faculty of engineeringfoe.mmu.edu.my/lab/lab sheet/trim3/epsilon/eel412… · · 2018-04-17column...

FACULTY OF ENGINEERING

LAB SHEET

EEL4126 Power System Operation and Control

TRIMESTER 3 2017-2018

PSOC 1 – Contingency Analysis of Power Systems

PSOC 2 – Study of Excitation Control System Responses

[The report must be submitted to the respective lab by forenoon on the next day of

the experiment]


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Experiment # 1

Contingency Analysis of Power Systems

Objectives

To evaluate the effect of generator outage in a power system using AC power-flow

method

To evaluate the effect of line outages in a power system using AC power-flow

method

Introduction

The major security function in a power system is contingency analysis. The results of

contingency analysis allow systems to be operated defensively. The majority of the

problems that occur on power system can cause serious trouble within such a quick time

period that the operator could not take action fast enough. This is often the main reason of

cascading failures. Hence, the computers in modern power system operation control centers

are equipped with the contingency analysis programs that model the possible systems

troubles before they arise. These programs are based on a model of the power system and

are used to study outage events and alarm the operators to any potential overloads or out-

of-limit voltages. For example, the simplest form of contingency analysis can be put

together with the procedures to set up the power-flow data for each outage to be studied by

the power-flow program. Several variations of this type of contingency analysis scheme

involve fast solution methods, automatic contingency event selection, and automatic

initializing of the contingency power flows using actual data and state estimation

procedures.

Contingency Analysis Using Newton-Raphson (N-R) Power-Flow Technique The most widely used power-flow solution employs Newton-Raphson technique. For large

power systems, the Newton-Raphson method is found to be more efficient and practical.

Because of its quadratic convergence, this method is less prone to divergence with ill-

conditioned problems. The number of iterations required to obtain a solution is independent

of the system size. This method is used in this experiment to study the contingency analysis.

A MATLAB program developed and reported in the book “Power System Analysis” by

Hadi Saddat is used in this experiment. Read this program carefully and understand how

to prepare the data for the power-flow analysis.

Data Preparation

To run the power-flow program the following data are to be given.

Base MVA of the system: The variable name is ‘basemva’

Accuracy to terminate the iteration: The variable name is ‘accuracy’

Maximum number of iterations: The variable name is ‘maxiter’


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Bus data: The bus data has to be given in the matrix form and the variable name is

‘busdata’. The various columns of the 11- column matrix are:

Column 1 – bus number

Column 2 – bus code (0 – load bus, 1 – Slack bus, 2 – Voltage controlled bus)

Column 3 – voltage magnitude in pu

Column 4 – voltage phase angle in degree

Column 5 – Load in MW

Column 6 – Load in MVAR

Column 7 – Generation in MW

Column 8 – Generation in MVAR

Column 9 – Minimum MVAR generation

Column 10 – Maximum MVAR generation

Column 11 – Reactive power injection

If value for a particular column is not specified, enter zero.

Line data: The line data has to be given in the matrix form and the variable name is

‘linedata’. The various columns of the 6-colum matrix are:

Columns 1& 2 – bus numbers between which the line is connected

Column 3 – Line resistance in pu

Column 4 – Line reactance in pu

Column 5 – One half of total line charging susceptance in pu

Column 6 – For transformer tap setting; for lines 1 must be entered.

N-R Power-flow program

clear

basemva = 100; accuracy = 0.001; maxiter = 10;

busdata=[ ];

linedata=[ ];

Lfybus % form the bus admittance matrix

warning off

Lfnewton % Load flow solution by Newton-Raphson method

Busout % Prints the power flow solution on the screen

Lineflow % computes and displays the line flow and losses

Test System

The figure shows the one-line diagram of a 5-bus power system with generators at

buses 1, 2 and 3. Bus 1 is the slack bus and its voltage is set at 1.060o pu. Voltage

magnitude and real power generation at buses 2 and 3 are 1.045 pu, 40 MW and

1.03pu, 30 MW, respectively. Each line is rated for 65 MVA and Bus1 generator rating

is 100 MVA. The allowable voltage variation in load buses is 1.05pu to 0.95pu. Assume

minimum and maximum MVAR for each generator to be 0 and 50 MVAR. When doing

the power-flow do not set the maximum limit for generation. Maximum value is given to

verify the overloading of generators for contingencies.


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Procedure

For the test system prepare the linedata and busdata matrices and do the following.

Case 1: Base case

Perform the power-flow analysis for the base case system. Show the results in the one-line

diagram of the system. Check for overloading of generators and transmission lines and

voltage limit violation in load buses. Indicate all the limit violations clearly in red ink.

Case 2: Generator outage

Open Generator connected to Bus 3, perform power-flow analysis and show the results in

the one-line diagram of the system. Check for overloading and voltage limit violation.

Indicate all the limit violations clearly in red ink. [Changing the bus to be a load bus with

generated MW and MVAR to be zero may simulate opening of a generator.]

Case 3: Line outages

1. Restore the original busdata matrix. Open line 4-5, perform power-flow analysis

and show the results in the one-line diagram of the system. Check for overloading

and voltage limit violation. Indicate all the limit violations clearly in red ink.

[Delete the row in the linedata matrix corresponding to line 4-5 for line removal].

2. Restore the original linedata matrix. Open line 2-5, perform power-flow analysis

and show the results in the one-line diagram of the system. Check for overloading

and voltage limit violation. Indicate all the limit violations clearly in red ink.

3. Restore the original linedata matrix. Open lines 2-4 and 4-5 simultaneously,

perform power-flow analysis and show the results in the one-line diagram of the

system. Check for overloading and voltage limit violation. Indicate all the limit

violations clearly in red ink.


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Exercise

1. Discuss your results for all the cases done.

2. In the case of generator outage (Case 2) which generator takes over the lost

generation?

3. Suggest suitable action to be taken to remove the limit violations in case 2.

4. Compute the change in the line flows for outage of Generator 3 (case 2) using

generation shift factors and compare the results with the ones obtained by AC

power-flow method.

5. Find the change in line flow in line 2 – 4 for the outage of line 4 – 5 (case 3-1) using

line outage distribution factor and compare the result with the one obtained by AC

power-flow method.


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Experiment # 2

Study of Excitation Control System Responses

Objectives

To develop a suitable model for the excitation system of a generator

To simulate the excitation system using SIMULINK and analyse the responses of

the system with different types of controllers

Synchronous Generator Excitation System

The generator excitation system maintains generator voltage and controls the reactive

power flow. The generator excitation of older systems may be provided through slip rings

and brushes by means of dc generators mounted on the same shaft of the rotor of the

synchronous machine. However, modern excitation systems usually use ac generators with

rotating rectifiers, and are known as brushless excitation. Recently Static Excitation System

is increasingly used. Static rectifier, controlled or uncontrolled, supplies the excitation

current directly to the field of the main alternator through its slip rings. The supply of power

to the rectifiers is from the main generator or the station auxiliary bus through a transformer

to step down the voltage to an appropriate level.

It is well known that a change in the real power demand affects essentially the frequency,

whereas a change in the reactive power affects mainly the voltage magnitude. The sources

of reactive power are generators, capacitors, and reactors. The generator reactive power is

controlled by field excitation. Other supplementary methods of improving the voltage

profile on electric transmission systems are transformer load-tap changers, switched

capacitors, step-voltage regulators, and static var control equipment. The primary means

of generator reactive power control is the generator excitation control using automatic

voltage regulator (AVR). The role of an (AVR) is to hold the terminal voltage magnitude

of a synchronous generator at a specified level. The schematic diagram of a simplified

AVR is shown in Figure1.

A drop in the terminal voltage magnitude accompanies an increase in the reactive power

load of the generator. The voltage magnitude is sensed through a potential transformer on

one phase. This voltage is rectified and compared to a dc set point signal. The amplified

error signal controls the exciter field and increases the exciter terminal voltage. Thus, the

generator field current is increased, which results in an increase in the generated emf. The

reactive power generation is increased to a new equilibrium, raising the terminal voltage

to the desired value. We will look briefly at the simplified models of the component

involved in the AVR system.


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Amplifier Model The excitation system amplifier may be a magnetic amplifier, rotating amplifier, or modern

electronic amplifier. The amplifier is represented by a gain KA and a time constant τA, and

the transfer function is

----(1)

Typical values of KA are in the range of 10 to 400. The amplifier time constant is very

small, in the range of 0.02 to 0.1 second, and often is neglected.

Exciter Model There is a variety of different excitation types. However, modern excitation systems uses

ac power source through solid-state rectifiers such as SCR. The output voltage of the

exciter is a nonlinear function of the field voltage because of the saturation effects in the

magnetic circuit. Thus, there is no simple relationship between the terminal voltage and the

field voltage of the exciter. Many models with various degrees of sophistication have been

developed and are available in the IEEE recommendation publications. A reasonable model

of a modern exciter is a linearized model, which takes into account the major time constant

and ignores the saturation or other nonlinearities. In the simplest form, the transfer function

of a modern exciter may be represented by a single time constant τE and a gain KE, i.e.,

---(2)

The time constant of modern exciters are very small.

Generator Model


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The synchronous machine generated emf is a function of the machine magnetization curve,

and its terminal voltage is dependent on the generator load. In the linearized model, the

transfer function relating the generator terminal voltage to its field voltage can be

represented by a gain KG and a time constant τG and the transfer function is

---(3)

These constants are load-dependent, KG may vary between 0.7 to 1, and τG between 1.0

and 2.0 seconds from full-load to no-load.

Sensor Model The voltage is sensed through a potential transformer and, in one form, it is rectified

through a bridge rectifier. The sensor is modeled by a simple first order transfer function,

given by

---(4)

τR is very small, and we may assume a range of 0.01 to 0.06 second. Utilizing the above

models the AVR block diagram (without the stabilizer) is shown in Figure 2.

The open-loop transfer function of the block diagram in Figure 2 is

---(5)

and the closed-loop transfer function relating the generator terminal voltage Vt(s) to the

reference voltage Vref(s) is

---(6)

or

---(7)

For a step input Vref(s) = 1/s, using the final value theorem, the steady-state response is

(if KE, KG and KR = 1) ---(8)

Test System


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The AVR system of a generator has the following parameters

Substitution of the system parameters in the AVR block diagram of Figure 2 results in the

block diagram shown in Figure 3.

The SIMULINK block diagram of the test AVR system, with KA = 10, is given in Fig 4.

Excitation System Stabilizer - Rate Feedback

It is observed for higher values of KA the system become unstable, and a value exceeding

12.5 results in an unbounded response. Thus, we must increase the relative stability by

introducing a controller, which would add a zero to the AVR open-loop transfer function.

On way to do this is to add a rate feedback to the control system as shown in Figure 5. By

proper adjustment of KF and τF, a satisfactory response can be obtained.


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Excitation System Stabilizer - PID Controller

One of the most common controllers available commercially is the proportional integral

derivative (P1D) controller. The PID controller is used to improve the dynamic response

as well as to reduce or eliminate the steady-state error. The derivative controller adds a

finite zero to the open-loop plant transfer function and improves the transient response.

The integral controller adds a pole at origin and increases the system type by one and

reduces the steady-state error due to a step function to zero. The PID controller transfer

function is

---(9)

The block diagram of an AVR compensated with a PID controller is shown in figure 6.

Construction of SIMULINK Model

To create a SIMULINK block diagram presentation of Figure 4 select new... from the File

menu. This provides an untitled blank window for designing and simulating a dynamic

system. You can copy blocks from within any of the seven block libraries or other

previously opened windows into the new window by depressing the mouse button and

dragging. Open the Source Library and drag the Step Input block to your window. Double

click on Step Input to open its dialog box. Set the step time to ‘0’ and set the Initial Value

and the Final Value to represent the step input. Open the Linear Library and drag the Sum

block to the right of the Step Input block. Open the Sum dialog box and enter + - under

List of Signs. Using the left mouse button, click and drag from the Step output port to the


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Summing block input port to connect them. Drag a copy of the Transfer Function block

from the Linear Library and connect it to the output port of the Sum block. Click on the

Transfer Function block once to highlight it. Use the Edit command from the menu bar to

copy and paste copies of the Transfer Function. Open the Transfer Function dialog box and

enter values of gains and time constants to represent the correct transfer function. Put

appropriate names to the blocks. Highlight the Sensor block, and from the pull-down

Options menu, click on the Flip Horizontal to rotate the Sensor block by 180 degree.

Connect all the blocks as shown in Figure 4 by connecting the output to input ports. Finally,

get one Auto-scale Scope from the Sink Library and connect it to the output of the

Generator block.

Before starting simulation, you must set the simulation parameters. Pull down the

Simulation dialog box and select Parameters. Use default values for the Start and Stop

Time, and Maximum Step Size. Leave the other parameters at their default values. Press

OK to close the dialog box.

If you don’t like some aspect of the diagram, you can change it in a variety of ways. You

can move any of the icons by clicking on its center and dragging. You can move any of the

lines by clicking on one of its corners and dragging. You can change the size and the shape

of any of the icons by clicking and dragging on its corners. You can remove any line or

icon by clicking on it to select it and using the cut command from the edit menu. You

should now have exactly the same system as shown in Figure 4. Pull down the File menu

and use Save as to save the model in a file. Make sure to delete this file at the end of your

experiment.

SIMULINK enables you to construct and simulate many complex systems, such as control

systems modeled by block diagram with transfer functions including the effect of

nonlinearities. In addition, SIMULINK provides a number of built-in state variable models

and subsystems that can be utilized easily.

Procedure

1. Draw the SIMULINK block diagram and construct the SIMULINK model of Fig 4. Run

the simulation and record the response. Find out the time domain performance

specifications, namely, peak time, rise time, settling time and percent overshoot.

2. Change the value of the amplifier gain, KA to 5, note the peak time, rise time, settling

time and percent overshoot, and discuss the improvement or otherwise of the output

response. Record the response.

3. Change the value of the amplifier gain, KA to 15 and check whether the system is

stable. Record the response.

4. Draw the SIMULINK block diagram and construct the SIMULINK model of Fig 5.

Assume the values of the parameters of Amplifier, Exciter, Generator and Sensor as

in Fig. 4. Assume KF and τF to be 1 and 0.04, respectively. Record the step response

and check the stability of the system.


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5. Draw the SIMULINK block diagram and construct the SIMULINK model of Fig 6.

Assume the values of the parameters of Amplifier, Exciter, Generator and Sensor as

in Fig. 4. Assume KP, KI and KD to be 1.0, 0.25 and 0.28 respectively. Record the step

response and check the stability of the system.

EXERCISE

1. Print the SIMULINK block diagrams of all the test cases.

2. Print the system responses in each case.

3. Give values of peak time, rise time, settling time and percent overshoot for cases 1, 2

and 3.

4. Compare the performances of cases 4 and 5.

5. Discuss the improvement of the excitation response, if any, when the excitation

system stabilizer is used.

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