Transient Stability Improvement of SMIB With Unified Power Flow Controller(1)
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Transcript of Transient Stability Improvement of SMIB With Unified Power Flow Controller(1)
Transient Stability Improvement of SMIB with Unified Power Flow Controller
Abstract
The focus of this project is on a FACTS device known as the Unified Power Flow Controller (UPFC),
which can provide simultaneous control of basic power system parameters like voltage, Impedance
and phase angle. In this research work, two simulation models of single machine Infinite bus (SMIB)
system, i.e. with & without UPFC, has been developed. This simulation Models have been
incorporated into MATLAB based Power System Toolbox (PST) for their Transient stability analysis.
These models were analyzed for three phase fault , i.e. receiving end of the transmission line keeping
the location of UPFC fixed at the receiving end of the line. Transient stability was studied with the
help of curves of fault current, active & reactive power at receiving end, shunt injected voltage & its
angle, and series injected voltage & its angle and excitation voltage. With the addition of UPFC, the
magnitude of fault current reduces and oscillations of excitation voltage also reduce. Series and Shunt
parts of UPFC provide series and shunt injected voltage at certain different angles. Therefore, it can be
concluded that transient stability of SMIB is improved with the addition of Unified Power Flow
Controller.
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CHAPTER-1
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INTRODUCTION
TRANSMISSION INTERCONNECTIONS
Most if not all of the world's electric power supply systems are widely interconnected, involving
connections inside utilities' own territories which extend to inter-utility interconnections and then to
inter-regional and international connections. This is done for economic reasons, to reduce the cost of
electricity and to improve reliability of power supply.
1.1.1 Why We Need Transmission Interconnections
We need these interconnections because, apart from delivery, the purpose of the transmission network
is to pool power plants and load centers in order to minimize the total power generation capacity and
fuel cost. Transmission interconnections enable taking advantage of diversity of loads, availability of
sources, and fuel price in order to supply electricity to the loads at minimum cost with a required
reliability. In general, if a power delivery system was made up of radial lines from individual local
generators without being part of a grid system, many more generation resources would be needed to
serve the load with the same reliability, and the cost of electricity would be much higher. With that
perspective, transmission is often an alternative to a new generation resource. Less transmission
capability means that more generation resources would be required regardless of whether the system is
made up of large or small power plants. In fact small distributed generation becomes more
economically viable if there is a backbone of a transmission grid. One cannot be really sure about what
the optimum balance is between generation and transmission unless the system planners use advanced
methods of analysis which integrate transmission planning into an integrated value-based
transmission/generation planning scenario.
The cost of transmission lines and losses, as well as difficulties encountered in building new
transmission lines, would often limit the available transmission capacity. It seems that there are many
cases where economic energy or reserve sharing is constrained by transmission capacity, and the
situation is not getting any better. In a deregulated electric service environment, an effective electric
grid is vital to the competitive environment of reliable electric service.
Since the development of interconnection of large electric power systems, there have been
spontaneous system oscillations at very low frequencies in order of 0.2–3.0 Hz. Once started, they
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would continue for a long period of time. In some cases, they continue to grow causing system
separation due to the lack of damping of the mechanical In the past three decades, power system
stabilizers (PSSs) have been extensively used to increase the system damping for low frequency
oscillations. The power utilities worldwide are currently implementing PSSs as effective excitation
controllers to enhance the system stability [1–12]. However, there have been problems experienced
with PSSs over the years of operation.
Some of these were due to the limited capability of PSS, in damping only local and not inter area
modes of oscillations. In addition, PSSs can cause great variations in the voltage profile under severe
disturbances and they may even result in leading power factor operation and losing system stability
This situation has necessitated a review of the traditional power system concepts and practices to
achieve a larger stability margin, greater operating flexibility, and better utilization of existing power
systems. Flexible AC transmission systems (FACTS) have gained a great interest during the last few
years, due to recent advances in power electronics.
FACTS devices have been mainly used for solving various power system steady state control
problems such as voltage regulation, power flow control, and transfer capability enhancement. As
supplementary functions, damping the inter area modes and enhancing power system stability using
FACTS controllers have been extensively studied and investigated. Generally, it is not cost-effective
to install FACTS devices for the sole purpose of power system stability enhancement.
In this work, the current status of power system stability enhancement using FACTS controllers was
discussed and reviewed. This paper is organized as follows. The development and research interest of
FACTS is presented in Section 2. Section 3 discusses the potential of the first generation of FACTS
devices to enhance the low frequency stability while the potential of the second generation is discussed
in Section 4. Section 5 highlights some important issues in FACTS installations such as location,
feedback signals, coordination among different control schemes, and performance comparison. Major
real-world installations and recent developments in power electronic devices used in FACTS
controllers have been summarized in Section 6. Applications of FACTS to optimal power flow and
deregulated electricity market as steady state problems have been discussed in Section 7. Some
concluding remarks are highlighted in Section 8. About two hundred research publications are
reviewed, discussed, classified, and appended for a quick reference.
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CHAPTER-2
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INTRODUCTION TO TRANSIENTS
Transient:
A transient is a high voltage spike caused by external or internal transient sources
A transient is a high voltage spike of less than 10 microseconds in duration. Transients in power lines
may have voltage spikes up to 6,000 volts, and it is not unusual that spikes in commercial industrial
circuits excess 1,000 volts.
High voltage transients follows the path of least resistance to the ground, creates a damaging heat in
the circuit components and causing malfunctions and failure.
A transient event is a short-lived burst of energy in a system caused by a sudden change of state.
The source of the transient energy may be an internal event or a nearby event. The energy then couples
to other parts of the system, typically appearing as a short burst of oscillation.
Sources for transients: Transients, also more commonly known as surges, can be caused by
lightning or internal switching events. Both forms have different characteristics and are defined by
IEEE using two different types of waveforms.
The 8x20 waveform is associated with naturally occurring lightning events. The first number (8)
signifies the time in microseconds that it takes for the surge to reach 90 % of its peak value. This is
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also known as “rise” time. The second number (20) represents the time in microseconds that it takes
for the surge to decay from its peak to half value.
The 10x1000 waveform is associated with man-made surges, representing a rise time of 10 μsand a
decay time of 1000 μs. Even though we are looking at microseconds, it is obvious that the 10x1000
switching surge lasts longer then the 8x20 lightning event. Although it is not as strong as the 8x20
event, the longer duration allows the surge greater time to cause more damage across printed circuit
boards. Since today’s electronic equipment incorporates more transistors per chip and smaller trace
widths, surge vulnerability is increasing in significance.
While lighting is the most well known cause of equipment damaging transients, the more common
source are man-made surges. It is estimated that approximately 80 % of all surges are actually created
from within the system. In commercial facilities, generators, AC units and other large pieces of
equipment turning on and off often generate these switching surges that are hazardous to sensitive
electronics like computers
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CHAPTER-3
INTRODUCTION TO FACTS
From the part towards the future the supply of electrical energy developed from separated
utilities to large interconnected systems. In former times distributed power generation supplied load
centers within a limited supply area. These smaller systems were operated at lower voltage levels.
Nowadays there is increased power exchange over larger distances at highest system voltages allowing
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reverse sharing and competition. Electrical energy shall be made available at most locations at
minimum cost and at highest reliability.
Following problems have been observed in three phase systems:
Voltage control at various load conditions
Reactive power balance (voltage, transmission losses)
Stability problems at energy transfer over long distances
Increase of short circuit power in meshed systems
Coupling of asynchronous systems
Coupling of systems with different system frequencies
The last two problems can be solved using HVDC technology and the upper over can
be solved by proper use of reactive power compensation based on FACTS devices.
3.1 Shunt compensation:
Tasks of dynamic shunt compensation
Steady state and dynamic voltage control.
Reactive power control of dynamic loads.
Damping of active power oscillations.
Improvement of system stability.
Example of shunt compensation device:
SVC (Thyristor technology):
Conventional SVCs consist of thyristor controlled (TCR) and thyristor switched branches
(TSC/TSR) together with filter branches for harmonic current absorption.
3.2 Series compensation:
Tasks of dynamic series compensation
Reduction of load dependents on voltage drops.
Reduction of system transfer impedance.
Reduction of transmission angle.
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Increase of system stability.
Load flow control for specified power paths.
Damping of active power oscillations.
3.3 WHAT LIMITS THE LOADING CAPABILITY?
Assuming that ownership is not an issue, and the objective is to make the best use of the transmission
asset, and to maximize the loading capability (taking into account contingency conditions), what limits
the loading capability, and what can be done about it?
Basically, there are three kinds of limitations:
• Thermal
• Dielectric
• Stability
Thermal capability of an overhead line is a function of the ambient temperature, wind conditions,
condition of the conductor, and ground clearance. It varies perhaps by a factor of 2 to 1 due to the
variable environment and the loading history. The nominal rating of a line is generally decided on a
conservative basis, envisioning a statistically worst ambient environment case scenario. Yet this
scenario occurs but rarely which means that in reality, most of the time, there is a lot more real time
capacity than assumed. Some utilities assign winter and summer ratings, yet this still leaves a
considerable margin to play with.
There are also off-line computer programs that can calculate a line's loading capability based on
available ambient environment and recent loading history. Then there are the on-line monitoring
devices that provide a basis for on-line real-time loading capability. These methods have evolved over
a period of many years, and, given the age of automation (typified by GPS systems and low-cost
sophisticated communication services), it surely makes sense to consider reasonable, day to day, hour
to hour, or even real-time capability information. Sometimes, the ambient conditions can actually be
worse than assumed, and having the means to determine actual rating of the line could be useful.
During planning/design stages, normal loading of the lines is frequently decided on a loss evaluation
basis under assumptions which may have changed for a variety of reasons; however losses can be
taken into account on the real-time value basis of extra loading capability. Of course, increasing the
rating of a transmission circuit involves consideration of the real-time ratings of the transformers and
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other equipment as well, some of which may also have to be changed in order to increase the loading
on the lines. Real-time loading capability of transformers is also a function of ambient temperature,
aging of the transformer and recent loading history. Off-line and on-line loading capability monitors
can also be used to obtain real time loading capability of transformers. Also, the transformer also lends
itself to enhanced cooling. Then there is the possibility of upgrading a line by changing the conductor
to that of a higher current rating, which may in turn require structural upgrading. Finally, there is the
possibility of converting a single-circuit to a double-circuit line. Once the higher current capability is
available, then the question arises of how it should be used. Will the extra power actually flow and be
controllable? Will the voltage conditions be acceptable with sudden load dropping, etc.? The FACTS
technology can help in making an effective use of this newfound capacity.
Dielectric from an insulation point of view, many lines are designed very conservatively. For a given
nominal voltage rating, it is often possible to increase normal operation by +10% voltage (i.e., 500 kV-
550 kV) or even higher.
Care is then needed to ensure that dynamic and transient overvoltage’s are within limits. Modern
gapless arresters or line insulators with internal gapless arresters, or powerful thyristor-controlled
overvoltage suppressors at the substations can enable significant increase in the line and substation
voltage capability.
The FACTS technology could be used to ensure acceptable over-voltage and power flow conditions.
Stability
There are a number of stability issues that limit the transmission capability.
These include:
• Transient stability
• Dynamic stability
• Steady-state stability
• Frequency collapse
• Voltage collapse
• Sub synchronous resonance
3.4 BASIC TYPES OF FACTS CONTROLLERS
In general, FACTS Controllers can be divided into four categories:
• Series Controllers
• Shunt Controllers
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• Combined series-series Controllers
Series Controllers:
The series Controller could be variable impedance, such as capacitor, reactor, etc., or power
electronics based variable source of main frequency, sub synchronous and harmonic frequencies (or a
combination) to serve the desired need. In principle, all series Controllers inject voltage in series with
the line. Even variable impedance multiplied by the current flow through it, represents an injected
series voltage in the line. As long as the voltage is in phase quadrature with the line current, the series
Controller only supplies or consumes variable reactive power. Any other phase relationship will
involve handling of real power as well.
Shunt Controllers:
As in the case of series Controllers, the shunt Controllers may be variable impedance, variable source,
or a combination of these. In principle, all shunt Controllers inject current into the system at the point
of connection. Even variable shunt impedance connected to the line voltage causes a variable current
flow and hence represents injection of current into the line. As long as the injected current is in phase
quadrature with the line voltage, the shunt Controller only supplies or consumes variable reactive
power. Any other phase relationship will involve handling of real power as well.
Combined series-series Controllers:
This could be a combination of separate series controllers, which are controlled in a coordinated
manner, in a multi line transmission system. Or it could be a unified Controller, in which series
Controllers provide independent series reactive compensation for each line but also transfer real power
among the lines via the power link. The real power transfer capability of the unified series-series
Controller, referred to as Interline Power Flow Controller, makes it possible to balance both the real
and reactive power flow in the lines and thereby maximize the utilization of the transmission system.
Note that the term "unified" here means that the dc terminals of all Controller converters are all
connected together for real power transfer.
Combined series-shunt Controllers:
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This could be a combination of separate shunt and series Controllers, which are controlled in a
coordinated manner or a Unified Power Flow Controller with series and shunt elements.In principle,
combined shunt and series Controllers inject current into the system with the shunt part of the
Controller and voltage in series in the line with the series part of the Controller. However, when the
shunt and series Controllers are unified, there can be a real power exchange between the series and
shunt Controllers via the power link.
3.5 Relative importance of Different Types of Controllers
It is important to appreciate that the series-connected Controller impacts the driving voltage and hence
the current and power flow directly. Therefore, if the purpose of the application is to control the
current/power flow and damp oscillations, the series Controller for a given MVA size is several times
more powerful than the shunt Controller. As mentioned, the shunt Controller, on the other hand, is like
a current source, which draws from or injects current into the line. The shunt Controller is therefore a
good way to control voltage at and around the point of connection through injection of reactive current
(leading or lagging), alone or a combination of active and reactive current for a more effective voltage
control and damping of voltage oscillations. This is not to say that the series Controller cannot be used
to keep the line voltage within the specified range. After all, the voltage fluctuations are largely a
consequence of the voltage drop in series impedances of lines, transformers, and generators.
Therefore, adding or subtracting the FACTS Controller voltage in series (main frequency, sub
synchronous or harmonic voltage and combination thereof) can be the most cost-effective way of
improving the voltage profile. Nevertheless, a shunt controller is much more effective in maintaining a
required voltage profile at a substation bus. One important advantage of the shunt Controller is that it
serves the bus node independently of the individual lines connected to the bus. Series Controller
solution may require, but not necessarily, a separate series Controller for several lines connected to the
substation, particularly if the application calls for contingency outage of any one line. However, this
should not be a decisive reason for choosing a shunt-connected Controller, because the
required MVA size of the series Controller is small compared to the shunt Controller, and, in any case,
the shunt Controller does not provide control over the power flow in the lines. On the other hand,
series-connected Controllers have to be designed to ride through contingency and dynamic overloads,
and ride through or bypass short circuit currents. They can be protected by metal-oxide arresters or
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temporarily bypassed by solid-state devices when the fault current is too high, but they have to be
rated to handle dynamic and contingency overload. The above arguments suggest that a combination
of the series and shunt Controllers can provide the best of both, i.e., an effective power/ current flow
and line voltage control. For the combination of series and shunt Controllers, the shunt Controller can
be a single unit serving in coordination with individual line Controllers. This arrangement can provide
additional benefits (reactive power flow control) with unified Controllers. FACTS Controllers may be
based on thyristor devices with no gate turn-off (only with gate turn-on), or with power devices with
gate turn-off capability. Also, in general, as will be discussed in other chapters, the principal
Controllers with gate turn-off devices are based on the dc to ac converters, which can exchange active
and/ or reactive power with the ac system. When the exchange involves reactive power only, they are
provided with a minimal storage on the dc side. However, if the generated ac voltage or current is
required to deviate from 90 degrees with respect to the line current or voltage, respectively, the
converter dc storage can be augmented beyond the minimum required for the converter operation as a
source of reactive power only. This can be done at the converter level to cater to short-term (a few tens
of main frequency cycles) storage needs. In addition, another storage source such as a battery,
superconducting magnet, or any other source of energy can be added in parallel through an electronic
interface to replenish the converter's dc storage. Any of the converter-based, series, shunt, or combined
shunt-series Controllers can generally accommodate storage, such as capacitors, batteries, and
superconducting magnets, which bring an added dimension to FACTS technology. The benefit of an
added storage system (such as large dc capacitors, storage batteries, or superconducting magnets) to
the Controller is significant. A Controller with storage is much more effective for controlling the
system dynamics than the corresponding Controller without the storage. This has to do with dynamic
pumping of real power in or out of the system as against only influencing the transfer of real power
within the system as in the case with Controllers lacking storage. Here also, engineers have to rethink
the role of storage, particularly the one that can deliver or absorb large amounts of real power in short
bursts. A converter-based Controller can also be designed with so-called high pulse order or with pulse
width modulation to reduce the low order harmonic generation to a very low level. A converter can in
fact be designed to generate the correct waveform in order to act as an active filter. It can also be
controlled and operated in a way that it balances the unbalance voltages, involving transfer of energy
between phases. It can do all of these beneficial things simultaneously if the converter is so designed.
Given the overlap of benefits and attributes, it can be said that for a given problem one needs to have
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an open mind during preliminary evaluation of series versus shunt and combination Controllers and
storage versus no storage.
3.6 Shunt Connected Controllers
Static Synchronous Compensator (STATCOM):
A Static synchronous generator operated as a shunt-connected static Var compensator whose
capacitive or inductive output current can be controlled independent of the ac system voltage.
STATCOM is one of the key FACTS Controllers. It can be based on a voltage sourced or current-
sourced converter. As mentioned before, from an overall cost point of view, the voltage-sourced
converters seem to be preferred, and will be the basis for presentations of most converter-based
FACTS Controllers. For the voltage-sourced converter, its ac output voltage is controlled such that it is
just right for the required reactive current flow for any ac bus voltage dc capacitor voltage is
automatically adjusted as required to serve as a voltage source for the converter. STATCOM can be
designed to also act as an active filter to absorb system harmonics. STATCOM as defined above by
IEEE is a subset of the broad based shunt connected Controller which includes the possibility of an
active power source or storage on the dc side so that the injected current may include active power.
Static Synchronous Generator (SSG):
A static self-commutated switching power converter supplied from an appropriate electric energy
source and operated to produce a set of adjustable multiphase output voltages, which may be coupled
to an ac power system for the purpose of exchanging independently controllable real and reactive
power. Clearly SSG is a combination of STATCOM and any energy source to supply or absorb
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power. The term, SSG, generalizes connecting any source of energy including a battery, flywheel,
superconducting magnet, large dc storage capacitor, another rectifier/inverter, etc. An electronic
interface known as a "chopper" is generally needed between the energy source and the converter. For a
voltage-sourced converter, the energy source serves to appropriately compensate the capacitor charge
through the electronic interface and maintain the required capacitor voltage. Within the definition of
SSG is also the Battery Energy Storage System (BESS), defined by IEEE as:
Battery Energy Storage System (BESS):
A chemical-based energy storage system using shunt connected, voltage-source converters capable of
rapidly adjusting the amount of energy which is supplied to or absorbed from an ac system. . For
transmission applications, BESS storage unit sizes would tend to be small (a few tens of MWHs), and
if the short-time converter rating was large enough, it could deliver MWs with a high MW/MWH ratio
for transient stability. The converter can also simultaneously absorb or deliver reactive power within
the converter's MVA capacity. When not supplying active power to the system, the converter is used
to charge the battery at an acceptable rate. Yet another subset of SSG, suitable for transmission
applications, is the Superconducting Magnetic Energy Storage (SMES), which is defined by IEEE .
Superconducting Magnetic Energy Storage (SMES):
A Superconducting electromagnetic energy storage device containing electronic converters that
rapidly injects and/or absorbs real and/or reactive power or dynamically controls power flow in an ac
system. Since the dc current in the magnet does not change rapidly, the power input or output of the
magnet is changed by controlling the voltage across the magnet with a suitable electronics interface for
connection to a STATCOM.
Static Var Compensator (SVC):
A shunt-connected static Var generator or absorber whose output is adjusted to exchange capacitive or
inductive current so as to maintain control specific parameters of the electrical power system (typically
bus voltage). This is a general term for a thyristor-controlled or thyristor-switched reactor, and/or
thyristor-switched capacitor or combination SVC is based on thyristors without the gate turn-off
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capability. It includes separate equipment for leading and lagging vars; the thyristor-controlled or
thyristor-switched reactor for absorbing reactive power and thyristor-switched capacitor for supplying
the reactive power. SVC is considered by some as a lower cost alternative to STATCOM, although
this may not be the case if the comparison is made based on the required performance and not just the
MVA size.
Thyristor Controlled Reactor (TCR):
A shunt-connected, thyristor-controlled inductor whose effective reactance is varied in a continuous
manner by partial-conduction control of the thyristor valve. TCR is a subset of SVC in which
conduction time and hence, current in a shunt reactor is controlled by a thyristor-based ac switch with
firing angle control
Static Var Generator or Absorber (SVG):
A static electrical device, equipment, or system that is capable of drawing controlled capacitive and/or
inductive current from an electrical power system and thereby generating or absorbing reactive power.
Generally considered to consist of shunt-connected, thyristor-controlled reactor(s) and/or thyristor-
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switched capacitors.The SVG, as broadly defined by IEEE, is simply a reactive power (var) source
that, with appropriate controls, can be converted into any specific- or multipurposereactive shunt
compensator. Thus, both the SVC and the STATCOM are static var generators equipped with
appropriate control loops to vary the var output so as to meet specific compensation objectives.
Static Var System (SVS):
A combination of different static and mechanically-switched var compensators whose outputs are
coordinated.
Thyristor Controlled Braking Resistor (TCBR):
A shunt-connected thyristor-switched resistor, which is controlled to aid stabilization of a power
system or to minimize power acceleration of a generating unit during a disturbance. TCBR involves
cycle-by-cycle switching of a resistor (usually a linear resistor) with a thyristor-based ac switch with
firing angle control. For lower cost, TCBR may be thyristor switched, i.e., without firing angle control.
However, with firing control, half-cycle by half-cycle firing control can be utilized to selectively damp
low-frequency oscillations.
3.7 Series Connected Controllers
Static Synchronous Series Compensator (SSSC):
A static synchronous generator operated without an external electric energy source as a series
compensator whose output voltage is in quadrature with, and controllable independently of, the line
current for the purpose of increasing or decreasing the overall reactive voltage drop across the line and
there by controlling the transmitted electric power. The SSSC may include transiently rated energy
storage or energy absorbing devices to enhance the dynamic behavior of the power system by
additional temporary real power compensation, to increase or decrease momentarily, the overall real
(resistive) voltage drop across the line. SSSC is one the most important FACTS Controllers. It is like a
STATCOM, except that the output ac voltage is in series with the line. It can be based on a voltage
sourced converter or current-sourced converter. Usually the injected voltage in series would be quite
small compared to the line voltage, and the insulation to ground would be quite high. With an
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appropriate insulation between the primary and the secondary of the transformer, the converter
equipment is located at the ground potential unless the entire converter equipment is located on a
platform duly insulated from ground. The transformer ratio is tailored to the most economical
converter design.
Interline Power Flow Controller (IPFC):
The IPFC is a recently introduced Controller and thus has no IEEE definition yet. A possible definition
is: The combination of two or more Static Synchronous Series Compensators which are coupled via a
common dc link to facilitate bi-directional flow of real power between the ac terminals of the SSSCs,
and are controlled to provide independent reactive compensation for the adjustment of real power flow
in each line and maintain the desired distribution of reactive power flow among the lines. The IPFC
structure may also include a STA TCOM, coupled to the IFFC's common dc link, to provide shunt
reactive compensation and supply or absorb the overall real power deficit of the combined SSSCs.
Thyristor Controlled Series Capacitor (TCSC):
A capacitive reactance compensator which consists of a series capacitor bank shunted by a thyristor-
controlled reactor in order to provide a smoothly variable series capacitive reactance.
Thyristor-Switched Series Capacitor (TSSC):
A capacitive reactance compensator which consists of a series capacitor bank shunted by a thyristor-
switched reactor to provide a stepwise control of series capacitive reactance. Instead of continuous
control of capacitive impedance, this approach of switching inductors at firing angle of 90 degrees or
180 degrees but without firing angle control, could reduce cost and losses of the Controller. It is
reasonable to arrange one of the modules to have thyristor control, while others could be thyristor
switched.
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Thyristor-Controlled Series Reactor (TCSR):
An inductive reactance compensator which consists of a series reactor shunted by a thyristor
controlled reactor in order to provide a smoothly variable series inductive reactance. When the firing
angle of the thyristor controlled reactor is 180 degrees, it stops conducting, and the uncontrolled
reactor acts as a fault current limiter. As the angle decreases below 180 degrees, the net inductance
decreases until firing angle of 90 degrees, when the net inductance is the parallel combination of the
two reactors. As for the TCSC, the TCSR may be a single large unit or several smaller series units.
Thyristor-Switched Series Reactor (TSSR):
An inductive reactance compensator which consists of a series reactor shunted by a thyristor-
controlled switched reactor in order to provide a stepwise control of series inductive reactance. This is
a complement of TCSR, but with thyristor switches fully on or off (without firing angle control) to
achieve a combination of stepped series inductance.
3.8 Combined Shunt and Series Connected Controllers
Unified Power Flow Controller (UPFC):
A combination of static synchronous compensator (STATCOM) and a static series compensator
(SSSC) which are coupled via a common dc link, to allow bidirectional flow of real power between
the series output terminals of the SSSC and the shunt output terminals of the STATCOM, and are
controlled to provide concurrent real and reactive series line compensation without an external electric
energy source. The UPFC, by means of angularly unconstrained series voltage injection, is able to
control, concurrently or selectively, the transmission line voltage, impedance, and angle or,
alternatively, the real and reactive power flow in the line. The UPFC may also provide independently
controllable shunt reactive compensation.
Thyristor-Controlled Phase Shifting Transformer (TCPST):
A phase-shifting transformer adjusted by thyristor switches to provide a rapidly variable phase angle.
In general, phase shifting is obtained by adding a perpendicular voltage vector in series with a phase.
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This vector is derived from the other two phases via shunt connected transformers. The perpendicular
series voltage is made variable with a variety of power electronics topologies. A circuit concept that
can handle voltage reversal can provide phase shift in either direction. This Controller is also referred
to as Thyristor-Controlled Phase Angle Regulator (TCPAR).
Interphase Power Controller (IPC):
A series-connected controller of active and reactive power consisting, in each phase, of inductive and
capacitive branches subjected to separately phase-shifted voltages. The active and reactive power can
be set independently by adjusting the phase shifts active and capacitive impedance form a conjugate
pair, each terminal of the IPC is a passive current source dependent on the voltage at the other
terminal. This is a broad based concept of series Controller, which can be designed to provide control
of active and reactive power end/or the branch impedances, using mechanical or electronic switches.
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CHAPTER-4
INTRODUCTION OF UPFC
Unified Power Flow Controller (UPFC) is one of the FACTS devices, which can control power
system parameters such as terminal voltage, line impedance and phase angle. Therefore, it can be used
not only for power flow control, but also for power system stabilizing control.
Unified Power Flow Controllers are capable of directing real and reactive power flows through
a designated route and regulating the system voltage through reactive power compensation. Thus,
UPFC provides several features for power flow control namely: voltage control through shunt
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compensation, real power flow control through quadrature voltage injection and reactive power flow
control through in-phase voltage injection.
This report, however, investigates the three control methods, namely, voltage control through
shunt compensation, real power flow control through quadrature voltage injection and reactive power
flow control through in-phase voltage injection for the UPFC in order to improve the stability of the
power system, thus providing the security for the increased power flow.
Power System Model with UPFC
A simple power system is chosen and studied in PSCAD/EMTDC environment in order to
evaluate the performance of the UPFC with different control strategies. The power system whose
parameters are given in appendix comprises a 100MVA, 16.64kV synchronous generator connected to
an infinite bus through a transmission line and a transformer stepping up the voltage to 330kV. The
generator is assumed to have Automatic Voltage Regulator (AVR) controlling its terminal voltage.
The single-machine infinite-bus (SMIB) system used in this study is for better understanding of
transient stability of Nigerian Grid System since the purpose for the use of UPFC is to improve
transient stability of the system. The UPFC is placed between bus 2 and bus 3 on the transmission line
as shown in Figure 1. The UPFC is designed to control the power (real and reactive) through line as
well as the voltage at bus 3 using PWM power controller.
Figure 1. Single-machine infinite bus system with UPFC
Generator modelA detailed dynamic generator model for the single-machine infinite bus system is used for a
UPFC controller design to give more accurate controller parameters. It is given as follows [7, 8]:
Page | 23
Mechanical equations:
(1)
(2)
(3)
where ;
is the power angle of the generator;
is the power angle of the generator at the operating point;
is the relative speed of the generator;
is the mechanical input power (assumed constant);
is the real power delivered by the generator;
is the synchronous machine speed;
Dm is the per unit damping constant; H is the inertia constant.
Generator electrical dynamics:
(4)
where is the transient Electromotive force (EMF) in the quadrature axis of the generator;
Eq(t) is the EMF in the quadrature axis; Ef (t) is the equivalent EMF in the excitation coil; is the
direct axis open-circuit transient time constant.
Electrical equations:
(5)
(6)
(7)
Page | 24
(8)
(9)
(10)
(11)
where is the transient Electromotive force (EMF) in the quadrature axis of the generator;
Eq(t) is the EMF in the quadrature axis;
Q(t) is the reactive power;
If(t) is the excitation current;
Iq(t) is the quadrature axis current;
xad is the mutual reactance between the excitation coil and the stator coil;
xd is the direct axis reactance of the generator;
xd;is the direct axis transient reactance of the generator ׳
xds;is the mutual transient reactance between the direct axis of generator and transformer ׳ δ(t) is the
power angle of the generator;
xds is the mutual reactance between the direct axis of generator and transformer;
xT is the reactance of the step up transformer;
xE is the reactance of the Thevenin equivalent viewed from bus ;
VE is the voltage magnitude of the Thevenin equivalent viewed from bus .
UPFC model and control strategies
The mathematical UPFC model was derived with the aim of being able to study the relations
between the electrical transmission system and UPFC in steady-state conditions. The basic scheme of
this model is shown in Figure 2.
Page | 25
Figure 2. Model of UPFC
The mathematical UPFC model was derived with the aim of being able to study the relations
between the electrical transmission system and UPFC in steady-state conditions. The basic scheme of
this model is shown in Figure 2. This figure represents a single-line diagram of a simple transmission
line with impedance, UPFC, sending-end voltage source and receiving-end voltage source. According
to Figure 3, the power circulation and the line flow are calculated by the following expressions :
(neglecting losses) (12)
(13)
(14)
where Psh is the power at the shunt side of the UPFC;
Pse is the power at the series part of UPFC;
PL is the real power flow; QL is the reactive power flow;
V2 is the voltage at the bus2;
Vm2 is the series voltage of UPFC;
V1 is the voltage at bus1;
Xt2 is the reactance between buses 1 and 2;
θ1and θ2 are the angles of buses 1 and 2 respectively.
Page | 26
CHAPTER-5
Page | 27
MODELING OF SMIB
SMALL SIGNAL ANALYSIS REPRESENTATION:
Consider a single machine system shown in Fig.5.1. For simplicity, we will
assume a synchronous machine represented by model 1.0 neglecting damper windings both
in the d and q axes. (It is possible to approximate the effects of damper windings by a
nonlinear damping term, if necessary). In addition, the armature resistance of the machine is
neglected and the excitation system represented by a single time-constant system shown in
Fig. 5.2.
Figure 5.1: A single machine system
Page | 28
Figure 5.2: Excitation system
The algebraic equations of the stator are
E1q + X1
d id = Vq (5.1)
-Xqiq = Vd (5.2)
The complex terminal voltage can be expressed as
VQ + jVD = (Vq + jVd )ej = (iq + jid) (Re + jXe) ej + Eb0
From which
(Vq + jVd) = (iq + jid) (Re + jXe) + Ebe-j (5.3)
Separating real and imaginary parts, Eq. (6.3) can be expressed as
Vq = Reiq - Xe id + Eb cos (5.4)
Vd = Reid + Xeiq - Eb sin (5.5)
Substituting Eqs. (5.4) and (5.5) in Eqs. (5.1) and (5.2), we get,
……….. (5.6)
The expressions for id and iq are obtained from solving (5.6) and are given below
Page | 29
id = [Re Eb sin + (Xq + Xe) ( Eb cos - E1q)]/A (5.7)
iq = [(X1d + Xe )Eb sin - Re(Eb cos - E1
q)]/A (5.8)
Where
A= (X1d + Xe ) (Xq + X) + R2
e (5.9)
Linearizing Eqs. (6.7) and (6.8) we get
id = C1 + C2 E1q (5.10)
iq = C3 + C4 E1q (5.11)
Where
C1 = [ReEb coso - (Xq + Xe) ( Ebsino ]/A
C2 = - (Xq + Xe)/A
C3 = [(X1d + Xe ) Eb coso+ ReEbsino ]/A
C4 = Re/A
Linearizing Eqs. (5.1) and (5.2), and substituting from Eqs. (5.10) and (5.11), we get
Vq = X1d C1 + (1 + X1
d C2 ) E1q (5.12)
Vd = - XqC3 - XqC4 E1q (5.13)
It is to noted that the subscript ‘o’ indicates operating value of the variable.
5.1 ROTOR MECHANICAL EQUATIONS AND TORQUE ANGLE LOOP:
The rotor mechanical equations are
d/dt = B(Sm - Smo) (5.14)
2H(dSm/dt) = - DSm + Tm - Te (5.15)
Page | 30
Te = E1q iq - ( Xq - X1
d) id iq (5.16)
Linearizing Eq. (5.16) we get
Te = [E1qo - ( Xq - X1
d) ido] iq + iqoE1q - ( Xq - X1
d) iqo id (5.17)
Substituting Eqs. (5.10) and (5.11) in Eq. (5.17), we can express Te as
Te = K1 + K2E1q (5.18)
Where
K1 = EqoC3 - ( Xq - X1d) iqoC1 (5.19)
K2 = EqoC4 + iqo - ( Xq - X1d) iqoC2 (5.20)
Eqo = E1qo - ( Xq - X1
d) ido (5.21)
Linearizing Eqs. (5.14) and (5.15) and applying laplace transform, we get
= BSm/s = B/s (5.22)
Sm = [Tm - Te - DSm ]/2Hs (5.23)
The combined Eqs. (5.18), (5.22) and Eq. (5.23) represent a block diagram shown
in fig.5.3. This represents the torque-angle loop of the synchronous machine.
5.2 REPRESENTATION OF FLUX DECAY:
The equation for the field winding is expressed as
T1dodE1
q /dt = Efd - E1q + ( Xd - X1
d )id (5.24)
Page | 31
Figure 5.4. Representation of flux decay
Linearizing Eq. (5.24) and substituting from Eq. (5.10) we have
T1dodE1
q /dt = Efd -E1q + + Vdo E1
q) (5.25)
Taking Laplace transform of (5.25), we get,
(1+sT1doK3 ) E1
q = K3Efd - K3 K4 (5.26)
Where
K3 = 1/ [1- ( Xd - X1d ) C2] (5.27)
K4 = -( Xd - X1d )C1 (5.28)
Eq. (5.26) can be represented by the block diagram shown in Fig.5.4
5.3 REPRESENTATION OF THE EXCITATION SYSTEM:
The block diagram of the excitation system considered is shown in Fig. 5.2. The
same block diagram omitting the limiter can also represent the linearized equations of this system.
For the present analysis we can ignore the auxiliary signal V s. The perturbation in the terminal
voltage Vt can be expressed as
Vt = VdoVd/ Vto + VqoVq/ Vto (5.29)
Page | 32
Substituting from Eqs. (5.12) and (5.13) in (5.29), we get
Vt = K5 + K6E1q (5.30)
Figure 5.5: Excitation system block diagram
where
K5 = - (Vdo/ Vto)XqC3 + (Vqo/ Vto) X1d C1 (5.31)
K6 = - (Vdo/ Vto)XqC4 + (Vqo/ Vto) (1+ X1d C2) (5.32)
Using Eq. (5.30) the block diagram of the excitation system is shown in Fig. 5.5.
The coefficients K1 to K6 defined in Eqs (5.19), (5.20), (5.27), (5.28), (5.31) and (5.32) are
termed as Heffron-Phillips constants. They are dependent on the machine parameters and
the operating conditions. Generally, K1, K2, K3 and K6 are positive. K4 is also mostly positive
for cases when Re is high. K5 can be either positive or negative. K5 is positive for low to
medium external impedances (Re +jXe) and low to medium loadings. K5 is usually negative for
moderate to high external impedances and heavy loadings.
Page | 33
5.4 COMPUTATION OF HEFFRON-PHILLIPS CONSTANTS FOR
LOSSLESS NETWORK:
For Re = 0, the expressions for the constants K1 to K6 are simplified. As the
armature resistance is already neglected, this refers to a lossless network on the stator side.
The expressions are given below
Fig 5.5. Block Diagram of the Excitation system
K1= [(EbEq0 cosδ0)/ (Xe+Xq)] + {[(Xq-Xq1) (Ebiq0sinδ0)]/ (Xe+Xd
1)} (5.33)
K2= {[(Xe+Xq) (iq0)]/ (Xe+Xd1)} = (Ebsinδ0)/ (Xe+Xd
1) (5.34)
K3= (Xe+Xd1)/ (Xd+Xe) (5.35)
K4= [(Xd-Xd1) (Ebsinδ0)]/ (Xd
1+Xe) (5.36)
K5= {(XqVd0Ebcosδ0)/ [(Xe+Xq0) (Vt0)]}-(Xd1Vq0Ebsinδ0)/ [(Xe+Xd
1) (Vt0)] (5.37)
K6= (Xe Vq0)/ [(Xe+Xd1) (Vt0)] (5.38)
It is not difficult to see that for Xe > 0, the constants K1, K2, K3, K4 and K6 are positive. This
is because o is generally less than 90degrees and iqo is positive. is independent of the
Page | 34
operating point and less than unity (as X1d < Xd). Note that Xe is generally positive unless
the generator is feeding a large capacitive load (which is not realistic).
5.5 SYSTEM REPRESENTATION:
The system block diagram, consisting of the representation of the rotor
swing equations, flux decay and excitation system, is obtained by combining the component
blocks shown in Figs. 5.3 and 5.5. The overall block diagram is shown in Fig. 5.6. Here the
damping term (D) in the swing equations is neglected for convenience. (Actually D is
generally small and neglecting it will give slightly pessimistic results)
Fig 5.6. Over all system block diagram
For a static exciter, TE is very small and for large values of Ke the
electrical torque compound Te2 is related to by the following relation
Te2(s)/ (s) = - (K2 K5/ K6)/ [sT1do/ ( K6 KE) +1] (5.39)
Page | 35
CHAPTER-6
Page | 36
MODELING OF UNIFIED POWER FLOW CONTROLLER
6.1 MODIFIED HEFFRON-PHILLIPS SMALL PERTURBATION TRANSFER
FUNCTION MODEL OF A SMIB SYSTEM INCLUDING UPFC:
Figure 6.1 shows the small perturbation transfer function block diagram of a
machine-infinite bus system including UPFC relating the pertinent variables of electric torque,
speed, angle, terminal voltage, flux linkage, UPFC control parameters, and dc link voltage. This
model has been obtained by modifying the basic heffron-phillips model including UPFC. This
linear model has been developed by linearising the non-linear differential equations around a
nominal operating point. The twenty-eight constants of the model depend on the system
parameters and the operating condition in figure 6.1, [∆u] is the column vector while [Kpu], [Kqu],
[Kvu] and [Kcu] are the row vectors as defined below,
[∆u] = [∆mE ∆δE ∆mB ∆δB]T (6.1)
[Kpu] = [Kpe Kpδe Kpb Kpδb] (6.2)
[Kvu] = [Kve Kvδe Kvb Kvδb] (6.3)
[Kqu] = [Kqe Kqδe Kqb Kqδb] (6.4)
[Kcu] = [Kce Kcδe Kcb Kcδb] (6.5)
The significant control parameters of UPFC are,
mB modulating index of series inverter. By controlling mB, the magnitude of series
injected voltage can be controlled, there by controlling the reactive power compensation.
δB phase angle of series inverter which when controlled results in the real power
exchange
Page | 37
mE modulating index of shunt inverter. By controlling mE, the voltage at a bus
where UPFC is installed, is controlled through reactive power compensation.
δE phase angle of the shunt inverter, which regulates the dc voltage at dc link
ANALYSIS
Computation of constants of the model
The initial d-q axes voltage and current components and
torque angle needed for computing K-constants for the nominal operating condition are computed
and are as follows:
Q = 0.1670 pu Ebdo = 0.7331 pu
edo = 0.3999 pu Ebqo = 0.6801 pu
eqo = 0.9166 pu Ido = 0.4729 pu
δo = 47.13080 pu Iqo = 0.6665 pu
The K-constants of the model computed for nominal operating condition and system parameters
are
K1 = 0.3561 Kpb = 0.6667 Kpδe = 1.9315
K2 = 0.4567 Kqb = 0.6118 Kqδe = -0.0404
K3 = 1.6250 Kvb = -0.1097 Kvδe = 0.1128
K4 = 0.09164 Kpe = 1.4821 Kcb = 0.1763
K5 = -0.0027 Kqe = 2.4918 Kce = 0.0018
K6 = 0.0834 Kve = -0.5125 Kcδb = 0.4987
K7 = 0.1371 Kpδb = 0.0924 Kcδe = 0.4987
K8 = 0.0226 Kqδb = -0.0050 Kpd = 0.0323
Page | 38
K9 = -0.0007 Kvδb = 0.0061 Kqd = 0.0524
Kvd = -0.0107
Figure6.1 Modified Hefrron-Phillips model of SMIB system with UPFC
For this operating condition, the eigen-values of the system are obtained and it is clearly seen that
system is unstable.
Page | 39
6.2 DESIGN OF DAMPING CONTROLLERS:
The damping controllers are designed to produce an electrical
torque in phase with the speed deviation. The four control parameters of the UPFC (i.e., mB,mE, δB,
δE) can be modulated in order to produce the damping torque. The speed deviation Δω is
considered as the input to the damping controllers. The four alternative UPFC based damping
controllers are examined in the present work.
Damping controller based on UPFC control parameter m B shall
henceforth by denoted as damping controller (mB). Similarly damping controllers based on mE, δB,
and δL shall henceforth be denoted as damping controller (mE), damping controller (δB), and
damping controller (δE), respectively.
The structure of UPFC based damping controller is shown in fig 7.2. It
consists of gain, signal washout and phase compensator blocks. The parameters of the damping
controller are obtained using the phase compensation technique. The detailed step-by-step
produce for computing the parameters of the damping controllers using phase compensation
technique is given below:
Δu
Δω
Gain
Signal washout Phase compensator
Figure6.2 Structure of UPFC based damping controller
1. Computation of natural frequency of oscillation ωn from the mechanical loop
Page | 40
KdcsTω/(1+ sTω)
Ge(s) = (1+sT1)/ (1+sT2)
wn = (K1ω0/M)1/2 (6.6)
2. Computation of ∟GEPA (Phase lag between ∆u and Δ Pe) at s = jωn. Let it be γ.
3. Design of phase lead/lag compensator Gc:
The phase lead/lag compensator Gc is designed to provide the required degree of phase
compensation. For 100% phase compensation,
∟Gc(jωn)+ ∟GEPA(jωn ) = 0 (6.7)
Assuming one lead-lag network, T1 = a T2, the transfer function of the phase compensator
becomes,
Gc(s) = (1+saT2)/ (1+sT 2) (6.8)
Since the phase angle compensated by the lead –lag network is equal to – γ, the parameters a
and T2 are computed as,
a = (1+sin γ)/ (1-sin γ) (6.9)
T2 =1/ (ωn√a) (6.10)
4. computation of optimum gain Kdc:
The required gain setting Kdc for the desired value of damping ratio ζ =0.05 is obtained as,
Kdc = (2ζωBM)/ (│Gc(s) ││GEPA (S) │) (6.11)
Where
│Gc(s) │and│GEPA(S) │ are evaluated at s = jωn
The signal washout is the high pass filter that prevents steady changes in the speed from
modifying the UPFC input parameter. The value of the washout time constant Tw should be high
enough to allow signals associated with oscillations in rotor speed to pass unchanged. From the
Page | 41
viewpoint of the washout function, the value of Tw is not critical and may in the range of 1s to
20s. Tw equal to 10s is chosen in the present studies.
CHAPTER-7
MAT LAB/ SIMULINK
MAT LAB:
Page | 42
MATLAB is a programming environment for algorithm development, data analysis, visualization, and
numerical computation. Using MATLAB, you can solve technical computing problems faster than
with traditional programming languages, such as C, C++, and Fortran.
You can use MATLAB in a wide range of applications, including signal and image processing,
communications, control design, test and measurement, financial modeling and analysis, and
computational biology. For a million engineers and scientists in industry and academia, MATLAB is
the language of technical computing.
The MATLAB application is built around the MATLAB language, and most use of MATLAB
involves typing MATLAB code into the Command Window (as an interactive mathematical shell), or
executing text files containing MATLAB code and functions.
MATLAB is a high-level language and interactive environment that lets you focus on your course
work and applications, rather than on programming details. MATLAB enables you to solve many
numerical problems in a fraction of the time it takes to write a program in a lower-level language, such
as Java™, C, C++, or Fortran. MATLAB also enables analysis and visualization of data using
automation capabilities, avoiding the manual repetition common with other products.
Programming and developing algorithms are faster with MATLAB than with traditional languages
because MATLAB supports interactive development.
You do not need to perform low-level administrative tasks, such as declaring variables and allocating
memory. Thousands of engineering and mathematical functions are available, eliminating the need to
code and test them yourself.
MATLAB provides all the features of a traditional programming language, including arithmetic
operators, flow control, data structures, data types, object-oriented programming (OOP), and
debugging features.
MATLAB helps you better understand and apply concepts in a wide range of engineering, science, and
mathematics applications, including signal and image processing, communications, control design, test
and measurement, financial modeling and analysis, and computational biology. Add-on toolboxes
extend the MATLAB environment to solve particular classes of problems in these application areas.
(Toolboxes are collections of task- and application-specific MATLAB functions, available separately.)
MATLAB currently has over a million users and is recognized by employers worldwide as a useful
tool to increase the productivity of engineers and scientists.
Page | 43
Variables
Variables are defined using the assignment operator, =. MATLAB is a weekly dynamically typed
programming language. It is a weekly typed language because types are implicitly converted. It is a
dynamically typed language because variables can be assigned without declaring their type, except if
they are to be treated as symbolic objects, and that their type can change. Values can come from
constants, from computation involving values of other variables, or from the output of a function. For
example:
>> x = 17
x =
17
>> x = 'hat'
x =
hat
>> y = x + 0
y =
104 97 116
>> x = [3*4, pi/2]
x =
12.0000 1.5708
>> y = 3*sin(x)
y =
-1.6097 3.0000
File extensions
Native
.fig
MATLAB Figure
.m
MATLAB function, script, or class
.mat
MATLAB binary file for storing variables
.mex...
MATLAB executable (platform specific, e.g. ".mexmac" for the Mac, ".mexglx" for Linux,
etc.)
.p
Page | 44
MATLAB content-obscured .m file (result e() )
Third-party
.jkt
GPU Cache file generated by Jacket for MATLAB (AccelerEyes)
.mum
MATLAB CAPE-OPEN Unit Operation Model File (AmsterCHEM)
Secondary programming
MATLAB also carries secondary programming which incorporates the MATLAB standard code into a
more user friendly way to represent a function or system.
Interfacing with other languages
MATLAB can call functions and subroutines written in the C programming language or Fortran. A
wrapper function is created allowing MATLAB data types to be passed and returned. The dynamically
loadable object files created by compiling such functions are termed "MEX-files" (for MATLAB
executable).
Libraries written in Java, ActiveX or .NET can be directly called from MATLAB and many
MATLAB libraries (for example XML or SQL support) are implemented as wrappers around Java or
ActiveX libraries. Calling MATLAB from Java is more complicated, but can be done with MATLAB
extension, which is sold separately by Math Works, or using an undocumented mechanism called JMI
(Java-to-Mat lab Interface), which should not be confused with the unrelated Java Metadata
Interface that is also called JMI.
As alternatives to the MuPAD based Symbolic Math Toolbox available from Math Works, MATLAB
can be connected to Maple or Mathematics. Libraries also exist to import and export MathML.
SIMULINK:
Simulink, developed by Math Works, is a commercial tool for modeling, simulating and analyzing
multi-domain dynamic systems. Its primary interface is a graphical and a customizable set of
Page | 45
block libraries. It offers tight integration with the rest of the MATLAB environment and can either
drive MATLAB or be scripted from it. Simulink is widely used in control theory and digital signal
processing for multi-domain simulation and Model-Based Design.
Simulink Verification and Validation enables systematic verification and validation of models through
modeling style checking, requirements traceability and model coverage analysis. Simulink Design
Verifier uses formal methods to identify design errors like integer overflow, division by zero, dead
logic and assertion violation, to generate test vectors and for model checking.
Use the Simulink interactive tools for modeling, simulating, and analyzing dynamic systems, including
controls, signal processing, communications, and other complex systems. Simulink supports linear and
nonlinear systems, modeled in continuous time, sampled time, or a hybrid of the two. Systems
also can be multirate (having different parts that are sampled or updated at different rates).
You can easily build new models, or take an existing model and add to it. With instant access to all the
MATLAB analysis tools, you can analyze and visualize the results. The Simulink environment
provides a sense of fun and discovery in modeling and simulation. It encourages you to pose a
question, model it, and see what happens.
Thousands of engineers around the world use Simulink to model and solve real problems. Simulink is
a tool that you can use throughout your professional career.
Key Features
Extensive and expandable libraries of predefined blocks
Interactive graphical editor for assembling and managing intuitive block diagrams
Ability to manage complex designs by segmenting models into hierarchies of design components
Model Explorer to navigate, create, configure, and search all signals, parameters, properties, and
generated code associated with your model
Application programming interfaces (APIs) that let you connect with other simulation programs and
incorporate hand-written code
MATLAB Function blocks for bringing MATLAB algorithms into Simulink and embedded system
implementations
Page | 46
Simulation modes (Normal, Accelerator, and Rapid Accelerator) for running simulations interpretively
or at compiled C-code speeds using fixed- or variable-step solvers
Graphical debugger and profiler to examine simulation results and then diagnose performance and
unexpected behavior in your design
Full access to MATLAB for analyzing and visualizing results, customizing the modeling environment,
and defining signal, parameter, and test data
Model analysis and diagnostics tools to ensure model consistency and identify modeling errors
Getting Started with Simulink
Build and simulate a model.
Add-on products extend Simulink software to multiple modeling domains, as well as provide tools for
design, implementation, and verification and validation tasks.
Simulink is integrated with MATLAB, providing immediate access to an extensive range of tools that
let you develop algorithms, analyze and visualize simulations, create batch processing scripts,
customize the modeling environment, and define signal, parameter, and test data.
You can construct a model by assembling design components, each of which could be a separate
model.
Creating and Working with Models
With Simulink®, you can quickly create, model, and maintain a detailed block diagram of your system
using a comprehensive set of predefined blocks. Simulink provides tools for hierarchical modeling,
data management, and subsystem customization, making it easy to create concise, accurate
representations, regardless of your system's complexity.
Page | 47
Selecting and Customizing Blocks
Simulink software includes an extensive library of functions commonly used in modeling a system.
These include:
Continuous and discrete dynamics blocks, such as Integration and Unit Delay
Algorithmic blocks, such as Sum, Product, and Lookup Table
Structural blocks, such as Mux, Switch, and Bus Selector
You can customize these built-in blocks or create new ones directly in Simulink and place them into
your own libraries.
Additional blocksets (available separately) extend Simulink with specific functionality for aerospace,
communications, radio frequency, signal processing, video and image processing, and other
applications.
You can model physical systems in Simulink. Simscape™, SimDriveline™, SimHydraulics®,
SimMechanics™, and SimPowerSystems™ (all available separately) provide expanded capabilities
for modeling physical systems, such as those with mechanical, electrical, and hydraulic components.
Incorporating MATLAB® Algorithms and Hand-Written Code
When you incorporate MATLAB® code, you can call MATLAB functions for data analysis and
visualization. Additionally, Simulink lets you use MATLAB code to design embedded algorithms that
can then be deployed through code generation with the rest of your model. You can also incorporate
hand-written C, Fortran, and Ada code directly into a model, enabling you to create custom blocks in
your model.
Building and Editing Your Model
With Simulink, you build models by dragging and dropping blocks from the library browser onto the
graphical editor and connecting them with lines that establish mathematical relationships between the
Page | 48
blocks. You can arrange the model by using graphical editing functions, such as copy, paste, undo,
align, distribute, and resize.
Options for connecting blocks in Simulink. You can connect blocks manually, by using the mouse, or
automatically, by routing lines around intervening blocks and through complex topologies.
The Simulink user interface gives you complete control over what you can see and use onscreen. You
can add your commands and submenus to the editor and context menus. You can also disable and hide
menus, menu items, and dialog box controls.
Organizing Your Model
Simulink lets you organize your model into clear, manageable levels of hierarchy by using subsystems
and model referencing. Subsystems encapsulate a group of blocks and signals in a single block. You
can add a custom user interface to a subsystem that hides the subsystem's contents and makes the
subsystem appear as an atomic block with its own icon and parameter dialog box.
Creating and Masking Subsystems
Create hierarchy and modularize system behavior using subsystems.
You can also segment your model into design components to model, simulate, and verify each
component independently. Components can be saved as separate models by using model referencing,
or as subsystems in a library. They are compatible with configuration management systems, such as
Page | 49
CVS and Clear Case, and with any registered source control provider application on
Windows® platforms.
Modular Design Using Model Referencing
Explore the value of model referencing for component-based modeling.
You can reuse the design components on multiple projects, easily maintaining audit and revision
histories.
Organizing your models in this way lets you select the level of detail appropriate to the design task.
For example, you can use simple relationships to model high-level specifications and add more
detailed relationships as you move toward implementation.
Manage Design Variants
Manage design variants in the same model using reference model variants and variant subsystems.
This capability simplifies the creation and management of designs that share components, as one
model can represent a family of designs.
Variant Subsystems
Manage variants of a design and use data-driven conditions to switch between them.
Conditionally Executed Subsystems
Conditionally executed subsystems let you change system dynamics by enabling or disabling specific
sections of your design via controlling logic signals. Simulink lets you create control signals that can
enable or trigger the execution of the subsystem based on specific time or events.
Logic blocks let you model simple commands to control enabled or triggered subsystems. You can
include more complex control logic, as well as model state machines, with Stateflow® (available
separately).
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Defining and Managing Signals and Parameters
Simulink® enables you to define and control the attributes of signals and parameters associated with
your model. Signals are time-varying quantities represented by the lines connecting blocks. Parameters
are coefficients that help define the dynamics and behavior of the system.
Signal and parameter attributes can be specified directly in the diagram or in a separate data
dictionary. Using the Model Explorer, you can manage your data dictionary and quickly repurpose a
model by incorporating different data sets.
Loading and Logging data
Use MATLAB data in Simulink models and save simulation results.
You can define the following signal and parameter attributes:
Data type—single, double, signed or unsigned 8-, 16- or 32-bit integers; Boolean; and fixed-point
Dimensions—scalar, vector, matrix, or N-D arrays
Complexity—real or complex values
Minimum and maximum range, initial value, and engineering units
Enhanced Model Explorer
Use Model Explorer to quickly import and export data and to view items by groups and filters.
Fixed-point data types provide support for scaling and arbitrary word lengths of up to 128 bits. These
data types require Simulink® Fixed Point™ software(available separately) to simulate and generate
code.
You can also specify the signal sampling mode as sample-based or frame-based, to enable the faster
execution of signal processing applications in Simulink and DSP System Toolbox™ (available
separately).
Using Simulink data-type objects, you can define custom data types and bus signals. Bus signals let
you define interfaces between design components.
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Simulink lets you determine the level of signal specification. If you do not specify data attributes,
Simulink determines them via propagation. You can specify only component interfaces or all data for
your model. In all instances, Simulink conducts consistency checking to ensure data integrity.
You can restrict the scope of your parameters to specific parts of your model through a hierarchy of
workspaces, or share them across models via a global workspace.
Running a Simulation
After building your model in Simulink®, you can simulate its dynamic behavior and view the results
live. Simulink software provides several features and tools to ensure the speed and accuracy of your
simulation, including fixed-step and variable-step solvers, a graphical debugger, and a model profiler.
Using Solvers
Solvers are numerical integration algorithms that compute the system dynamics over time using
information contained in the model. Simulink provides solvers to support the simulation of a broad
range of systems, including continuous-time (analog), discrete-time (digital), hybrid (mixed-signal),
and multirate systems of any size.
These solvers can simulate stiff systems and systems with state events, such as discontinuities,
including instantaneous changes in system dynamics. You can specify simulation options, including
the type and properties of the solver, simulation start and stop times, and whether to load or save
simulation data. You can also set optimization and diagnostic information for your simulation.
Different combinations of options can be saved with the model.
Using Solvers
Change default solver settings to improve accuracy and speed of simulation
Debugging a Simulation
The Simulink debugger is an interactive tool for examining simulation results and locating and
diagnosing unexpected behavior in a Simulink model. It lets you quickly pinpoint problems in your
model by stepping through a simulation one method at a time and examining the results of executing
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that method. (Methods are functions that Simulink uses to solve a model at each time step during the
simulation. Blocks are made up of multiple methods.)
The Simulink debugger lets you set breakpoints, control the simulation execution, and display model
information. It can be run from a graphical user interface (GUI) or from the MATLAB® command
line. The GUI provides a clear, color-coded view of the model's execution status. As the model
simulates, you can display information on block states, block inputs and outputs, and other
information, as well as animate block method execution directly on the model.
Simulink debugger GUI used with a multirate control system. You can step through the simulation one
method at a time or run to breakpoints.
Executing a Simulation
Once you have set the simulation options for your model, you can run your simulation interactively,
by using the Simulink GUI, or systematically, by running it in batch mode from the MATLAB
command line. The following simulation models can be used:
Normal (the default), which interpretively simulates your model
Accelerator, which speeds model execution by creating compiled target code while still letting you to
change model parameters
Rapid Accelerator, which can simulate models faster than Accelerator mode but with less interactivity
by creating an executable separate from Simulink that can run on a second processing core
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You can also use MATLAB commands to load and process model data and parameters and visualize
results.
Profiling a Simulation
Model profiling can help you identify performance bottlenecks in your simulations. You can collect
performance data while simulating your model and then generate a simulation profile report based on
the collected data that shows how much time Simulink takes to execute each simulation method.
Running Models on Target Hardware
Simulink provides built-in support for prototyping, testing, and running models on low-cost target
hardware, including Arduino®, LEGO® MINDSTORMS® NXT, and BeagleBoard. You use the Run on
Target Hardware installer to select and download a support package and configure Simulink for your
hardware. After building a model, you generate an executable application that loads and runs on the
target hardware. You can design algorithms in Simulink for control systems, robotics, audio
processing, and computer vision applications and see them perform with hardware.
Analyzing Results
Simulink® includes several tools for analyzing your system, visualizing results, and testing, validating,
and documenting your models.
Visualizing Results
You can visualize the system by viewing signals with the displays and scopes provided in Simulink
software. Alternatively, you can build your own custom displays using MATLAB® visualization and
GUI development tools. You can also log signals for post-processing.
Visualizing Simulation Results
Visualize simulation results using scopes and viewers.
To gain deeper insight into complex 3-D motion of your dynamic system, you can incorporate virtual
reality scenes into your visualization using Simulink 3D Animation™ software (available separately).
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Testing and Validating Your Models
Simulink includes tools to help you generate test conditions and validate your model's performance.
These include blocks for creating simulation tests. For example, the Signal Builder block lets you
graphically create waveforms to exercise models. Using the Signal & Scope Manager, you can inject
signals into your model, as well as log and view signals, without adding blocks. Simulink also
provides model verification blocks to check that block outputs conform to your design requirements.
Simulation Data Inspector
Analyze signal data from multiple simulations to compare designs and validate model results with
external data.
You can formally link requirements to sections of your model, write custom model standards checks,
and run model coverage using Simulink® Verification and Validation™ software (available
separately). You can generate tests for your model that satisfy model coverage and user-defined
objectives and prove properties using Simulink® Design Verifier™ software (available separately). To
manage and store tests independently of your model, you can use System Test™ software (available
separately) to develop test sequences and generate test reports.
Documenting Your Model
It is easy to add documentation to your Simulink model. Annotations, including hyperlinks to other
documents and Web pages, can be added directly in the diagram. Detailed descriptions can be added to
each block's properties as well as model properties, such as model history information. The Doc Block
lets you include a text file document as a block within your model. Simulink also offers printing
capabilities that let you easily document your model. With one command, you can create a HTML
document that describes your entire model, including snapshots of the different levels of hierarchy,
and all the block specifications.
Using the Simulink Manifest Tools you can create a report listing the files that your model requires to
function and, additionally, compress those files for sharing with other users. Using Simulink® Report
Generator™ software (available separately) you can create customized reports that comply with
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specific document standards, as well as share interactive renditions of your models viewable in a Web
browser.
Generating C/C++ and HDL Code
Models that are built in Simulink can be configured and made ready for code generation. Using
Simulink Coder™ and Embedded Coder™ products (both available separately), you can generate
C/C++ code from the model for real-time simulation, rapid prototyping, and embedded system
deployment. Using the Simulink® HDL Coder™ product (available separately), you can generate
synthesizable, target independent Verilog and VHDL code, as well as test benches for code validation
in external HDL simulators.
Building a simulink model:
Creating a New Model:
Before creating a model, you need to start MATLAB and then start Simulink.
1. In the MATLAB Command Window, enter simulink
The Simulink Library Browser opens.
2. From the Simulink Library Browser menu, select File > New > Model.
A Simulink editor window opens with an empty model.
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1. Select File > Save as. The Save As dialog box opens.
2. In the File name box, enter a name for your model, and then click Save. For example,
enter simple_model.
Your model is saved with the file name simple_model.mdl.
Adding Blocks to a Model
To create a model, begin by copying blocks from the Simulink Library Browser to the Simulink editor
window. For a description of the blocks in this example, see Overview of a Simple Model.
1. In the Simulink Library Browser, select the Sources library.
The Simulink Library Browser displays blocks from the Sources library in the right pane.
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2. Select the Sine Wave block, and then drag it to the editor window.
A copy of the Sine Wave block appears in your model.
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3. Add the following blocks to your model in the same way you added the Sine Waveblock.
Library Block
Sinks Scope
Continuous Integrator
Signal Routing Mux
4. Your model now has the blocks you need for the simple model.
Moving Blocks in the Model
Before you connect the blocks in your model, you should arrange them logically to make the signal
connections as straightforward as possible.
1. Move the Scope block after the Mux block output. To move a block in a model, you can either:
Click and drag the block.
Select the block, and then press the arrow keys on the keyboard.
2. Move the Sine Wave and Integrator blocks before the Mux block Inputs.
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Your model should look similar to the following figure.
Your next task is to connect the blocks together with signal lines. See Connecting Blocks in the
Simple Model.
BLOCK CONNECTIONS IN A MODEL
After you add blocks to your model, you need to connect them. The connecting lines represent the
signals within a model.
Most blocks have angle brackets on one or both sides. These angle brackets represent input and output
ports:
The > symbol pointing into a block is an input port.
The > symbol pointing out of a block is an output port.
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DRAWING LINES BETWEEN BLOCKS
Connect the blocks by drawing lines between output ports and input ports. For how to add blocks to
the model in this example, see Adding Blocks to a Model.
1. Position your mouse pointer over the output port on the right side of the Sine Wave block.
The pointer changes to a cross hairs (+) shape while over the port.
2. Click and drag a line from the output port to the top input port of the Mux block.
While you hold the mouse button down, the connecting line appears as a dashed line.
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3. Release the mouse button over the output port.
Simulink connects the blocks with an arrow indicating the direction of signal flow.
4. Drag a line from the output port of the Integrator block to the bottom input port on the Mux block.
The Integrator block connects to the Mux block with a signal line.
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5. Select the Mux block, hold down the Ctrl key, and then select the Scope block.
A line is drawn between the blocks to connect them. Your model should now look similar to the
following figure.
Note The Ctrl+click shortcut is useful when you are connecting widely separated blocks, or
when working with complex models.
DRAWING A BRANCH LINE
The simple model is almost complete, but one connection is missing. To finish the model, you need to
connect the Sine Wave block to the Integrator block.
This final connection is different from the other three connections, which all connect output ports to
input ports. Because the output port of the Sine Wave block is already connected, you must connect
this existing line to the input port of the Integrator block. The new line, called abranch line, carries the
same signal that passes from the Sine Wave block to the Mux block.
1. Position the mouse pointer on the line between the Sine Wave and the Mux block.
2. Hold down the Ctrl key, and then drag a line to the input port of the Integrator block input port.
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3. From the File menu, click Save. Your model is now complete.
After you finish building a model, you can simulate the dynamic behavior of the model. See
Simulating the Simple Model.
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Simulating the Simple Model
SETTING SIMULATION OPTIONS
Before you simulate a model, you have to set simulation options. Specify options, such as the stop
time and solver, using the Configuration Parameters dialog box. For how to build the model in this
example, see Creating the Simple Model.
1. In the Simulink editor window, select Simulation > Configuration Parameters. The Configuration
Parameters dialog box opens to the Solver pane.
2. In the Stop time field, enter 20, and in the Max step size field, enter 0.2.
3. Click OK.
The software updates the parameter values with your changes and closes the Configuration
Parameters dialog box.
RUNNING A SIMULATION AND OBSERVING RESULTS
After entering your configuration parameter changes, you are ready to simulate the simple model and
visualize the simulation results.
1. In the Simulink editor window, select Simulation > Start from the menu.
The simulation runs, and then stops when it reaches the stop time specified in the Configuration
Parameters dialog box.
Tip Alternatively, you can control a simulation by clicking the Start simulation button
and Stop simulation button on the editor window toolbar.
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2. Double-click the Scope block.
The Scope window opens and displays the simulation results. The plot shows a sine wave signal
with the resulting cosine wave signal from the Integrator block.
3. From the toolbar, click the Parameters button , and then the Style tab. The Scope Parameters
dialog box displays the figure editing commands.
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4. Make changes to the appearance of the figure. For example, select white for the Figure and Axes
background color, and change the signal line colors to blue and green. Click the Apply button to
see your changes.
Block Library Description
COMMONLY
USED BLOCKS
Group of the most commonly used blocks, such as
the Constant,In1, Out1, Scope, and Sum blocks. Each of the blocks in this
library are also included in other libraries.
Continuous Model linear functions using blocks such as the Derivative and
Integrator blocks.
Discontinuities Create outputs that are discontinuous functions of their inputs using blocks such
as the Saturation block.
Discrete Represent discrete time functions using blocks such as the Unit Delay block.
Logic and Bit
Operations
Perform logic or bit operations using blocks such as the Logical
Operator and Relational Operator blocks.
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Block Library Description
Lookup Tables Use lookup tables to determine their outputs from their inputs using blocks such
as the Cosine and Sine blocks.
Math Operations Perform mathematical and logical functions using blocks such as
the Gain, Product, and Sum blocks.
Model Verification Create self-validating models using blocks such as the Check Input
Resolution block.
Model-Wide Utilities Provide information about the model using blocks such as the Model Info block.
Ports & Subsystems Create subsystems using blocks such as the In1, Out1, and Subsystem blocks.
Signal Attributes Modify the attributes of signals using blocks such as the Data Type
Conversion block.
Signal Routing Route signals from one point in a block diagram to another using blocks such as
the Mux and Switch blocks.
Sinks Display or export output using blocks such as the Out1 andScope blocks.
Sources Generate or import system inputs using blocks such as theConstant, In1,
and Sine Wave blocks.
User-Defined
Functions
Define custom functions using blocks such as the MATLAB Function block.
Additional Math &
Discrete
Additional libraries for mathematical and discrete function blocks.
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Graph between rotor angle vs time.
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Graph between mechanical power vs time.
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Graph between rotor angle vs time.
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CONCLUSION:
The transient stability improvement of single machine infinite bus system with unified power flow
controller (UPFC) has been implemented in MATLAB/SIMULINK. A brief knowledge has been gained about the
MATLAB/SIMULINK block sets which were used in the implementation of this project,
The transients that occur in the SMIB can be removed by using upfc device,the three parameter like rotor
angle, voltage, sasuptances can be control,
following conclusions are drawn if UPFC is added in SMIB system:
• Fault current is reduced when fault occurs in the line.
• Excitation voltage is modified with damping out of oscillations when
fault occurs at of the line.
The three parameters(voltage, impedance and angle), determined, the power flow through a
transmission line.
From the simulation of SMIB with UPFC characteristic the transient stability is improved.
REFERENCES:
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1 KR. Padiyar and V. Kalyana Raman, "Study of voltage collapse at con-
verter bus in asynchronous MTDC-AC systems", Int. J. of Elec. Power
and Energy Syst., Vol. 15, No.1, Feb. 1993, pp. 45-53
2. KR. Padiyar and S. Suresh Rao, "Dynamic analysis of voltage instability
in AC-DC systems", To appear in Int. J. of Elec. Power & Energy Syst.
3. G.K Morrison, B. Gao and P.Kundur, "Voltage stability a n a l y s i ~ using
static and dynamic approaches", IEEE Trans. on Power Systems, Vol. 8,
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4. P.A.Lof,G. Anderson and D.J. Hill, "Voltage stability indices for stressed
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bility", IEEE Trans on Power Delivery, Vol. 7, No.2, April 1992, pp.
480-488
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bility as Affected by Excitation Control", IEEE Transactions on Power
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8. K.R. Padiyar and Kalyani Bhaskar, "An Integrated Analysis of Voltage
and Angle Stability of a Three Node Power System", to appear in the
International Journal of Electrical Power & Energy Systems.
9. K.R. Padiyar and S.S. Rao, "Dynamic Analysis of Small Signal Voltage
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