in Fig. 10b. The RMS voltage
then it has some influence on the operation of the proposed fuzzy
at the point of common coupling (PCC) or the wind farm terminal
logic controller. In fact, the fuzzy control parameters need to be
(VWF ) is used to detect faults by comparing with a preset thresh-
tuned to adapt to the changing operating conditions. However, in
old voltage Vth . When VWF > Vth , the IGBTs are turned on and when
this work since we are dealing with fault or transient situations, it
VWF < Vth , a fault is detected and IGBTs are turned off to bypass the
is assumed that the wind speed is constant during the short time
fault current to the shunt path.
period under consideration and hence only one set of fuzzy con-
The design criteria require that the shunt path of the BFCL
trol parameters are used to show the effectiveness of the proposed
emulates the load impedance to the wind farm. The wind farm is
work. Certainly, the fuzzy parameters are well tuned so that they
connected to the transmission system, where the impedance does
can work well for both balanced and unbalanced faults conditions.
not change that much compared to that of a distribution system.
This consequently makes the design of the BFCL simple. The val-
4.5. PRFCL design considerations ues of the Rsh and Lsh are determined by measuring the impedance
seen from PCC and using the techniques described in [3]. The values
A consolidated average model of IGBT is considered in this work Rsh = 4.2
and Lsh = 0.1168 mH are used in this work.
which can withstand system operation. The main job to design the
PRFCL is to determine appropriate values of the shunt path capac-
6. Simulation results and discussions
itor Csh and inductor Lsh . Many combinations of Csh and Lsh values
would give resonance at power frequency. But standard values of
The simulation results are illustrated with relevant discussions
Csh are picked from [32] and Lsh value is calculated considering the
in the following subsections.
resonance at power frequency. Different resonating pairs of Csh and
Lsh values were trialed. Among the explored pairs, Csh = 300 ␮F and
Lsh = 38 mH were found to provide the best performance under fault 6.1. Simulation considerations
conditions.
The simulations were executed using the Matlab/Simulink soft-
ware. The time span of the fault is too brief for the wind speed to
4.6. PRFCL with proportional-integral (PI) control cause any impact on the transient performance. So the wind speed
is assumed to be fixed at 15 m/s. Temporary three-line-to-ground
To compare the performance of the proposed FLC-PRFCL with a (3LG), line-to-line (LL), double-line-to-ground (2LG) and line-to-
simple yet useful controller, the proportional-integral (PI) control ground (1LG) faults were applied at point F1, located at bus 8 end
has been chosen. The topology of the controller is shown in Fig. 9. To of one of the double circuit transmission lines. The fault at this point
keep the comparison fair and reasonable, only the fuzzy controller makes the most severe effect on the wind farm compared to other
portion of Fig. 6 is replaced with a PI control block. The control points of the multi-machine system because the farm is attached
parameters were adjusted for optimal system performance, and it at this point. The fault is applied at 0.1 s and withdrawn at 0.7 s.
was found that the proportional gain of 0.7 and integral gain of 0.75 Circuit breakers on the faulty line open at 0.2 s and reclose success-
yield the optimum system performance. fully at 1.2 s. A simulation time step of 20 ␮s was used. Results are
shown for the most critical fault (3LG) and the least severe but most
frequent fault (1LG) in the following sections. To capture all the
possible details and for better representation, a common time span
of 0–10 s and per unit (pu) measurement are used in the graph-
ical results. The zoomed portion is also provided inside most of
the figures for better visualization. For a rational comparison, four
separate cases are considered in the simulations, namely,

1) Case A: with Crowbar only

Fig. 9. Per phase proportional-integral (PI) controller for PRFCL. 2) Case B: with BFCL only
6 G. Rashid, M.H. Ali / Electric Power Systems Research 146 (2017) 1–8

70

SG1 Load Angle (deg)

60

50
Crowbar
BFCL
40 PI-PRFCL
FLC-PRFCL
30
0 2 4 6 8 10
Time (s)
Fig. 11. Wind farm voltage profile for 3LG fault. Fig. 15. SG1 load angle profile for 3LG fault.

BFCL. The BFCL also helps improve the voltage profile as compared
to the crowbar. But it is apparent that the FLC-PRFCL helps keeping
the best voltage profile with the lowest amount of voltage fluctua-
tion and hence enhances the FRT capability of the wind farms under
consideration.
Fig. 12 illustrates that the FLC-PRFCL keeps the active power
profile smooth at the event of a 3LG fault. Output power goes really
low with the crowbar in action. The PI-PRFCL and the BFCL can
contribute in keeping a better active power profile, but their per-
formances are inferior to the FLC-PRFCL.
Fig. 13 provides DFIG rotor speed profile for 3LG fault. It can
Fig. 12. Wind farm active power profile for 3LG fault.
be seen that there is a rotor speed jump caused by the fault with
the crowbar. The PI-PRFCL and the BFCL can minimize it. However,
the FLC-PRFCL is more capable of subduing the speed change and
keeping the speed fluctuation to the minimum level.
The DFIG dc link voltage profile is manifested in Fig. 14 for the
3LG fault. It is apparent that the 3LG fault causes disturbance to
the dc link voltage. The FLC-PRFCL, PI-PRFCL and BFCL can keep the
dc link voltage closer to the nominal voltage as compared to the
crowbar. But the FLC-PRFCL offers the lower deviation from fault
initiation to breaker opening.
Fig. 15 displays the SG1 load angle profile. It is clear that SG1
can maintain the least deviation of load angle when aided by the
FLC-PRFCL.

6.3. FRT improvement by FLC-PRFCL for 1LG fault

Fig. 13. DFIG rotor speed profile for 3LG fault.

Figs. 16–20 show the fault responses for 1LG fault. It is notice-
3) Case C: with PI-PRFCL only
able that the system is less affected by 1LG fault than the 3LG fault
4) Case D: with FLC-PRFCL only
as the former is the least severe fault. From the wind farm termi-
nal voltage (Fig. 16) and output active power (Fig. 17) profile, it is
6.2. FRT improvement by FLC-PRFCL for 3LG fault evident that the FLC-PRFCL ensures the least deviation along with
a steady response.
Figs. 11–15 show the fault responses for 3LG fault. Wind farm The DFIG rotor speed (Fig. 18) and dc link voltage (Fig. 19) face
terminal voltage profile for 3LG fault given at Fig. 11 indicates that oscillations with the crowbar action, as the 1LG fault is an unbal-
at fault event voltage goes very low if only the crowbar is used. With anced fault. The BFCL and the PI-PRFCL can somewhat reduce the
the application of the FLC-PRFCL, the voltage profile is significantly oscillation but the FLC-PRFCL is more effective in damping the
improved. The PI-PRFCL also gives a better voltage profile than the speed oscillation, thus giving a more stable operation.

Fig. 14. DFIG dc-link voltage profile for 3LG fault. Fig. 16. Wind farm voltage profile for 1LG fault.
 G. Rashid, M.H. Ali / Electric Power Systems Research 146 (2017) 1–8 7

Table 2
Performance index values for 3LG fault.

Index parameters (%) Values of indices

Crowbar BFCL PI-PRFCL FLC-PRFCL

vlt (pu s) 70.40 34.62 18.67 14.70

pow (pu s) 29.14 6.62 6.85 5.77
spd (pu s) 3.14 0.32 0.31 0.19

Table 3
Performance index values for 1LG fault.

Fig. 17. Wind farm active power profile for 1LG fault. Index parameters (%) Values of indices

Crowbar BFCL PI-PRFCL FLC-PRFCL

vlt (pu s) 39.60 10.56 10.40 8.84

pow (pu s) 5.34 3.96 4.13 2.80
spd (pu s) 0.25 0.19 0.19 0.16

parameters, their lower values are indicative of better system per-

formance. They are defined by the following equations accordingly.
 T
vlt (pu s) = |V | dt (12)
0

 T
Fig. 18. DFIG rotor speed profile for 1LG fault.
pow (pu s) = |P| dt (13)
0

 T
spd (pu s) = |ω| dt (14)
0

where V, P and ω stand for the deviation of the wind farm
terminal voltage, active power, and the DFIG rotor speed, respec-
tively. The time period of interest spanning from 0 s to T = 10 s.
Tables 2 and 3 represent the values of the indices for 3LG and 1LG
fault, respectively. It is apparent from the tables that the improve-
ment is significant using the FLC-PRFCL because it provides the
smallest index values. The FLC-PRFCL gives the smaller value of the
indices compared to that of the BFCL and the PI-PRFCL. Hence, the
Fig. 19. DFIG dc-link voltage profile for 1LG fault.
FLC-PRFCL performs better than both the BFCL and the PI-PRFCL to
enhance FRT for both types of faults. The numerical results indeed
Fig. 20 represents that the load angle of the SG1 is least disturbed support the graphical results.
due to 1LG fault when FLC-PRFCL is in action. The FLC-PRFCL helps
the SG1 more compared to the crowbar, the BFCL, and the PI-PRFCL.
7. Conclusion
6.4. Index based performance
A fuzzy logic controlled parallel resonance fault current limiter
(FLC-PRFCL) scheme is proposed in this paper to improve the FRT
For the sake of numerical quantification of the system perfor-
capability of a DFIG based wind farm connected to a multi-machine
mance, some indices [34] like vlt (pu s), pow (pu s) and spd (pu s)
power system. The effectiveness of the FLC-PRFCL is compared with
have been exploited. As they account for the deviation of system
that of the crowbar, the BFCL, and the PI-PRFCL. From the simulation
results and discussions, the following points can be inferred.
70
SG1 Load Angle (deg)

1) The FRT capability of a DFIG based wind farms can be enhanced

60 significantly using the proposed FLC-PRFCL for both symmetrical
and asymmetrical faults.
50 2) More stable operation of the DFIG based wind generator system
Crowbar is ensured by the proposed FLC-PRFCL.
40 BFCL
PI-PRFCL 3) The FLC-PRFCL provides much better performance than the
FLC-PRFCL crowbar, the BFCL, and the PI-PRFCL counterpart.
30
0 2 4 6 8 10
Time (s) Investigation of the usefulness of the FLC-PRFCL on a system with
distributed generation and grid-tied microgrid, will be our future
Fig. 20. SG1 load angle profile for 1LG fault. work.
8 G. Rashid, M.H. Ali / Electric Power Systems Research 146 (2017) 1–8

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