Designing a Lab View based Automatic Generation Control Training System Introduction 1.1 Background Power generation control aims to deliver power in an interconnected system as economically and reliably as possible while maintaining the voltage and frequency within permissible limits. Change 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 supplementary control, known as AGC is shown in Figure 1.1. It accomplishes more than just frequency control. However, if the power system is being maintained in economic dispatch, the AGC is responsible for allocating generation changes in Karnataka State Open University Page 1
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Designing a Lab View based Automatic Generation Control Training System
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Designing a Lab View based Automatic
Generation Control Training System
Introduction
1.1 Background
Power generation control aims to deliver power in an interconnected system
as economically and reliably as possible while maintaining the voltage and
frequency within permissible limits. Change 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 supplementary control, known as AGC is shown in Figure 1.1. It
accomplishes more than just frequency control. However, if the power
system is being maintained in economic dispatch, the AGC is responsible for
allocating generation changes in manner that the new total generation
matches the needed power for the system while being allocated in an
economic manner. In addition, the control of active and reactive power is
necessary in order to keep the power system in the steady state. Economic
dispatch optimizes the available mix of generation resources and maximizes
the use of low cost sources of electricity, while recognizing any operational
limits.
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Figure 1.1: Schematic Diagram of Load Frequency Control System with Economic Dispatch
The LFC loop controls the real power and frequency while the AVR loop
regulates the reactive power and voltage magnitude.
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The functions of the (AGC) are as follows:
Matching area generation to area load. That is, to match the tie – line
interchanges with the schedules and to control the system frequency.
Distributing the changing loads among generators minimize the
operation costs subject to additional constraints such as might be
introduced by security considerations.
The objectives of (AGC) are as follows:
A small change in the system load produces proportional changes in
the system frequency. That is, the Area Control Error (ACE)
provides each area with approximate knowledge of the load change
and directs the supplementary controller for the area to manipulate
the turbine valves of the regulating units.
The second objective is met by sampling the load every few minutes
(1–5 minutes) and allocating the changing load among different units
so as to minimize the operating costs. This pre assumes the load
demand remains constant during each period of economic dispatch.
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Designing a Lab View based Automatic
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Economic dispatch optimizes the available mix of generation resources and
maximizes the use of low cost sources of electricity, while recognizing any
operational limits.
1.2 Objectives
The objective of this project is to design a user friendly LabView based
training module to teach AGC. This simulink includes the
implementation of combination of LFC and AVR to compensate for load
demand variation and maintain both frequency and terminal voltage
within standard limits.
1.3 Problem Definitions
A large frequency deviation can damage equipments, reduce loads
performance and lead to lose of synchronism. For efficient and reliable
operation of the power system the voltage at the generator terminals has to
be maintained within acceptable limits by AVR. Teaching AGC using only
the simulation is not enough. There is a need for implementing the system
physically.
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1.4 Methodology
The general solution approach is to research about background information
& industrial survey to familiarize team members about AGC system and
conducting research on the current approach for solving the AGC model
under normal operating conditions. Once the research was completed, a
model for AGC was simulated in MATLAB to test the performance of AGC.
Then, power circuit was built & LabView was programmed to be used to
control the performance of the system. After that, the AGC module was
constructed and the operation was tested to make sure it works as per
standards.
1.5 Limiting Factors
The main task was to develop a simulink/MATLAB based simulator and
design the experimental setup within a short period. Only single area AGC
was considered in this project. The proposed AGC could not be built like a
real power plant therefore we have developed a power plant simulator using
the equipment available in lab.
1.6 Main Findings
The load frequency & excitation voltage control was investigated
independently. Also, both the simulator and the experimental setup for
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Designing a Lab View based Automatic
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single area AGC system were designed. Analogue OP AMP regulator and
LabView based control technique were implemented.
1.7 The Report Structure
In chapter 2, a survey of the different commercial AGC modules is presented.In chapter 3, the design development of AGC/AVR system is detailed.
In chapter 4, the design procedure of the training system is detailed.
In chapter 5, the testing and validation of the proposed AGC training module
are detailed.
In chapter 6, presented a summary of main finding of the projects and
discuses different proposed for improving the proposed AGC
Survey of state of the art
2.1 What was published:
2.1.1 Automatic Power Generation Control Simulation:
AGC Simulation was published by Mr. Ravindrakumar Yadav.
Typical responses to real power demand were illustrated using the latest
simulation technique available by the MATLAB SIMULINK package [1].
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The requirement of reactive power, voltage regulation and the influence on
stability of both speed and excitation controls with suitable feedback signals
were examined. An isolated power systems were simulated using AGC.
In an interconnected power system, LFC and AVR equipment were installed
for each generator. Figure 2.1 represents the schematic diagram for the LFC
and AVR loops. The controllers were 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.
Figure 2.1: Schematic diagram of LFC and AVR of a synchronous generator.
The change in frequency is sensed as which is the change in rotor angle
and the error. The LFC system with addition of the secondary loop is as
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shown in Figure 2.2. The integral controller gain KI must be adjusted for a
satisfactory transient response.
Figure 2.2: Block diagram of AGC
Modern energy control centers (ECC) are equipped with online computers
performing all signal processing through the remote acquisition systems
known as “supervisory control and data acquisition (SCADA) systems”.
2.1.2 Load Frequency Control for Multiple-Area Power
Systems
A multi-area power system comprises areas that are interconnected by high
voltage transmission lines or tie-lines [2]. The deviation of frequency
measured in each control area is an indicator of the trend of the mismatch
power in the interconnection and not in the control area alone. The LFC
system in each control area of an interconnected (multi-area) power system
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should control the interchange power with the other control areas as well as
its local frequency. The power flow on the tie-line from area 1 to area 2 is
(2.1)
Where X12 is the tie-line reactance between areas 1 and 2. 1, 2 are the
power angles of equivalent machines of the areas 1 and 2. V1, V2 are the
voltages at equivalent machine’s terminals of the areas 1 and 2.
In a multi-area power system, in addition to regulate area frequency, the
supplementary control should maintain the net interchange power with
neighboring areas at scheduled values. This is generally accomplished by
adding a tie-line flow deviation to the frequency deviation in the
supplementary feedback loop. A suitable linear combination of frequency
and tie-line power changes for area i, is known as the Area Control Error
(ACE).
(2.2)
Where i is a bias factor.
The block diagram shown in Figure 2.3 illustrates how supplementary
control is implemented using (2.2).
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Figure 2.3: Control area i with complete supplementary control
2.2 What is available in the Market:
2.2.1 Open System International Company (OSI)
The AGC and economy dispatching software are used to control generated
power of subordinate power plants to ensure secure, effective and economic
operation of the power system [3]. Figure 2.4 shows the AGC data flow.
It aims at real-time balancing of power supply and demand to accomplish
the following targets:
Keep power network frequency within allowable error limits.
Keep interchanging power between controlled areas to present value.
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Coordinate power plants under remote regulation to contribute based
on generation cost or bidding prices, so as to obtain maximum
economic benefits.
OpenAGC can easily be integrated into an existing control center
environment because it is based on open standards for software and database
implementation. OpenAGC is ideal for those searching for an upgrade from
an existing AGC product can be a primary or backup control center site.
Featured OpenAGC functionality includes:
Market operation
Multi-area Control
NERC performance monitoring
LFC
Online economic dispatching
Reserve monitoring (RM)
AGC performance monitoring
Unit generation schedule
Trade schedule and evaluation
Production cost analysis
Unit response test
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Figure 2.4: AGC System data Flow
In today's deregulated environment, power producers need a means of easily
separating generation resources into control groupings (sometimes referred
to as multi-area). OpenAGC is specifically designed to meet this need,
allowing individual generator assignments to separate control groupings or
areas. The user interface makes it easy to view resources according to these
groupings because it consists of tabular and graphic displays that put the
operator “in control” of all resources.
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Trends and plots are used to summarize vital system information and can
easily be customized based on information preference. When used in
conjunction with OSI's OpenView. NET based Graphical User Interface,
AGC information can be made available to the company enterprise via a
web browser, subject to individual permissions.
OpenAGC supports many features for tuning and control, yet it maintains its
simplicity through intuitiveness, making optimum performance and control
response easily realizable. Also, realistic system response is achieved
through proven non-linear filtering techniques for computing Area and Unit
Control Errors (ACE and UCE). Unit models are general-purpose, allowing
for any generator type to be modeled and numerous control modes and
regulation participations allow for tailored generation response as shown in
Figure 2.5.
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Figure 2.5: AGC monitor for tailored generation response
2.2.2 Advanced Control Systems
AGC is a stand-alone subsystem that can be installed on any PRISM
SCADA Master as shown in Figure 2.6 [4]. AGC regulates the power
output of electric generators within a prescribed area in response to changes
in system frequency, tie-line loading, and the relation of these to each other.
This maintains the scheduled system frequency and established interchange
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with other areas within predetermined limits. AGC monitors and controls
power generation with these overall objectives:
Minimize area control error.
Minimize operating costs in conjunction with ED calculation
software.
Maintain generation at fixed (base load) values.
Ramp generation in a linear fashion according to a schedule specified
by the operator.
In normal operation, the AGC subsystem adjusts the power of the generating
units automatically. This keeps the area's actual net interchange approximate
to the scheduled interchange and the actual frequency near the scheduled
frequency.
Figure 2.6: AGC installed on PRISM SCADA Master
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All NERC performance calculations and reports are provided, including
alarming and event storage for post analysis. A time error correction
mechanism is also included. All tuning parameters are located in the Real-
time database and can be adjusted through screen displays without invoking
the database editor. For special filtering performance, the Real-time
database has a set of linear and non-linear data filtering functions that can be
selected and redefined.
AGC can communicate with any data source or data link through the Real-
time database. It supports primary and secondary data sources for important
variables, such as the system frequency, unit generation and tie-line power
and automatically switches the data source if one source fails to provide
reliable data.
Design Development
3.1 INTRODUCTION
As shown in Figure 3.1, the control of active and reactive power is necessary
in order to keep the power system in the steady state. The objective of the
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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. Change 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 LFC loop controls
the real power and frequency and the AVR loop regulates the reactive power
and voltage magnitude. LFC has made the operation of interconnected
system possible [5].
Figure 3.1: Schematic diagram of LFC and AVR of a synchronous generator.
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3.2 Frequency Control:
The operation objectives of the LFC are to maintain reasonably uniform
frequency to divide the load between generators 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 . The error signal,
i.e., f and Ptie, are amplified, mixed and transformed into a real power
command signal Pv, 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 Pg which will change the values of f and Ptie 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 design linear as well as nonlinear systems. In order to use
the transfer function and linear state equations, the system must first be
linearized. Proper assumptions and approximations are made to linearize the
mathematical equations describing the system, so the transfer functions
model are obtained for the following components.
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3.2.1 Generator Model
The overall generator–load dynamic relationship between the incremental mismatch power (ΔPm−ΔPe) and the frequency deviation (Δw) can be expressed as:
(3.1)
Equation (3.1) can be represented in a block diagram as in Figure 3.2.
Figure 3.2 Generator block diagram.
3.2.2 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. The speed-load characteristic of a
composite load is approximated by:
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(3.2)
Where PL is the nonfrequency-sensitive load change, and Dw is the
frequency-sensitive load change. D is expressed as percent change in load
divided by percent change in frequency. For example, if load is changed by
1.6 percent for a 1 percent change in frequency, then D = 1.6. Including the
load model in the generator block diagram, results in the block diagram of
Figure 3.3, eliminating the simple feedback loop in Figure 3.3, results in the
block diagram shown in Figure 3.4.
Figure 3.3: Generator and load block diagram.
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Figure 3.4: Generator and load block diagram.
3.2.3 Prime Mover Model
The source of mechanical power commonly known as the prime mover. The
model for the prime mover relates to changes in mechanical power output
Pm to changes in the controller of the mechanical power Pv. The simplest
prime mover model for the motor can be approximated with a single time
constant T, resulting in the following function
(3.3)
Figure 3.5: block diagram for simple nonreheat steam turbine
3.2.4 Governor Model
When the generator electrical load is suddenly increased, the electrical
power exceeds the mechanical power input. The reduction in kinetic energy
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causes the motor speed and consequently the generator frequency to fall.
The change in speed is sensed by the PI controller which acts to adjust the
mechanical power controller value to bring the speed to a new steady-state.