Review on stability analysis of grid connected wind power generating system1

International Journal of Electrical and Electronics Engineering Research and Development (IJEEERD)
Electrical and Electronics Engineering Research
ISSN 2248-9282 (Print), ISSN ISSN 2248 – 9282(Print)
ISSN 2248 – 9290(Online), Volume 3, Number 1
IJEEERD
and Development (IJEEERD), 2248-9290 (Online) Volume 3, Number 1, Jan-March (2013)

Jan - March (2013), pp. 01-33
© PRJ Publication, http://www.prjpublication.com/IJEERD.asp
© PRJ PUBLICATION

REVIEW ON STABILITY ANALYSIS OF GRID CONNECTED
WIND POWER GENERATING SYSTEM

M.K. Deshmukh, C. Balakrishna Moorthy
Department of EEE and Instrumentation,
BITS, Pilani-K.K. Birla Goa Campus, Zuarinagar,
Goa 403726, India.

ABSTRACT

Wind power technology has been developing widely in recent years. Several research fields
in power systems such as prediction of wind speed, wind generator system modeling, system
stability and control of wind energy conversion system are emphasized further with the
consideration of wind power. With increasing penetration level in power system, the issue
concerning the influence of wind power on power system stability has arisen the interests of
researchers. This paper reviews various models of generators for studies of stability of power
systems and then analysis, effects and enhancement of power system stability of grid
connected wind power system.
Keywords: Wind power, doubly fed induction generator, small signal stability, transient
stability and dynamic stability.
I. INTRODUTION

Growing environmental concerns and attempts to reduce dependency on fossil fuel resources
are bringing renewable energy resources to the mainstream of the electric power sector.
Among the various renewable resources, wind power is assumed to have the most favorable
technical and economical prospects. In the last five years, the world wind turbine market has
been growing at over 30% a year and wind power is playing an increasingly important role in
electricity generation. By 2020, wind power would account for more than 12% of the world's
total installed capacity.
When deployed in small scale, the impact of wind turbine generators on power system
stability is minimal. When the penetration level increases, the dynamic performance of the
power system can be affected. Among the several wind generation technologies, variable
speed wind turbines utilizing doubly fed induction generators (DFIGs) are gaining
prominence in the power industry. DFIG has been popular among various other techniques of
wind power generation, because of its higher energy transfer capability, low investment, and
1

ISSN 2248-9282 (Print), ISSN 2248-9290 (Online) Volume 3, Number 1, Jan-March (2013)

flexible control. The DFIG is different from the conventional induction generator in a
way that it employs a series voltage-source converter to feed the wound rotor. The
feedback converters consist of a rotor-side converter (RSC) and a grid side Converter
(GSC). The control capability of these converters gives DFIG an additional advantage
of flexible control and stability over other induction generators. A detailed design and
a full stability analysis are necessary for the DFIG before connected to the grid. Also
simulation is one of the most important points for system modeling.

With increasing penetration level in power system, the issue concerning the
influence of wind power on power system stability has arisen the interests of
researchers. Such influence can occurs in two ways: it can be caused by the
uncertainty of wind energy, or a disturbance or faults on grids influence the wind plant
first, then the instability of wind turbines affect the grid significantly. With the
increased number of wind farms in operation, the system experiences a change in
dynamic characteristics. In case of DFIGs, generator load disturbances also give rise
to variations in the speed and the position of the rotor. However, due to the
asynchronous operation involved, the position of the rotor flux vector is not dependent
on the physical position of the rotor and the synchronizing torque angle characteristic
does not exist. In the event of grid disturbances due to grid faults, an energy storage
system or a control device for a large-scale high-capacity power generation system is
generally required to compensate fluctuating components when connecting to a power
grid.

Small signal stability analysis is carried out based on the system nonlinear
equations, describing the dynamic behavior of the system, linearized around a chosen
operating point. Transient stability is the ability of a power system to maintain
synchronism when subjected to a large disturbance. The severe disturbances include
equipment outages, load changes or faults that result in large excursion of generator
rotor angles. The resulting system response is influenced by the nonlinear power-angle
relationship. The time frame of interest in transient stability studies is usually 3–5 s
following the disturbance. The duration may extend up to 10–20 s for a very large
system with dominant inter-area swings.

This paper provides review on various models of induction generators for wind
energy conversion system and then analysis, effects and enhancement of stability of
grid connected wind power system. The rest of the paper is organized in the following
sections. Section II gives the details of models of the DFIG and literature survey of the
DFIG models for power system stability studies. In section III, analysis, effect and
enhancement of stability of wind energy conversion system. Conclusions are given in
section IV.

II. DOUBLY FED INDUCTION MOTOR MODELLING FOR STABILITY
ANALYSIS

A wind turbine (WT) consists of turbine blades, rotor, generator, nacelle (gearbox
and generator drive), shaft, drive or coupling device, converter and control system.
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9282 2248 March

Wind turbines can be classified as fixed speed wind turbine and variable speed wind turbine.
Fixed speed turbine can only operate at a fixed speed and induction machine is used as
generator. Variable speed wind turbine use double fed induction machine (DFIG) or
permanent magnet synchronous machine (PMSM) as a generator. In brief, Wind turbine
model can be mainly divided into three parts namely mechanical drive and control, generator,
ded
converter and control system. The model of the generator is most important.
he
In this study, DFIG model is considered. It consists of a wound rotor asynchronous
generator, whose stator windings are directly connected to the grid, while the rotor windings
dings
are interfaced with a back-to-back variable frequency voltage source converter. This unit
back
allows a variable speed operation with a wide range from sub-synchronous to su
synchronous super-
synchronous speed. Fig. 1 reports the basic configuration of a DFIG wind turbine. The use of
a back-to-back power converter on the rotor side allows to decouple the control action on the
back
DFIG. In such a way, the rotor side converter is used to optimize the power gener
generation of the
DFIG and improve the stability, while the grid side converter ensures a quite constant voltage
on the DC link with a desired power factor. Grid side and rotor side converters are modelled
as four quadrant Pulse Width Modulation (PWM) AC/DC and DC/AC inverters. By
idth
adjustment of the switching of the Insulated Gate Bipolar Transistors (IGBT) in both
converters, the power flow between the rotor circuit and the supply can be controlled both in
magnitude and in direction. This is effectively the same as connecting a controllable voltage
source to the rotor circuit. The DFIG can be regarded as a traditional induction generator with
a nonzero rotor voltage.

FIG: 1 CONFIGURATION OF A DFIG WIND TURBINE [10]

FIG: 2 EQUIVALENT CIRCUIT OF DFIG

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Associated mathematical equations of the dfig are given below.

Stator voltage
vୢୱ ൌ rୱ iୢୱ ൅ ωୱ ψ୯ୱ----------------1
v୯ୱ ൌ rୱ i୯ୱ െ ωୱ ψ ----------------2
ୢୱ
Rotor voltage
ୢψౚ౨
vୢ୰ ൌ r୰ iୢ୰ െ sωୱ ψ୯୰ ൅ -----3
ୢ୲
ୢψ౧౨
v୯୰ ൌ r୰ i୯୰ ൅ sωୱ ψ ൅ ୢ୲
-----4
ୢ୰
Flux linkage
ψୢୱ ൌ െLୱୱ iୢୱ ൅ L୫ iୢ୰ -----------5
ψ୯ୱ ൌ െLୱୱ i୯ୱ ൅ L୫ i୯୰ -----------6
ψୢ୰ ൌ െL୫ iୢୱ ൅ L୰୰ iୢ୰ -----------7
ψ୯୰ ൌ െL୫ i୯ୱ ൅ L୰୰ i୯୰ -----------8
Electromagnetic torque
Tୣ୫ ൌ ψ୯୰ iୢ୰ െ ψୢ୰ i୯୰ -----------9

Kazachkov et al [2] reviewed and discussed the most significant characteristics and
models of fixed and variable speed wind turbine which are developed in the PSSE (Power
System Simulator for Engineering) program. Also detailed models such as air dynamical
mechanical and electrical factors have been reviewed and have been constructed in
PSCAD/EMTDC. Symmetrical fault is considered. These detailed simulations helpful to
understand the functionality of the controls and their interaction and were critical in terms of
working out the approach to reducing the order of models for stability studies. It is observed
that for the bandwidth of transient stability, the PWM control can be considered as
instantaneously generating rotor current components or even electrical power and reactive
power as inputs for a machine model. Suggested that these models will allow the wind farms
to be represented in the load flow and stability analysis involved in the planning and
operation of power systems.

Pablo Ledesma et al [3] proposed a model of the doubly fed induction generator
(DFIG) suitable for transient stability studies. The proposed model is based on two main
simplifications. The first one assumes that the EM transients in the stator and in the branch
between the inverters and the grid can be neglected. The second simplification assumes that
the current control may be considered instantaneous neglecting the dynamics in the current
control loops. MATLAB software is used for the study. The Power System Toolbox uses a
predictor-corrector numerical integration algorithm. The iterative process used to solve the
DFIG model has converged satisfactorily in all of the simulated cases. The small number of
iteration steps in the simulated cases indicates that the DFIG model does not consume an
excessive processing time. Further, the integration step used in the simulations is a typical
one in transient stability simulations (10 ms), because the DFIG model does not impose a
small integration step as there are not small time constants. This is a great advantage
compared to a detailed model, including the current control systems and the inverter’s
operation, which need smaller integration steps (on the order of 1 ms).
Istvan Erlich et al [4] analyzed modelling of the doubly-fed induction generator
(DFIG) and the corresponding converter for stability studies. To enable efficient
computation, a reduced-order DFIG model is developed that restricts the calculation to the

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fundamental frequency component. However, the model enhancement introduced in this
paper allows the consideration of the alternating components of the rotor current as well,
which is necessary for triggering the crowbar operation. Suitable models are presented for the
rotor and grid side converters as well as the dc-link, taking into account all four possible
operating modes. The proposed model for speed and pitch angle control can be used when
wind and rotor speed variations are significant. Since the reduced-order model does not
consider the dc-components of the stator current and thus the corresponding alternating rotor
currents, it is not suitable for triggering crowbar switching. For this purpose, a model
enhancement is proposed in this paper that allows using the ROM further on, but an
additional model part is activated when necessary to superimpose the dc-components on the
simulation results. The presented model is suitable for power system simulation studies.
Yazhou et al [5] developed DFIG wind turbine model in which the power converter is
simulated as a controlled voltage source, regulating the rotor current to meet the command of
real and reactive power production. This model has the form of traditional generator model
and hence is easy to integrate into the power system simulation tool such as PSS/E. The
model performance and accuracy was also compared with the detailed model developed by
DIgSILENT. In this paper, a controllable voltage source in the rotor circuit was used to
simulate the power converter. Such simplifications allows for reduction of the model order
whilst retaining the capability of observing principle features of the converter such as the
maximum current levels. Such capability is important for assessing criteria such as fault-ride-
through performance. The response of the wind turbine to a step increase in the wind speed
and to an electrical bus three phase fault was studied. However, due to the assumption
adopted, the model cannot be used to study the internal dynamics of the power converter.
Andreas et al [6] presents an alternative way of obtaining the third order model for the
doubly-fed induction machine model and introduced the possibility of modeling voltage
sources in the rotor circuit, which can be very useful when simulating some generating
schemes, such as variable speed asynchronous wind turbines. The purpose of this paper is to
obtain a set of more simplified equations than those generally used. A model is presented in
order to make it easier to dynamically simulate doubly-fed induction machines. Simulations
are presented to prove that the model is adequate from the point of view of steady-state. The
advantage of the model is that it allows one to deal with the machine with only one
differential equation in the electrical part.
Kretschmann et al [7] presents an extension of [m3] which accounts for the neglected
stator DC-components without increasing the modeling and simulation effort considerably.
Thus the converter DC-circuit can be considered to represent the triggering of the crowbar
firing more realistically to the stability model of the doubly fed induction generator (DFIG)
used for wind turbines. With the proposed extension it is possible to consider the alternating
components of the rotor current and thus the variation of the converter DC-link voltage. With
realistic DC-voltage responses, a more accurate modeling of crowbar switching will be
possible. The paper also presents suitable models for rotor and line side converters, as well as
for the DC link. Moreover, the paper provides simulation results not only for model
verification but also for demonstrating the behavior of the DFIG and the corresponding
control system during fault. Also shows the dynamic performance of a typical wind energy
DFIG system's response to a 3-phase grid fault. The proposed model extension allows the
simulation of the true sequence of the DFIG-response to grid faults by using basically the
reduced order models (stability model) and the corresponding simulation algorithm. The grid
is modeled in this approach by algebraic equations, so that the simulation performance is
much better than the alternative instantaneous value calculation based on full order models
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for both DFIG and grid as well. Therefore, it is essential to consider the true control sequence
and crowbar switching of DFIG-based wind turbines when simulating power system dynamic
behavior. Moreover, this paper provides simulation results suited not only for model
verification but also for demonstrating the behavior of the DFIG and the corresponding
control system during fault.
Samuel Neto et al [8] developed a reduced order model for grid connected wind turbines
with doubly fed induction generators. The model is based on the field oriented control of the
generator, considering that the rotor is fed by an ideal current regulated voltage source. This
assumption makes the order if the induction machine model to be reduced to three but still
allows representing with good accuracy. A simplified model is presented in order to reduce
the computational effort of simulating grid connected wind farms driven by doubly fed
induction generators (DFIG) in ATP, which is a software free and one of the most used
programs around the world for power system transient studies. Some considerations are
presented to show how the time step for the simulation can be increased with the reduced
models. Simulation results are used to compare the dynamic responses of complete and
reduced models. In the reduced model presented here, the generator rotor current components
and also the GSC output filter current components are considered to be ideally imposed. This
assumption greatly simplifies the system model, since the induction machine model has its
order reduced to three due to the previous assumption of the rotor currents imposition. The
simulation results showed that that proposed reduced model is adequate for evaluating the
effects of connecting wind farms with doubly fed induction generators to large power
systems using ATP.
Janaka et al [9] derived a dynamic model which can be used to simulate the DFIG wind
turbine using a single-cage and double-cage representation of the generator rotor, as well as a
representation of its control and protection circuits. The model is suitable for use in transient
stability programs that can be used to investigate large power systems. The behavior of a
wind farm and the network under various system disturbances was studied using this dynamic
model. The influence of the DFIG control on the stability of the wind farm was also
investigated by considering different control gains and by applying network voltage control
through both stator side and rotor side converters. The generalized reduced order machine
model was developed based on the following conditions and assumptions. a) The stator
current was assumed positive when flowing toward the machine. b) The equations were
derived in the synchronous reference frame using direct and quadrature axis representation. c)
The -axis was assumed to be 90 ahead of the -axis in the direction of rotation. d) The
component of the stator voltage used within the model is chosen to be equal to the real part of
the generator busbar voltage obtained from the load flow solution that is used to initialize the
model. e) The dc component of the stator transient current was ignored, permitting
representation of only fundamental frequency components.f) The higher order harmonic
components in the rotor injected voltages are neglected. In order to investigate the effect of
various control approaches to the behavior of the machine and the network after the fault was
cleared, the following three cases were simulated using the DFIG double-cage model. In all
three cases the proportional gain of the controller was set low . a) Compensation for the
generator magnetising reactive power (No load PFC) was applied. b) Compensation for the
generator magnetising reactive power (No load PFC) and terminal VC were applied through
.c) Compensation for the generator magnetizing reactive power (no load PFC) was applied on
and terminal VC on. The models that have been developed are suitable for including in large
power system transient stability programs.

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Mohamed et al [10] analyzed the doubly fed induction generator (DFIG) for wind
energy conversion system. In order to control the power flowing between the stator of (DFlG)
and the grid, a control law is synthesized using PI controllers. In this study, the control
strategy of power flow exchanged between the stator of (DFIG) and the grid are considered.
After modeling the (DFIG), active and reactive powers are controlled with Integral-
Proportional (PI) controller. The performances of the controller are then studied in terms of
reference tracking and sensitivity to perturbations. Two types of regulators are studied and
compared: hysteresis and Integral-Proportional (PI) controllers. The proposed system has
been simulated using Matlab simulink to validate all the control strategy and then evaluate
performance of the PI controller. Stator flux orientation control (SFOC ) technique have been
applied in order to control stator active and reactive power exchanged between the grid and
the doubly fed induction generator (DFIG) for wind energy conversion systems. A
mathematical model of the (DFIG) is established and a synthesis of the PI controller. The
performances of this controller are compared to a hysteresis controller in terms of power
reference tracking and sensitivity to perturbation. The better results are obtained with PI
controller.
Andreas et al [11] analyzed the fault response of a DFIG wind turbine system and to
verify simulations with experimental results. Also studied how a reduced-order (second-
order) model manages to predict the response of the DFIG system. In this paper, simulations
and experimental verification of the dynamic response to voltage sags of a DFIG wind
turbine were presented. Simulations were carried out using a full-order model and with a
reduced-order model. Both models produced acceptable results. Perfect results were not
expected, since simulations were carried out on a fictitious DFIG wind turbine. The response
to symmetrical as well as unsymmetrical voltage sags was verified. The reduced-order model
used in this paper includes the flux dynamics, which is not the case for the reduced-order
models found in the literature. In this paper, the rotor current was put to its reference value,
and thereby, it was possible to preserve the main dynamical behavior of the DFIG that
corresponds to the flux dynamics.

EI-Sattar et al [12] developed a variable speed wind turbine model with its proposed
control system for studying the operation of controllers at different wind speeds and flow of
rotor power. The overall model has been developed using Matlab/Simulink.Four controllers
are used namely, pitch angle, active power, reactive power and speed controllers. A dynamic
model of the DFIG has been derived to develop a vector controller to decouple dynamically
active and reactive power control.
Xingjia et al [13] sets up a complete DFIG dynamic model, including the generator
model, converter model and converter protection, grid model etc. to study the transient
characters. The method of sensorless direct torque control (DTC) and model referencing
adaptive system (MRAS) method were used in the converter control. In this paper, the
dynamic model of the DFIG, the control model of rotor side converter and stator side
converter for DFIG will be set up respectively, as well as the protection of the converter.
Then a complete model of DFIG will be founded in PSCAD platform. So here the doubly fed
induction generator based on variable-speed wind turbines use dynamic fifth-order model of
induction machine in a two-axis d-q reference frame rotating at synchronous speed. The
simulation of the transient analysis is done when the power system take the phase ground
fault. The result of the simulation indicate that the DTC control and MRAC principle used in
the DFIG can improve the power system fault ride-through capacity ,that is to say when the
system fault is phase ground in a little time ,the DFIG can implement the running of

7


disconnected network. And this give the theory base for future study the ride through the
network fault to wind farm.
Luis et al [14] proposed a new equivalent model of wind farms with doubly fed
induction generator wind turbines to represent the collective response of the wind farm by
one single equivalent wind turbine, even although the aggregated wind turbines operate
receiving different incoming winds. The effectiveness of the equivalent model to represent
the collective response of the wind farm is demonstrated by comparing the simulation results
of equivalent and complete models both during normal operation and grid disturbances. In
this paper, a reduced model of a DFIG wind turbine has been implemented by means of the
third-order model of induction generator and modelling the power converter. as two
controlled sources, as usual for power system simulations. The modelling and simulation of
the complete model of a wind farm with high number of wind turbines suppose the use of a
high-order model and a long computation time if all the wind turbines are modelled. In order
to reduce the model order and computation time, equivalent models have been developed to
represent the collective response of the wind farm at point common coupling (PCC) to grid.
These wind farm models have been implemented and simulated by using MATLAB/
Simulink.
Milton et al [15] presented an integrated dynamic model of a DFIG-based WECS.
The mathematical models of wind, rotor and gear and induction generator are simulated and
validated using realistic data. The proposed model is also applied for choosing an appropriate
WECS for any given wind regime. This paper presents simulation of mathematical models
for wind, rotor, gear and doubly-fed induction generator using MATLAB Simulink. The
model will be useful for wind energy developers in proper designing of wind energy
conversion systems at the time of planning wind power stations.
Miguel et al [16] analysed the simplest representation of generators on wind turbine
modelling, giving the accuracy required in power system disturbance studies.The order of the
generator model and the numerical integration methods employed are compared.Since time
simulation is a significant parameter, large power systems require simulating with the
simplest possible wind generator models. This paper presents a comparative study
considering the order of the model and the numerical integration methods used. Furthermore,
a new equivalent model is proposed in order to ameliorate the accuracy for representing the
dynamic response of wind farm on power system simulations with an important reduction on
simulation time. In order to compare the numerical integration methods used in the
simulation, the software packages PSS/E and PSCAD/EMTDC are considered. PSS/E uses a
fundamental frequency simulation which is based on the modified explicit Euler method,
whereas PSCAD/EMTDC is instantaneous value simulation software. The fifth-, third- and
first order models have been considered in the PSS/E study. The aggregated wind farm
models allow reducing the computation time more than the order of the generator model
used.
Balasubramaniam et al [17] analyzed the steady state characteristics of a WECS using
doubly fed induction generator (DFIG) using MATLAB. Simulation analysis is performed to
investigate a variety of DFIG characteristics, including torque-speed, real and reactive-power
over speed characteristics. Based on the analysis, the DFIG operating characteristics are
studied. From the simulation analysis it is clear that the DFIG characteristics are affected by
its injected rotor voltage. The simulated stator real power characteristics of the DFIG show
that with increase in the rotor injected voltage, the DFIG real power characteristics shifts
more in to the sub-synchronous speed range and the pushover power of the DFIG rises. It can

8


also be seen that the DFIG rotor power is capacitive when the DFIG operates in the
generating mode under a subsynchronous speed and is inductive otherwise.
Chowdhury et al [18] presented a complete and aggregated wind farm models with
Doubly Fed Induction Generator (DFIG) are presented. Simulations have been carried out for
both models and compared to demonstrate effectiveness of the aggregated model in terms of
accuracy in approximation of the dynamic collective responses at the Point of Common
Connection (PCC) and reduction in simulation computation time. The wind farm models
have been implemented and simulated by using Matlab.The parameters used for comparison
are active and reactive power at the PCC. The simulations have been carried out under two
operating conditions: (1) normal operation and (2) grid disturbance. It is observed that the
proposed simplified aggregated model gives an accurate approximation of the collective
responses at the PCC having minor discrepancies in magnitude with a faster simulation
computation time.
Chitti Babu et al [19] presented the complete modeling and simulation of wind turbine
driven doubly-fed induction generator which feeds ac power to the utility grid. The complete
system is modeled and simulated in the MATLAB Simulink environment in such a way that
it can be suited for modeling of all types of induction generator configurations. The model
makes use of rotor reference frame using dynamic vector approach for machine model can be
simulated as both motoring and generating mode when testing control strategies. Through the
model developed in this paper can be used for simulating all types of induction generator
configurations. The choice of synchronous rotating reference frame makes it particularly
favorable for the simulation of doubly-fed configuration in transient conditions.
Mattia Marinelli et al [20] presented the dynamic behavior of a wind turbine equipped
with a doubly fed induction generator (DFIG) in case of disturbances in the interconnected
grid. A model of a DFIG is presented and adapted for analyzing the response of the wind
generator to voltage control, frequency control, voltage sags and wind variations.
Ekanayake et al [21] investigated the impacts of the DFIG installations on the
operation and control of the power system, accurate models are required. A fifth order and
reduced order (3rd) machine models are described and the control of the wind turbine
discussed. The capability of the DFIG for voltage control (VC) and its performance during a
network fault is also addressed. For detailed representation of fault current contribution, the
5th order model provides better resolution although it must be recognized that the behavior of
the converter control systems is likely to have a dominant effect on fault currents. A three-
phase short circuit on the network close to the generator was investigated. As, expected, the
5th order generator model represented the behavior of the generator in more detail and
included the transient behavior of the stator current. The 3rd order representation gave a
similar mean value of the stator current correctly but did not show any details of the transient.
For classical, phasor domain electro-mechanical dynamic studies of large power systems the
simplicity and reduced computation time of the 3rd order model appears attractive. For more
detailed representations of fault current contribution and investigation of the required ratings
of the converters then the 5th order representation may be preferred. However, other effects,
such as the control system and various limits of the converters as well as the transient
behavior of the generator rotor circuits are also likely to be important in more detailed
studies.
Katherine et al [22] compared the behavior of different order models, for large scale wind
farms comprising doubly fed induction generators (DFIGs). It is also important to have
simple models, not only to reduce computation time, but also to simplify the design of
9


controllers. This article compares the characteristics of different order models for DFIGs and
their responses to control. Eigen value analysis and numerical simulations are used to
compare the characteristics of the different order models. Simulations are performed using
Simpow. Higher order models are often used, but these introduce high frequency dynamics
which are not usually of interest in classical electro-mechanical dynamic studies of large
power systems. the first order model gives almost the same information about the inter-area
oscillations as the third order model does, but does not show the same effect that the
controllers have on the real valued eigenvalues. The first order model is clearly capable of
representing lightly damped oscillatory modes of the system, and may be of interest for
designing non-linear damping controllers because of its simplicity. However, the third order
model may be a more suitable model for analyzing transient stability.
Maider Santos et al[23]presented the simulation results of various dynamic models of a
variable speed doubly fed induction generator (DFIG) wind turbine, the control system is
made up of two control levels developed in MATLAB and PSCAD.The main goal is to
develop and to validate reduced models of wind turbines which are suitable for wind turbine
grid integration studies. To achieve this aim a complete MATLAB Power System Blockset
(PSB) model will be compared with several reduced models. Generator models with and
without flux transient terms have been compared. In the case of the converter, models with
and without PWM have been used. The control system has been modeled with and without
current regulators. The grid has been modeled in the static reference frame. Even thought the
obtained results using PSCAD and MATLAB are very similar it is necessary to emphasize
that PSCAD compiles much better electrical circuits than MATLAB does, what means that
the simulation takes less time. Even so, MATLAB has tools make easier the introduction of
the control systems.
III. STABILITY ANALYSIS, EFFECTS AND ENHANCEMENT
According to the classification of power system stability in reference [1], power system
stability could be categorized into voltage stability, frequency stability and rotor angle
stability. Stability of the system is analyzed for two types of disturbances mainly, small and
great disturbances. Small disturbances occur continually due to small variations on load and
generation. The system must be able to adjust to the changing conditions and operate
satisfactorily, and must also be able to survive numerous disturbances of a severe nature, such
as a short circuit or loss of a large generator. It is classified as small signal stability.

A. SMALL SIGNAL STABILITY

Small signal stability is defined as the capability of a power system to return to a
stable operating point or to the original steady, after the occurrence of a disturbance that leads
to an incremental change in one or more of the state variables of the power system. The
definition of small signal stability refers to the system's response to a small change in one or
more of its state variables. The small signal stability problem normally occurs due to
insufficient damping torque which results in rotor oscillations of increasing amplitude. The
Eigen values of the system matrix characterize the stability of the system. The change in
design and operating condition of the power system is reflected in the Eigen values of the
system state matrix. The effect of the system parameters on the overall system dynamics can
be examined by evaluating the sensitivity of the Eigen values with respect to variations in
system parameters. The variable speed wind turbine generator (WTG) design consisting of
power electronics converter imparts significant effect on the dynamic performance of the
DFIG. The introduction of large amounts of wind generation does have the potential to
change the electromechanical damping performance of the system.
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An approach for computerized formulation of power system linearised state equations
including those of transmission network and the associated apparatus is introduced in [24]. A
small-signal Eigen analysis software tool is developed based on the proposed state space
formulation. The application of the packages is primarily for the analysis of power system
small-signal dynamics in the high-frequency range (above 5 Hz), e.g. interactions among
power electronic devices such as multiple SVCs. An application example of the software tool
has also been reported. A novel method using particle swarm optimization (PSO) is proposed
for optimizing parameters of controllers of a wind turbine (WT) with doubly fed induction
generator (DFIG) in [24]. The implementation of the algorithm for optimizing the controllers’
parameters is described in detail. In the analysis, the generic dynamic model of WT with
DFIG and its associated controllers is presented, and the small signal stability model is
derived. The small signal stability analysis of the WT system with and without controllers has
also been carried out. In addition, using the optimised parameters, the dynamic performance
of WT system can be improved, and therefore the capability of the fault ride through can be
enhanced. Small signal stability analysis considering grid-connected wind farms of doubly-
fed induction generator (DFIG) is addressed in [25]. The power system small signal stability
analysis is then carried out to explore and exploit the essential impacts on the existing power
grid by Eigen value analysis for a specific test system. A simplified and practical DFIG
model is presented with the stator flux-oriented vector control based method utilized to
implement stator active and reactive powers control. The power system small signal stability
analysis is then carried out on IEEE 3-generator-9 bus test system as benchmark to explore
and exploit the impacts on the power grid due to the high penetration of grid-connected wind
farms of DFIG type. The full order model of the DFIG with series grid-side converter is
given in [26]. The stability of this system considering the linearized model is analyzed. This
model is feasible for applications where the grid voltage is unbalanced. The configuration
presented in this paper can be a good alternative to mitigate the effects of voltage unbalance
and stator flux oscillations. The super/subsynchronous operation of the doubly fed induction
generator (DFIG) system is addressed in [27]. The impact of a damping controller on the
different modes of operation for the DFIG-based wind generation system is investigated. The
effectiveness of damping controller under super/subsynchronous modes of operation is also
investigated. This study would help in understanding the interaction of the oscillatory modes
of DFIG-based WT with other components of power systems. This paper [28] investigates
modes of response introduced by wind parks with doubly fed asynchronous generators
(DFAGs) as well as their impact on electromechanical oscillations in interconnected power
systems. The purpose is to further the stability studies referred to above by showing the effect
of system stiffness, as well as some possible interactions (and their causes and remedies)
between DFAG voltage/reactive power control and electromechanical oscillations. A model
of the wind turbine (WT) with direct drive permanent magnet generator (DDPMG) and its
associated controllers is presented in [29]. Small signal stability analysis model is derived
from the model. Dynamic simulations are performed on a single machine infinite bus (SMIB)
system and a four machine system to simulate the dynamics of the WT with DDPMG and to
evaluate the control capability of the proposed controller under the system disturbances. The
simulations were performed to evaluate the control capability of the proposed controller
under the system fault in MATLAB/SIMULINK, and the dynamic responses of the WT with
DDPMG were compared with those of the WT with DFIG to illustrate the impact of the wind
generation with different configurations on the stability of the power systems. The simulation
results have illustrated that in comparison to the WT with DFIG, the WT with DDPMG has
better dynamic responses. The small signal stability of renewable energy based distribution
system is investigated in [30]. The distribution system is fed by synchronous, induction and

11


static generators. Eigen-sensitivity with respect to active power fluctuations is proposed as a
sensitivity parameter to study the impact of penetration. The results show that rotor flux
variables of wind generators participate significantly in the system oscillations. Hybrid
methodology for small signal stability assessment is addressed in [31]. The proposed
methodology is validated against an electromagnetic transient simulation program
(PSCAD/EMTDC) using time responses. The impact of the increased penetration of general
induction generator based WTGs on small signal stability is examined for a single machine
infinite system in [32]. To examine the performance difference of WTGs and the
synchronous generators, wind farm within and without dynamic reactive compensation are
developed. Small signal stability of large scale variable speed wind turbines with doubly fed
induction generator integration is addressed in [33]. In this method, stability analysis is done
by computing Eigen values and right and left eigenvectors of a Jacobian matrix which
obtained from the power flow equations.
B.CONTROL OF DFIG
Dawei Xiang et al [34] analyze the ability of a doubly fed induction generator (DFIG)
in a wind turbine to ride through a grid fault and the limitations to its performance. The
fundamental difficulty for the DFIG in ride-through is the electromotive force (EMF) induced
in the machine rotor during the fault, which depends on the dc and negative sequence
components in the stator-flux linkage and the rotor speed. The investigation develops a
control method to increase the probability of successful grid fault ride-through the current
and voltage capabilities of the rotor-side converter. A time-domain computer simulation
model is developed and laboratory experiments are conducted to verify the model and a
control method is proposed. The performance of fault ride-through control is verified with the
DFIG initially operating with no load. Simulations based on a validated model provide the
feasibility regions, in terms of fault severity and prefault speed, of successful ride through
control for DFIG connected to the grid through a double-circuit network.
Feng Wu et al [35] presented a detailed model of the WT with DFIG and its
associated controllers based on which the small signal stability model is derived. Small signal
stability analysis shows that the DFIG control can significantly improve the stability of WT
system. Applying a set of optimized controller parameters, the stability can be further
enhanced. Dynamic simulations are performed to illustrate the control performance. It has
been recognized that the DFIG controllers have significant effects on the system stability. In
order to address this issue, a dynamic model including the dynamics of converters and
controllers is presented. The rotor side converter controllers aim to control the DFIG active
power output for tracking the input power of the wind turbine, and maintain the terminal
voltage to the reference value. The grid side converter controller aims to maintain the DC link
voltage, and control the terminal reactive power. In this paper, Particle Swarm Optimization
(PSO) algorithm is utilized to optimize the parameters of the DFIG controllers. Simulations,
which were performed in MATLAB/ SIMULINK, aimed to verify the improvement in
stability by the DFIG controllers with the optimized parameters. It can be seen that using the
optimized controller parameters, the dynamics of the WT have been significantly improved.
The oscillation after the disturbance was damped out very quickly. In particular the peak DC
link voltage was reduced noticeably, which is very beneficial to the operation of the fed back
converters.
Ming et al [36] analyzed model of DFIG and developing control strategy for grid-
connected DFIG. In order to study the influence of the grid disturbances on the DFIG, grid
voltage dip and quick frequency change are simulated in MATLAB/Simulink. Control

12


designing methods such as the pole-placement method and internal model control method are
implemented for designing the PI controllers.
Lie Xu et al [37] presented an analysis and control design of a doubly-fed induction
generator (DFIG)-based wind generation system operating under unbalanced network
conditions. A rotor current control strategy based on positive and negative (dq) reference
frames is used to provide precise control of the rotor positive and negative sequence currents.
Simulation results using EMTDC/PSCAD are presented. Methods for providing enhanced
system control and operation for DFIG-based wind turbines during network unbalance i.e.,
power, torque, or current oscillation minimizations, are identified.
Seung-Ho et al [38] investigated the dynamic response of WECS to the events in
power system, an accurate simulation model for DFIG (doubly-fed induction generator)
system is developed using PSCAD/EMTDC and a hardware-in-loop simulator is
implemented. The model consists of wind model, rotor dynamics, wound rotor induction
generator, power electronics converter and control strategies. Control strategies can be
programmed at torque-speed plane as needed and implemented in DSP controlled power
converters. Simulation and experimental results shows smooth change of control modes and
efficient power variables such as the control performances.
Abolfazl et al [39] focused on modeling and controlling of a doubly-fed induction
generator (DFIG). The presented model is developed based on the basic flux linkage, voltage
and torque equations. In order to control the DFIG's active power, a suitable method based on
PSO algorithm has been proposed. The simulation results show that the presented method
using PI controller is a useful way to improve the output power of DFIG.
Yi Wang et al [40] investigate the control of doubly-fed induction generator (DFIG)
based wind farms for compensating voltage unbalance in weak networks. A control strategy
for compensating grid voltage unbalance using DFIG systems is proposed. Various methods
such as the required negative sequence current is solely provided by the DFIG stator through
the RSC, The required negative sequence current is solely provided by the GSC, The required
negative sequence current is provided from both the RSC and GSC. The required negative
sequence currents for the RSC and GSC are for coordinating these two converters and their
impact on system operation are analyzed. The capabilities of the converters with a DFIG
system for negative sequence current compensation are also discussed. The validity of the
proposed control strategy is demonstrated by Matlab/Simulink simulations. With the
proposed strategy, DFIG based wind farms can provide voltage unbalance compensation for
the connected weak grid to improve the performance and stability of the whole wind energy
system.
Lingling et al [41] converted a wound rotor induction motor to a DFIG by injecting a
three-phase voltage to the rotor at various frequencies. The stator is connected to a three-
phase resistance load. Both computer simulation and experiments are performed to
demonstrate the frequency, voltage and power relationships between the rotor and the stator.
Using the relationship between the stator and rotor voltages, a PWM based slip control
scheme together with volts/Hz control for the rotor side converter is developed and the
performance verified in PSIM. The DFIG with the proposed control scheme generates a
constant voltage with constant frequency at the stator. The experiments, simulation and
analysis help to understand DFIG operation and PWM control.
Ghennam et al [42] dealth with the modeling and control of the doubly fed induction
generator based wind conversion system. A model of the DFIG is then detailed in dq
13


reference frame. A decoupled dq control is adopted for both GSC and RSC. For GSC control
algorithm, the q-component of the filter current is used for the DC voltage regulation and the
d-component is devoted for the reactive power regulation. Beside this, for the RSC control
algorithm, the q-component of the rotor current is used for controlling the active power
injected by the DFIG to the grid while the d-component deals with the control of the reactive
power. Both GSC and RSC control algorithms are implemented on a DSPACE board. The
presented experimental results show good performances of the decoupled d-q control.
Milton et al [43] developed a mathematical model of the DFIG in an appropriate d-q
reference frame for simulation purpose. Secondly, the controller is designed to control the
power exchange between the stator of the DFIG and the utility grid network. Two types of
control strategies are considered - PI control and pitch angle (Pitch-to-feather) control. The
respective performances of the two types of controllers are compared in terms of power
reference tracking, response to sudden speed variations, sensitivity to perturbations and
robustness against machine parameters variations. controller are designed based on pole
placement theory.
Wei et al [44] presented and developed two different models in PSCAD/EMTDC to
represent a variable-speed wind turbine equipped with a doubly fed induction generator
(DFIG). One is the most detailed switching-level (SL) model. The other is a simplified
fundamental-frequency (FF) model. The effect of different shaft system representations on
the dynamic behavior of the wind turbine generator (WTG) system and the issue of damping
low-frequency tensional oscillations are investigated. Dynamic and transient simulation
studies are carried out to compare two models with different shaft system representations.
This detailed switching-level (SL) model uses excessive computation time and is unsuitable
for dynamic and transient study of large power systems with a high-level penetration of DFIG
wind turbines. Therefore, the two-mass shaft model should be used for the study of power
system transient dynamics.
Luna et al [45] presents a new VOC [voltage oriented control] strategy able to control
the operation of DFIG with no need of flux position estimation, something that conducts to a
more simple and robust algorithm. In order to evaluate the advantages of this new control
proposal, namely VOC-RRF, their performance will be compared with the response obtained
with a classical VOC algorithm by means of PSCAD/EMTDC simulation models. The
simulation and experimental results have demonstrated that the VOC-RRF can be considered
as a good alternative for the classical VOC-SRF control algorithm as its performance has
been proven to be robust and fast.
Yongfeng et al [46] derived the wind turbine model and the dynamic mathematical
model of DFIG. The control of the rotor current inner loop and the rotating speed outer loop
are designed based on internal model control (IMC) strategies, respectively. A complete
variable speed constant frequency (VSCF) DFIG wind power generation system model is
developed based on PSCAD/EMTDC. The simulation results show that the system has fast
dynamic response under various run conditions and can operate at sub-synchronous speed
and super-synchronous speed.
Hamon et al [47] several computer programs exist to carry out dynamic simulations
and this study will focus on one of them, namely DigDilent Power Factory. It offers two
built-in models of doubly-fed induction generator. A new model has also been developed,
based upon a controllable voltage source. These three models are compared, in terms of
dynamic behavior and simulation time. A third new DFIG model has been created using a
voltage source. The behaviors of the two built-in models and the new model are compared.
14


Two PI controllers are used to control either active and reactive powers or active power and
stator voltage. It is more complicated to use than built-in components but it is more flexible
because it relies on code and can be made to do exactly what the user wishes.
Jiabing Hu et al [48] presented a mathematical model of a doubly fed induction
generator (DFIG) in the positive synchronous reference frame under distorted grid voltage
conditions. The oscillations of the DFIG’s electromagnetic torque and the instantaneous
stator active and reactive powers are fully described when the grid voltage is harmonically
distorted. Four alternative control targets are proposed to improve the system responses
during grid harmonic distortions. A new rotor current control scheme implemented in the
positive synchronous reference frame is developed. The control scheme consists of a
proportional–integral (PI) regulator and a harmonic resonant (R) compensator tuned at six
times the grid frequency. Consequently, the fundamental and the fifth- and seventh-order
components of rotor currents are directly regulated by the PI–R controller without sequential-
component decompositions. The feasibility of the proposed control strategy is validated by
simulation studies on a wind-turbine-driven DFIG system. Compared with the conventional
vector control scheme based on standard PI current controllers, the proposed control scheme
leads to significant elimination of either DFIG power or torque oscillations under distorted
grid voltage conditions. Simulations of the proposed control strategy for a DFIG based wind
power generation system were carried out using MATLAB/Simulink.

TRANSIENT STABILITY
Transient stability is the ability of a power system to maintain synchronism when
subjected to a large disturbance. The severe disturbances include equipment outages, load
changes or faults that result in large excursion of generator rotor angles. The resulting system
response is influenced by the nonlinear power-angle relationship. The time frame of interest
in transient stability studies is usually 3–5 s following the disturbance. The duration may
extend up to 10–20 s for a very large system with dominant inter-area swings.
Three main aspects of wind farm that affect the transient stability. These are listed
below.
Location of wind generator: Especially when high wind resources are located in one
particular area leading to highly modified power flows including increased tie-line flows,
critical fault clearing times can be considerably reduced and additional lines might be
required.
Generator technology: Variable speed wind generators are able to improve transient
stability margins, when being equipped with low voltage ride-through capability, reactive
current boosting and ideally with fast voltage control.
Connection of large wind farms to lower voltage levels: The integration of wind
generation into sub transmission and distribution systems has a negative impact on transient
stability, because the reactive contribution is highly limited due to reactive losses in sub-
transmission and distribution systems.
Claudio et al [49] analyzed the transient stability of electrical power systems
including the influence of induction generators. Also overviewed induction generators. Using
an existing transient stability program, simulations are carried out to compare the
performance of a typical electrical system with and without the presence of induction
generators. With the event of a system disturbance, such as a loss of a generator, this tends to
15


cause transient stability problems, the presence of these induction generators acts as a
stabilizing factor. Thus, these machines cause the electrical system to become stiffer from the
point of view of the stability.
Nunes et al [50] analyzed the transient stability margin of variable speed wind
turbines with the doubly fed induction generator connected to the electric grid. The controller
model of the DFIG including rotor current limits and its effect on the transient stability of the
wind system will be considered. The models presented are implemented using MATLAB.The
simulation results clearly show that the DFIG improves the short-term post-fault stability of
wind turbine generators when integrated to power systems with conventional generation. The
doubly fed machine is more robust than cage generators in the events of critical faults, as a
short-circuit.The DFIG is able to keep the torque equilibrium, still maintaining the necessary
transient stability margin. It was also observed that it is possible to reduce the dynamic
reactive compensation demands when using the DFIG. This is an important feature
considered in the choice of the wind system integrated on strong or weak electrical grids.
Julio et al[51] addressed two main issues. First, models for dynamic studies are
described; Secondly, transient stability studies involving wind energy conversion systems are
presented. These studies will include fixed speed and variable speed devices, and several
situations on the grid are considered. Studied the analysis of the dynamic response of the
system to network faults such as short circuits, line trips, and generator trips. From the
analysis performed, it has been concluded that the effect of fluctuations of wind power
generation is negligible compared with the effect of short circuits in the power grid. Also
concluded that simplified models of wind energy systems may be used for dynamic studies,
without significant loss of accuracy. Variable speed devices seem to be better for system
stability than fixed speed ones.
Markus et al [52] presented a fundamental frequency doubly-fed induction machine
model including a typical control system and discussed the accuracy of reduced order models
under various operating conditions. It includes models of all components, the induction
generator, the rotor-side- and the grid-side converters and typical approaches for the control
circuits and aerodynamics of the wind turbine. All models have been implemented and tested
in the power system analysis program Dig SILENT. In the simulation of the fifth order
model, not only stator transients of the induction machine but also the transient behaviour of
transformers and lines was considered (EMT-compatible network model).Together with the
third order machine model, a quasi-steady-state network model was used, corresponding to
the classical stability approach are described .When comparing the results from both models,
it can be noted that the reduced order model represents the average of power and voltage very
well.The reduced order model can therefore be used for analyzing the influence of doubly-fed
induction machines to the power system, but it is not possible to predict peaks in electrical
power or torque correctly. Therefore, the fifth order model together with a "transient"
network model is required. Every reduced order model was validated against higher order
models. The results of the test cases show that a third order induction machine model
including crow bar protection together with a simplified model of the grid-side converter
provides sufficient accuracy and the necessary computational efficiency for carrying out
stability studies in large power systems with several hundreds of machines.
Tao et al [53] concentrated on transient analysis of variable speed wind turbines with
doubly fed induction generator (DFIG) after an external short-circuit fault. A simulation
model of a variable speed wind turbine with DFIG developed in PSCAD/EMTDC is
presented, and the control and protection schemes are described in detail. When the post-fault

16


situation is not serious enough to trigger the protection devices in the rotor circuit, the control
schemes of the DFIG operates as normal and are capable of forcing the rotor speed down and
re-establishing the voltage at the wind turbine terminal after the short-circuit fault is cleared.
The simulation results demonstrate how the control schemes effectively manage to restore the
wind turbines normal operation after the clearance of an external short-circuit fault.
Muyeen et al [54] analyzed the transient stability of WTGS using the six-mass, three-
mass and two-mass drive train models for severe network disturbance in two different types
of power system models. A detailed transformation methodology from the six-mass to two-
mass drive train models is presented, which can be used in the simulation analysis with
reasonable accuracy. For transient stability analysis the symmetrical three line-to-ground
faults (3LG) is considered. Some unsymmetrical faults such as double line-to-ground fault
(2LG), double line-to-line fault (2LS) and single line-to-ground fault (1LG) (phase a) are also
considered. The simulations have been done by using PSCAD/EMTDC. By using the
transformation procedure, the inertia constants, spring constants, self-damping’s of individual
masses and mutual-damping of adjacent masses of the six-mass drive train model can be
converted to reduced order models. The effects of drive train parameters such as inertia
constants, spring constants and damping constants are examined for the above mentioned
three-types of drive train models. Considering all the simulation results, it can be concluded
that the WTGS can be expressed by the simple two-mass shaft model with reasonable
accuracy and that this model is suitable for the transient stability analysis of grid connected
WTGS.
Katherine et al [55] derived a third order model for a DFIG which is suitable for use
with the standard one-axis model for synchronous generators, also developed a mathematical
model of a complete system, and described the linearization of the system. Results presented
and compared from eigenvalue analysis and dynamic simulations. Eigenvalue analysis is used
as a method for tuning control parameters. We have noted that a determination of the
eigenvalues is not sufficient for describing post-disturbance behavior, and that dynamic
results are also required. Converters might be utilized to improve this behavior.
Libao et al [56] focused on studying the dynamic performance of the DFIG based
wind farm and investigating the impacts of the DFIG based wind farm on power system
transient stability. Two kinds of indices are employed to evaluate the system transient
stability. Power angle-based stability margin or index and Critical clearance time (CCT) of
faults .CCT is the longest allowed fault clearance time without losing stability. This is
obtained, using a binary search method , within a specified fault clearance range with a set
threshold. If the change of the system operation can increase CCT, it is considered that such
change is favorable to improve power system transient stability. All simulations are
conducted on the DSATSAT/UDM™. The analysis and simulation results show that under
the specified fault condition, the increased penetration level, i.e. replacing synchronous
generators with the DFIG based wind farm in the case studies, tends to improve the transient
stability for a specific test power system.
Chenxi et al [57] presented a study on the transient characteristics of a power
generation when the power is generated from wind turbine using DFIGs. The transient
behaviours of active power, reactive power and voltages in a wind power generation system
are analyzed. In this study, a third-order system of nonlinear differential equations is used to
describe the behavior of a DFIG, in terms of the voltage magnitude dynamics, voltage angle
dynamics and the dynamics of its electromechanical system. A novel analysis is proposed
based on the linear state space representation of the system. The study finds that the stable

17


operation region of the PV curve remains almost the same when the system faces
perturbations such as changes in wind speed and load, which means that the system presents a
stable behavior under these disturbances.
Li et al [58] analyzed the transient stability of a grid connected wind turbine with
SCIG, a three-mass wind turbine equivalent model has been proposed by considering both the
bending flexibility of the blades and the torsional flexibility of the drive drain shaft.
Combined with the electromagnetic transient models of SCIG, the transient behaviors of
wind turbine system are simulated and compared when the stator terminal of SCIG is
subjected to a three-phase fault. The results of transient stability analysis are also compared
with the traditional two-mass shaft model and one-mass lumped model, respectively. The
comparative results have shown that the influence of blades flexibility on transient responses
of the wind turbine system is more and more obvious as the wind turbine capacity increasing,
a three-mass wind turbine model that takes into account both shaft flexibility and blades
flexibility may be more suitable than the traditional models of the wind turbine drive train. In
addition, in order to quickly estimate the transient stability limit of wind turbine system
considering both generator electrical transients and the drive train flexibility, a direct method
based on the normal form theory has been investigated.
HAN Pingping et al [59] constructed a model for a simple electric power system with
a large wind power plant consists of Doubly Fed Induction Generator (DFIG). The studies
include examining the transient stability of the power plant in serious system fault under two
operation strategies, i.e. fixed power factor operation and fixed voltage operation. Following
conclusions could be obtained, under fixed voltage operation strategy; the wind power
generation system could help to increase the voltage level of stator terminals by regulating its
reactive power output. Therefore, the ability of fault ride-through and transient stability of the
wind farm are improved. During serious disturbances of the grid, such as a three-phase
ground fault, the power balance between two sides of the DC-Link are destroyed, causing the
voltage to increase rapidly and reach the over-voltage limit in short time, protection schemes
are triggered to protect damage on the wind turbine system. Therefore, taking measures to
limit rotor power output and reduce the power imbalance of the converters under large
disturbances so that the grid-connection is preserved are of importance to increase the ability
of fault ride-through and the global transient stability and dynamic voltage stability of wind
power generation system.
Hongjing et al [60] focused on the comparison of transient stability characteristic
between wind farm based on double fed induction generator (DFIG) and tradition power
plant with the same capacity. During steady state, the reactive power between wind farm and
the grid is zero. The study indicates that, in this system, when the scale of wind farm
connected is below 12.3%, the transient stability is better than synchronous generator
integrated with the identical capacity. And with the increasing capacity of wind farm, the
fault critical clearing time (CCT) is shorter, and it lasts longer time during the recovery.
When the scale of wind farm exceeds 12.3%, the terminal voltage of point of common
coupling (PCC) is below 0.95 p.u. The stability is inferior to the synchronous generator
connected. Under the circumstance, the stability will be enhanced through adding the reactive
power compensative device.
Melicio et al [61] focused on the transient stability of variable speed wind turbines
with PMSG at a pitch control malfunction. Hence, we study the influence of a pitch control
malfunction on the quality of the energy injected into the electrical grid, analyzing the
transient stability with different topologies for the power-electronic converters. Also

18


proposed a new control strategy based on fractional-order controllers for the variable-speed
operation of wind turbines with PMSG/full-power converter topology. The performance of
disturbance attenuation and system robustness is ascertained. Computer simulations obtained
by using Matlab/Simulink.
Lasantha et al [62] presented transient stability analysis for a power system with high
wind penetration. The transient stability has been evaluated based on two stability criteria:
rotor angle stability and voltage stability. DIgSILENT power factory has been used as the
main simulation tool for this analysis. The installation of DFIG based wind farms has also
yielded a significant improvement in system stability due to their reduced reactive power
consumption. Although these factors have improved the stability at low wind penetration
levels, system stability is significantly degraded at high penetration levels (50%) due to the
high reactive power absorption of wind generators under transient disturbances.
Khosravi et al [63] evaluated transient stability of a power system when large
amounts of wind farm with the DFIG technology is connected to the system.Digsilent
software is used for simulating program. Simulation studies are carried out to demonstrate
and compare the transient performance of test system with and without wind power
integration during a severe grid fault. The results are extracted and diagrams are drawn by
MATLAB. During the simulation, a 150 ms three-phase short circuit is applied. Simulation
results show that ever the more penetration level of wind farm we have in the system, the
worse transient stability and more rotor angle and rotor speed oscillations . Also we could not
have an unlimited DG generation in the power system and at a certain penetration level, the
power network would become unstable and the synchronous generators will lose their
synchronism because of the weak capability of the wind turbines in fault detection and their
cooperation in supplying additional current due to fault occurrence.
Piergiovanni et al [64] presented the model and control scheme of a Doubly-Fed
Induction Generator (DFIG). The controllers are designed in order to take into account the
different operating conditions of the generator. In normal operations the DFIG can work with
variable rotor angular speed between a minimum and a maximum value, covering a wide
range from subsynchronous to supersynchronous angular speeds. Up to the rated value, the
rotor angular speed is regulated to those values which allow transferring the maximum wind
power into electrical power. For angular speeds higher than the rated one, a blade pitch angle
regulation limits the transferred power to prevent damages to the machine and instability. A
single DFIG connected to a high voltage network has been implemented with ATP-EMTP.
Simulations are obtained considering normal operating and fault conditions. Related to this
last case, a new stabilizing technique is proposed to improve transient stability. The system
has been simulated under normal operating and fault conditions.
B. EFFECTS AND ENHANCEMENT OF STABILITY IN WIND ENERGY
CONVERSION SYSTEM
Perdana et al[65] developed a model to investigate the dynamic response of a wind
turbine with DFIG connected to the power system during grid disturbance. This model
includes aerodynamics, the mechanical drive train, the induction generator as well as the
control parts. The response of the system during grid disturbances is studied. An inclusion of
saturation effect in the generator during faults is included as well. A wind turbine model with
DFIG is developed in Matlab/Simulink and simulations of the model during grid disturbance.
Two different operation modes, i.e.sub-synchronous and super-synchronous operation, are
treated separately. In the simulation, a three-phase fault is applied at the middle bus. The
magnitude of fault is controlled by the selection of an appropriate fault resistance. Various
19


simulations are conducted, In the first simulation, the ability of the DFIG controller to
recover terminal voltage after fault clearance is investigated. The second simulation describes
the sequence action of the over-current protection during a fault, which leads to converter
blocking. The terminal voltage recovery of the DFIG is somewhat better than the identical
squirrel cage induction generator. DFIG is sensitive to severe voltage dips that result in an
excessive stator and rotor current, which leads to the rotor converter being blocked.
Vinodh et al [66] has presented a study on grid-connected wind electric generators,
WT-SCIG and WT-DFIG, subjected to transient faults on transmission lines connected to the
windfarm. All simulations are performed in MATLAB/Simulink. The dynamic responses to
wind speed variations and transient faults on transmission line are studied. The author
includes monitoring of critical values of voltage and power as well as stability assessment at
several points in the simulated model of a wind farm-grid interface. Different types of faults
(L-G, L-L-G and L-L-L-G) are simulated. Results obtained from the study provide useful
information regarding the behavior of these generators when connected to grid and helps a
comparison between the two types.
Fei et al [67] studied the impact of large scale wind farm integration on power
systems transient stability.Then the 8 th and 5th order dynamic models of DFIG of wind
turbines based on DFIG is used to study the impact of wind power integration on the transient
stability of the grid.The simulations are carried out by MATLAB and PSS/E to verify the
theoretical analysis. It is concluded in the paper that the performance of DFIG for integration
is better than that of synchronous generation units at a same point in the power systems as far
as transient stability is concerned. Also with the voltage control, the transient stability of
power system is enhanced as the fault happens. and concluded in the paper that the transient
stability of DFIG connected to power system is better than that of synchronous generation
units.
Li et al [68] modelled grid-connected wind farm which contains SCIGs and DFIGs is
built, and the transient operation characteristics of DFIGs and SCIGs which have different
rates of capacity are studied. A new control measure is put forward to improve the transient
performance of the DFIG, which is proved effective through the simulation. Also the impact
of the control measure on the SCIG running in parallel with the DFIG is also investigated.
The detailed model of grid-connected wind farm which contains the DFIGs and SCIGs is
carried out in PSCAD/EMTDC. The fault event is a three-phase to ground short-circuit
fault.The transient operation characteristics of DFIG and SCIG with or without RSC voltage
control are studied. With the DFIG RSC voltage control, the transient performance of DFIG
is greatly improved. Also there is an apparent impact on the transient performance of SCIG,
which can recover to pre-fault stable operation state, furthermore the recovery time is much
less along with the capacity of DFIG increasing.
A.A. El-Sattar et al [69] studied the transient response of variable speed wind turbines
with DFIG after the clearance of short-circuit fault at the generator bus. A simulation model
of wind turbine with DFIG is presented, and the control schemes of the wind turbine are
described in detail. Based on the wind turbine model, the stability of wind turbine after a
short-circuit fault has been investigated. The simulation results show how the control
schemes effectively manage to restore the wind turbine’s normal operation after the clearance
of an external short-circuit fault. During faults a high rotor currents will flow in the rotor
converter which could damage it. A crowbar is used to disconnect the rotor converter during
fault to protect it against short-circuit currents.Different cases are simulated to study the
response of variable speed wind turbine and its control when subjected to three phase short

20


circuit at the generator bus (worst case). The analysis was carried out in
MATLAB/SIMULINK environment.
Wei Qiao et al [70] investigates the effect of wind power integration on power system
transient stability, based on a SG is replaced by a large wind farm equipped with the DFIG
wind turbines. Simulation studies are carried out in PSCAD/EMTDC.DFIG wind turbines
can successfully ride through grid faults and have no problem of angular stability associated
with the conventional SGs. Because of these features, the DFIG wind turbines might be
superior over the SGs to help maintain power system transient stability during some severe
grid disturbances. System components, such as the SGs, the DFIG and the two-mass shaft
system model in the WTG are built with the standard component models from the
PSCAD/EMTDC.Three-phase short circuit is applied to the system. Therefore after the fault,
the system changes to a new operating condition. Results show that better transient
performance and stability are achieved by the 39-bus system with wind power integration.
Guo Jia-hu et al [71] analyzed the behaviour of DFIG and converter under
symmetrical and unsymmetrical grid fault with mathematic method in details, and gave the
equation of flux and dc-voltage under grid fault. The fault response of the DFIG system
includes DFIG and converters are analyzed. From the investigating of the response of the
DFIG system due to different grid disturbances, it has been shown that the amplitude of the
flux oscillation when the voltage returns after a voltage sag can vary between zero and twice
the initial amplitude of the flux oscillations due the sag. The maximum grid fault current have
been derived and also it occurs moment. It shows that the maximum value of DFIG current is
independent of flux and only depends mainly on the stator and rotor leakage inductance. At
last, the methods of grid fault ride-through are proposed including crowbar solution and
compensating for the changes in stator flux.
Folly et al [72] investigated the impact of fixed speed and variable speed grid-
connected wind generators on the transient stability of a power system. The wind generators
considered are the squirrel cage induction generator (SCIG), the doubly-fed induction
generator (DFIG) and the converter driven synchronous generator (CDSG). We investigated
the level of penetration of the wind generators that can cause system instability or
significantly reduce the stability margins under three-phase fault conditions. Two scenarios
are investigated. Under the first scenario, the conventional synchronous generator is not
equipped with an Automatic Voltage Regulator (AVR) when the system is subjected to a
three-phase fault. Under the second scenario, the AVR of the conventional synchronous
generator is included. It was found the squirrel cage induction generator performs poorly and
contributes negatively to the transient stability of the network as compared to both the
doubly-fed induction generator and the converter driven synchronous generator. The
converter driven synchronous generator has the best performance.When the AVR is included,
the penetration level of the squirrel cage induction generator could be further increased
without loosing the stability of the system. Simulations were carried to investigate the impact
of the above discussed three types of wind generators on the transient stability of power
systems using DigSilent Software package. A three phase fault was applied at the middle of
the transmission line. The external voltage controllers improve the transient stability margin
of the power systems due to the ability to control the voltage at the terminal of the generators.
When the AVR was included, it improves the transient stability.
Durga Gautam et al [73] this paper presents a systematic approach based on
eigenvalue sensitivity to examine the effect of penetration of DFIGs on a large system. The
approach involves detailed analysis of a fairly large system using commercial grade software.

21


The analysis of the critical modes of oscillation is further extended to observe whether or not
the system is transiently stable when the particular mode is excited due to a large disturbance.
The simulation results carried out for the two different study objectives, namely, small signal
stability and transient stability are detailed. With the objective of observing the system
response for small and large disturbances, the same base case operating scenario is
considered for small signal stability and transient stability study cases. The study is
conducted using the package DSATools developed by Powertech Labs, Inc. This includes
power flow and short circuit analysis tool (PSAT), transient security assessment tool (TSAT)
and small signal analysis tool (SSAT).
He Ren-Mu et al [74] investigated the impact of DFIG-based wind farm on power
system load modeling Then, the ZIP (the constant impedance, constant current, and constant
power load model, namely ZIP load model) in parallel with induction-motor was adopted to
fit the load characteristics. It was concluded that wind farm based on small scalar capacity
does not have much impact on the load modeling, thus using the ZIP in parallel with
induction-motor load model is appropriate. Wind farm based on large-scale capacity have
changed the load flow largely. If the ZIP in parallel with induction-motor load model is still
used it will bring a large error in system analysis. Using the ZIP in parallel with
asynchronous generator model can bring more accurate results.
Milton et al[75] development of a model of a grid-connected DFIG-based WECS for
studying its dynamic behaviour during grid disturbance. This model includes aerodynamics,
the mechanical drive train, the DFIG and the controller. It is observed that the generator-side
controller provides good decoupling between active and reactive power. development of a
wind turbine model with DFIG in Matlab/Simulink, followed by simulations of the model
during grid disturbance. In the simulation, the ability of the DFIG to recover terminal voltage
after grid disturbance is presented. The response of the DFIG to faults and subsequent action
of the over-current protection is described. The results from the super-synchronous operation
mode are evaluated here. The inclusion of the saturation effect in the generator to provide
better prediction of current magnitude is included as well.

Sundeep et al [76] presented modelling and effect of Doubly Fed Induction Generator
(DFIG) for wind turbines on transient stability analysis when connected to grid system. A
reduced order model for the DFIG has been used. A controller for speed, voltage and power
factor has also been implemented.The DFIG model and the controller are presented as
Differential Algebraic Equations. The behaviour of DFIG with and without synchronous
machine under the fault condition has been observed. Method used to solve DAE equation is
“Simultaneous Implicit” method. first the Differential equations are converted to algebraic
equations using the trapezoidal integration method and the resulting algebraic equations
along with the other algebraic equations are solved simultaneously using the Newton’s
method at each time step. DFIG was simulated with a three phase fault. PSO technique has
been implemented for optimizing the controller gains. From the results it has been observed
that, the behaviour of both DFIG and synchronous machine under fault conditions has been
affected by each other’s presence in the power system network. When connected to infinite
bus system (which is a strong network) and to a synchronous machine system (which is a
weaker network), the DFIG remains stable for both the cases. This shows that DFIG is
capable of withstanding grid faults when interconnected with the grid. This is one of the
major advantages of DFIG when compared to its other equivalent machine types. Also,
DFIG-based wind generation with the basic control scheme used provides better performance
in terms of voltage control and damping.
22


Djilali et al [77] developed a full model and the control strategy of the DFIG.The
mechanical model of the wind turbine is also introduced in order to investigate the maximum
power point tracking (MPPT) and the pitch angel control. The paper mainly focuses on the
DFIG transient state variables prediction for various operating conditions with regard on the
crowbar design. To demonstrate the behaviour of the system, simulations have been
performed using MATLAB/ SIMULINK software.The crowbar circuit used in simulation
consist of simple resistance added to the rotor resistance during fault, in the same time the
rotor circuit is disconnected from the rotor side converter. the effect of crowbar system, in
different cases, is examined. Thus, it present a good approach to provide the optimal crowbar
resistance.
Libao et al [78] examined transient stability simulation of power system with
consideration of large-scale grid-connected wind farms of DFIG. The multiple wind farm
integration with replacing synchronous generators is studied first. Furthermore, the impact on
the power system transient stability with direct connection of wind farm of DFIG. It should
be pointed out that these conclusions and comments can provide useful information for power
system planning and design when considering integrations of large wind farms with the
existing power system.
Muyeen et al [79] analyzed the stabilization of wind farms connected with multi-
machine power system in a severe network disturbance. For this purpose, the STATCOM
incorporated with battery energy storage system (BESS), i.e., STATCOM/BESS topology is
proposed to enhance the transient stability of entire power system. At each wind farm
terminal one PWM based STATCOM/BESS is connected. Two-mass drive train model of
wind turbine generator system (WTGS) is used in the analyses as the drive train modeling has
great impact on the dynamic characteristics of fixed speed wind generator. Both of
symmetrical and unsymmetrical faults are considered as network disturbances. it can also
enhance the low voltage ride through (LVRT) capability of WTGS. Simulations have been
done by using PSCAD/EMTDC. A symmetrical 3LG fault is considered. it is concluded that
the proposed STATCOM/BESS can be applied effectively to enhance the transient stability
of multi-machine power system including wind farms.

Hansen et al [80] concentrates on the fault ride-through capability of doubly fed
induction generator (DFIG) wind turbines. The main attention in the paper is, therefore,
drawn to the control of the DFIG wind turbine and of its power converter and to the ability to
protect itself without disconnection during grid faults. The dynamic behaviour of DFIG wind
turbines during grid faults is simulated in PowerFactory DIgSILENT. the presence of the
damping controller is very important for minimizing the grid fault effect both on the
mechanical and on the electrical side of the turbine.
Nayeem et al[81] investigates possible improvements in grid voltage stability and
transient stability with wind energy converter units using modified P/Q control. The
simulations are done using the power system simulation software PSS/E. A three-phase to
ground fault is applied at the middle of the line , and the generator rotor-angle and the grid
power are studied in the presence of different types of WECS. For the investigated power
system considered in this paper, the critical fault clearing time of the generator was increased
by two cycles,when the suggested method was used.
Tarafdar et al[82] studied a wind farm modeling and UPFC using are to solve the
wind farms power transmission problems. In this paper structure and UPFC functional basics
under stable conditions and induction generator model and wind turbine model is mentioned
23


initially and then the effect of UPFC connected to a sample wind farm, in respect wind
velocity changes and wind farm distance to grid and power flow are studied. Wind turbines
are studied in wind velocity changes conditions and also reactive and active power flow
control in the presence of UPFC and without that is examined in modeling. UPFC is
simulated in MATLAB/Simulink. A FACTS device in order to transmit maximum wind farm
generated power by keeping their stability under various system conditions is considered. In
this paper UPFC function in wind farms generated maximum transmission power is studied.
Mamta et al [83] presented a pitch controlled Wind Turbine Generation System
(WTGS) used to have optimum power flow and to reduce overloading of wind turbine when
higher wind speeds are available. Also, a pitch control system is used for stabilization of the
wind turbine at grid faults. A simple control strategy for STATCOM is adopted, where only
measurement of rms voltage at induction generator (IG) terminal is needed. For the stability
behavior of a Fixed Speed Wind Turbine (FSWT) connected to the grid, after a short-circuit
fault in the utility, the model is developed in the simulation tool MATLAB/SIMULINK and
created as a modular structure. From the results it is observed that with STATCOM the
oscillations are reduced as compared to the capacitive bank compensation and no
compensation. Finally we can conclude that STATCOM gives better performance than the
static capacitive bank.
Muyeen et al[84]presents a new method to enhance the transient stability of
multimachine power system including wind farms, when a severe network disturbance occurs
in the power system. For this purpose, the energy capacitor system (ECS) composed of power
electronic devices and electric double layer capacitor (EDLC) is proposed. The control
scheme of ECS is based on a sinusoidal PWM voltage source converter (VSC) and fuzzy
logic controlled dc–dc buck/boost converter using insulated gate bipolar transistors (IGBT).
Two wind farms are considered to be connected to the power system. To obtain the realistic
responses, the two-mass shaft model of WTGS is considered in this paper. Fuzzy logic
controller (FLC) is proposed as the control methodology of dc–dc buck/boost converter since
it can be applied to a system with uncertainties. The symmetrical three-line-to-ground fault,
and the unsymmetrical double-line-to-ground fault, double-line fault, 2LL, and single-line to
ground fault are considered as a network disturbance, Simulations have been done by using
PSCAD/EMTDC.Simulation results clearly show that the proposed ECS can enhance the
transient stability of wind generators in multimachine power system as well as their low
voltage ride through (LVRT) capability.
Tarafdar et al [85] studied a wind farm modeling and STATCOM used to increase the
upper limits of induction generators dynamic stability in various distortion conditions in grid.
Also studied the effects of using a local resistance (stabilizer) and STATCOM in keeping and
increasing stability of wind farms by MATLAB SIMULNK software. In this issue, FACTS
devices usage in distribution voltage level in order to wind farms stability conditions
optimization in system different conditions is considered visually. In this paper STATCOM
application role in induction generators stability increase to grid is studied.
Mishra et al [86] studied the effect of the damping controller on the DFIG system; 2)
to tune damping controller to improve the damping of the oscillatory modes; 3) to study the
effect of the damping controller on the variation of the dc voltage across capacitor; and 4) to
study the efficacy of the damping controller in improving the fault ride-through capability of
the system. Tuning of the damping controller to enhance the damping of the oscillatory
modes is presented using bacterial foraging (BF) technique. Among various methods for the
optimization, BF is selected because of its better capability of locating optimal solution and

24


higher convergence speed has been applied for the optimization of the controller for the RSC
in time domain. The nonlinear simulation of the DFIG system is observed to validate the
efficacy of the damping controller. The optimized controller parameters are used and the
system is simulated in MATLAB using ODE15s. The efficacy of the optimization procedure
is observed and the fault ride-through capability is also studied. A damping controller using
the auxiliary signal of speed deviation is used in the angle control of the RSC controller in the
DFIG system. It gives promising results in damping out the low frequency oscillations, and
hence, improves the system stability of the grid-connected DFIG system. The coordinated
tuning of the damping controller with the other DFIG controllers is also reported in this
paper. It is observed that this tuning is helpful in not only improving the damping of the
oscillatory modes but also in enhancing the fault ride-through capability of the DFIG system.
Hence, tuned damping controller is necessary for enhancing the stability of the DFIG system
connected to the grids.
Zengqiang et al [87] studied the use of static synchronous compensator (ST ATCOM)
for wind farms integration composed with DFIGs, and proposes a reactive power cooperative
control strategy for the wind farm combined with STATCOM. On PSCAD/EMTDC, a
detailed whole dynamic model for VSCF wind power system and STATCOM are
established. Then optimization cooperative control strategy of the DFIG is proposed. To
control a nonlinear system is to design a linear controller using the linearized model of the
nonlinear system dynamics at a desired operating point. Among a variety of linear control
techniques, the PI controllers are the most commonly used ones. In this paper, the control
method used the PI controller. Finally, simulation studies are carried out to examine the
dynamic performance of the PCC with and without STATCOM. the wind fann equipment
tendency can be predicted that: as wind farms become larger and further away from the point
of connection, reactive power compensation provided by STATCOM might become essential
in order to meet Grid Code requirement for the wind farm connection.
Bijaya et al [88] this paper evaluates the use of STATCOM to provide dynamic
reactive power compensation for mitigating transient disturbances in DFIG-based wind farm
hence enhancing the overall performance of DFIG-based wind farm interconnected to weak
distribution grid. The study here in this paper is based on the three phase non-linear dynamic
simulation, utilizing the SimPowerSystem block-set in MATLAB/Simulink. The different
cases studied on this test system are: (1) 2-cycle, 3-phase, high impedance fault to ground, (2)
sudden change in load in the system and (3) voltage swelling and sagging in DFIG wind
farm. Hence with the presence of STATCOM in the system, the power factor of the wind
farm generated power can be controlled. DFIG-based wind farm connected to weak
distribution network requires disturbances mitigating system to enhance the voltage stability
of the wind farm. Dynamic reactive power compensation using STATCOM at the point of
common coupling (PCC) is a feasible option for minimizing effects of grid-side disturbances
on wind farm. Mechanically switchable capacitor bank can also be combined with
STATCOM for making compensation system economical. STATCOM also helps wind farm
to generate power with controllable power factor as per the demand of the locally connected
customer load. Hence STATCOM also improves the performance of overall distribution
system.
Olimpo et al [89] DFIG-based wind farm connected to weak distribution network
requires disturbances mitigating system to enhance the voltage stability of the wind farm.
And the ability to provide Power System Stabiliser (PSS) capabilities that improves overall
network damping. A three-generator network model that combines synchronous and wind
farm generation has been developed to assess dynamic performance. Simulation results are
25


presented and discussed that demonstrate the capabilities and contributions of this DFIG
controller to network dynamic and transient stability. Dynamic reactive power compensation
using STATCOM at the point of common coupling (PCC) is a feasible option for minimizing
effects of grid-side disturbances on wind farm. Mechanically switchable capacitor bank can
also be combined with STATCOM for making compensation system economical.
STATCOM also helps wind farm to generate power with controllable power factor as per the
demand of the locally connected customer load. Hence STATCOM also improves the
performance of overall distribution system.
Zengqiang et al [90] studied the use of static synchronous compensator (ST ATCOM)
for wind farms integration composed with DFIGs, and proposes a reactive power cooperative
control strategy for the wind farm combined with ST ATCOM. On PSCAD/EMTDC, a
detailed whole dynamic model for VSCF wind power system and STATCOM are
established. Considering the reality, the target of the control strategy is to maintain the
voltage prescribed at the point of common coupling (PCC) and supply the optimization
reactive power for the gird. To make the wind farm meet the regulation drawn up by grid and
further more realize optimization economic, the reactive power provided by DFIG is hope to
remain zero. The reactive power absorbed by wind farm is provided by Dynamic reactive
power compensation firstly. The Cooperative control strategy of wind farm is also needed. To
control a nonlinear system is to design a linear controller using the linearized model of the
nonlinear system dynamics at a desired operating point. Among a variety of linear control
techniques, the PI controllers are the most commonly used ones. In this paper, the control
method used the PI controller. To analyze the transient performance of wind farm with
STATCOM, the three-phase short fault is considered to occur again. From the results we
obtained, the wind farm equipment tendency can be predicted that: as wind farms become
larger and further away from the point of connection, reactive power compensation provided
by STATCOM might become essential in order to meet Grid Code requirement for the wind
farm connection.
IV. CONLUSIONS
In this paper, review on various models of wind energy conversion system, analysis of
small signal stability and transient stability and enhancement of stability is given. Various
models for wind energy conversion system for stability studies are proposed by various
researchers and reported in [4-14]. These models are varied from simple models to reduced
order models. Model simplification is important to keep a balance between computation time
and result accuracy. In this context, third order, fifth order and sixth order models have been
proposed for the study of stability analysis of wind energy conversion systems.
Unlike the synchronous machine whose operating characteristics have been
documented and understood for decades, the generation of bulk ac electricity using non-
synchronous machine-based generators is a relatively new phenomenon. With increased
penetration level of wind power, the influence of wind power on power system stability has
drawn great attention to the power system engineers and scientists. One of the most important
issues is the impact of wind power penetration on power system small signal stability [5]-[19]
of an existing interconnected large-scale power system. Small signal stability is is analysed in
[21-31]. Various methods are proposed for analysis of small signal stability and presented.
Small signal stability is closely related to the eigenvalues of the system (state) matrix. Several
computational techniques for calculating the eigenvalues of realistic power systems have
been developed.

26


The behavior of the DFIG is well known and has been modeled in detail by several
authors in order to design the control system. Some works studied the model of the wind
turbine with a DFIG for transient stability analysis to demonstrate the capability of the DFIG
to maintain system stability for various faults such LG, LLG and symmetrical faults.
Dynamic mathematical models of DFIG and its converters are also discussed. Transient
stability analysis is done for other than electrical parameters variations like pitch control and
wind speed disturbance. In [32-46], various models and methods are proposed for the
analysis of transient stability of wind energy conversion systems.
Enhancement of stability or stabilization of wind energy conversion system is
important in real time operation. Power system controllers are receiving a wide interest since
many technical studies have proven their effects on damping system oscillations and stability
enhancement. In order to improve the damping of electromechanical oscillations when
necessary, such systems should be designed to allow proper processing of stabilization
signals, usually derived from the machine rotor-speed or electrical power.
Voltage or current source inverter based flexible AC transmission systems (FACTS)
devices such as static var compensator (SVC), static synchronous compensator (STATCOM),
dynamic voltage restorer (DVR), solid state transfer switch (SSTS) and unified power flow
controller (UPFC) have been used for flexible power flow control, secure loading and
damping of power system oscillation. Various methods have been proposed in [47-74] for
enhancement of the stability of wind energy conversion systems. Tuning parameters of some
controllers can be optimized using some optimization methods such as genetic algorithms,
particle swarm optimization and etc.
Many authors have developed various models in commercial software’s like PSSE,
Matlab(Simulink), PSCAD and EMTC. These models can be used for offline studies of wind
energy conversion systems.
From the Literature survey, it is observed that for the anlaysis of transient stability of DFIG
Connected to Grid the most suitable order is third order, also it is found that MATLAB
software has tools make easier to analyze the transient stability. In Future, authors will be
focusing on Transient stability studies using MATLAB. For analyzing the stability studies
three phase fault can be considered. And for improving the transient stability STATCOM can
be adopted.
V. REFERENCES
[1] Prabha Kundur, John Paserba, Venkat Ajjarapu, Goran Andersson, Anjan Bose , Claudio
Canizares , Nikos Hatziargyriou , David Hill, Alex Stankovic, Carson Taylor, Thierry Van
Cutsem and Vijay Vittal “Definition And Classification Of Power System Stability”, IEEE
Transactions On Power Systems, Vol. 19, No. 2, May 2004.
[2] Y. A. Kazachkov, J.W. Feltes, and R. Zavadil,,” Modeling Wind Farms For Power System
Stability Studies”, IEEE Power Engineering Society General Meeting, 2003,Vol.3,PP 1526-
1533.
[3] Pablo Ledesma,” Doubly Fed Induction Generator Model for Transient Stability Analysis”,
IEEE Transactions on Energy Conversion, Vol. 20, No. 2, June 2005, PP 388-397.
[4] Istvan Erlich, Jorg Kretschmann, Jens Fortmann, Stephan Mueller-Engelhardt and Holger
Wrede,” Modeling Of Wind Turbines Based On Doubly-Fed Induction Generators For
Power System Stability Studies”, IEEE Transactions On Power Systems, Vol. 22, No. 3,
August 2007,PP 909-919.
27


[5] Yazhou Lei, Alan Mullane, Gordon Lightbody and Robert Yacamini,” Modeling Of The
Wind Turbine With A Doubly Fed Induction Generator For Grid Integration Studies”,IEEE
Transactions On Energy Conversion, Vol. 21, No. 1, March 2006, PP 257-264.
[6] Andres Feijoo, Jose Cidras, Camilo Carrillo,” A Third Order Model For The Doubly-Fed
Induction Machine”, Electric Power Systems Research, Vol.56, 2000, PP 121–127.
[7] J.Kretschmann, H.Wrede, S. Mueller-Engelhardt, I. Erlich, “Enhanced Reduced Order
Model Of Wind Turbines With DFIG For Power System Stability Studies”, First
International Power And Energy Coference,November 28-29, 2006, Putrajaya, Malaysia.
[8] A. Samuel Neto, S. L. A. Ferreira, J. P. Arruda, F. A. S. Neves, P. A. C. Rosas, M. C.
Cavalcanti,” Reduced Order Model For Grid Connected Wind Turbines With Doubly Fed
Induction Generators”, 2007 IEEE, PP 2655- 2660.
[9] Janaka B. Ekanayake, Lee Holdsworth, Xueguang Wu and Nicholas Jenkins,” Dynamic
Modeling Of Doubly Fed Induction Generator Wind Turbines”, IEEE Transactions On
Power Systems, Vol. 18, No. 2, May 2003,PP 803- 809.
[10] M.B.Mohamed, M.Jemli, M-Gossa, K. Jemli,” Doubly Fed Induction Generator DFIG In
Wind Turbine-Modeling And Power Flow Control”, IEEE International Conference On
Industrial Technology,2004,PP 580- 584.
[11] Andreas Petersson, Torbjorn Thiringer, Lennart Harnefors,And Tomas Petru,” Modeling
And Experimental Verification Of Grid Interaction Of A Dfig Wind Turbine”, IEEE
Transactions On Energy Conversion, Vol. 20, No. 4, December 2005,PP 878- 886.
[12] A. A. Ei-Sattar. N. H. Saad and M. Z. Shams Ei-Dein,” Modelling and Simulation Of
Doubly Fed Induction Generator Variable Speed Wind Turbine”, The Eleventhinternational
Middle Eastpower Systems Conference, 2006, PP 492-497.
[13] Xingjia Yao, Hongxia Sui and Zuoxia Xing Dayong Liu,” The Dynamic Model Of Doubly-
Fed Induction Generator Based On Wind Turbine”, Proceedings of the IEEE International
Conference On Automation And Logistics August 18 - 21, 2007, Jinan, China, PP 1023 -
1027.
[14] Luis M. Fernandez,Francisco Jurado, Jose Ramon Saenz,” Aggregated Dynamic Model For
Wind Farms With Doubly Fed Induction Generator Wind Turbines”, Renewable
Energy,Vol. 33, 2008,PP 129–140.
[15] Milton Kumar Das, S.P.Chowdhury, S.Chowdhury and Alexander Domijan”, Dynamic
Modelling And Performance Analysis Of A DFIG Wind Energy Conversion System”,
Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy
in the 21st Century, 2008 IEEE ,PP 1-5.
[16] Miguel Garcıa-Gracia, M. Paz Comech, Jesus Sallan, Andres Llombart,” Modelling Wind
Farms For Grid Disturbance Studies”, Renewable Energy, Vol.33, 2008, PP 2109–2121.
[17] Balasubramaniam, Babypriya and Rajapalan Anita,” Modelling, Simulation and Analysis
Of Doubly Fed Induction Generator For Wind Turbines”, Journal Of Electrical
Engineering, Vol. 60, No. 2, 2009, PP 79–85.
[18] M. A. Chowdhury, N. Hosseinzadeh, M. M. Billah and S. A. Haque,” Dynamic DFIG Wind
Farm Model With An Aggregation Technique”, 6th International Conference on Electrical
and Computer Engineering, Dhaka, Bangladesh, 18-20 December 2010,PP 330-333.

28


[19] B.Chitti Babu and K.B.Mohanty,” Doubly-Fed Induction Generator For Variable Speed
Wind Energy Conversion Systems- Modeling & Simulation”, International Journal of
Computer and Electrical Engineering, Vol. 2, No. 1, February, 2010, PP 1793-8163.
[20] Mattia Marinelli, Andrea Morini, Andrea Pitto and Federico Silvestro,” Modeling Of
Doubly Fed Induction Generator (DFIG) Equipped Wind Turbine For Dynamic Studies”
43rd International ,Universities Power Engineering Conference, 2008. UPEC 2008,PP 1-6.
th rd
[21] J.B. Ekanayake A,C, L. Holdsworth B, N. Jenkins,” Comparison Of 5 Order and 3 Order
Machine Models for Doubly Fed Induction Generator (DFIG) Wind Turbines”, Electric
Power Systems Research, Vol.67,2003, PP 207-215.
[22] Katherine Elkington and Mehrdad Ghandhari,” Comparison Of Reduced Order Doubly Fed
Induction Generator Models For Nonlinear Analysis”,IEEE Electrical Power & Energy
Conference,2009,PP 1-6.
[23] Maider Santos Mugica, Aitor Milo Urkiola, Miguel Rodriguez Vidal and Raul Reyero
Redondo,” Comparison Of Dynamic Models For Wind Turbine Grid Integration Studies”,
PP 1-7.
[24] M. Pariniani and M.R. Lravani,” Coimputer Analysis Of Small-Signal Stability Of Power
Systems Including Network Dynamics”, IEE Proe.-Gener. Transm. Distrib., November
1995,Vol. 142, No. 6,PP 613-617.
[25] F. Wu, X.-P. Zhang, K. Godfrey and P.Ju,” Small Signal Stability Analysis And Optimal
Control Of A Wind Turbine With Doubly Fed Induction Generator”, IET Gener. Transm.
Distrib., 2007, Vol.1,No. 5, PP. 751–760.
[26] Jorge Rodrigo Massing and Humberto Pinheiro,” Small Signal Stability Of DFIG With
Series Grid-Side Converter”, Power Electronics Conference, 2009. COBEP '09. Brazilian
,2009 IEEE,PP 711-718.
[27] Yateendra Mishra, S. Mishra, Fangxing Li, ,Zhao Yang Dong and Ramesh C. Bansal,”
Small-Signal Stability Analysis of a DFIG-Based Wind Power System Under Different
Modes Of Operation”, IEEE Transactions On Energy Conversion, Vol. 24, No. 4,December
2009,PP-972-982.
[28] G. Tsourakisa, B.M. Nomikosb and C.D. Vournas”, Effect Of Wind Parks With Doubly
Fed Asynchronous Generators On Small-Signal Stability”, Electric Power Systems
Research,Vol. 79,2009,PP 190–200.
[29] F.Wua, X.P. Zhang ,P. Jua Zhang and P. Jua,” Small Signal Stability Analysis And Control
Of The Wind Turbine With The Direct Drive Permanent Magnet Generator Integrated To
The Grid”, Electric Power Systems Research, Vol. 79,2009,PP 1661–1667.
[30] S. Dahal, N. Mithulananthan and T. Saha,” Investigation Of Small Signal Stability Of A
Renewable Energy Based Electricity Distribution System”, 2010 IEEE,PP-1-8.
[31] Chandana Karawita U. and D. Annakkage,”A Hybrid Network Model For Small Signal
Stability Analysis Of Power Systems”, IEEE Transactions On Power Systems, Vol. 25, No.
1, February 2010,PP 443-451.
[32] Lin Li, Song Liangliang, Yang Yihan,Miao Youzhong, Wu Tao,” Impact Of Svc On Small
Signal Stability Of Induction Generator Connected Power Systems”, 2010 IEEE PP 1-4.
[33] Xianqi Li, Zhiyuan Zeng, Jianzhong Zhou, Yongchuan Zhang,” Small Signal Stability
Analysis Of Large Scale Variable Speed Wind Turbines Integration”, IEEE,PP 2526-2530.

29


[34] Dawei Xiang, Li Ran,Peter J. Tavner, And Shunchang Yang,”Control Of A Doubly Fed
Induction Generator In A Wind Turbine During Grid Fault Ride-Through “,IEEE
Transactions On Energy Conversion, Vol. 21, No. 3, September 2006,Pp 652-662.
[35] Feng Wu, Xiao-Ping Zhang, Keith Godfrey and Ping Ju,” Modeling And Control Of Wind
Turbine With Doubly Fed Induction Generator”, 2006 IEEE,PP 1404-1409.
[36] Ming Yin, Gengyin Li, Ming Zhou,Guoping Liu, Chengyong Zhao,” Study On the Control
of DFIG And Its Responses To Grid Disturbances”, 2006 IEEE,PP 1-6.
[37] Lie Xu and Yi Wang,” Dynamic Modeling And Control Of DFIG-Based Wind Turbines
Under Unbalanced Network Conditions”, IEEE Transactions On Power Systems, Vol. 22,
No. 1, February 2007,PP 314-323.
[38] Seung-Ho Song, Ji-Hoon Iml, Hyeong-Jin Choi, Seung-Gi Jeong, Byoung-Chang Jeong,”
Simulation Modeling And Experimental Validation Of Generator Control Strategy in DFIG
System”, 2007 IEEE,PP 1329-1333.
[39] Abolfazl Jalilvand, Mehdi Jabbari, Gholamreza Zarei Govar and Hamid Khoshkhoo,”
Modeling And Control Of A Doubly Fed Induction Generator Using PSO Algorithm”, 2008
IEEE,PP 24-27.
[40] Yi Wang,Lie Xu and Barry W. Williams,” Control Of DFIG-Based Wind Farms For
Network Unbalance Compensation”, 2008 IEEE,PP 113- 119.
[41] Lingling Fan, Subbaraya Yuvarajan,” Modeling and Slip Control Of A Doubly Fed
Induction Wind Turbine Generator”,IEEE 2008,PP 1-6.
[42] T. Ghennam, E.M.Berkouk, B.Francois,” Modeling And Control Of A Doubly Fed
Induction Generator (DFIG) Based Wind Conversion System”, Lisbon, Portugal, March 18-
20, 2009,PP 507-512.
[43] Milton Kumar Das, S.Chowdhury, S.P.Chowdhury and C.T.Gaunt,” Control Of A Grid
Connected Doubly-Fed Induction Generators For Wind Energy Conversion”, 2009 IEEE,PP
1-5.
[44] Wei Qiao,” Dynamic Modeling And Control Of Doubly Fed Induction Generators Driven
By Wind Turbines”, 2009 IEEE,PP 1-8.
[45] Luna A, Rolan, A. Medeiros, G. Rodríguez, P. Teodorescu R,” Control Strategies For
DFIG Wind Turbines Under Grid Fault Conditions “,2009 IEEE,PP 3886- 3891.
[46] Yongfeng Ren, Limin Cao, Jie Zhou, Lei Liu, Mingming Zhang, And Hanshan Li,” The
Modeling And Control Of VSCF DFIG Wind Power Generation Based On PSCAD”,
August 13-15, 2010 - Dalian, China,PP 24-28.
[47] C. Hamon, K. Elkington, M. Ghandhari,” Doubly-Fed Induction Generator Modeling And
Control In Digsilent Powerfactory”, 2010 IEEE,PP 1-7.
[48] Jiabing Hu, Heng Nian, Hailiang Xu, And Yikang He, “Dynamic Modeling And Improved
Control Of Dfig Under Distorted Grid Voltage Conditions”, IEEE Transactions On Energy
Conversion, Vol. 26, No. 1, March 2011,PP 163- 175.
[49] Claudio L.Souza, Lucian M. Neto, Gerald C. Guimarles, Adelio J. Moraes,”Power System
Transient Stability Analysis Including Synchronous And Induction Generators”, Power
Tech Proceedings, 2001 IEEE Porto ,Vol 2.PP 1-6.
[50] M.A.V Nunnes,U.H.Bezeera and H.H.Ziirin,”Transient stability Margin of Variable versus
fixed wind systems in Electrical Grids”,IEEE Bologna Power Tech Conference,June 23-
26,Bologna,Itlay,PP 1-7.
30


[51] Julio Usaola, Pablo Ledesma,Juan M. Rodriguez, Jost L. Fernlndez, R Wilhelmi,”Transient
Stability Studies In Grids With Great Wind Power Penetration- Modelling Issues And
Operation Requirements”, 2003 IEEE PP 1534-1541.
[52] Markus A. Poller,” Doubly-Fed Induction Machine Models for Stability Assessment of
Wind Farms”, IEEE Bologna PowerTech Conference, June 23-26, Bologna, Italy,IEEE
2003,PP 1-6.
[53] Tao Sun, Z Chen, Frede Blaabjerg,” Transient Analysis of Grid-Connected Wind Turbines
with DFIG After an External Short-Circuit Fault”, Nordic Wind Power Conference, 1-2
March, 2004, Chalmers University of Technology,PP 1-6.
[54] S.M. Muyeen, Md. Hasan Ali, R. Takahashi, T. Murata, J. Tamura, Y. Tomaki, A. Sakahara
and E. Sasano,”Comparative Study On Transient Stability Analysis Of Wind Turbine
Generator System Using Different Drive Train Models”, IET Renew. Power Gener., 2007,
Vol.1, No.2, PP. 131–141.
[55] Katherine Elkington, Valerijs Knazkins, Mehrdad Ghandhari,” On The Stability Of Power
Systems Containing Doubly Fed Induction Generator-Based Generation”, Electric Power
Systems Research,Vol. 78,2008,PP 1477–1484.
[56] Libao Sh, Shiqiang. Dai, Yixin Ni, , Liangzhong Yao and Masoud Bazargan,” Transient
Stability of Power Systems With High Penetration Of DFIG Based Wind Farms”, 2009
IEEE
[57] Chenxi Lin, Maria Tamayo,John N. Jiang,”An Analysis of Transient Characteristics of
Interconnected Wind Power Generation System with DFIG”, IEEE ICSET 2010, PP 1-6.
[58] H. Li , B. Zhao, C. Yang , H.W. Chen , Z. Chen,” Analysis And Estimation Of Transient
Stability For A Grid-Connected Wind Turbine With Induction Generator”, Renewable
Energy,2010,PP 1-8.
[59] Han Pingping, Ding Ming, and Li Binbin,” Study on Transient Stability of Grid-connected
Large Scale Wind Power System”, IEEE International Symposium on Power Electronics for
Distributed Generation Systems, 2010 IEEE,PP 621- 625.
[60] Hongjing Hou ， Li Lin,Tao Wu, Youzhong Miao,” Comparison Of Transient Stability
Between Wind Farm Based On DFIG And Traditional Power Plant In An Actual Grid”,
2010 IEEE
[61] R. Melicio , V.M.F. Mendes , J.P.S. Catalao,” Transient Analysis Of Variable-Speed Wind
Turbines At Wind Speed Disturbances And A Pitch Control Malfunction”, APPlied Energy,
2010,PP 1-9.
[62] Lasantha Meegahapola, Damian Flynn, Tim Littler,” Transient Stability Analysis of a
Power System with High Wind Penetration”,PP 1-6.
[63] A.Khosravi, M.Jazaeri, S.A.Mousavi,” Transient Stability Evaluation of Power Systems
with Large Amounts of Distributed Generation”,PP 1-6.
[64] Piergiovanni La Seta and Peter Schegner,” New Control Scheme for Doubly-Fed Induction
Generators to Improve Transient Stability”, 2007 IEEE,PP 1-10.
[65] A.Perdana, O. Carlson and J. Persson,” Dynamic Response Of Grid-Connected Wind
Turbine With Doubly Fed Induction Generator During Disturbances”, Electric Power
Systems Research,Vol.78, 2008,PP1240–1246

31


[66] Vinodh Kumar.P, Meera K S and Sasi K Kottayil,” Transient Fault Response of Grid
Connected Wind Electric Generators”, 2006 IEEE,PP 1-6.
[67] Fei Ye, Xueliang Huang, Chaoming Wang, Gan Zhou, Ping Luo,” The Impact and
Simulation on Large Wind Farm Connected to Power System”, 2008DRPT,PP 2608-2614.
[68] Li Lin, Yan Zhang, Yihan Yang,” Transient Characteristics of the Grid-connected Wind
Power Farm with DFIGs and SCIGs”, DRPT 2008 6-9 April 2008 Nanjing China,PP 2676-
2681.
[69] A.A. El-Sattar, N.H. Saad, M.Z. Shams El-Dein,” Dynamic response of doubly fed
induction generator variable speed wind turbine under fault”, Electric Power Systems
Research Vol.78,2008,PP 1240–1246.
[70] Wei Qiao and Ronald G. Harley,” Effect of Grid-Connected DFIG Wind Turbines on
Power System Transient Stability”, 2008 IEEE,PP 1-7.
[71] Guo Jia-hu1,2, Zhang Lu-hua1 and Cai Xu,” Dynamic Response of Wind Power Generation
Based on DFIG under Grid Fault”, IPEMC 2009,IEEE,PP 2275-2278.
[72] K. A. Folly and S. P. N. Sheetekela,” Impact of Fixed and Variable Speed Wind Generators
on the Transient Stability of a Power System Network”, 2009 IEEE,PP 1-7.
[73] Durga Gautam, , Vijay Vittal, Terry Harbour,” Impact Of Increased Penetration Of Dfig
Based Wind Turbine Generators On Transient And Small Signal Stability Of Power
Systems”, IEEE Transactions On Power Systems, Vol. 24, No. 3, August 2009 ,PP -1426-
1434
[74] He Ren-Mu , Wang Ji-Li, Ma Jin, Xu Yan-Hu, Han Dong,” Impacts of DFIG-based wind
farm on load modeling”, 2009 IEEE,PP 1-6.
[75] Milton Kumar Das, S.Chowdhury, S.P.Chowdhury & C.T.Gaunt,” Dynamics Behaviour of
a Grid Connected DFIG for Wind Energy Conversion during Disturbances”, 2009 IEEE,PP
1-5.
[76] Sundeep Sheri, B Shankarprasad, V V Bhat, S Jagadish,” Effect of Doubly Fed Induction
Generator on Transient Stability Analysis of Grid”, Third International Conference on
Power Systems, Kharagpur, India, December 27-29,2009,PP 1-6.
[77] Djilali kairous, Rene Wamkeue, Bachir Belmadani and Mustapha Benghanem,” Dynamic
Performances and Protection Scheme for Doubly-Fed Induction Generator during
Disturbances”, 14th International Power Electronics and Motion Control Conference, EPE-
PEMC 2010,PP 114-119.
[78] Libao Shi, Shiqiang Dai, Liangzhong Yao, Yixin Ni, Masoud Bazargan,” Impact of Wind
Farms of DFIG Type on Power System Transient Stability” , J. Electromagnetic Analysis &
Applications, 2010, Vol.2, PP 475-481.
[79] S. M. Muyeen, M. H. Ali, R. Takahashi, T. Murata, Andj. Tamura,” Stabilization Of Wind
Farms Connected With Multi Machine Power System by Using STATCOM”, 2007 IEEE
Powertech 2007, PP 299-304.
[80] Anca D. Hansen, Gabriele Michalke,” Fault ride-through capability of DFIG wind
turbines”, Renewable Energy,Vol. 32, 2007, PP 1594–1610.
[81] Nayeem Rahmat Ullah, And Torbjorn Thiringer,” Variable Speed Wind Turbines For
Power System Stability Enhancement”, IEEE Transactions On Energy Conversion, Vol. 22,
No. 1, March 2007, PP-52-60.

32


[82] M. Tarafdar Hagh, A. Lafzi And A. Roshan Milani,” Dynamic And Stability Improvement
Of A Wind Farm Connected To Grid Using UPFC”, 2008 IEEE.
[83] Mamta M.Misal And Dr. M.K.Khedkar ,” Stabilization Of Pitch Controlled Wind Turbine
Induction Generator By STATCOM”, ICSET 2008,IEEE,PP 469-473.
[84] S. M. Muyeen, Rion Takahashi, Mohd. Hasan Ali, Toshiaki Murata, And Junji Tamura,”
Transient Stability Augmentation Of Power System Including Wind Farms By Using ECS”,
IEEE Transactions On Power Systems, Vol. 23, No. 3, August 2008,PP 1179-1187.
[85] M. Tarafdar Hagh, A. Roshan Milani, A. Lafzi,” Dynamic Stability Improvement Of A
Wind Farm Connected To Grid Using STATCOM “,Proceedings Of Ecti-Con 2008, 2008
IEEE, PP 1057- 1060.
[86] Y. Mishra, , S. Mishra, M. Tripathy, N. Senroy, And Z. Y. Dong,” Improving Stability Of
A DFIG-Based Wind Power System With Tuned Damping Controller”, IEEE Transactions
On Energy Conversion, Vol. 24, No. 3, September 200, PP 650 -660.
[87] Zengqiang Mi, Yingjin Chen, Liqing Liu, Yang Yu,” Dynamic Performance Improvement
of Wind Farm with Doubly Fed Induction Generators Using STATCOM”, 2010
International Conference on Power System Technology, 2010 IEEE,PP 1-6.
[88] Bijaya Pokharel and Wenzhong Gao,” Mitigation of Disturbances in DFIG-based Wind
Farm Connected to Weak Distribution System Using STATCOM”, North American Power
Symposium (NAPS), 2010 ,PP 1-7.
[89] Olimpo Anaya-Lara, F. Michael Hughes, Nicholas Jenkins and Goran Strbac,” DFIG
control contributions to power network dynamic and transient stability”,PP 1-5.
[90] Zengqiang Mi, Yingjin Chen, Liqing Liu, Yang Yu,” Dynamic Performance Improvement
of Wind Farm with Doubly Fed Induction Generators Using STATCOM”, 2010
International Conference on Power System Technology,2010 IEEE,PP 1-6.
ABOUT THE AUTHORS
Dr Mukund K. Deshmukh received the M.Tech and Ph.D degrees in
Energy Studies at Indian Institute of Technology, Delhi in the years 1986 and
1993 respectively. He has extensive research and consultancy experience in
the areas of Renewable energy, Energy conservation management and
planning, Energy and Environmental Engineering. He has guided research in
the area of Grid-integration of Renewable Energy Power Generation Systems
and published more than 30 research papers in reputed journals. Presently he
is Professor of Electrical and Electronic Engineering at Birla Institute of
Technology and Science, Pilani,Goa Campus,Goa. Also, he is Chief
Coordinator for Renewable Energy Research programme of the Institute, and
the Govt. funded project on SPV+Wind Hybrid Power Generation project in
the Institute.
C.Balakrishna Moorthy received M.E Degree in Power system
Engineering from Annamalai University in year 2002. Presently, he is
working as Lecturer in the Department of Electrical and Electronic
Engineering at Birla Institute of Technology and Science ,Pilani, Goa
Campus, Goa and pursing Ph.D in the area of Power Quality Issues
pertaining to Grid Integration of WECS. He is an Associate Coordinator for
SPV+Wind hybrid power generation project funded by Govt. of India.
33

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