Improvement Transient Stability of Fixed Speed Wind Energy Conversion System by using Transformer-Type Superconducting Fault Current Limiter

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 04 Issue: 11 | Nov -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 1090
Improvement Transient Stability of Fixed Speed Wind Energy
Conversion System by Using Transformer-Type Superconducting Fault
Current Limiter
Ali Azizpour1, Seyed Etezad Moghimi2, Sajad Dadfar3
1 Department of Electrical Engineering, Mazandaran university of Science and Technology, Behshahr, Iran
2,3 Iran Power Generation, Transmission and Distribution Management Company (TAVANIR), Iran
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract -The windturbinegenerationsystem(WTGS)
is one of the representative renewable energy systems.
With the rapid development of WTGS and its increased
capacity, the level of short circuit currentwillincreasein
distribution systems. The application of the
Superconducting Fault Current Limiter (SFCL), would
not only reduce the level of the short circuit current but
also offer a reliable interconnection to the network. The
transformer-type superconducting fault current limiter
(SFCL) is one of the fault current limiters, and has many
advantages such as design flexibility. In this paper, the
effect of transformer -type SFCL on transientbehaviorof
grid connected to WTGS is studied. The WTGS is
considered as a fixed-speed system, equipped with a
squirrel-cage induction generator. The drive-train is
represented by two-mass model. The simulation results
show that the transformer -type SFCL not only limits the
fault current but also can improve the dynamic
performance of the WTGS.
Key Words: Wind Turbine Integration, Fixed Speed
Wind Turbine, Induction Generator, Transformer-Type
SFCL, Transient Stability
1.INTRODUCTION
There are promising reasons that future power grids
will be different compared to current power grids due
to integration of renewable energy resources which
require new controlling, monitoring and protection
models [1-2] .Energy and environmental issues have
become one of the main challenges facing the world.
Concerning about environmental pollution and a
possible energy shortage, the capacities of renewable
energy generation systems, are being expanded.
Generally, renewable energy resources provide both
electric utilities and customers with a lot of benefits
including: high quality electricity, emission reduction,
and so on [3-6]. By increasing development of robotics
field using renewable energy in this fieldalsoattractsa
lot of researchers’ attention [7-10]. Free and clean
renewable energy resourcessuchassolarphotovoltaic
and wind generation offer flexibility to the power
network and are the key players in reducing operating
cost and emissions of the system [11-13]. However,
due to their intermittency and uncertainty, integrating
them into the power system is challenging and
complicated [14-15]. Each renewable energy sources
have different challenges. Some photovoltaic systems
challenges are their optimum tilt angle [16] and effect
of temperature on PV panels[17]. Indeed, balancing
supply and demand in power systems including large
amount of renewable energy penetration requires
flexible renewable energy resources [18-27].
The WTGS is one of the representative renewable
energy systems. Wind energyconversionsystemshave
two types: fixed and variable speed systems. As a
simple conversion system, the fixed speed system is
still applied at electric power industry. It is necessary
to research power flow and transient stability of
distribution system with wind turbine generators [28-
30].
The connection of wind turbines to the grid causes the
fault current level increase beyond capabilities of
existing equipment in some points of grids. This not
only might damage the series equipment but also can
cause negative effect on WTGS with respect to voltage
stability [31].
Increasing fault currents often requires the costly
replacementofsubstationequipmentortheimposition
of changes in the configuration that may lead to
decreased operational flexibility and lower reliability.
An alternative approach to reduce the fault current is
the application of Fault Current Limiters (FCLs). Their
application allows equipment to remain in service,
even if the fault current exceeds its rated peak and
short time withstand current[32-33].Sincethevoltage
sag during the fault is proportional to the short circuit
current, an effective fault current limiter connected to
the WTGS not only limits the large fault current but
also improves the voltage stability of WTGS [34]. In

recent years, various types of FCL such as, solid state
FCL, resonant circuit and SFCL (SuperconductingFault
Current Limiter) have been proposed and developed
[35]. SFCL offers a solution to limit fault current with
many significant advantages. The application of the
SFCL would not only decrease the stress on device but
can also improve reliability, improve power quality,
limit the inrush current of transformers, reduce the
transient recovery voltage (TRV) across the CBs and
improve transient stability of power systems by
reducing the fault current. There are different types of
SFCLs which are based on different superconducting
materials and designs such as, flux-lock, transformer,
resistive and bridge-types SFCL [36-38]. The
transformer-type SFCL has zero impedance under
normal conditions and large impedance under fault
conditions (the same as other FCLs) [39-43].But,ithas
significant advantages as follow:
 large design flexibility of the current limiting
device,
 isolation between the current limiting device
and the power transmission line,
 reduction of heat loss of the current limiting
device
 prevention from instantaneously deep
voltage drop during fault
This characteristic of the transformer-type SFCL
suppresses the instantaneous voltage drop and it is
able to improve transient behavior of WTGS during
fault. In this paper, the effect of transformer-type SFCL
on transient behavior of WTGS is studied. The WTGS is
considered as a fixed-speed system, equipped with a
squirrel-cage induction generator. The drive-train is
represented by two-mass model. The simulation
results show that the transformer-type SFCL can
improve the dynamic performance of the WTGS.
2. Transformer-Type Fault Current Limiter
2.1. Power Circuit of Transformer-Type SFCL
The transformer-type SFCLisshowninFig.1.Thistype
of FCL basically consists of a transformerinserieswith
the line and a resistive superconducting current
limiting device connected to the secondary winding of
the series transformer (T).
R(t)
N1
N2
M
iL
iSC
Superconducting Coil
(SC)
Fig. 1: Transformer-type SFCL
2.2. Characteristic of Transformer-Type SFCL
During Fault
The circuit shown in Fig. 2 has been used for analytical
studies. The source impedance has been modeled by zs
= rs + jωLs . The impedance, zL = rL + jωLL presents the
line and load impedance.
Vs
Zs
ZL
Fault
iL
Rsc(t)
VFCL
iSC
M
L1
L2
Fig. 2: Circuit topology for analytical analysis
L1 and L2 presents the primary and secondary leakage
inductance of transformer, M is the mutual inductance
between the primaryandsecondarywindingandRSC(t)
is the resistance of the superconducting current
limiting device. iL and iSC presents the line current and
superconducting current limiting device currents,
respectively. In this paper, the time-dependent
resistance of the superconducting current limiting
device during its S-N transition (transition from
Superconducting state to Normal-conducting state) is
represented by an exponential function as following
expression:
RSC(t) = 0 t<tf (1)
RSC(t)=Rm(1-e(t-t1)/T) t≥tf (2)
Rm is the maximum value of the superconducting
current limiting device current limiting device
resistance; T is the time constant of the resistance

increase. The characteristic of the SC device used for
analysis is shown in Fig. 3.
Fig. 3: Resistance of superconducting current limiting
device during transition
Under the normal operating condition, the
transformer-type SFCL shows very low impedance
because the resistance of the superconducting current
limiting device is zero (RSC(t)=0). But, when fault
occurs (t=tf) in the line, large fault current flows
through the transformer. This will cause the current
throughthesuperconductingcurrentlimitingdevice,to
increase beyond its critical level and the resistance of
superconducting current limiting device is increased
during fault. As a result,thetransformer-typeSFCLwill
limit the fault current at determined value as shown in
Fig. 4.
Fig. 4: Fault current during fault and normal operation
with using transformer-type SFCL
3.Modeling of Fixed Speed Wind Turbine
Fixed-speed wind turbine utilizes squirrel cage IG
directly connectedtothepowergridand,therefore,the
wind turbine rotor speed is fixed and determined by
the frequency of the supply grid, the gear ratio and the
IG design. IGs always need to absorb a particular
amount of reactive power. Thus, they generally have
fixed reactive power support devices [44].
3.1. Wind Speed Model
One approach tomodelawindspeedsequenceistouse
measurements. A more flexible approach is to use a
wind speed model that can generate wind speed
sequences with characteristics to be chosen by the
user. As shown in Fig. 5, wind speed is modeled as the
sum of vwa(t) base wind speed , vwg(t) gust wind
speed , vwr(t) ramp wind speed and vwt(t) noise wind
speed [45]. According to these four wind speeds, the
adopted wind speed model for a single wind turbineis,
as follows:
vw (t) = vwa (t) + vwr (t) + vwg (t) + vwt (t) (3)
Fig. 5: Wind Speed Model
3.2. Wind Turbine Model In general, the relation
between described, as follow [46]:
Pwt =
2

.Awt.Cp(λ,θ)νw
3 (4)
where, Pwt is the power extracted from the wind, ρ is
the air density, vw is the wind speed, CP is the
performance coefficient or power coefficient, λ is the
tip speed ration, Awt = πR2 is the area covered by the
wind turbine rotor, R is the radius of the tip speed
ration and λ is defined, as follows:
Pwt= r
w
R
v

(5)
where, ωr is the angular mechanical speed. The
performance coefficient is different for each turbine
and is relative to the tip speed ratio λ and pitch angleβ.
In this paper, the Cp is, as follows:
2 0.171
( 0.022 5.6)e
2
pC  
     (6)

The CP - λ curves are shown in Fig. 6 for different
values of β.
Fig. 6: CP- λ curves for different pitch angles
3.3. Shaft Model/ Drive Train System
The shaft model of the wind turbine is described by
the two-mass model as shown in Fig. 7 and defined
by the following equation:
t g
t

   

(7)
1
( ( ))
2
t
t s s g t
t
T K D
t H

     

(8)
1
( ( ))
2
g
e s s g t
t g
T K D
H

      

(9)
Where,
Tt : the mechanical torque referred to the generator
side,
Te: the electromagnetic torque,
Ht : the equivalent turbine-blade inertia,
Hg: the generator inertia,
ωt: the turbine’s rotational speed,
ωg: the generator’s rotational speed,
K: the shaft stiffness
D: the damping constant
Θs: the angular displacement between the ends of the
shaft
Fig. 7: Two mass model of wind turbine train
3.4. Induction Generator Model
The PSCAD/EMTDC software library provides a
standard model for the induction generator,
represented by a standard seventh-order model inad-
q reference frame. This model is used in this paper.
4. Stability Analysis
The concept of the induction generator stability can be
further explained by using the electrical torque versus
rotor speed curve ofaninductiongenerator.Inorderto
obtain a mathematical relationship between electrical
torque and rotor speed, the steady-state equivalent
circuit of an induction generatorshowninFig.8isused
[47-49].
Xr Rs Xs
Xm
Rr/S
Vt
XthRthXr
Vt
Rr/S
(a)
(b)
Fig. 8: Steady-state equivalent circuit of induction
generator(a),completemodeland(b)Theveninmodel.
The electrical torque, Te can be calculated, as
follows:
2
2
2 2
( / ) ( )
thr r
e r
th r th r
VR R
T I
S s R R s X X
 
  
(10)

When the induction machine operates as a generator,
the mechanical torque is negative. Therefore, the
electrical-mechanical equilibrium equation of an
induction generator can be written, as follows:
( )
2
e mr T Td
dt H

 (11)
where, H is the inertia constant. From Eq. (11), two
equilibrium points, where the electricaltorqueisequal
to the mechanical torque, can be found. Using FCL has
advantages as follows:
 The fault current is limited and voltage sag is
prevented at the terminal voltage of induction
generator (Vt). According to Eq. (10), the
electrical torque is proportional to the square
of the terminal voltage. Therefore, FCL
prevents from the decreasing electrical torque
and accelerating the induction generator.
 FCL prevents from increasing speed
independent of fault clearing time. According
Eq. (10), the electrical torque is inversely
proportionaltoslipandrotorspeed.Therefore,
FCL prevents from decreasingelectricaltorque
and accelerating induction generator.
5. Simulation Results
A single line diagram of the simulated power system
with transformer-type SFCL is shown in Fig. 9. The
parameters of this system are listed in table I in
appendix A. A 3-phase short circuit fault is simulated
on line 2which starts at t=10s. After 200ms, the circuit
breaker isolated the faulted line. The simulations have
been carried out by PSCAD/EMTDC for two cases, as
follows:
 Case A: Without using any FCL in the system
 Case B: By using the transformer-type SFCL
Fig. 9: Simulated power system with transformer-type
SFCL
Fig. 10 shows the rms value of the PCC voltage in the
both cases (A) and (B). It can be observed that the PCC
voltage decreases to zero in case A,approximately.The
transformer-type SFCL not only decreases the voltage
sag to 0.95 pu, but also prevents from instantaneous
voltage sag in fault instant. Fig. 11 shows the total
active power generated bytheinductiongeneratorand
the grid. During the fault (10s<t<10.2s), the active
power generated by the induction generator is
increased by using the transformer-type SFCL. Fig. 12
shows the total reactive powerexchangedbetweenthe
induction generator and the grid. After the fault has
cleared (at t = 10.2 s), the absorbing reactive power
from the grid is significantly reduced. However, the
reactive power absorbedby the induction generator is
reduced, in case B. Figures 13 and 14 show the rotor
speed of the induction generator, and the electrical
torque, respectively. As shown in Fig. 13,thegenerator
rotor-speed swing is reduced in case B. These results
show that transformer-type SFCL can provide an
effective damping to the post-fault oscillations of the
induction generator. As shown in Fig. 14, the variation
of the electrical torque is reduced in case B. Because
the transformer-type SFCL in prevents an
instantaneous voltage sag during fault. The
transformer-type SFCL is very effective insuppressing
the variations of the electrical torque during fault, but
it results in swings after fault clearing.
Fig. 15 shows the rotor current of induction generator.
In both figures, the amplitude of rotor currents is
reduced in case B. However, the rotor current
transients are significantly reduced in faultinstantand
after fault clearing.
Fig. 10: Effect of transformer-type SFCL on PCC voltage

Fig. 11: Active power of induction generator during fault
Fig. 12: Reactive power of induction generator during
fault
Fig. 13: Rotor speed of induction generator during fault
Fig. 14: Electrical torque of induction generator during
fault
Fig. 15: Electrical torque of induction generator during
fault
6. CONCLUSION
In this paper, the effect of the transformer-type SFCL
in transient performance of fixed speed turbines has
been studied based simulation by PSCAD/EMTDC.
The simulation results show that the transformer -
type SFCL not only limits the fault current but also
suppresses the voltage drop and improves generator
stability. Also, the oscillation of active and reactive
powers, electrical torque and stator and rotor
currents are reduced effectively during fault.

Appendix
Table 1: Parameters of test system
Parameters Value
grid
Supply 20 kV
Frequency 50Hz
Step down
transformer
.69kV/20
kV
line
R 0.1(Ω/km)
X 0.2(Ω/km)
Length of
Line1
20 km
Length of
Line2
20 km
Induction Generator
Power 1MW
Voltage 690 V
Frequency 50 Hz
Number of
poles
4
Stator
resistance
0. 00577 Ω
Stator
reactance
0.0782 Ω
Rotor
resistance
0. 0161 Ω
Rotor
reactance
0.1021 Ω
Magnetizing
reactance
2.434 Ω
FCL SC resistance 10 Ω
REFERENCES
[1] A. Ghasemkhani, H. Monsef, A. Rahimi-Kian, and A.
Anvari- Moghaddam, “Optimal Design of a Wide Area
Measurement System for Improvement of Power
Network Monitoring Using a Dynamic Multi Objective
Shortest Path Algorithm,” IEEE Syst. J., vol. PP, no. 99,
pp. 1–12, 2015.
[2] A. Ghasemkhani, A. Anvari-Moghaddam, J. M.
Guerrero, and B. Bak-Jensen, “An Efficient
Multi-objective Approach for Designing of
Communication Interfaces in Smart Grids,”
Proceedings of IEEE PES Innovative Smart Grid
Technologies, Ljubljana, Slovenia (ISGT
Europe 2016), Oct. 2016.
[3] L. A. Duffaut Espinosa, M. Almassalkhi, P. Hines, S.
Heydari, and J. Frolik, “Towards a Macromodel for
Packetized Energy Management of Resistive Water
Heaters,” in Conference on Information Sciences and
Systems, Mar. 2017.
[4] F. Farmani, M. Parvizimosaed,H.Monsef,A.Rahimi-
Kian, A conceptual model of a smart energy
management system for a residential building
equipped withCCHPsystem,InInternationalJournalof
Electrical Power & Energy Systems, Volume 95, 2018,
Pages 523-536.
[5] M. Parvizimosaed, F.Farmani,H.Monsef,A.Rahimi-
Kian, A multi-stage Smart Energy ManagementSystem
under multiple uncertainties: A data mining approach,
In Renewable Energy, Volume 102, Part A, 2017, Pages
178-189.
[6] Parvizimosaed M, Farmani F, Anvari-Moghaddam
A. Optimal energy management of a micro-grid with
renewable energy resources and demand response. J
Renew Sustain Energy 2013;5:053148.
[7] Gharghabi, S., Azari, B., Shamshirdar, F. and
Safabakhsh, R., “Improving person recognition by
weight adaptationofsoftbiometrics,”In Computerand
Knowledge Engineering (ICCKE), 2016 6th
International Conference on(pp. 36-40). IEEE.
[8] Gharghabi, S. and Safabakhsh, R., “Person
recognition based on face and body information for
domesticservicerobots,”In RoboticsandMechatronics
(ICROM), 2015 3rd RSI International Conference
on (pp. 265-270). IEEE.
[9] Andani, M.T. and Ramezani, Z., 2017. Robust
Control of a Spherical Mobile Robot.
[10] Pourseif, T., Andani, M.T., Ramezani, Z. and
Pourgholi, M., 2017. Model ReferenceAdaptiveControl
for Robot Tracking Problem: Design & Performance
Analysis. International Journal of Control Science and
Engineering, 7(1), pp.18-23.
[11] S. Aznavi, P. Fajri, M. Benidris and B. Falahati
“Hierarchical Droop Controlled Frequency
Optimization and Energy Management of a Grid-
Connected Microgrid,” presented at 2017 IEEE
Conference on Technologies for Sustainability,
(SusTech), Phoenix, AZ, 2017.
[12] Yousefpour, Kamran. "Placement of Dispersed
Generation with the Purpose of Losses Reduction and
Voltage Profile Improvement in DistributionNetworks
Using ParticleSwarmOptimizationAlgorithm."Journal
of World’s ElectricalEngineeringandTechnology2322
(2014): 5114.
[13] Yousefpour,Kamran,SeyyedJavadHosseiniMolla,
and Seyyed Mehdi Hosseini. "A Dynamic Approach for

Distribution System Planning Using Particle Swarm
Optimization." International JournalofControlScience
and Engineering 5.1 (2015): 10-17.
[14] Amini, Mahraz, and Mads Almassalkhi.
"Investigating delays in frequency-dependent load
control." Innovative Smart Grid Technologies-Asia
(ISGT-Asia), 2016 IEEE. IEEE, 2016.
[15] Jafarishiadeh, Seyyedmahdi, and Mahraz Amini.
"Design and comparison of axial-flux PM BLDC motors
for direct drive electric vehicles: conventional or
similar slot and pole combination." International
Journal of Engineering Innovations and Research 6.1
(2017): 15.
[16] H. Pourgharibshahi, M. Abdolzadeh, and R.
Fadaeinedjad, "Verification of computationaloptimum
Tilt angles of a photovoltaic module using an
experimental photovoltaic system," Environmental
Progress & Sustainable Energy, vol.34,no.4,pp.1156-
1165, 2015.
[17] A. Rouholamini, H. Pourgharibshahi, R.
Fadaeinedjad, and M. Abdolzadeh, "Temperature of a
photovoltaic module under the influence of different
environmentalconditions–experimentalinvestigation,"
International Journal of Ambient Energy, vol. 37, no. 3,
pp. 266-272, 2016.
[18] S.M.M. H.N, S. Heydari, H. Mirsaeedi, A.
Fereidunian,A.R.Kian,”Optimallyoperatingmicrogrids
in the presence of electric vehicles and renewable
energy resources,” Smart Grid Conference (SGC), Iran,
Dec., 2015.
[19] Imani, SM Hossein, S. Asghari, and M. T. Ameli.
"Considering the load uncertainty for solving security
constrained unit commitment problem in presence of
plug-in electric vehicle." Electrical Engineering(ICEE),
2014 22nd Iranian Conference on. IEEE, 2014.
[20] Imani, M. Hosseini, Payam Niknejad, and M. R.
Barzegaran. "The impact of customers’ participation
level and various incentive values on implementing
emergency demand response program in microgrid
operation." International Journal of ElectricalPower&
Energy Systems 96 (2018): 114-125.
[21] F. Rahmani, F. Razaghian, and A. Kashaninia,
"Novel Approach to Design of a Class-EJ Power
Amplifier Using High Power Technology," World
Academy of Science, Engineering and Technology,
InternationalJournalofElectrical,Computer,Energetic,
Electronic and Communication Engineering, vol. 9, pp.
541-546, 2015.
[22] F. Rahmani, F. Razaghian,andA.Kashaninia,"High
Power Two-Stage Class-AB/J Power Amplifier with
High Gain and Efficiency," Journal of Academic and
Applied Studies (JAAS), vol. 4, pp. 56-68, 2014.
[23] P. Niknejad, T. Agarwal, andM.Barzegaran,"Using
gallium nitride DC-DC converter for speed control of
BLDC motor," in Electric Machines and Drives
Conference (IEMDC), 2017 IEEE International, 2017,
pp. 1-6.
[24] T. Agarwal, D. Kumar, and N. R. Prakash,
"Prolonging network lifetime using ant colony
optimization algorithmonLEACHprotocolforwireless
sensor networks," Recent Trends in Networks and
Communications, pp. 634-641, 2010.
[25] Parvizimosaed M, Farmani F, Rahimi-Kian A,
Monsef H. A multi-objective optimization for energy
management in a renewable micro-grid system: a data
mining approach. J Renew Sustain Energy
2014;6:023127.
[26] A. Ameli, M. Farrokhifard, A. Shahsavari, A.
Ahmadifar and H. A. Shayanfar, "Multi-objective DG
planning considering operational and economic
viewpoints," 2013 13th International Conference on
Environment and Electrical Engineering (EEEIC),
Wroclaw, 2013, pp. 104-109.
[27] A. Ameli, A. Ahmadifar, M. H. Shariatkhah, M.
Vakilian, and M. R. Haghifam. "A dynamic method for
feeder reconfiguration and capacitor switching in
smart distribution systems." International Journal of
Electrical Power & Energy Systems, vol. 85, pp. 200-
211, 2017.
[28] D. Gautam, V. Vittal, and T. Harbour, "Impact of
increased penetration of DFIG-based wind turbine
generators on transient and small signal stability of
powersystems,"PowerSystems,IEEETransactionson,
vol. 24, pp. 1426-1434, 2009.
[29] J. M. Rodríguez, J. L. Fernández, D. Beato, R. Iturbe,
J. Usaola, P. Ledesma, et al., "Incidence on power
system dynamicsofhighpenetrationoffixedspeedand
doubly fed wind energy systems: study of the Spanish
case," Power Systems, IEEE Transactions on, vol. 17,
pp. 1089-1095, 2002.
[30] W.-J. Park, B. C. Sung, and J.-W. Park, "The effect of
SFCL on electric power grid with wind-turbine

generation system," Applied Superconductivity, IEEE
Transactions on, vol. 20, pp. 1177-1181, 2010.
[31] CIGRE WG A3.10: “Fault Current Limiters in High
Electrical Medium and Voltage Systems”, CIGRE
Technical Brochure, No.239, 2003.
[32] CIGRE WG A3.10: “Fault Current Limiters Report
on the Activities of CIGRE WG 3.16”, CIGRE Technical
Brochure, 2006.
[33] M. Firouzi, G. Gharehpetian, and M. Pishvaei, "A
dual-functional bridge type FCL to restore PCC
voltage," International Journal of Electrical Power &
Energy Systems, vol. 46, pp. 49-55, 2013.
[34] H. G. Sarmiento, R. Castellanos, G. Pampin, C.
Tovar, and J. Naude, "An example in controlling short
circuit levels in a large metropolitan area," in Power
EngineeringSocietyGeneralMeeting,2003,IEEE,2003.
[35] S.-Y. Kim, J.-O. Kim, I.-S. Bae, and J.-M. Cha,
"Distribution reliability evaluation affected by
superconductingfaultcurrentlimiter,"inTransmission
and Distribution Conference and Exposition: Latin
America (T&D-LA),2010IEEE/PES,2010,pp.398-402.
[36] S. M. R. Tousi and S. Aznavi, “Performance
optimization of a STATCOM based on cascaded multi-
level converter topology using multi-objective Genetic
Algorithm,”inElectricalEngineering(ICEE),201523rd
Iranian Conference on, 2015, pp. 1688–1693.
[37] Babaei, M., Jafari-Marandi, R., Abdelwahed, S. and
Smith, B., 2017, August. Application of STATCOM for
MVDC shipboard power system. In Electric Ship
Technologies Symposium (ESTS), 2017 IEEE (pp. 142-
147). IEEE.
[38] Babaei, M., Jafari-Marandi, R., Abdelwahed, S. and
Smith,B.,2017,February.AsimulatedAnnealing-based
optimal design of STATCOM under unbalanced
conditions and faults. In PowerandEnergyConference
at Illinois (PECI), 2017 IEEE(pp. 1-5). IEEE.
[39] T. Kataoka and H. Yamaguchi, "Comparativestudy
of transformer-type superconducting fault current
limiters considering magnetic saturation of iron core,"
Magnetics, IEEE Transactions on, vol. 42, pp. 3386-
3388, 2006.
[40] Rostaghi-Chalaki, Mojtaba, A. Shayegani-Akmal,
and H. Mohseni. "HARMONIC ANALYSIS OF LEAKAGE
CURRENT OF SILICON RUBBER INSULATORS IN
CLEAN-FOG AND SALT-FOG." 18th International
Symposium on High Voltage Engineering. 2013.
[41] Rostaghi-Chalaki, Mojtaba, A. Shayegani-Akmal,
and H. Mohseni. "A STUDY ON THE RELATION
BETWEEN LEAKAGE CURRENT AND SPECIFIC
CREEPAGEDISTANCE." 18thInternationalSymposium
on High Voltage Engineering (ISH 2013). 2013.
[42] Rahimnejad, A., and M. Mirzaie. "Optimal corona
ring selection for 230 kV ceramic I-string insulator
using 3D simulation." InternationalJournalofScientific
& Engineering Research 3.7 (2012): 1-6.
[43] Akbari, Ebrahim, Mohammad Mirzaie, Abolfazl
Rahimnejad, andMohammadBagherAsadpoor."Finite
Element Analysis of Disc Insulator Type and Corona
Ring Effect on Electric Field Distribution over 230-kV
Insulator Strings." InternationalJournalofEngineering
& Technology 1, no. 4 (2012): 407-419.
[44] H. Gaztanaga, I. Etxeberria-Otadui, D. Ocnasu, and
S. Bacha, "Real-time analysis of the transient response
improvement of fixed-speed wind farms by using a
reduced-scale STATCOM prototype," Power Systems,
IEEE Transactions on, vol. 22, pp. 658-666, 2007.
[45] A. Murdoch, J. Winkelman, S. Javid, and R. Barton,
"Control design and performance analysis of a 6 MW
wind turbine-generator," Power Apparatus and
Systems, IEEE Transactions on, pp. 1340-1347, 1983.
[46] P. Anderson and A. Bose, "Stability simulation of
wind turbine systems," Power ApparatusandSystems,
IEEE transactions on, pp. 3791-3795, 1983.
[47] B. Adkins and R. G. Harley, The general theory of
alternating current machines: Springer, 1975.
[48] A. Foroush Bastani, Z. Ahmadi, D. Damircheli, A
Radial basis collocation method for pricing American
options under regime-switching jump-diffusion
models, Appl. Numer. Math. 65, 79–90, 2013.
[49] A. Foroush Bastani, D. Damircheli An adaptive
algorithm for solving stochastic multi-point boundary
value problems, Numerical Algorithms 74 (4), 1119-
1143, 2016.

Improvement Transient Stability of Fixed Speed Wind Energy Conversion System by using Transformer-Type Superconducting Fault Current Limiter

More Related Content

What's hot (20)

Similar to Improvement Transient Stability of Fixed Speed Wind Energy Conversion System by using Transformer-Type Superconducting Fault Current Limiter (20)

More from IRJET Journal (20)

Recently uploaded (20)

Improvement Transient Stability of Fixed Speed Wind Energy Conversion System by using Transformer-Type Superconducting Fault Current Limiter