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Transient Stability Improvement of SMIB With Unified Power Flow Controller(1)

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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. Page | 1
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Page 1: 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]:

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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)

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(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.

 

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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.                                                                    

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CHAPTER-5

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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

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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

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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)

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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)

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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)

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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.

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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

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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)

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CHAPTER-6

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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

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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

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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.

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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

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KdcsTω/(1+ sTω)

Ge(s) = (1+sT1)/ (1+sT2)

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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

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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:

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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.

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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 

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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

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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

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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.

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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

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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

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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,

No.3, August 1993, pp. 1159-1171

4. P.A.Lof,G. Anderson and D.J. Hill, "Voltage stability indices for stressed

power systems", IEEE Trans. on Power Systems, Vol. 8, No.1, Feb.

1993, pp. 326-385

5. C. Rajagopalan,B. Lesieutre,P.W. Sauer and M.A. Pai, "Dynamic aspects

of voltage/power characteristics" , IEEE Trans. on Power Systems, Vol. 7,

No.3, Aug. 1992, pp. 990-1000

6. C.W. Taylor, "Cuncepts of undervoltage load shedding for voltage sta-

bility", IEEE Trans on Power Delivery, Vol. 7, No.2, April 1992, pp.

480-488

7. F.P. de Mello and C. Concordia, "Concepts of Synchronous Machine Sta-

bility as Affected by Excitation Control", IEEE Transactions on Power

Apparatus and Systems, Vol. PAS-88, No.4, 1969, pp. 316-329

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

Instability Decoupled from Angle Instability", International Journal on

Electric Power and Energy Systems, Vol. 18, No.7, 1996, pp. 445-452

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