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									Seminar Report ’04            Intelligent Management Of Electrical Systems in Industries




                          ACKNOWLEDGEMENT



               First of all, I thank the Almighty for His blessings and support for

       presenting this Seminar with my utmost satisfaction.

               Then I would like to express my sincere gratitude to Dr. PMS.

       Nambisan(Head of the Department of Electrical and Electronics Engineering)

       for extending all help and support for the Seminar.

               I also thank my guide, Mr. Abdul Naseer.P for his valuable advice

       and co-operation he had given during the Seminar work.

               My thanks are also due to Mr.GylsonThomas, our Seminar

    Coordinator for offering all liberties to present the Seminar in the best possible

    manner.

               Finally, I would like to thank all the teaching and non-teaching staff

    for giving all the required information and help at every point of need.




Dept. of EEE                                1                       MESCE, Kuttippuram
Seminar Report ’04            Intelligent Management Of Electrical Systems in Industries




                                       Abstract




            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.




Dept. of EEE                                 2                       MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries



                                      CONTENTS


1 Introduction …………………..…………………….………………... 04

2 Applications for supporting the public
  distribution network management        ................................................ 05

3 Description of the system environment …………………………….….08

4 Application functions for distribution
  management in industrial plants ………………………………............ 11

5 Advanced Distribution
  Automation ………………...............................………………....……..14

       5.1 Distribution System of Future
           with ADA          ………………………………………….….17

6 Distribution Management
  Functions           …...............……………………………….…....18

7Application Functions of Data Management
 Systems ………………………………........................…......…...…..21

       7.1) Load modeling ………..……….….........................................21

       7.2) Reliability management………………………….........……..23

       7.3) Voltage dip analyses.........……………........……...............…25

       7.4) Power quality analyses……………………………................26

       7.5) Condition monitoring…………………………………..........26

8 Conclusion….......................................……………..…………….…...29

9 Bibliography.……………….................……………………................30



Dept. of EEE                                  3                        MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries



                                     Introduction



       Industrial plants have put continuous pressure on the advanced process

automation. However, there has not been so much focus on the automation of the

electricity distribution networks. Although, the uninterrupted electricity distribution is

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

the―downrun‖ of the process may cost huge amount of money. Thus the intelligent

management of electricity distribution including, for example, preventive condition

monitoring and on-line reliability analysis has a great importance. Nowadays 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. Very promising results has been gained, for example, in

decreasing outage times of customers. However, the same concept as such cannot be

applied in the field of industrial electricity distribution, 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 distribution, which is more homogeneous

domain. The automation devices, computer systems, and databases are not in the same

level and the integration of them is more complicated.




Dept. of EEE                                 4                       MESCE, Kuttippuram
Seminar Report ’04            Intelligent Management Of Electrical Systems in Industries



                   Applications for supporting the public
                    distribution network management


       It was seen already in the end of 80's that the conventional automation system (i.e.

SCADA) cannot solve all the problems regarding to network operation. On the other

hand, the different computer systems (e.g. AM/FM/GIS) include vast amount of data

which is useful in network operation. The operators had considerable heuristic knowledge

to be utilized, too. Thus new tools for practical problems were called for, to which AI-

based methods (e.g. object-oriented approach, rule-based technique, uncertainty modeling

and fuzzy sets, hypertext technique, neural networks and genetic algorithms) offers new

problem solving methods. So far a computer system entity, called as a distribution

management system (DMS), has been developed. The DMS is a part of an integrated

environment composed of the SCADA, distribution automation (e.g. microprocessor-

based protection relays), the network database (i.e. AM/FM/GIS), the geographical

database, the customer database, and the automatic telephone answering machine system.

The DMS includes many intelligent applications needed in network operation. Such

applications are, for example, normal state-monitoring and optimization, real-time

network calculations, short term load forecasting, switching planning, and fault

management.




Dept. of EEE                                5                       MESCE, Kuttippuram
Seminar Report ’04           Intelligent Management Of Electrical Systems in Industries




      The core of the whole DMS is the dynamic object-oriented network model. The

      distribution network is modeled as dynamic objects which are generated based on

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

      real-time state of the network (e.g. topology and loads). Different network

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

      modules can operate interactively with each other through the network model,

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

      in the network model, where they are available in all other modules for different

      purposes).The present DMS is a Windows NT -program implemented by Visual

      C++. The prototyping meant the iteration loop of knowledge acquisition,

      modeling, implementation, and testing. Prototype versions were tested in a real

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

      models, external connections, and the user-interface was obtained at a very early

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

      The DMS entity was tested in the pilot company, Koillis-Satakunnan Sähkö Oy,

      having about 1000 distribution substations and 1400 km of 20 kV feeders. In the

      pilot company different versions of the fault location module have been used in

      the past years in over 300 real faults. Most of the faults have been located with an

      accuracy of some hundred meters, while the distance of a fault from the feeding

      point has been from a few to tens of kilometers. The fault location system has

      been one reason for the reduced outage times of customers (i.e. about 50 % in the

      8 past years) together with other automation.




Dept. of EEE                               6                       MESCE, Kuttippuram
Seminar Report ’04           Intelligent Management Of Electrical Systems in Industries




        The experiences as a whole were so encouraging that the DMS was modified as

a commercial product. The vendor was first a small Finnish software company. Since

1997 the DMS has been a worldwide software product of ABB Transmit Oybeing

integrated to the MicroSCADA platform. At present the DMS is in everyday use in

several distribution companies all over the world. Part of the research group behind the

development of the DMS works at present as the employees of ABB, which has

confirmed the successful commercially phase.




Dept. of EEE                               7                      MESCE, Kuttippuram
Seminar Report ’04            Intelligent Management Of Electrical Systems in Industries




                  Description of the system environment

         A big industrial plant differs from public distribution company by organizatory

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

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

Very often the maintenance is maintained by a service company. An energy department

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

Above organizations may have some control systems that serve for their needs only, but

usually information systems are closely connected together. A process automation system

is the most important system in an industrial plant, sometimes including other systems, as

illustrated in Fig. 1. For example, all energy production and distribution network control

tasks can be done in a process automation system. Normally, because of the reliability

reasons, 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 systems, too.




Figure1: Automation and information systems of an industrial plant.




Dept. of EEE                                8                      MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries


       The systems in Fig. 1 utilize many databases, which contain data that can be used

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

optimization tools. The databases contain information of material flow, energy flow and

control data of production machines. Maintenance databases include technical

specifications and condition data of production machine components. Similar information

of electricity network components is supported by network database. Production

programs are stored in the databases of administrative systems.

       Intelligent applications are needed to:

- Handle large amount of information available. This includes filtering of data and

producing new information by collecting data.

- Illustrate complex dependencies of electricity distribution and production processes in

abnormal situations.

- Give instructions for operators in fault situations. A risk of misoperation in unusual

fault situation is obvious and prevents or delay operators’ decision making.

- Automize analysis tasks. Continuous information analysis is not possible manually.



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

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

requirements should be satisfied:

- Documentation of electricity distribution network is available for the systems. Network

databases can supply this information.




Dept. of EEE                                  9                       MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries


- Network, process and motor measurements are available for the system. This means,

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

methods is needed, as illustrated in Fig. 2.




Dept. of EEE                                   10                  MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries


       Application functions for distribution management in

                                   industrialplants


       As mentioned above the concept of public distribution automation cannot be

applied as such in the management of industrial electricity networks. For example, fast

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

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

function in industrial networks. Predictive condition monitoring, reliability calculations,

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

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

dynamic phenomena and harmonics, and to calculate load-flow and fault currents in ring

connected networks. An 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 real-time 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 following:

* Real-time network monitoring, state estimation and optimization:

- Topology management

- load flow and fault currents also as dynamic phenomena

- Monitoring and compensation of reactive power

- monitoring of harmonics and resonances




Dept. of EEE                                 11                       MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries


- Minimization of power losses

* Planning and simulation of operation actions

- switching planning

- Automatic load shedding and forming a local island

- switching the network as a part of the national grid

- fault situations

* Management of disturbances

- Event analysis

- Fault location and network restoration

- Preventive condition monitoring

- Protection relay coordination

- Reliability calculations

- reporting



          Distribution Automation which includes feeder automation and distribution

management systems (DMS) is an important technique in distribution network. The

distribution management systems are composed of distribution management functions.

The DMF 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. Various

application functions for distribution management in industrial plants are mainly load

modeling ,reliability management , power quality analysis, voltage dip analysis and

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




Dept. of EEE                                 12                    MESCE, Kuttippuram
Seminar Report ’04           Intelligent Management Of Electrical Systems in Industries


functions. Advanced distribution automation (ADA) modern day approach towards

efficient management of distribution networks.




Dept. of EEE                              13                     MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries


          ADVANCED DISTRIBUTION AUTOMATION


       Traditional distribution systems were designed to perform one function—

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

versatile and will be multifunctional.

Strategic drivers for ADA are to

• Improve system performance

• Reduce outage times

• Allow the efficient use of distributed energy resources

• Provide the customer more choices and

• To integrate the customer systems

       For ADA to work, the various intelligent devices must be interoperable both in

the electric system architecture and in the communication and control architecture.




                                             .

                                    Figure3: ADA architecture




Dept. of EEE                                14                      MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries


       ADA 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.




                             Fig: 4

       The three major components of ADA

– Flexible electrical system architecture

– Real-time state estimation tools

– Communication and control system based on open architecture standards

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

will be a cornerstone of ADA. It will provide a variety of functions including

– Voltage stepping

– Voltage regulation

– Power quality enhancement

– New customer service options such as DC power output

– Power electronic replacement for conventional copper and iron transformers




Dept. of EEE                                15                      MESCE, Kuttippuram
Seminar Report ’04            Intelligent Management Of Electrical Systems in Industries




The Flexible Electric Architecture and the Open Communications Architecture

synergistically empower each other to create the distribution system of the future.



Each of these is made more valuable by its interaction with the other.

       ADA will provide improvements in many areas including

– Reliability

– System performance

– Condition monitoring

– Outage detection and restoration

– Maintenance practices and prioritization

– Automated switching and fault management

– Reactive power and voltage management

– Loss reduction and load management

– Customer service options




Dept. of EEE                                 16                     MESCE, Kuttippuram
Seminar Report ’04      Intelligent Management Of Electrical Systems in Industries




               Distribution System of Future with ADA




Dept. of EEE                         17                     MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries




         DISTRIBUTION MANAGEMENT FUNCTIONS

       Distribution management functions form an entity of applications supporting

documentation of network data, and planning, operation and reliability management of

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

computer systems, like AM/FM/GIS, Distribution Management System (DMS), and

SCADA or case specific customized applications. The main functions of distribution

management entity for the industrial networks are listed in the following:

• Documentation of network data

• Graphical user interfaces

• Real-time network monitoring, state estimation and optimization

- Topology management, load flow and fault current calculation, monitoring and

compensation of reactive power, monitoring of harmonics and resonance, and

minimization of power losses

• Planning and simulation of operation actions

- switching planning, fault situations, automatic load shedding and forming a local island

• Management of disturbances and reliability

- Preventive condition monitoring, reliability and availability management, protection

relay coordination, event analysis, fault location and network restoration, reporting.

       Caused 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. An essential need is the load modeling which differs considerable from

the public distribution. Predictive condition monitoring, reliability management, and


Dept. of EEE                                 18                      MESCE, Kuttippuram
Seminar Report ’04            Intelligent Management Of Electrical Systems in Industries




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

Some functions of the DMS for the management of public distribution networks can be

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

topology management.




Dept. of EEE                               19                     MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries




  APPLICATION FUNCTIONS OF DATA MANAGEMENT

                                      SYSTEMS



1) Load modeling

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

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

However, loading of every load node of the network must be known in the network

calculations. For that purpose the loads are estimated by load models.

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

calculations. Results of load-flow calculations are utilized different kind of tasks as real-

time network monitoring and optimization, and switching planning. Information on loads

can also be utilized in preventive condition monitoring and reliability analyses. Although,

the loads (i.e. the current) of some nodes can be measured on-line, models are needful

because of the DMS can be used also in simulated state, when the information of system

does not correspond the current real-time 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 load-flow calculation and load

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




Dept. of EEE                                 20                      MESCE, Kuttippuram
Seminar Report ’04            Intelligent Management Of Electrical Systems in Industries




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

in different known process conditions. However, the industrialplants vary from each

other quite much, which means that load models determined in one plant may not be able

to used as such in other one. One aim of the research work is to develop tools and

methods by which the determination of the plant specific load models can be achieved

during the installation of the automation system when enough measurements have been

done and certain process specific parameters are known. Neural networks can be used to

learn the correlations between the measurements and the process in order to produce the

load model

         Significant features of the load models are swiftness, simplicity, a capability to

utilize measured information, a capability to utilize inaccurate information and a

capability to adapt alternating and different conditions. The state monitoring of the DMS

acts in real times which appoint demands to the swiftness of the load models. Further the

industrial processes will be developed and so the load models must be able to adapt in

varied situation.

        Demands, mentioned above, could be achieved using advanced methods and

technologies. This means using neural networks technology, fuzzy logic and self-

adaptively technologies in further development of load models of the industrial

distribution networks.




Dept. of EEE                                21                      MESCE, Kuttippuram
Seminar Report ’04                Intelligent Management Of Electrical Systems in Industries




                    Fig 5: Network Load Model Determining



        Load forecasting in the industrial environment cannot be based on any regularity

of behavior. Reliable forecasting assumes use of methods which can utilize 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 process, earlier measured values and the planned

production.

 Calculation methods for meshed networks

       The DMS for public distribution management included load flow and fault current

calculation procedures, 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).

         Load flow calculation for meshed network leads to a group of non-linear




Dept. of EEE                                   22                     MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries




equations. Classic Newton-Raphson iteration is considered be the most competent

method for solving load flow equations, and was selected as the solver. Fault current

calculation is performed only in the symmetrical three-phase case. In fact, the calculation

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

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

called Z-bus algorithm is used for calculating inverse effectively.

        The load flow and fault current algorithms are implemented as a part of the DMS

so that they can utilize the common network model and topology analysis. The primary

information for the load-flow calculation is the loads of the secondary substations and

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

the Access –database including the load models for different situations. The results of

load flow and fault current calculations can be studied through the user-interface of the

DMS by selecting the desired node.

2) Reliability management

        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 join

here.

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

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

these are determined with non-numerical methods. The failure modes, effects and




Dept. of EEE                                23                        MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries




criticality analyses are adapted generally on the qualitative methods. Using failure modes,

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 analyzed 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. For example, availability, fault frequencies, 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 in

several different systems which are, among others, AM/FM/GIS, the Distribution

Management System (DMS), SCADA system, maintenance systems, 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

faults, to plan     relaying arrangements and network operations. Switching plans

operational instructions can furthermore be stored in databases. An 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 user-interface makes available the

developing of the different sophisticated user friendly functions, for example,

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




Dept. of EEE                                 24                       MESCE, Kuttippuram
Seminar Report ’04               Intelligent Management Of Electrical Systems in Industries


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

system together with real-time condition supervision and maintenance programmes are in

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

minimization of their effects.

         The analysis of reliability technical state and capability of power distribution

network is closely related to the protection coordination, too. Using fault current and

load-flow calculations personnel can evaluate how the distribution and the primary

processes will behave in fault situations of the distribution network.



3) Voltage dip analyses

       A voltage dip is a sudden reduction of the supply voltage to a value between 90

%and 1 % of the declared voltage, followed by a voltage recovery after a short period of

time. Possible 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 MV overhead network. The interest

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

e.g. tripping of adjustable-speed drives (both ac and dc drives), process-control

equipment, computers and contactors in front of some devices. The employment of IUT

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


4) Power quality analyses


       The term Power Quality (PQ) is used with slightly different meanings. More

extensive meaning can be associated with any problems in voltage, current or frequency




Dept. of EEE                                  25                      MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries


deviations which result in failure, malfunction, disturbances or combination of voltage

quality and current quality. However, the voltage quality is addressed in most cases. Voltage

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

can be described as with regard to frequency, magnitude, waveform, symmetry of the

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

amount of disturbing devices (e.g. adjustable drives and power electronics) and on the

other hand increasing amount of sensitive devices (computers, process automation

,electronic devices and adjustable drives) have caused growing concern about power

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




5 ) Condition monitoring

        There exist many systems for condition monitoring of industrial processes,

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

connected to the monitored processes. There are on-line systems designed mainly for

condition monitoring of electric motors, too. These systems usually include measuring

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

bus supplying information for analyzing computer or data can be collected from device

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

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

often considered to be very reliable, which means that investment not economically

justified.




Dept. of EEE                                 26                      MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries


         On-line condition monitoring of components of electricity distribution network

is not commonly used. Protection relays include some functions for condition monitoring

such as self diagnostics of relay and counter of operations.

       The applications described which are required to collect data from various

sources, for example from process automation, electricity grid and energy management

system. These systems contain data or are able to collect data to be used for condition

monitoring purposes. Process automation and energy management can provide energy,

power, current and temperature measurements of motors as well as measurement of

output quantity of drive, such as mass flow of pump. Electricity grid protection and

measuring devices supply quantitative and sometimes also qualitative information of

voltage and current. Some useful information of condition of components can be created

just by collecting and analyzing information available.

         Database information is used in condition monitoring and condition planning of

network components as follows:



* Component data from the network database:

- Date of installation, model, and nominal life time

- Plan for service and replacement investments

* Operation counters and operation time of switches and disconnectors:

- Mechanical condition can be estimated

- Test instruction for unused disconnectors to prevent sticking

* Integrated lifetime (estimate of aging)

* Reliability analysis:




Dept. of EEE                                27                     MESCE, Kuttippuram
Seminar Report ’04             Intelligent Management Of Electrical Systems in Industries


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

* Analysis (reconstruction) of actual faults:

- Simulated network state using topology, load and voltage information of previous

situation.




Dept. of EEE                                    28                 MESCE, Kuttippuram
Seminar Report ’04           Intelligent Management Of Electrical Systems in Industries




                                    Conclusion


       Requirements 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 heterogeneous, and the infrastructure of automation and

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

process automation.

       On the other hand the chance to apply intelligent software methods is promising

from the point of view of end-user attitudes, because the same kind of methods have been

successfully applied in process automation, e.g. in fuzzy control and system modeling

using neural networks. This paper discusses the requirements of intelligent methods in

the new domain, introduces the system environment and presents initial results gained in

the research work. Intelligent management will provide improvements inmany areas

including Reliability, System performance, loss reduction and load management.

        The emergence of intelligent management is a promising step towards efficient

maintenance and complete automation.




Dept. of EEE                              29                      MESCE, Kuttippuram
Seminar Report ’04            Intelligent Management Of Electrical Systems in Industries


                               BIBILIOGRAPHY




1) Jero.A,‖ Load modeling for distribution management function of industrial medium

  Voltage distribution networks ―, IEEE Transactions on Industry applications, Vol.32

   No 4, January 2001.

2) Frank R. Goodman, Jr., Ph.D.‖ Advanced Distribution Automation‖, www.epri.com.

3) Markku Kauppinen, Tampere University of Technology, Finland ―Management of

electrical systems in industrial plants‖, www.energyline.com .

4) Lijun Qin,‖A new principle fro system protection in distribution networks‖, IEEE

transactions on power delivery, Vol 10, No 4, June 2001.

5) Monclar F.R,‖ Intelligent support system for distribution network management ―,

International conference on Intelligent system application to power systems ―, Sweden,

June 2000.




Dept. of EEE                               30                     MESCE, Kuttippuram

								
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