UNIT V

COMPUTER CONTROL OF POWER SYSTEMS

5.1 Need For Computer Control Of Power System

5.2 Energy Control Centre

5.3 Data Acquisition And Control (DAS)

5.4 Supervisory Control And Data Acquisition System

5.5 Scada System Components

5.6 Energy Management System

5.7 Operating States Of Power System

5.8 Control Strategies

5.9 State Estimation

5.10 Weighted Least Square (WLS) Algorithm

5.1 NEED FOR COMPUTER CONTROL OF POWER SYSTEM

• Increase in unit size, growth of interconnected and the need to maintain the

system in normal mode require sophisticated control, instrumentation and

protection.

• The multiplicity of monitoring instruments in the control room and their

distance apart make the observation almost impossible, especially during the

intense activity of plant start up.

• The operation of changing plot parameters and take critical decisions.

• These requirements led to the development and application of more advanced

computer based direct control and data processing systems.

5.2 ENERGY CONTROL CENTERS

Today’s power systems are very huge in terms of Installed capacity, Energy

generated, Transmission and Distribution system, Number of customers and Total

investment. Installed capacity in India exceeds 206 GW with annual energy generated

energy exceeding 1000 Billion KWh (1000 x 1012 KWh). The power system feeds a

very large number of domestic, commercial, industrial, agriculture and other

customers. Operation and control of such a big interconnected power system is really

challenging task and it cannot be done manually. Therefore power systems are

controlled by using powerful computers installed at Energy Control Centers.

Fig.5.1 Energy control centre

The various functions of an energy control centre can be enumerated as under:

1. Load forecasting

2. Planning studies

3. System monitoring
4. State estimation

5. Unit commitment and economic dispatch

6. Automatic generation control

7. Reactive power management

8. Security control

9. System maintenance

5.3 DATA ACQUISITION AND CONTROL (DAS)

In general analog DASs are used for measurement systems with wide

bandwidth. But the accuracy is less. So digital DASs which have high accuracy, low

perchannel cost and narrow bandwidth (slowly varying signal) are designed. Figure

shows the block diagram of a digital data acquisition system. The function of the

digital data acquisition system include handling analog signals, making the

measurement, converting and handling digital data, internal programming and

control.

Figure shows the block diagram of Data acquisiti0on system. Here, the

transducer translates physical parameters to electrical signals acceptable by the

acquisition system. The physical parameters include temperature, pressure,

acceleration, weight, displacement, velocity etc.

 Fig 5.2 .Data acquisition system

Electrical quantities such as voltage, stance, and frequency may be measured

directly. The signal conditioner includes the supporting circuitry for the transducer.

This circuit may provide excitation power, balancing circuits and calibration elements

and an example of this is a strain-gauge bridge lance and power supply unit The

scanner or multiplexer accepts multiple analog inputs and sequentially connects them

to one measuring instrument.

The signal converter translates the analog signal to a form acceptable by the

analog to digital converter like an amp1ifier used for amplifying low-level voltages

generated by thermocoup1es or strain gauges. The analog to digital converter (ADC)

converts the analog voltage to its equivalent digital form. The output of the ADC may

displayed visually and is also available as voltage outputs in discrete steps for further

processing or recording on a digital recorder.

The auxiliary section contains instruments for system programming and digital

data processing such as linearising and limit comparison. These functions may be

performed by individual instruments or by a digital computer. The digital recorder

records digital information on punched cards, perforated paper tape, magnetic tape,

typewritten pages or a combination of these systems. Digital recorder may be

preceded by a coupling unit that translates the digital information to the proper form

for entry into particular digital recorder selected .

5.4 SUPERVISORY CONTROL AND DATA ACQUISITION SYSTEM

Proper and efficient energy management system requires lot of data about the

operating conditions. Further, many control actions are to be carried out at far off

places. Executing such control actions manually will cause time delays resulting long

outage duration and poor reliability. SCADA systems have been developed to

overcome such problems. The following are the some of the main functions of

SCADA.

Supervisory control and data acquisition (SCADA) is a control

system architecture that uses computers, networked data communications

and graphical user interfaces for high-level process supervisory management, but

uses other peripheral devices such as programmable logic controllers and

discrete PID controllers to interface to the process plant or machinery.

Data Acquisition: To provide data, measurements and status information to the

operator.

Automatic generation control: To control the generations at the power plants.

Load Shedding: To make automatic load shedding in emergent conditions to avoid

system collapsing.

Load Restoration: To restore the loads in steps to bring the system to normal state.
Supervisory Control: To operate the circuit breaker remotely.

Logging: To log all data and information in a systematic manner.

Alarms: To send alarm signals in case of undesirable operating conditions. To

fulfill the above operations SCADA has the following components:

Sensors and Control Relays: Analog and digital sensors along with control relays

which can interface with the system.

Remote Terminal Units (RTU): RTUs are microprocessor controlled electronic

devices deployed in field at specific sites and locations. They collect necessary data

and transmit them to SCADA for processing.

Master Unit: Large computer system which serves as a central processor.

Communication Links: Fiber optic / satellite / microwave communications are

employed to link RTUs with SCADA.

Necessary Software: To execute different operational problems.

Fig 5.3 simple scada system

 The operator interfaces which enable monitoring and the issuing of process

commands, such as controller set point changes, are handled through the SCADA

supervisory computer system. However, the real-time control logic or controller

calculations are performed by networked modules which connect to the field sensors

and actuators. The key attribute of a SCADA system is its ability to perform a

supervisory operation over a variety of other proprietary devices.

The SCADA software exists only at this supervisory level as control actions

are performed automatically by RTUs or PLCs. SCADA control functions are usually

restricted to basic overriding or supervisory level intervention. For example, a PLC

may control the flow of cooling water through part of an industrial process to a set

point level, but the SCADA system software will allow operators to change the set

points for the flow.

Fig 5.4.SCADA Layout

 The SCADA also enables alarm conditions, such as loss of flow or high

temperature, to be displayed and recorded. A feedback control loop is directly

controlled by the RTU or PLC, but the SCADA software monitors the overall

performance of the loop.Data acquisition begins at the RTU or PLC level and

includes instrumentation readings and equipment status reports that are

communicated to level 2 SCADA as required.

Data is then compiled and formatted in such a way that a control room operator

using the HMI (Human Machine Interface) can make supervisory decisions to adjust

or override normal RTU (PLC) controls. Data may also be fed to a historian, often

built on a commodity database management system, to allow trending and other

analytical auditing.

SCADA systems typically use a tag database, which contains data elements

called tags or points, which relate to specific instrumentation or actuators within the

process system according to such as the Piping and instrumentation diagram. Data is

accumulated against these unique process control equipment tag references.

5.5 SCADA SYSTEM COMPONENTS

5.5.1 Supervisory computers

5.5.2 Remote terminal units

5.5.3 Programmable logic controllers

5.5.4 Communication infrastructure

5.5.5 Human-machine interface

5.5.6 Alarm handling

Fig 5.5 Scada Components

5.5.1 Supervisory computers

This is the core of the SCADA system, gathering data on the process and

sending control commands to the field connected devices. It refers to the computer

and software responsible for communicating with the field connection controllers,

which are RTUs and PLCs, and includes the HMI software running on operator

workstations. In smaller SCADA systems, the supervisory computer may be

composed of a single PC, in which case the HMI is a part of this computer.

In larger SCADA systems, the master station may include several HMIs hosted

on client computers, multiple servers for data acquisition, distributed software

applications, and disaster recovery sites. To increase the integrity of the system the

multiple servers will often be configured in a dual-redundant or hot-standby

formation providing continuous control and monitoring in the event of a server

malfunction or breakdown.

5.5.2 Remote terminal units

Remote terminal units also known as (RTUs), connect to sensors and actuators

in the process, and are networked to the supervisory computer system. RTUs are

"intelligent I/O" and often have embedded control capabilities such as ladder logic in

order to accomplish boolean logic operations.

5.5.3 Programmable logic controllers

Also known as PLCs, these are connected to sensors and actuators in the

process, and are networked to the supervisory system in the same way as RTUs.

PLCs have more sophisticated embedded control capabilities than RTUs, and are

programmed in one or more IEC 61131 programming languages. PLCs are often used

in place of RTUs as field devices because they are more economical, versatile,

flexible and configurable.

5.5.4 Communication infrastructure

This connects the supervisory computer system to the remote terminal units

(RTUs) and PLCs, and may use industry standard or manufacturer proprietary

protocols. Both RTUs and PLCs operate autonomously on the near-real time control

of the process, using the last command given from the supervisory system. Failure of

the communications network does not necessarily stop the plant process controls, and

on resumption of communications, the operator can continue with monitoring and

control. Some critical systems will have dual redundant data highways, often cabled

via diverse routes.

5.5.5 Human-machine interface

The human-machine interface (HMI) is the operator window of the supervisory

system. It presents plant information to the operating personnel graphically in the

form of mimic diagrams, which are a schematic representation of the plant being

controlled, and alarm and event logging pages.

The HMI is linked to the SCADA supervisory computer to provide live data to

drive the mimic diagrams, alarm displays and trending graphs. In many installations

the HMI is the graphical user interface for the operator, collects all data from external

devices, creates reports, performs alarming, sends notifications, etc.Mimic diagrams

consist of line graphics and schematic symbols to represent process elements, or may

consist of digital photographs of the process equipment overlain with animated

symbols.

Supervisory operation of the plant is by means of the HMI, with operators

issuing commands using mouse pointers, keyboards and touch screens. For example,

a symbol of a pump can show the operator that the pump is running, and a flow meter

symbol can show how much fluid it is pumping through the pipe. The operator can

switch the pump off from the mimic by a mouse click or screen touch. The HMI will

show the flow rate of the fluid in the pipe decrease in real time.

The HMI package for a SCADA system typically includes a drawing program

that the operators or system maintenance personnel use to change the way these
points are represented in the interface. These representations can be as simple as an

on-screen traffic light, which represents the state of an actual traffic light in the field,

or as complex as a multi-projector display representing the position of all of the

elevators in a skyscraper or all of the trains on a railway.

5.5.6 Alarm handling

An important part of most SCADA implementations is alarm handling. The

system monitors whether certain alarm conditions are satisfied, to determine when an

alarm event has occurred. Once an alarm event has been detected, one or more

actions are taken (such as the activation of one or more alarm indicators, and perhaps

the generation of email or text messages so that management or remote SCADA

operators are informed).

In many cases, a SCADA operator may have to acknowledge the alarm event;

this may deactivate some alarm indicators, whereas other indicators remain active

until the alarm conditions are cleared. Alarm conditions can be explicit—for example,

an alarm point is a digital status point that has either the value NORMAL or ALARM

that is calculated by a formula based on the values in other analogue and digital

points—or implicit: the SCADA system might automatically monitor whether the

value in an analogue point lies outside high and low- limit values associated with that

point.

Examples of alarm indicators include a siren, a pop-up box on a screen, or a

coloured or flashing area on a screen (that might act in a similar way to the "fuel tank

empty" light in a car); in each case, the role of the alarm indicator is to draw the
operator's attention to the part of the system 'in alarm' so that appropriate action can

be taken.

PLC/RTU programming

Smart" RTUs, or standard PLCs, are capable of autonomously executing

simple logic processes without involving the supervisory computer. They employ

standardized control programming languages such as under, IEC 61131-3(a suite of 5

programming languages including function block, ladder, structured text, sequence

function charts and instruction list), is frequently used to create programs which run

on these RTUs and PLCs.

Unlike a procedural language such as the C programming or FORTRAN, IEC

61131-3 has minimal training requirements by virtue of resembling historic physical

control arrays. This allows SCADA system engineers to perform both the design and

implementation of a program to be executed on an RTU or PLC. A programmable

automation controller (PAC) is a compact controller that combines the features and

capabilities of a PC-based control system with that of a typical PLC.

PACs are deployed in SCADA systems to provide RTU and PLC functions. In

many electrical substation SCADA applications, "distributed RTUs" use information

processors or station computers to communicate with digital protective relays, PACs,

and other devices for I/O, and communicate with the SCADA master in lieu of a

traditional RTU.
PLC commercial integration

Since about 1998, virtually all major PLC manufacturers have offered

integrated HMI/SCADA systems, many of them using open and non-proprietary

communications protocols. Numerous specialized third-party HMI/SCADA

packages, offering built-in compatibility with most major PLCs, have also entered the

market, allowing mechanical engineers, electrical engineers and technicians to

configure HMIs themselves, without the need for a custom-made program written by

a software programmer.

The Remote Terminal Unit (RTU) connects to physical equipment. Typically,

an RTU converts the electrical signals from the equipment to digital values such as

the open/closed status from a switch or a valve, or measurements such as pressure,

flow, voltage or current. By converting and sending these electrical signals out to

equipment the RTU can control equipment, such as opening or closing a switch or a

valve, or setting the speed of a pump.

Communication infrastructure and methods

SCADA systems have traditionally used combinations of radio and direct

wired connections, although SONET/SDH is also frequently used for large systems

such as railways and power stations. The remote management or monitoring function

of a SCADA system is often referred to a telemetry . Some users want SCADA data

to travel over their pre-established corporate networks or to share the network with

other applications. The legacy of the early low-bandwidth protocols remains, though.

SCADA protocols are designed to be very compact.

 Many are designed to send information only when the master station polls the

RTU. Typical legacy SCADA protocols include Modbus RTU, RP-570, Profibus and

Conitel. These communication protocols, with the exception of Modbus (Modbus has

been made open by Schneider Electric), are all SCADA-vendor specific but are

widely adopted and used. Standard protocols are IEC 60870-5-101 or 104, IEC

61850 and DNP3. These communication protocols are standardized and recognized

by all major SCADA vendors.

Many of these protocols now contain extensions to operate over TCP/IP.

Although the use of conventional networking specifications, such as TCP/IP, blurs the

line between traditional and industrial networking, they each fulfill fundamentally

differing requirements. Network simulation can be used in conjunction with SCADA

simulators to perform various 'what-if' analyses.

RTUs and other automatic controller devices were developed before the

advent of industry wide standards for interoperability. The result is that developers

and their management created a multitude of control protocols. Among the larger

vendors, there was also the incentive to create their own protocol to "lock in" their

customer base. A list of automation protocols is compiled here.

5.6 ENERGY MANAGEMENT SYSTEM

Energy Management is the process of monitoring, coordinating and controlling

the generation, transmission and distribution of electrical energy. An energy control

centre utilizes the computer aided tools to monitor, control and optimize the

generation, transmission and distribution of electrical energy.

 The functions of a typical control centre can be categorized into three

subsystems as shown namely the data acquisition and processing subsystem, the

energy management / automatic generation control subsystem and the security

monitoring and control subsystem. SCADA (Supervisory Control and Data

Acquisition System) forms the front end for Energy Management Systems (EMS).

A simple SCADA provides the raw data of the operating condition of the

system to the control centre operators. State Estimation forms the backbone for

Energy Management System. Although reliability remains a central issue, the need

for the real time network models becomes more important than before due to new

energy market related functions are to be added to the existing EMS.

These models are based on the results yielded by state estimation and are used

in network applications such as security monitoring, contingency analysis, optimal

power flow, economic dispatch, unit commitment, automatic generation control and

economic interchange evaluation An(EMS) is a system of computer-aided tools used

by operators of electric utility grids to monitor, control, and optimize the performance

of the generation and/or transmission system.

 Fig 5.6 . Energy Management System

The computer technology is also referred to as SCADA/EMS or

EMS/SCADA. In these respects, the terminology EMS then excludes the monitoring

and control functions, but more specifically refers to the collective suite of power

network applications and to the generation control and scheduling applications.

Manufacturers of EMS also commonly supply a corresponding dispatcher

training simulator (DTS). This related technology makes use of components of

SCADA and EMS as a training tool for control centre operators. It is also possible to

acquire an independent DTS from a non-EMS source such as EPRI

Energy management systems are also often commonly used by individual

commercial entities to monitor, measure, and control their electrical building loads.
Energy management systems can be used to centrally control devices like HVAC

units and lighting systems across multiple locations, such as retail, grocery and

restaurant sites.

Energy management systems can also provide metering, submetering, and

monitoring functions that allow facility and building managers to gather data and

insight that allows them to make more informed decisions about energy activities

across their sites.

5.7 OPERATING STATES OF POWER SYSTEM

For purpose of analyzing power system security and designing appropriate

control systems, it is helpful to conceptually classify the system operating conditions

into the following five states. Normal, Alert, Emergency, In extremis (or extreme

emergency) and Restorative. Figure 2 depicts these operating states and the ways in

which transition can take place from one state to another.

5.7.1 Normal State

5.7.2 Alert State

5.7.3 Emergency State

5.7.4 In Extremis State

5.7.5 Restorative State

 Fig 5.7 Operating states of a power system

5.7.1 NORMAL STATE:

In the normal state, all system variables are within the normal range and no

component is being overloaded. The system operates in a secure manner and is able

to withstand a contingency without violating any of the constraints.

5.7.2 ALERT STATE:

The system enters the alert state if the security level falls below a certain limit

of adequacy, or if the possibility of disturbance increases because of adverse weather

conditions such as the approach of severe storms. In this state, all the system

variables are still within the acceptable range and all the constraints are satisfied.

However, the system has been weakened to a level where a contingency may cause

an overloading of a component that places the system in an emergency state. If the

disturbance is very severe, the in extremis state may result directly from the alert

state.

5.7.3 EMERGENCY STATE:

The system enters the emergency state, if a sufficiently severe disturbance

occurs when the system is in the alert state. In this state, voltages at many buses are

low and / or component loadings exceed the short-term emergency ratings. The

system is still intact and may be restored to the alert state by initiating emergency

control actions such as fault clearing, excitation control, fast-valving and load

curtailment. If the above measures are not applied or are ineffective, the system will

move to in extremis state.

5.7.4 IN EXTREMIS STATE:

If the control action taken during the emergency state is insufficient, then the

system enters into in extremis state. The result is cascading outages and possibly a

shut-down of major portion of the system. Control actions, such as load shedding and

controlled system separation, are aimed at saving as much system as possible from a

widespread blackout.

5.7.5 RESTORATIVE STATE:

Preventive action, such as generation shifting or increased reserve, can be

taken to restore the system to the normal state. If the restorative steps do not succeed

fully, the system will move into the alert state. In case the control action taken are

effective, the system moves to restorative state in which further action is being taken

to reconnect all the facilities and to restore the system load. The system transits from

the restorative state to either alert state or normal state, depending on the system
conditions.

5.8 CONTROL STRATEGIES

The control strategies which are to be adopted when the system is not in normal state

can be summarized as under.

Alert State: Preventive control to restore adequate spinning reserve, generation

shifting, tie-line rescheduling and voltage reduction (if extremely needed)

Emergency State: Immediate control to clear component overload, fast-valving,

exciter control, load control, capacitor switching and all controls mentioned in alert

state.

In extremis State: Heroic action to control disruption of entire system, load

shedding, controlled islanding and all controls mentioned in emergency state.

Restorative State: Corrective control to re-establish viable system, generator units

restarting and synchronization, load restoration, re- synchronization of different

islands and areas

5.9 STATE ESTIMATION

The state estimation can be defined as a process which determines the

operating state of the power system to allow the system operator to make decisions

aimed at maintaining the security of the power system. A state estimator is capable of

filtering the information to provide a more accurate picture of the status of the

system.
 The traditional objective of the state estimation is to reduce measurement

errors by utilizing the redundancy available in the most measurement systems. In

particular, the objectives are to reduce the variance of the estimate and to improve the

overall efficiency. The various roles and functions of state estimation in Energy

Management System are shown in Figure.

Fig.5.8 Roles and functions of state estimation

The other major objectives of traditional state estimation are.,

➢ Detection of erroneous measurements and bad data

➢ Detection of erroneous assumptions about the system, particularly the status of

switches and breakers.

➢ Ability to provide information for unmetered or unmonitored parts of the

system.

➢ Use of redundancy in order to improve the parameters for the electrical models

of the system.
 State estimation stands in between the real time information and power system

control and monitor applications, playing a very crucial role in the real time power

system control and operation. The SCADA data, phasor measurement data, network

model and the pseudo measurements form the input for the power system state

estimation algorithm. The applications such as contingency analysis, security

analysis, optimal power flow etc., are carried out based on the estimates provided by

the state estimator.

State estimation is a digital processing scheme, which provides a real time data

for many of the central control and dispatch functions in a power system. Its purpose

is to improve the dispatch of energy, system reliability and planning capabilities by

understanding the operating state of the power system. In general the state variables

in power system are the voltage magnitudes and phase angles at all the buses except

the slack bus.

In order to ensure secure and economical operation of the power systems, the

operator must be aware of the exact state of the power system at regular intervals.

The main objective of state estimation in power systems is therefore to build a

complete and reliable database. Such a database is obtained by feeding the measured

data to a central real time computer, which on the basis of a prewritten mathematical

program, filters the data and extends it to cover all information regarding the system.

In short, state estimation guarantees reliable information even if some of the

measurements are inaccurate. Thus, the central task of the state estimator is to

validate the information supplied to the system operator. The major ingredients of 20

state estimation are: measurement devices located at strategic points on the system,
high speed data transfer system to convey the measured information to the control

centre, a real time computer with interfacing equipment to accept and display

information and efficient estimation algorithm.

5.10 Weighted Least Square (WLS) algorithm

Weighted Least Square (WLS) algorithm is normally used for estimating the

state of the system. The state of a system may be defined as the minimal amount of

information that one has to know about the system in order to predict its future

evaluation. From this view point, the complex voltages in all buses in a power system

are qualified to be assigned as state variables. Specifically, for an N bus system,

taking a particular bus (preferably the swing bus) as reference, we may assign N

voltage magnitudes and (N – 1) phase angles of voltages, which are to be called as

state variables.

Thus, for an N bus system, the dimension of the state vector is (2N – 1). The

rationale behind this choice is that, knowing these variables along with the active and

reactive power injections at the N buses (real Pi and reactive Qi at all buses except Pi

at the swing bus) and system parameters it is possible to compute all measurements

pertaining to the system. When observation errors are present the success of state

estimation depends on the redundancy of observed data.

Thus, if the state variables are ‘n’ (equal 2N – 1) in number and if ‘n’ load

injections at the buses are given then the problem reduces to a load flow calculation.

State estimation is different from load flow studies in that the number of input

variables ‘m’ should be greater than (2N – 1), the dimension of the state vector.

It is this redundant information (number of unknown variables being less than

the number of defining equations) which is to be effectively used in some form of

averaging process to filter the data. The relationships between the different variables

involved in the state estimation are explicitly given in Figure

Fig 5.9 Different variables involved in the state estimation