Simulation Of Two Area Control System Using Simulink

Simulation of Two Area Control System using Simulink

A Major Project Report Submitted in partial fulfillment of the requirements for the Degree of Bachelor of Technology Under Biju Pattnaik University of Technology

By

Vikas Kumar Sabata Santosh Kumar Tripathy

Roll #ECE 200425380 Roll #ECE 200413459

March - 2008

Under the guidance of

Mr. O. P. Suresh

NATIONAL INSTITUTE OF SCIENCE & TECHNOLOGY Palur Hills, Berhampur, Orissa - 761 008, India

ABSTRACT The aim of this project “Simulation of two area control system using simulink” is to construct the SIMULINK block diagram and obtain frequency response for each area with inclusion of the ACEs. The two area system is a form of multiarea system of AGC, where a group of generator is closely coupled internally and swing in unison. Furthermore, the generator turbine tends to have the same response characteristics. Such a group of generators are said to be “coherent” .Then it is possible to represent the whole system, which referred to as a “control area”. In two area system, generation and load demand of two domains is dealt. Any load change within the area has to be met by generators in both the area. Thus we can maintain the constant frequency operation irrespective of load change.

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ACKNOWLEDGEMENT We express our deep sense of gratitude to Mr. O.P.Suresh, Advisor, B.Tech Project Coordinator for his valuable guidance and constant unfailing encouragement for completing this project report. We thank our Examiners Mrs. Sasmita Padhi and Ms. P.Sunita for their suggestions and guidelines to make some improvements in the project. We are also grateful to Mr. G.V.Kiran Kumar, Format Examiner for his help in editing this report. Finally we thank Mr. Sangram Mudali, Director, for his continued drive for better quality in everything that happens at NIST. This report is a small contribution towards the greater goal.

Vikas Kumar Sabata Roll # 200425380

Santosh Kumar Tripathy Roll # 200413459

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TABLE OF CONTENTS ABSTRACT...................................................................................................................ii ACKNOWLEDGEMENT..............................................................................................i TABLE OF CONTENTS...............................................................................................ii LIST OF FIGURES......................................................................................................iii LIST OF TABLES........................................................................................................iv 1. INTRODUCTION......................................................................................................1 2. BASIC GENERATOR CONTROL LOOPS............................................................3 3. LOAD FREQUENCY CONTROL............................................................................5 3.1 GENERATOR MODEL......................................................................................5 ....................................................................................................................................5 3.2 LOAD MODEL....................................................................................................6 3.3 PRIME MOVER MODEL...................................................................................7 3.4 GOVERNOR MODEL........................................................................................7 4. AUTOMATIC GENERATION CONTROL...........................................................10 4.1 AGC IN A SINGLE AREA SYSTEM..............................................................11 4.2 AGC IN MULTIAREA SYSTEM.....................................................................12 4.3 TIE-LINE BIAS CONTROL.............................................................................13 5. SIMULINK .............................................................................................................15 5.1 WHAT IS SIMULINK ............................................................................15 5.2 MODELING PROCESS....................................................................................16 1. DEFINING THE SYSTEM.............................................................................17 2. IDENTIFYING SYSTEM COMPONENTS...................................................17 3. MODELING THE SYSTEM WITH EQUATIONS........................................18 4. BUILDING THE SIMULINK BLOCK DIAGRAM.......................................18 5. RUNNING THE SIMULATION.....................................................................18 6. VALIDATING THE SIMULATION RESULTS............................................18 .................................................................................................................................18 5.3 STARTING SIMULINK....................................................................................19 5.3 SIMULINK LIBRARY BROWSER.................................................................20 6. TWO AREA CONTROL SYSTEM .......................................................................20 7. SIMULATION RESULT.........................................................................................24 8. CONCLUSION........................................................................................................25 ..............................................................................................................................25 REFERENCE ..............................................................................................................26 APPENDIX A..............................................................................................................24 A.1 NOMENCLATURE..........................................................................................24

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LIST OF FIGURES Figure 2.1 Schematic diagram of LFC and AVR of a synchronous generator .............3 Figure 3.1 Transfer function model for generator model .............................................6 Figure 3.2 Transfer function model for load model....................................................6 Figure 3.3 block diagram for a simple nonreheat steam turbine....................................7 Figure 3.4 Speed governing system...............................................................................8 Figure 3.5 LFC block diagram of an isolated system ..................................9 Figure 4.1 AGC for an isolated power system..........................................................11 ..............................................................................................................................11 Figure 4.2 Equivalent network for two area power system..........................................12 Figure 4.3 Two area system with primary LFC loop...................................................13 Figure 4.4 AGC block diagram for two area system....................................................14 Figure 5.1 Simulink library browser............................................................................19 Figure 6.1 Simulation block diagram...........................................................................23 Figure 7.1 Simulation result.........................................................................................24

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LIST OF TABLES Table 5.1.......................................................................................................................20 Table 6.1 ......................................................................................................................21

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SIMULATION OF TWO AREA CONTROL SYSTEM USING SIMULINK

1. INTRODUCTION The primary purpose of an ac electric power system is to move electric power from the sources of the electric power, the generators, to the consumers of the electric power, the loads, through the wires joining the two, the transmission and distribution system. Power systems come in a variety of sizes, ranging in size from those with a single small generator and perhaps a handful of loads to the gigantic. For example, except for a few islands and some small isolated systems, the entire electric grid in North America is really just one big electric circuit. This grid encompasses billions of individual electric loads, tens of millions of miles of wires, and thousands of generators. The objective of control strategy is to generate and deliver power in an interconnected system as economically and reliably as possible while maintaining the voltage and frequency within permissible limits. Changes in real power affect mainly the system frequency, while reactive power is less sensitive to changes in frequency and is mainly dependent on changes in voltage magnitude. Thus, real and reactive powers are controlled separately. The “load frequency control” (LFC) loop controls the real power and frequency and the “automatic voltage regulator” (AVR) loop regulates the reactive power and voltage magnitude. Load frequency control (LFC) has gained in importance with the growth of interconnected systems and has made the operation of interconnected system possible. While an interconnected system is really just on big electric circuit, it has historically been divided into groupings known as “operating areas” (or control areas). Typically, each operating area corresponded to the portion of the grid owned by a single utility. Lines joining different operating areas are known as “tie-lines”. The net flow of power out of an area is then defined as its “interchange”. Since it costs money to generate electric power, a key aspect of power system operations is concerned with insuring that each area's net interchange is equal to its specified "scheduled" value. This scheduled value is simply the sum of all the power transfers for the area, with a sign convention that power exported from the area (i.e., sold) is considered positive.

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SIMULATION OF TWO AREA CONTROL SYSTEM USING SIMULINK

As long as the system frequency is equal to its specified value (the assumption here), the difference between an area's actual interchange and its scheduled interchange is known as the “area control error” (ACE) (the area control error also includes a term dependent on the deviation in the system frequency from the specified value; this frequency-dependent term is not discussed here). The ACE is the single most important number associated with control operations; it is continuously monitored. Anytime the ACE is negative the area is “undergenerating” and needs to increase its total generation. Conversely, if the ACE is positive, the area is “overgenerating” and needs to decrease its generation. Over the last several decades, practically all control areas have switched to an automatic process known as “automatic generation control” (AGC). AGC automatically adjusts the generation in an area to keep the ACE close to zero, which in turn keeps the net area power interchange at its specified value. Since the ACE has a small amount of almost random "ripple" in its value due to the relentlessly changing system load, the usual goal of AGC is not to keep the ACE exactly at zero but rather to keep its magnitude close to zero, with an “average” value of zero. Modern power system network consists of a number of utilities interconnected together & power is exchanged between utilities over tie-lines by which they are connected. Automatic generation control (AGC) plays a very important role in power system as its main role is to maintain the system frequency and tie line flow at their scheduled values during normal period and also when the system is subjected to small step load perturbations. Many investigations in the field of automatic generation control of interconnected power system have been reported over the past few decades. Literature survey shows that most of the earlier work in the area of automatic generation control pertains to interconnected thermal system and relatively lesser attention has been devoted to automatic generation control (AGC) of interconnected hydro-thermal systems involving thermal and hydro subsystems of widely different characteristics]. These investigations mostly pertain to two equal area thermal systems or two equal areas hydrothermal systems considering the system model either in continuous or continuous discrete mode with step loads perturbation occurring in an individual area. 2

SIMULATION OF TWO AREA CONTROL SYSTEM USING SIMULINK

2. BASIC GENERATOR CONTROL LOOPS In an interconnected power system, load frequency control (LFC) and automatic voltage regulator (AVR) equipment are installed for each generator. Figure2.1 represents the schematic diagram of the load frequency control (LFC) loop and the automatic voltage regulator (AVR) loop. The controllers are set for a particular operating condition and take care of small changes in load demand to maintain the frequency and voltage magnitude within the specified limits. Small changes in real power are mainly dependent on changes in rotor angle “δ” and, thus, the frequency. The reactive power is mainly dependent on the voltage magnitude (i.e., on the generator excitation). The excitation system time constant is much smaller than the prime mover time constant and its transient decay much faster and does not affect the LFC dynamics. Thus, the cross-coupling between the LFC loop and the AVR loop is negligible, and the load frequency and excitation voltage control are analyzed independently.

Figure 2.1 Schematic diagram of LFC and AVR of a synchronous generator

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SIMULATION OF TWO AREA CONTROL SYSTEM USING SIMULINK

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3. LOAD FREQUENCY CONTROL The operation objectives of the LFC are to maintain reasonably uniform frequency, to divide the load between generators, and to control, and to control the tie-line interchange schedules. The change in frequency and tie-line real power are sensed, which is a measure of the change in rotor angle ‘δ’, i.e., the error ‘Δδ’ to be corrected. The error signal, i.e., Δf and ΔPtie, are amplified, mixed, and transformed into a real power command signal ΔPv, which is sent to the prime mover to call for an increment in the torque. The prime mover, therefore, brings change in the generator output by an amount ΔPg which will change the values of Δf and ΔPtie within the specified tolerance. The first step in the analysis and design of a control system is mathematical modeling of the system. The two most common methods are the transfer function method and the state variable approach. The state variable approach can be applied to the portray linear as well as nonlinear systems. In order to use the transfer function the system must first be linearized. The transfer function models for following components are obtained.

3.1 GENERATOR MODEL One of the essential components of power systems is the three phase ac generator known as synchronous generator or alternator. Synchronous generators have two synchronously rotating fields: one field is produced by the rotor driven at synchronous speed and excited by dc current. The other field is produced in the stator windings by the three-phase armature currents. The dc current for the rotor windings is provided by excitation systems. Today system use ac generators with rotating rectifiers, known as brushless excitation systems. The generator excitation system maintains generator voltage and controls the reactive power flow.

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ΔPm(s)

1/2Hs

ΔΩ(s)

_

ΔPe(s)

Figure 3.1 Transfer function model for generator model

In a power plant, the size of generators can vary fro 50 MW to 1500 MW.

3.2 LOAD MODEL The load on a power system consists of a variety of electrical devices. For resistive loads, such as lighting and heating loads, the electrical power is independent of frequency. Motor loads are sensitive to changes in frequency. How sensitive it is to frequency depends on the composite of the speed-load characteristics of all the driven devices. Including the load model in the generator block diagram, results in the block diagram of Figure 3.2.

ΔPL(s) _ ΔPm(s)

1/(2Hs+D) ΔΩ(s)

Figure 3.2 Transfer function model for load model

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3.3 PRIME MOVER MODEL The source of mechanical power, commonly known as prime mover, may be hydraulic turbines at waterfalls, steam turbines whose energy comes from the burning of coal, gas, nuclear fuel, and gas turbines. The model of the turbines relates change in mechanical power output ΔPm to changes in steam valve position ΔPv. Different types of turbines vary widely in characteristics. The simplest prime mover model for the nonreheat steam turbine can be approximated with a single time constant TT. The time constant TT is in the range of 0.2 to 2.0 seconds.

ΔPV(s)

1/(1+TTs)

ΔPm(s)

Figure 3.3 block diagram for a simple nonreheat steam turbine

3.4 GOVERNOR MODEL When the generator electrical load is suddenly increased, the electrical power exceeds the mechanical power input. This power deficiency is supplied by the kinetic energy stored in the rotating system. The reduction in kinetic energy causes the turbine speed and, consequently, the generator frequency to fall. The change in speed is sensed by the turbine governor which acts to adjust the turbine input valve to change the mechanical power output to bring the speed to a new steady-state. The earliest governors were the watt governors which sense the speed by means of rotating flyballs and provide mechanical motion in response to speed changes. However, most modern governors use electronic means to sense speed changes. Figure 3.4 shows schematically the essential elements of a conventional Watt governor which consists of the following major parts.

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1. Speed governor: The essential parts are centrifugal flyballs driven directly or through gearing by the turbine shaft. The mechanism provides upward and downward vertical movements proportional to the change in speed. 2. Linkage Mechanism: These are links for transforming the flyballs movement to the turbine valve through a hydraulic amplifier and providing a feedback from the turbine valve movement.

Figure 3.4 Speed governing system

3. Hydraulic Amplifier: Very large mechanical forces are needed to operate the steam valve. Therefore, the governor movements are transformed into high power forces via several stages of hydraulic amplifiers. 8

4. Speed Charger: the speed charger consist of servomotor which can be operated manually or automatically for scheduling load at nominal frequency. By adjusting this set point, a desired load dispatch can be scheduled at nominal frequency. ΔPL(s) _ ΔPref(s)

ΔPg

ΔPV

ΔΩ(s)

ΔPm

1/(1+Tgs)

1/(1+TTs)

1/(2Hs+D)

_ Governor

Turbine

Rotating mass and load

1/R

Figure 3.5 LFC block diagram of an isolated system

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4. AUTOMATIC GENERATION CONTROL When the load on the system is increased, the turbine speed drops before the governor can adjust the input of the steam to the new load. As the change in the value of speed diminishes, the error signal becomes smaller and position of the governor falls gets closer to the point required to maintain a constant speed. However the constant speed will not be the set point, and there will be offset. One way to restore the speed or frequency to its nominal value is to add an integrator. The integral unit monitors the average error over a period of time and will overcome the offset. Because of its ability to return a system to its set point, integral action is known as the rest action. Thus, as the system load change continuously, the generation is adjusted automatically to restore the frequency to the nominal value .This scheme is known as the “automatic generation control” (AGC). In an interconnected system consisting of several pools, the role of the automatic generation control (AGC) is to divide the loads among system, station generators so as to achieve maximum economy and correctly control the scheduled interchanges of tie-line power while maintaining a reasonably uniform frequency. During large transient disturbances and emergencies, AGC is bypassed and other emergency controls are applied. Modern power system network consists of a number of utilities interconnected together & power is exchanged between utilities over tie-lines by which they are connected. Automatic generation control (AGC) plays a very important role in power system as its main role is to maintain the system frequency and tie line flow at their scheduled values during normal period and also when the system is subjected to small step load perturbations. Many investigations in the field of automatic generation control of interconnected power system have been reported over the past few decades.

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4.1 AGC IN A SINGLE AREA SYSTEM With the primary LFC loop, a change in the system load will result in a steady-state frequency deviation, depending on the governor speed regulation. In order to reduce the frequency deviation to zero, we must provide a reset action. The rest action can be achieved by introducing an integral controller to act on the load reference setting to change the speed set point. The integral controller increases the system type by one which forces the final frequency deviation to zero. The LFC system, with addition the addition of the secondary Figure 4.1. The integral controller gain KI must be adjusted for a satisfactory transient response.

ΔPL(s) _ ΔPref(s)

ΔPg

ΔPV

ΔPm

1/(1+Tgs)

1/(1+TTs)

Governor

Turbine

1/(2Hs+D)

Rotating mass and load

1/R

KI/s

Figure 4.1 AGC for an isolated power system

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4.2 AGC IN MULTIAREA SYSTEM In many cases, a group of generators are closely coupled internally and swing in unison. Furthermore, the generator turbines tend to have the same response characteristics. Such a group of generators are said be coherent. Then it is possible to let the LFC loop represent the whole system, which is referred to as control area. The AGC of a multiarea system can be realized by studying first the AGC for a two-area system. Consider two areas represented by an equivalent by an equivalent generating unit interconnected by a lossless tie line with reactance Xtie. Each area is represented by a voltage source behind an equivalent reactance as shown in Figure 4.2.

Figure 4.2 Equivalent network for two area power system

During normal operation, the real power transferred over the tie line is given by P12 = |E1| |E2| sinδ12 X12 Where X12 = X1+ Xtie+ X2, and δ12= δ1 - δ2. The tie line power deviation then takes on the form ΔP12 = Ps(Δδ1 - Δδ2) The tie line power flow appears as a load increase in one area and a load decrease in the other area, depending on the direction of the flow. The direction of the flow. The 12

direction of flow is dictated by phase angle difference; if Δδ1 > Δδ2, the power flows from area 1 to area 2. A block diagram representation for the two-area system with LFC containing only the primary loop is shown in Figure 4.3.

Figure 4.3 Two area system with primary LFC loop

4.3 TIE-LINE BIAS CONTROL In the normal operating state, the power system is operated so that the demands of the areas are satisfied at the nominal frequency. A simple control strategy for the normal mode is • Keep frequency approximately at nominal value. • Maintain the tie-line flow at about schedule. • Each area should absorb its own load charges. 13

Conventional LFC is based upon tie-line bias control, where each area tends to reduce the area control error (ACE) to zero. The control error for each area tends to consists of linear combination of frequency and tie-line error. ACEi = Σnj=1 ΔPij +Ki Δω The area bias Ki determines the amount of interaction during a disturbance in the neighboring areas. An overall satisfactory performance is achieved when K is selected equal to the frequency bias factor of that area, i.e., Bi =1/Ri +Di . Thus, the ACEs for a two area systems are ACE1 = ΔP12 +B1 Δω1 ACE1 = ΔP21 +B2 Δω2 Where ΔP12 and ΔP21 are departures from scheduled interchanges. ACEs are used as actuating signals to activate changes in the reference power set points, and when steady state is reached, ΔP12 and Δω will be zero. The integrator gain constant must be chosen small enough so as not cause the area to go into a chase mode. The block diagram of a simple AGC for two area system is shown in Figure 4.4

Figure 4.4 AGC block diagram for two area system

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5. SIMULINK 5.1 WHAT IS SIMULINK Computers have provided engineers with immense mathematical powers, which can be used to simulate (or mimic) dynamic systems without the actual physical setup. Simulation of Dynamic Systems has proved to be immensely useful when it comes to control design, saving time and money that would otherwise be spent in prototyping a physical system. Simulink is a software add-on to MATLAB software which is a mathematical tool developed by The Mathworks, a company based in Natick, MA. MATLAB is powered by extensive numerical analysis capability. Simulink is a tool used to visually program a dynamic system (those governed by Differential equations) and look at results. Any logic circuit or a control system for a dynamic system can be built by using standard building blocks available in Simulink Libraries. Various toolboxes for different techniques, such as Fuzzy Logic, Neural Networks, DSP, Statistics etc. are available with Simulink, which enhance the processing power of the tool. The main advantage is the availability of building blocks, which avoid the necessity of typing code for small mathematical processes. With Simulink, we can move beyond idealized linear models to explore more realistic nonlinear models, factoring in friction, air resistance, gear slippage, hard stops, and the other things that describe real-world phenomena. Simulink turns a computer into a laboratory for modeling and analyzing systems that would not be possible or practical otherwise. Whether we are interested in the behavior of an automotive clutch system, the flutter of an airplane wing, or the effect of the monetary supply on the economy, Simulink provides we with the tools to model and simulate almost any real-world problem. Simulink also provides demos that model a wide variety of real-world phenomena. Simulink provides a graphical user interface (GUI) for building models as block diagrams, allowing us to draw models as we would with pencil and paper. Simulink also includes a comprehensive block library of sinks, sources, linear and nonlinear components, and connectors. If these blocks do not meet our needs, however, we can also create your own blocks. The interactive graphical environment simplifies the modeling process, eliminating the need to formulate differential and difference equations in a language or program. 15

Model-Based Design is a process that enables faster, more cost-effective development of

dynamic

systems,

including

control

systems,

signal

processing,

and

communications systems. In Model-Based Design, a system model is at the center of the development process, from requirements development, through design, implementation, and testing. The model is an executable specification that is continually refined throughout the development process. After model development, simulation shows whether the model works correctly. When software and hardware implementation requirements are included, such as fixed-point and timing behavior, you can automatically generate code for embedded deployment and create test benches for system verification, saving time and avoiding the introduction of handcoding errors. Model-Based Design allows you to improve efficiency by: • Using a common design environment across project teams • Linking designs directly to requirements • Integrating testing with design to continuously identify and correct errors • Refining algorithms through multidomain simulation • Automatically generating embedded software code • Developing and reusing test suites • Automatically generating documentation • Reusing designs to deploy systems across multiple processors and hardware targets. After we define a model, we can simulate it, using a choice of mathematical integration methods, either from the Simulink menus or by entering commands in the MATLAB Command Window. The menus are convenient for interactive work, while the command line is useful for running a batch of simulations. Using scopes and other display blocks, we can see the simulation results while the simulation runs. We can then change many parameters. The simulation results can be put in the MATLAB workspace for postprocessing and visualization.

5.2 MODELING PROCESS There are six steps to modeling any system:

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1. DEFINING THE SYSTEM The first step in modeling a dynamic system is to fully define the system. If you are modeling a large system that can be broken into parts, you should model each subcomponent on its own. Then, after building each component, you can integrate them into a complete model of the system. For example, the demo model used later in this guide models the heating system of a house. This system can be broken down into three main parts: • Heater subsystem • Thermostat subsystem • Thermodynamic model subsystem The most effective way to build a model of this system is to consider each of these subsystems independently. 2. IDENTIFYING SYSTEM COMPONENTS The second step in the modeling process is to identify the system components. There are three types of components that define a system: • Parameters — System values that remain constant unless you change them • States — Variables in the system that change over time • Signals — Input and output values that change dynamically during the simulation In Simulink, parameters and states are represented by blocks, while signals are represented by the lines that connect blocks. For each subsystem that you identified, ask yourself the following questions: • How many input signals does the subsystem have? • How many output signals does the subsystem have? • How many states (variables) does the subsystem have? • What are the parameters (constants) in the subsystem? • Are there any intermediate (internal) signals in the subsystem? Once you have answered these questions, you should have a comprehensive list of the system components, and are ready to begin modeling the system.

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3. MODELING THE SYSTEM WITH EQUATIONS The third step in modeling a system is to formulate the mathematical equations that describe the system. For each subsystem, use the list of system components you identified to describe the system mathematically. Your model may include: • Algebraic equations • Logical equations • Differential equations, for continuous systems • Difference equations, for discrete systems You use these equations to create the block diagram in Simulink. 4. BUILDING THE SIMULINK BLOCK DIAGRAM After you have defined the mathematical equations that describe each subsystem, you can begin building a block diagram of your model in Simulink. Build the block diagram for each of your subcomponents separately. After you have modeled each subcomponent, you can then integrate them into a complete model of the system. See “Creating a Simple Model” on page 3-3 for more information on building the block diagram in Simulink. 5. RUNNING THE SIMULATION The final step in modeling a system is to run the simulation and analyze the results. Simulink allows you to interactively define system inputs, simulate the model, and observe changes in behavior. This allows you to quickly evaluate your model. 6. VALIDATING THE SIMULATION RESULTS After you simulate your model, you must validate that the model accurately models the physical characteristics of the system. You can use the linearization and trimming tools available from the MATLAB command line, plus the many tools in MATLAB and its application toolboxes to analyze and validate your model. We perform the first three steps of this process outside of Simulink before you begin building your model.

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5.3 STARTING SIMULINK To start simulink, we have to first start the, MATLAB and then enter the Simulink command at the MATLAB Command Window or Click on the Simulink icon on the MATLAB toolbar. It will display the Simulink library browser.

Figure 5.1 Simulink library browser

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5.3 SIMULINK LIBRARY BROWSER The Library Browser displays the Simulink block libraries installed on system. we build models by copying blocks from a library into a model window. Table 5.1

Block Library Commonly used blocks

Description Contains group of the most commonly used blocks, such as the Constant, In1, Out1, Scope, and Sum blocks. Each of the blocks in library are also included in

Continuous

library Contains blocks that model linear functions, such as Derivatives and

Discontinuities

Integrator blocks. Contains blocks with outputs that are discontinuous function of their inputs,

Discrete

such as the Saturation block. Contains blocks that represent discrete time function, such as the unit delay

Logic and bit operations

block. Contains blocks that perform logic or bit operation, such as the logical operator

Lookup Tables

and relational operator. Contains blocks that use look up tables to determine their output from their input,

Math operations

such as cosine and sine blocks. Contains blocks that perform mathematical and logical functions, such

Signal Attributes

as the Gain, Product, and Sum blocks. Contains blocks that modify the attributes of signal, such as datatype conversion blocks.

6. TWO AREA CONTROL SYSTEM 20

Large scale power systems are normally composed of control areas or regions representing coherent groups of generators. Area load changes and abnormal conditions lead to mismatches in frequency and scheduled power interchanges between areas. These mismatches have to be corrected by Governor Control, which is defined as the regulation of the power output of generators within a prescribed area. The key assumptions in the classical Governor control problem are: i. The steady state frequency error following a step load change should vanish. The transient frequency and time errors should be reduced. ii. The static change in the tie power following a step load in any area should be zero, provided each area can accommodate its own load change. iii. Any area in need of power during an emergency should be assisted from other areas. The two area system is a form of multiarea system of AGC, where a group of generator is closely coupled internally and swing in unison. Furthermore, the generator turbine tends to have the same response characteristics. Such a group of generators are said to be “coherent” .Then it is possible to represent the whole system, which referred to as a “control area”. In two area system, generation and load demand of two domains is dealt. Any load change within the area has to be met by generators in both the area. Thus we can maintain the constant frequency operation irrespective of load change. Power system parameters taken for the design of the Governor controller are enlisted in Table 6.1.

Table 6.1

Parameters

Two area system 21

Area 1

Area 2

Turbine time constant(TT)

0.5s

0.6s

Governor time constant (Tg)

0.2s

0.3s

Frequenct-sens. load coeff.

0.6

0.9

Governor speed regulation(R)

0.05

0.0625

5

4

Inertia constant

1000 MVA

Base power

Tie line control system must use two pieces of information: the system frequency and the net power flowing in or out over the tie lines. (i). If frequency decreased and net interchange power leaving the system increased, a load increase has occurred outside the system. (ii). If frequency decreased and net interchange power leaving the system decreased, a load increase has occurred inside the system. Modeling two area systems are based on transfer function approach. Two area system with governor control is shown in Figure 6. 1. .

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Figure 6.1 Simulation block diagram

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7. SIMULATION RESULT

Figure 7.1 Simulation result

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8. CONCLUSION This shows that the static change in the tie power following a step load in any area should be zero, provided each area can accommodate its own load change. Any area in need of power during an emergency should be assisted from other areas. From the simulation result we have seen that the integrator gain constants are adjusted for a satisfactory response and frequency deviation returns to zero with settling time of approximately 20 seconds. .

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REFERENCE [1]

Elgerd, O. I. “Electric energy systems theory: An introduction”, 2nd Edition, McGraw-Hill; 1971.

[2]

Saadat, Haadi. “Power System Analysis”, 6th Edition, Tata McGraw-Hill edition 2002.

[3]

Jaleeli N, VanSlyck LS, Ewart DN, Fink LH, Hoffmann AG. “Understanding Automatic Generation Control”. IEEE Trans Power Systems 1992; 7(3):1106– 12.

[4]

Pan C.T., Liaw, CM.”An adaptive controller for power system load-frequency control”. IEEE Trans Power Systems 1989”, 4(1):122–8.

[5]

Talaq J, Al-Basri F. “Adaptive fuzzy gain scheduling for load frequency control”. IEEE Trans Power Systems 1999”, 14(1):145–50.

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APPENDIX A A.1 NOMENCLATURE δ: rotor angle. Δδ: change in rotor angle ‘δ’, i.e., the error. Bi: ith subsystem’s frequency-biasing factor Ri: speed regulation for ith subsystem due to the ith governor action in Hz/pu MW a12: the ratio between the base values of two areas fi: incremental frequency deviation in Hz PTi: incremental change in the ith subsystem’s output in pu MW PRi: incremental change in the output energy of the i th reheat type turbine in pu MW PCi: incremental change in the integral controller PTie: incremental change in the tie-line power Pdi: load disturbance for the ith area in pu MW Pm: mechanical power Pv: steam valve position Pref: reference set power ui: output of the automatic generation controller for ith area Tij: synchronizing coefficient of the tie-line between i th and j th areas TGi: ith governor time constant in s TTi: ith turbine time constant in s TRi: ith reheat time constant in s TPi: ith subsystem-model time constant in s KPi: ith subsystem gain KIj: ith subsystem’s integral control gain Ki: the ratio between output energy of the ith stage of turbine to total output energy Xtie: reactance with unit interconnected by a lossless tie line

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