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IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 19, NO. 3, JULY 2004 1049

The Performance Specification of Transmission LineProtection Using a Knowledge-Based Approach

Khalil El-Arroudi, Gza Jos, Donald T. McGillis, and Reginald Brearley

Abstract This paper introduces an automated approach totransmission line protection design for implementation in theform of a performance specification. The need for automation isthe result of the increased complexity of interconnected powersystems and despite numerous proprietary computer programs,the analysis of power system behavior requires significant engi-neering time and effort. Many scenarios have to be investigatedbefore selecting and setting a protective relay and its equipment.By automating the running of the various computer programs andanalyzing the results in a specific manner, the design scenarioscan be investigated relatively quickly, cover all possible cases,remove protection design redundancy, preserve protection designmethods, and assure consistency in protection system design.Additionally, by changing the system loading to some futureanticipated value, it can be determined if specified relays and theirequipment can be adjusted or will have to be replaced. It is alsoclear that such a design tool is useful in training system protectiondesign engineers.

Index Terms Knowledge-based system, power system protec-tion, power system relaying, power systems.

I. INTRODUCTION

A PROTECTION system performance specification is in-tended to define theoperating levels, thesetting limits, andthe required protective functions of any protection system in anelectric power network. This specification ensures that: a) theprotection equipment is selected to withstand therisk of damagefrom exceeding the operating levels, b) the protective functionsare dependable and secure, and c) the relays are set to respondto faults within their zones of protection. It also provides an in-tegrated source of input data to relay coordination studies.

The knowledge-based approach to protection applicationshasattracted a strong interest from researchers in universities andelectric utilities for more than a decade. These applications in-clude: a) relay selection, setting, and coordination, b) selectionof appropriate algorithm for fault locations, c) fault data anal-ysis, d) substation fault diagnosis, and e) power transformerfault diagnosis. Literature covering the most applications of ex-pert systems in protection is given in [ 1][5].

Analysis and classification of all possible credible systemevents are very important elements for designing protection sys-

Manuscript received March 29, 2003. This work was supported in part bythe General Electricity Company (GECOL), Libya; in part by Hydro Quebec,Canada; and in part by the National Science and Engineering Research Council(NSERC) of Canada.

The authors are with the Department of Electrical and Computer En-gineering, McGill University, Montreal, QC H3A 2A7, Canada (e-mail:[email protected]; [email protected]; [email protected];[email protected]).

Digital Object Identifier 10.1109/TPWRD.2004.829162

tems. These events should cover both primary and backup pro-tection. Some of the literature concerned with the analysis anddesign of protection systems is discussed below.

The work presented in [ 6] proposes a sequential trippingstrategy based on the analysis of certainty factorsthe certaintythat a transmission line affected by the fault is able to locatethe line most likely to prevent the occurrence of widespreadblackouts. These blackouts are prevented by providing selectiveand secure backups to region of a transmission network whenmain protection has failed to clear a fault.

The work reported in [ 7] presents an expert system for clas-

sification and analysis of a number of power system events interms of underlying events. The classification scheme is basedon identifying and characterizing the different stages of voltageduring an event.

The expert system in [ 8] develops a method for obtainingan optimal design in protection. The design procedure starts byusing the simplest protection function for each installed protec-tion devices in the nodes of the network. Then, the protection isgradually modified to achieve the required selectivity.

The work in [ 9] presents an expert system, which makes abasic design of an adequate protective relaying system basedon the knowledge gained from past practice. This expert systemcarries out relay setting and validation by means of integrated

power flow and fault calculation programs.The work presented in [ 10] is an integrated expert system for

protection system design using a relational database-manage-ment system. The expert system incorporates both proceduraland declarative operating modes. Rules dealing with the coor-dination, placement, and selection of protective devices are usedto incorporate expert knowledge into knowledge base.

A design support system for protection coordination in in-dustrial systems was developed in [ 11]. The aim of this projectwas to design overcurrent devices within an industrial distri-bution system. It acquires circuit configuration data, performsshort-circuit calculations, sets proper selection rules, searchesfor adequate protective devices from a database, and produces afinal report on selected devices.

The work done in [ 12] develops a decision support systemthat facilitates the validation of the protection operation duringa power system disturbance. This decision support system con-sists of two knowledge-based systems that interpret the systemdata and provide the protection engineers with an insight intodisturbances.

The system proposed in this paper is an automated protec-tiondesign environment (APDE)for writing a protection systemspecification based on the consequences of those events thatconstitute the design requirements of the systemprotection. The

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Fig. 1. Typical transmission system shows a target relay R .

useof this automatedapproach reduces theengineeringtime andeffort, and assures consistency in writing a protection systemspecification since many scenarios have to be investigated underdifferent system operating conditions and network topologiesbefore selecting and setting a protective system.

The idea behind this proposed APDE is that it is possible tobuild an automated protection design by combining a systemdatabase, a network analysis program, a protection relay model,and domain knowledge acquired from experience and processedby an expert system environment.

II. CONCEPT OF THE PROPOSED APDE

The concept of the proposed APDE is based on the interpre-tation of the analyses of the consequences of those events that constitute the design criteria of the system protection . The con-cept can be illustrated with reference to a typical power systemshown in Fig. 1. In this power system, the objective is to deter-mine the performance specification for each target relay and itsequipment.

The design procedure starts with a target relay , such asin this particular case, protecting the transmission line

using relay . This target relay can be described in terms of relay performance characteristics of the relay as shownin Fig. 2. These characteristics were derived to represent allfeasible system characteristics affecting protective relays and,therefore, are used to determine the performance specificationof the relay under study. Such performance characteristicsare loadability, stability, impedance, current, voltage, anddirectional. The loadability characteristic is concerned withthe load current and load impedance settings. By means of thestability characteristic, it is possible to select the automaticreclosing parameters and the power swing scheme parametersat a given location in the power system. The impedancecharacteristic allows determining the zone-reach settings and

Fig. 2. Proposed relay performance characteristics.

the zone-time settings. The current characteristic determinesthe current transformer parameters, the thermal current ratings,and the overcurrent operating curves. The voltage character-istic determines the voltage transformer parameters and the

overvoltage/undervoltage parameters Finally, the directionalcharacteristic specifies the directional requirements and theappropriate polarization quantities.

Each performance characteristic contains design rules andassociated prescribed design events . The design rules a) runthe simulations of the appropriate prescribed design events andb) interpret the analyses of the consequences of the simulatedevents. These events are simulated in the network simulator forthe relay under study and the consequences of these events areanalyzed in the protection relay model.

Associated with every design rule , there exist premises thatare named performance variables . The values of these perfor-mance variables represent facts about the network (or system

parameters) for given events . These facts are determined fromthe analysis of the consequences of these events . On the otherhand, the conclusion part of the design rule is termed decisionvariables that represent inferred facts . The decision variableshold the appropriate design values of every performance char-acteristic when the performance variables satisfy the objectivesstated in the design rules . Therefore, decision variables collec-tively describe the performance specification of the relay .The concept of the proposed APDE is shown in Fig. 3.

The concept can also be represented by the following math-ematical expressions:

(1)

(2)

(3)

(4)

whereset of the performance variables describingthe input states of the APDE. The valuesof these variables are determined from theanalysis of the consequences of prescribed design events , and from the system data-base. The performance variables are factsabout the state of the system;

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EL-ARROUDI et al. : SPECI FICATION OF TRANSMISSION LINE PROTECTION USIN G A KNOWLEDGE-BASED APPROACH 1051

Fig. 3. Concept of the proposed APDE.

set of the prescribed design events . Eachevent determines one or more perfor-mance variable(s) ;decision variables which are determinedaccording to the interpretation designrules . The decision variables are the inferred facts ;set containing the performance specifi-cation describing the output states of theAPDE for each target relay.interpretation design rules which producethe decision variables .

As an example, the interpretation design rules take the forms of the following pseudocode rules:

: A rule to determineIF ;AND ;

THEN .The premises of the rule are the performance variables, and while the conclusion is the decision vari-

able .: A rule to determine and

IF ;OR ;AND ;THEN .

where, and are constant data types which could in-

clude strings, numerical, etc.The forward chaining mechanism was adopted as an infer-

ence search engine for the proposed protection design. Concep-tually, forward chaining begins from a set of facts about the de-sign that are already known and searches for what can be in-ferred from these facts [ 13].

III. M ETHODOLOGY FOR THE PROPOSED APDE

Basically, this methodology involves three main categories of activity, namely: 1) assembling the relevant input data, 2) ma-nipulating the input data according to the design rules containedin the knowledge-based system, and 3) presenting the output inthe form of a specific design. This methodology is illustrated inFig. 4, which is a simplified version of Fig. 3.

Fig. 4. Simplified diagram of the proposed APDE.

The input data will require: a) user input data describing thetag of the target relay and the relay performance character-istic to be specified for a given case study, b) database of theevents required for the protection design, c) database on the net-work data, andd) consequencesof theexecuted events which aresimply the current and voltage data of the relay under study.

The knowledge-based system is the brain that governs the ex-ecution of the design rules embedded in the relay performancecharacteristics . These rules imitate the design processes and thedecisions that are normally performedby an expert in protectionsystem design.

Finally, the design output is displayed to the user in the formof performance specification of the relay under study.

The various steps associated with each performance charac-teristic can be identified in the form of specific tasks, which aresummarized as follows.

1) Select the target relay and the relay performance charac-teristic to be specified in a given network.

2) Simulate the system performance under the prescribed events that are associated with the selected performancecharacteristic to determine the consequences . The simu-lation is done in the network simulator.

3) Analyze the consequences (currents and voltages) re-sulting from each event in the protection relay model.

4) Store the relay model response (system parameters) in

the form of performance variables of the selected performance characteristic .

5) Interpret these performance variables to determine thecorresponding decision variables using the knowledgebase design rules embedded in the performance charac-teristics .

6) Repeat step 2 to 6 for each relay performance character-istic .

7) Compile the decision variables of all considered perfor-mance characteristics to generate the performance spec-ification of the selected relay.

In this methodology, the protection design knowledge is ar-ranged into several knowledge modules ( performance charac-teristics ). This makes the system an open system architecture,which has the advantages of expandability and ease of mainte-nance.

IV. A RCHITECTURE OF THE PROPOSED APDE

The architecture of the proposed APDE is shown in Fig. 5and requires the integration of the four main components: a)a system database to serve as a repository for prescribed de-sign events and network data, b) a network simulator to simulatethe prescribed design events to determine the consequences, c)a protection relay model to analyze the consequences of theseevents in terms of systemparameters, and d) a knowledge-based

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Fig. 5. Architecture of the proposed APDE.

system to interpret the system parameters to produce the protec-tion system performance specification.

A. System Database

The system database shown in Fig. 5 consists of two partsas follows: 1) network data which includes the connected com-ponents of the electric power system: buses, transmission lines,transformers, generators, compensators, and loads. These dataform the basic requirements for power flow, short circuit, andtransient computations, which, in turn, will be used to designthe protection system, and 2) event databases which define theprescribed design events that are simulated in the network sim-ulator.

B. Network Simulator

The network simulator is a program environment which canperform network studies such as load flow, short circuit, andtransient analysis [ 14].

C. Multifunction Relay Model

The relay model is a multifunction protection softwaremodel developed specifically as a part of this study. Thismultifunction model can be used for performing virtually anyprotection system studies. The protection algorithms withinthis software model are represented by both transient genericmodel (which calculates relay response at each instant of timefor specific current and voltage at that time) as well as phasormodel (uses phasor equations). The selection between thesetypes of modeling depends on the event to be studied. For

example, the steady-state events require phasor model whilethe transient events require transient model.

The relay model acquires the voltage and current informationat a given target relay location (the required relay under study)forsome specific eventand transforms this information into pro-tection system parameters through its mathematical algorithms.The purpose of this relay model is to analyze the consequences

of every simulated event in the network and generate the resultsin terms of protection system parameters as input to the knowl-edge-based system. Since this paper is not intended to discussthedetailedconstruction of this relay model,only thealgorithmscontained within it will be listed as follows:

transient overcurrent time duration; transient over/undervoltage time duration; sequence component analyzer; apparent impedance calculator; time-overcurrent calculator; directional power calculator; root mean square (RMS) magnitude and phase angle esti-

mator; fault classifier; frequency spectrum analyzer.

D. Knowledge-Based System

This is a proprietary knowledge-based system environment[15] which uses the inference engine to control and organizeall of the activities of the knowledge base. These activities in-clude processing the knowledge base rules, providing reasoningas well as communicating with the user, the external programs,and the database.

The following points present the vital role of the knowl-edge-based system in the proposed APDE.

1) In the knowledge-based system shown in Fig. 5, the pro-tection knowledge base is structured into performancecharacteristics shown in Fig. 2.

2) The knowledge-based system is the brain that controls allof the activities associated with the development of theAPDE, through the intervention of the inference engine.

3) These activities include processing the knowledge basedesign rules, providing reasoning as well as communi-cating with the user, the network simulator, the relaymodel, and the system database.

4) The knowledge-based system organizes the operation of the network simulator and the relay model in such a way

as to produce a performance specification of any targetedrelay from the results of the simulated events.

5) The key elements in this automated system are the selec-tion of thecritical prescribed designevents and the forma-tion of the design rules leading to the performance speci-fication of the targeted relay.

V. ANALYSIS OF THE RELAY PERFORMANCE CHARACTERISTICS

The concept of the proposed APDE involves the analysis of each relay performance characteristic to accomplish the fol-lowing.

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Fig. 6. Load current limits.

1) Extract the performance variables and the decision vari-ables from the properties pertaining to each relay perfor-mance characteristic .

2) Define the prescribed design events associated with eachrelay performance characteristic.

3) Define the design rules embedded in each relay perfor-mance characteristic .

The procedure for the determination of the performance vari-ables , decision variables , prescribed design events , and the de-sign rules is illustrated by a detailed analysis of the loadabilitycharacteristic.

The relay loadability characteristic determines the level towhich a protection system permits a transmission line to beloaded. This characteristic is defined by the protection settingphilosophy, protective equipment thermal rating, and fault char-acteristics. Therefore, to assure the security of a transmissionline, and hence, of the system, the protection system devicesmust be designed to respect the line loadability. The load limitincluding the security margins permitted by the relay , shownin Fig. 1 as an example, can be categorized as a) current loadlimit and b) impedance load limit. The performance variablesand the decision variables associated with the relay loadabilitycharacteristic can be extracted from the properties of these twolimiters as follows:

A. Load Current Limit

Fig. 6 shows the current properties of the relay . The sym-bols shown are defined in Tables I and II.

Referring to Fig. 6, one can extract from the diagram the loadcurrent limit properties that are considered as the performancevariables of the load current limit and they are given in Table I.The corresponding decision variables of the load current limitare given in Table II.

B. Load Impedance Limit

The mho characteristic shown in Figs. 7 and 8 are used toderive the necessary performance variables and the decisionvariables corresponding to load impedance limit. The samevariables are also valid for the other types of impedance-basedcharacteristics which include offset mho, impedance, lentic-ular, blinder, quadrilateral, reactance , etc. The performancevariables and the corresponding decision variables of the loadimpedance limit are given in Tables I and II, respectively.

TABLE ISUMMARY OF TYPICAL P ERFORMANCE V ARIABLES OF THE LOADABILITY

CHARACTERISTIC

TABLE IISUMMARY OF TYPICAL D ECISION V ARIABLES OF THE LOADABILITY

CHARACTERISTIC

A listof a sampleof the prescribed design events anda sampleof the design rules that determine the values the decision vari-ables of the loadability characteristic are given in Tables III andIV.

A similar approach is applied to each of the relay perfor-mance characteristics to complete the relay performance spec-ification .

VI. A PPLICATION EXAMPLE

In this application example, a sample case study is presented.The purpose of this case study is to demonstrate how a protec-tion system is designed using the proposed APDE. For this pur-pose, the performance specification of the loadability character-istic for the target relay R3 of the power system shown in Fig. 1is to be determined. The data for the power system of Fig. 1 aregiven in Appendix A.

The design methodology of the proposed APDE for this casestudy is illustrated in Fig. 9. Tables V and VI summarize the per-

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TABLE VSUMMARY OF TYPICAL P ERFORMANCE V ARIABLES OF THE CASE STUDY

TABLE VISUMMARY OF TYPICAL D ECISION V ARIABLES OF THE CASE STUDY

3) In this APDE, the protection design knowledge is subdi-vided into several knowledge modules (or relay perfor-

mance characteristics). This makes the system an opensystem architecture which has the advantages of expand-ability and ease of maintenance.

4) The knowledge-basedsystemin theproposed APDE gov-erns all of the activities associated with the interpretationof the protection system parameters through its designrules so as to generate the performance specification of each relay.

5) It has been found that the proposed approach reduces theengineering time required for protection design, coversall possible cases, removes protection design redundancy,preserves protection design methods, and assures consis-tency in protection system design.

APPENDIX A

This appendix contains thedata required forthe powersystemshown in Fig. 1. The base power has been chosen as 1000 MVA.

1) Generator and Unit Transformer Data:

Gen1 : rated Hz, ratedkV Inertia constant s,

p.u., p.u. Tr1 : rated Hz, rated

kV, p.u.,p.u., p.u., p.u.

Gen2 and Tr2 : are represented by an infinite bus withrated kV, Hz,

p.u., p.u.

2) 735-kV TransmissionLines Data: Rated , ratedkV, p.u./km),

p.u./km, p.u./km,p.u./km p.u. km, p.u. km,

km, km, km,km, and km.

3) Line Equipment Data: Circuit-breaker-ratedA, Line switch rated A, line-trap rated

A.4) Loads Data: p.u., and

p.u.

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[5] M. Kezunovic, Intelligent systems in protection engineering, in Proc.Power Con . Perth, Western Australia, Dec. 2000.

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[7] E. Styvaktakis, M. Bollen, and I. Gu, Expert system for classification

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[11] H.Satohand H. Serizawa, A design support system for overcurrent pro-tection coordination on industrial power distribution systems, in Proc.3rd Symp. Expert System Application to Power System , Tokyo-Kobe,Japan, Apr. 1991.

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S. M. Burt, On-line protection performance analysis using intelligentsystems, Int. J. Eng.Intell.Syst.Special Issueon AI Methods in Power Syst. Protection , vol. 5, no. 4, pp. 235 244, Dec. 1997.

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[14] EMTDC/PSCAD Simulation Software , 1993. Version 3.04, HVDC Re-search Centre.

[15] CLIPS Reference Manual , 2002. Version 6.2,Artificial Intelligence Sec-tion, Johnson Space Center.

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[19] P. M. Anderson, Power System Protection . Piscataway, NJ: IEEEPower Eng. Soc., IEEE Press, 1999.

[20] S. H. Horowitz, Protective Relaying for Power System II.A Selected Reprint Volume IEEE Power Engineering Society, Sponsor . NewYork: IEEE Press, 1992.

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Khalil El-Arroudi received the B.Sc and M.Sc.degrees from Garyounis University, Benghazi,Libya, in 1985 and 1994, respectively. He is cur-rently pursuing the Ph.D. degree in the Departmentof Electrical Engineering at McGill University,Montreal, QC, Canada.

Currently, he is with the General Electricity Com-pany of Libya, first starting as Protection Engineerand then becoming Head of the Power System Pro-tection Department in 1992.

Gza Jos received the M.Eng. and Ph.D. degreesfrom McGill University, Montreal, QC, Canada, in1974 and 1987, respectively.

Currently, he is Professor with the Department of Electrical and Computer Engineering at McGill Uni-versity, where he has been since 2001. He is engagedin teaching and research in the area of static powerconverter topologies and control issues. From1975 to1978, he was a Design Engineer with Brown BoveriCanada (now ABB), and involved in traction drives.From 1978 to 1988, he was a Professor at the Ecole

de technologie sup rieure, Montreal, with interests in power converters andadjustable speed drives, and at Concordia University, Montreal, QC, Canada,from 1988 to 2001. His research interests include the design and applicationof high-power converters with applications to power system compensation, in-cluding FACTS and custom power devices.

Donald T. McGillis received the B.Eng. degree inelectrical engineering from McGill University, Mon-treal, QC, Canada.

Currently, he is a Consultant for Hydro-Quebec In-ternational, Montreal, QC, Canada, and Adjunct Pro-fessor at McGill and Concordia Universities, Mon-treal, QC, Canada. His interests include the planningand design of extra-high-voltage systems, applyingpower electronics to power systems, the design and

use of expert systems for system planning, dynamicsecurity analysis, and power system reliability.

Reginald Brearley received the B.Sc.degree in elec-tricpower engineering fromQueen s University, ON,Canada, in 1951.

Currently, he is a Consulting Engineer whose ex-perience includes managingthe protection system forthe ALCAN electric power network in Quebec, Mon-treal, QC, Canada.

Mr. Brearley is a member of the order of engineersof Quebec.

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