Intelligent Management of Electrical Systems in Industries

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Intelligent Management Of Electrical Systems in Industries

S.R.M.S.C.E.T Bareilly

SEMINAR REPORT ON

Intelligent Management of Electrical

Systems in Industries

Submitted to Submitted byMr. Vineet Srivastava Saddam Hussain

1101 !10"

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A#stra$t

The automation of public electricity distribution has developed very

rapidly in the past few years. The same basis can be used to develop new

intelligent applications for electricity distribution networks in industrial plants.

Many new applications have to be introduced because of the different

environment and needs in industrial sector. The paper includes a system

description of industrial electric system management. The paper discusses on the

requirements of new applications and methods that can be used to solve

problems in the areas of distribution management and condition monitoring of

industrial networks.

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CONTENTS

1 Introduction ...... !

2 "pplications for supporting the public distribution network management ................................................ #

$ %escription of the system environment .. &

! "pplication functions for distribution management in industrial plants ............ 11

# "dvanced %istribution"utomation .....................................1!

#.1 %istribution 'ystem of (uturewith "%" ..1)

* %istribution Management (unctions ....................1&

)"pplication (unctions of %ata Management'ystems ...................................21

).1+ ,oad modeling ............................................21

).2+ -eliability management...........2$

).$+ oltage dip analyses................................2#

).!+ /ower quality analyses................2*

).#+ 0ondition monitoring..........2*

& 0onclusion.............................................2

ibliography..................................$

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Intr%du$ti%n

Industrial plants have put continuous pressure on the advanced process

automation. 3owever4 there has not been so much focus on the automation of the

electricity distribution networks. "lthough4 the uninterrupted electricity distribution is

one basic requirement for the process. " disturbance in electricity supply causing

the5downrun6 of the process may cost huge amount of money. Thus the intelligent

management of electricity distribution including4 for e7ample4 preventive condition

monitoring and on8line reliability analysis has a great importance. 9owadays the above

needs have aroused the increased interest in the electricity distribution automation of

industrial plants. The automation of public electricity distribution has developed very

rapidly in the past few years. ery promising results has been gained4 for e7ample4 in

decreasing outage times of customers. 3owever4 the same concept as such cannot be

applied in the field of industrial electricity distribution4 although the bases of automation

systems are common. The infrastructures of different industry plants vary more from each

other as compared to the public electricity distribution4 which is more homogeneous

domain. The automation devices4 computer systems4 and databases are not in the same

level and the integration of them is more complicated.

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"pplications for supporting the publicdistribution network management

It was seen already in the end of & :s that the conventional automation system ;i.e.

'0"%"+ cannot solve all the problems regarding to network operation.


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The core of the whole %M' is the dynamic ob@ect8oriented network model. The

distribution network is modeled as dynamic ob@ects which are generated based on

the network data read from the network database. The network model includes the

real8time state of the network ;e.g. topology and loads+. %ifferent network

operation tasks call for different kinds of problem solving methods. arious

modules can operate interactively with each other through the network model4

which works as a blackboard ;e.g. the results of load flow calculations are stored

in the network model4 where they are available in all other modules for different purposes+.The present %M' is a Aindows 9T 8program implemented by isual

0BB. The prototyping meant the iteration loop of knowledge acquisition4

modeling4 implementation4 and testing. /rototype versions were tested in a real

environment from the very beginning. Thus the feedback on new inference

models4 e7ternal connections4 and the user8interface was obtained at a very early

stage. The aim of a real application in the technical sense was thus been achieved.

The %M' entity was tested in the pilot company4 Coillis8'atakunnan 'DhkE


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The e7periences as a whole were so encouraging that the %M' was modified as

a commercial product. The vendor was first a small (innish software company. 'ince

1 ) the %M' has been a worldwide software product of " Transmit


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&es$ri'ti%n %( t)e system envir%nment

" big industrial plant differs from public distribution company by organi?atory

structure and by system environment. " production is divided into many departments or

many companies. These units have the responsibility of production and maintenance.

ery often the maintenance is maintained by a service company. "n energy department or

company is in charge of local energy production and of the distribution network. "bove

organi?ations may have some control systems that serve for their needs only4 but usually

information systems are closely connected together. " process automation system is the

most important system in an industrial plant4 sometimes including other systems4 as

illustrated in (ig. 1. (or e7ample4 all energy production and distribution network control

tasks can be done in a process automation system. 9ormally4 because of the reliability

reasons4 vital parts of distribution network control is independent on the process

automation. The independency of process automation system vendor has been one reason

for separate systems4 too.

(igure1G "utomation and information systems of an industrial plant.

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The systems in (ig. 1 utili?e many databases4 which contain data that can be used

in new applications. /rocess automation systems collect data for process monitoring and

optimi?ation tools. The databases contain information of material flow4 energy flow and

control data of production machines. Maintenance databases include technical

specifications and condition data of production machine components. 'imilar information

of electricity network components is supported by network database. /roduction

programs are stored in the databases of administrative systems.

Intelligent applications are needed toG

8 3andle large amount of information available. This includes filtering of data and producing new information by collecting data.

8 Illustrate comple7 dependencies of electricity distribution and production processes in

abnormal situations.

8 >ive instructions for operators in fault situations. " risk of misoperation in unusual fault

situation is obvious and prevents or delay operatorsH decision making.

8 "utomi?e analysis tasks. 0ontinuous information analysis is not possible manually.

In order to introduce new intelligent applications for the management of electric

systems in industrial plants4 a basis for implementation is needed. The following

requirements should be satisfiedG

8 %ocumentation of electricity distribution network is available for the systems. 9etwork

databases can supply this information.


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8 9etwork4 process and motor measurements are available for the system. This means4

that data acquisition from multiple sources with capability to use various data transfer

methods is needed4 as illustrated in (ig. 2.

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A''li$ati%n (un$ti%ns (%r distri#uti%n mana*ement in

industrial'lants

"s mentioned above the concept of public distribution automation cannot be

applied as such in the management of industrial electricity networks. (or e7ample4 fast

and accurate fault location has a great importance for reducing the outage time of

customers in the public electricity distribution4 while there is no special need of such a

function in industrial networks. /redictive condition monitoring4 reliability calculations4

and protection relay coordination to prevent disturbances in advance are more important.

0aused by the features of industrial networks there are needs for methods to model

dynamic phenomena and harmonics4 and to calculate load8flow and fault currents in ring

connected networks. "n essential need is the load modeling which differs considerable

from the public distribution. The basis of the distribution management system ;i.e. the use

of network model as the blackboard+ is common in the both domains. The network model

includes the real8time topology and network calculation results in the prevailing

switching and load conditions. The main functions of system entity for the industrial

networks are listed in the followingG

-eal8time network monitoring4 state estimation and optimi?ationG

8 Topology management

8 load flow and fault currents also as dynamic phenomena

8 Monitoring and compensation of reactive power

8 monitoring of harmonics and resonances

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8 Minimi?ation of power losses

/lanning and simulation of operation actions

8 switching planning

8 "utomatic load shedding and forming a local island

8 switching the network as a part of the national grid

8 fault situations

Management of disturbances

8 Jvent analysis

8 (ault location and network restoration8 /reventive condition monitoring

8 /rotection relay coordination

8 -eliability calculations

8 reporting

%istribution "utomation which includes feeder automation and distribution

management systems ;%M'+ is an important technique in distribution network. The

distribution management systems are composed of distribution management functions.

The %M( is an entity which incorporates different applications on a single platform over

which supervision is made. This mainly supports documentation of network data

planning operation and reliability management of distribution networks. arious

application functions for distribution management in industrial plants are mainly load

modeling 4reliability management 4 power quality analysis4 voltage dip analysis and

condition monitoring ."ll this are incorporated in a domain of distribution management

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functions. "dvanced distribution automation ;"%"+ modern day approach towards

efficient management of distribution networks.

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A&VANCE& &ISTRIB+TION A+TOMATION

Traditional distribution systems were designed to perform one functionK

distributing power to end users. The distribution system of the future will be more

versatile and will be multifunctional.

'trategic drivers for "%" are to

L Improve system performance

L -educe outage times

L "llow the efficient use of distributed energy resources

L /rovide the customer more choices and

L To integrate the customer systems

(or "%" to work4 the various intelligent devices must be interoperable both in the

electric system architecture and in the communication and control architecture.

.

(igure$G "%" architecture

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"%" will enable the distribution system to be configured in new ways for such

things as looped secondaries or intentional islanding to facilitate easy recovery from

outages and to deal with other emergencies.

(igG !

The three ma@or components of "%"

(le7ible electrical system architecture

-eal8time state estimation tools

0ommunication and control system based on open architecture standards

The intelligent universal transformer is a prime e7ample of a new electronic device that

will be a cornerstone of "%". It will provide a variety of functions including

oltage stepping

oltage regulation

/ower quality enhancement

9ew customer service options such as %0 power output

/ower electronic replacement for conventional copper and iron transformers

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The (le7ible Jlectric "rchitecture and the


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&istri#uti%n System %( ,uture -it) A&A

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&ISTRIB+TION MANA EMENT ,+NCTIONS

%istribution management functions form an entity of applications supporting

documentation of network data4 and planning4 operation and reliability management of

distribution network in industrial plants. The functions can be included into different

computer systems4 like "M=(M=>I'4 %istribution Management 'ystem ;%M'+4 and

'0"%" or case specific customi?ed applications. The main functions of distribution

management entity for the industrial networks are listed in the followingG

L %ocumentation of network data

L >raphical user interfaces

L -eal8time network monitoring4 state estimation and optimi?ation

8 Topology management4 load flow and fault current calculation4 monitoring and

compensation of reactive power4 monitoring of harmonics and resonance4 and

minimi?ation of power losses

L /lanning and simulation of operation actions

8 switching planning4 fault situations4 automatic load shedding and forming a local island

L Management of disturbances and reliability

8 /reventive condition monitoring4 reliability and availability management4 protection

relay coordination4 event analysis4 fault location and network restoration4 reporting.

0aused by the features of industrial networks the importance of the distribution

management functions are different as in public electricity networks. There are also needs

for new methods. "n essential need is the load modeling which differs considerable from

the public distribution. /redictive condition monitoring4 reliability management4 and

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protection relay coordination to prevent disturbances in advance have a great importance.

'ome functions of the %M' for the management of public distribution networks can be

applied almost as such also in the management of industrial electricity networks4 e.g.

topology management.

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APP/ICATION ,+NCTIONS O, &ATA MANA EMENT

S STEMS

1 /%ad m%delin*

The essential basis for advanced application functions is the modeling of loads

connected to the network. Nsually there are only few measurement points in the network.

3owever4 loading of every load node of the network must be known in the network

calculations. (or that purpose the loads are estimated by load models.

The essential need for the load models is that they form a basis for the load8flow

calculations. -esults of load8flow calculations are utili?ed different kind of tasks as real8

time network monitoring and optimi?ation4 and switching planning. Information on loads

can also be utili?ed in preventive condition monitoring and reliability analyses. "lthough4

the loads ;i.e. the current+ of some nodes can be measured on8line4 models are needful

because of the %M' can be used also in simulated state4 when the information of system

does not correspond the current real8time state of the distribution network.

In the domain of public electricity distribution hourly load curves have been

determined for each customer group to be used in load8flow calculation and load

forecasting. In industrial plants the load modeling should be based mainly on the process

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itself and its behavior. ,oad models can be determined by making enough measurements

in different known process conditions. 3owever4 the industrialplants vary from each other

quite much4 which means that load models determined in one plant may not be able

to used as such in other one.


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(ig #G 9etwork ,oad Model %etermining

,oad forecasting in the industrial environment cannot be based on any regularity

of behavior. -eliable forecasting assumes use of methods which can utili?e production

plans in some time distance which also can have a large difference with each other and

include inaccurate information. The load forecasting of the network feeding some process

bases on the known behavior of the process4 earlier measured values and the planned

production.

Cal$ulati%n met)%ds (%r mes)ed net-%r2s

The %M' for public distribution management included load flow and fault current

calculation procedures4 which worked only in radial networks. The need for calculating

meshed networks in industrial distribution networks is anyway obvious ;e.g. there are

several fault current sources+.

,oad flow calculation for meshed network leads to a group of non8linear

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equations. 0lassic 9ewton8-aphson iteration is considered be the most competent

method for solving load flow equations4 and was selected as the solver. (ault current

calculation is performed only in the symmetrical three8phase case. In fact4 the calculation

can be done simply by inverting a matri7. To calculate inverse of matri7 with

conventional methods is now too laborious and therefore discarded. Instead an algorithm

called O8bus algorithm is used for calculating inverse effectively.

The load flow and fault current algorithms are implemented as a part of the %M'

so that they can utili?e the common network model and topology analysis. The primaryinformation for the load8flow calculation is the loads of the secondary substations and

motors connected to the medium voltage network. The loading information is read from

the "ccess database including the load models for different situations. The results of

load flow and fault current calculations can be studied through the user8interface of the

%M' by selecting the desired node.

! Relia#ility mana*ement

The functions related to reliability have considerable economic significance in

industry. The losses of production caused by the disturbances and the inputs into the

investments of the systems including maintenance and operational arrangements @oin

here.

The reliability can be studied with both qualitative and quantitative methods.

Aith a qualitative analysis the possible states of the system and reasons which lead to

these are determined with non8numerical methods. The failure modes4 effects and

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criticality analyses are adapted generally on the qualitative methods. Nsing failure modes4

effects and criticality analysis it is aimed to identify those faults of the devices or of the

subsystems which affect the capabilities of the system significantly. The system is

systematically analy?ed and the effects of the component faults of the system are

evaluated. In a quantitative analysis indicators describing the capabilities of the system

are calculated. (or e7ample4 availability4 fault frequencies4 durations of disturbances and

indicators which describe the economic appreciation of interruptions can be evaluated.

The functions supporting power distribution reliability management can be included inseveral different systems which are4 among others4 "M=(M=>I'4 the %istribution

Management 'ystem ;%M'+4 '0"%" system4 maintenance systems4 and documentation

systems depending on the total concept.

The load flow calculations and short circuit calculations are applications which

have central meaning in reliability analyses. The calculations make it possible to simulate

faults4 to plan relaying arrangements and network operations. 'witching plans

operational instructions can furthermore be stored in databases. "n essential function

supporting reliability management and analyses is also the management of various

instructions and documents. There are many kind of documents which can be used to

support the reliability management. The graphical user8interface makes available the

developing of the different sophisticated user friendly functions4 for e7ample4

determination of the feeding routes of the components or loads to be e7amined

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The estimation of the reliability technical state and capabilities of the distribution

system together with real8time condition supervision and maintenance programmes are in

a central position in the anticipating and prevention of disturbances and in the

minimi?ation of their effects.

The analysis of reliability technical state and capability of power distribution

network is closely related to the protection coordination4 too. Nsing fault current and

load8flow calculations personnel can evaluate how the distribution and the primary

processes will behave in fault situations of the distribution network.

3 V%lta*e di' analyses

" voltage dip is a sudden reduction of the supply voltage to a value between

Fand 1 F of the declared voltage4 followed by a voltage recovery after a short period of

time. /ossible causes of these dips are typically faults in installations or in feeding public

networks and switching of large loads ;e.g. motors+. In rural areas voltage dips are

generally caused by short circuit faults in the public M overhead network. The interest

in voltage dips is mainly due to the problems they cause on several types of equipment

e.g. tripping of ad@ustable8speed drives ;both ac and dc drives+4 process8control

equipment4 computers and contactors in front of some devices. The employment of INT

with the support of "%" is a step towards reduction in these voltage dips.

P%-er 4uality analyses

The term /ower Puality ;/P+ is used with slightly different meanings. More

e7tensive meaning can be associated with any problems in voltage4 current or frequency

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deviations which result in failure4 malfunction4 disturbances or combination of voltage

quality and current quality. 3owever4 the voltage quality is addressed in most cases. oltage

quality is concerned with deviations of the voltage from the ideal and main characteristics

can be described as with regard to frequency4 magnitude4 waveform4 symmetry of the

three phase voltages and interruptions. In industrial plants on the other hand increasing

amount of disturbing devices ;e.g. ad@ustable drives and power electronics+ and on the

other hand increasing amount of sensitive devices ;computers4 process automation

4electronic devices and ad@ustable drives+ have caused growing concern about power

quality. Thus there is also a growing need to manage and monitor power quality.

Volts

5 C%nditi%n m%nit%rin*

There e7ist many systems for condition monitoring of industrial processes4

especially for rotating machines. Monitoring usually covers electric motors that are

connected to the monitored processes. There are on8line systems designed mainly for

condition monitoring of electric motors4 too. These systems usually include measuring

device connected with processing device4 which can be connected permanently to data

bus supplying information for analy?ing computer or data can be collected from device

occasionally. " selection between continuous data transfer and manually performed data

collection is made mainly by the costs of instrumentation and labour. Jlectric motors are

often considered to be very reliable4 which means that investment not economically

@ustified.

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8 Topology information and estimated reliability of components in a given load situation

"nalysis ;reconstruction+ of actual faultsG

8 'imulated network state using topology4 load and voltage information of previous

situation.

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C%n$lusi%n

-equirements of intelligent software applications for supporting the operation of

industrial distribution networks are different compared to the public distribution. The

domain is more segmented and heterogeneous4 and the infrastructure of automation and

computer systems for electricity networks are not so sophisticated and advanced as other

process automation.


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BIBI/IO RAPH

1+ Qero."46 ,oad modeling for distribution management function of industrial medium

oltage distribution networks 54 IJJJ Transactions on Industry applications4 ol.$2

9o !4 Qanuary 2 1.

2+ (rank -. >oodman4 Qr.4 /h.%.6 "dvanced %istribution "utomation64 www.epri.com .

$+ Markku Cauppinen4 Tampere Nniversity of Technology4 (inland 5Management of

electrical systems in industrial plants64 www.energyline.com .

!+ ,i@un Pin46" new principle fro system protection in distribution networks64 IJJJ

transactions on power delivery4 ol 1 4 9o !4 Qune 2 1.

#+ Monclar (.-46 Intelligent support system for distribution network management 54

International conference on Intelligent system application to power systems 54 'weden4

Qune 2 .
http://www.epri.com/http://www.energyline.com/http://www.energyline.com/http://www.epri.com/http://www.energyline.com/

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