Automated Fault Location System for Primary Distribution Networks

1332 IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 20, NO. 2, APRIL 2005

Automated Fault Location System forPrimary Distribution Networks

Eduardo Cesar Senger, Giovanni Manassero, Jr., Clovis Goldemberg, and Eduardo Lorenzetti Pellini

AbstractThis paper presents the development, simulation re-sults, and field tests of an automated fault location system for pri-mary distribution networks. This fault location system is able toidentify the most probable fault locations in a fast and accurateway. It is based on measurements provided by intelligent electronicdevices (IEDs) with built-in oscillography function, installed onlyat the substation level, and on a database that stores informationabout the network topology and its electrical parameters. Simula-tions evaluate the accuracy of the proposed system and the exper-imental results come from a prototype installation.

Index TermsDistribution system automation, fault location.

I. INTRODUCTION

S INCE the deregulation process has started, most of the re-search on power distribution systems focused on improvingthe performance of the electricity utilities. In other words, im-provement of performance means delivering power in a more ef-ficient way (in terms of quality, reliability, and end-user price).

Besides, the advances and widespread use of intelligent elec-tronic devices (IEDs), such as digital disturbance recording de-vices, relays, metering devices, and power-quality devices, havepromoted progress in measurement, monitoring, protection, andcontrol techniques applied to distribution networks.

Despite all of this technological progress and the need forperformance improvements, the fault location process employednowadays is still based on trouble calls from the affected cus-tomers. When a permanent fault occurs, the operators at the op-eration center identify the faulted feeder and the possible areaof occurrence. Then, a maintenance crew is sent to patrol thatarea, in order to identify and isolate the fault.

Under certain circumstances, this procedure proves to beinefficient, since it requires the maintenance crew to patrol alarge area and to switch protective devices in order to locate thefault point. Besides, when a transient fault occurs, the operationcenter will not receive any phone calls from customers and noinformation about its occurrence and location will be available.However, it may be important to investigate these faults with thepurpose of preventing them from becoming permanent ones.

A. Fault Location AlgorithmsMost of the proposed fault location algorithms were devel-

oped for power transmission systems. Few methods were pro-

Manuscript received December 29, 2003; revised February 27, 2004. Paperno. TPWRD-00659-2003.

The authors are with Universidade de So Paulo, So Paulo 01424-000, Brazil(e-mail: [email protected]; [email protected]; [email protected]).

Digital Object Identifier 10.1109/TPWRD.2004.834871

posed for distribution networks due to the following reasons [1],[2].

Variety of conductors and structures: Along a typicaldistribution feeder there are different cables and con-figurations (cross-arm, twisted, spacer, underground,etc.); therefore, there is no linear relation between theline impedance and the distance between the fault lo-cation and the substation.

Lateral branches: Unlike transmission lines, typicaldistribution feeders have several lateral branches.Thus, short circuits in different geographical locationscan produce the same currents and voltages measuredat the substation. Consequently, the fault locationprocedure may result in several different points aspossible locations.

Load distributed along the feeder: The current mea-sured at the substation during a fault includes a con-tribution given by the sum of the load currents at eachnode and, in contrast to transmission systems, it is im-possible to estimate these currents accurately.

Modifications in the feeder configuration: Distributionnetworks are subject to constant modifications in theirtopology. As a result, any fault location algorithmmust have access to a database, periodically updated,in order to give a better estimate of the fault point.

Basically, there are two different approaches for locatingfaults in distribution networks. One is based on fault detectorsinstalled along the feeders [3], whereas the other is based onalgorithms that use measurements of voltages and currentssignals provided by IEDs located only at the substation level[1], [2], [4][6]. The system presented in this paper is based onthe second approach.

The solution proposed by [4] describes a fault locationalgorithm based on the voltage and current signals provided bydigital disturbance recorders installed at the substations. Thefault location algorithm uses the symmetrical components ofthe voltage and current phasor quantities, estimated from theserecords. The methodology can only be applied to balancednetworks.

Reference [5] describes a fault location system based on arti-ficial intelligence methods (fuzzy logic). The proposed systemrequires a large set of information (short-circuit currents, atmo-spheric conditions, information provided by fault detection de-vices installed along the feeders, etc.). An estimate of the faultdistance is obtained from the current measured by the digitalovercurrent relays, considering no fault resistance. As a result,this method will estimate a fault location that, in most cases, isfar from the actual one.

0885-8977/$20.00 2005 IEEE

SENGER et al.: AUTOMATED FAULT LOCATION SYSTEM FOR PRIMARY DISTRIBUTION NETWORKS 1333

Fig. 1. Substation arrangement.

The solution presented by [6] uses a procedure somewhatsimilar to [4] but the algorithm is based on a three-phasepower-flow calculation and can be applied to any kind ofdistribution network. The fault location system proposed in thispaper is based on a similar procedure.

II. AUTOMATED FAULT LOCATION SYSTEMThe automated fault location system proposed in this paper

combines information provided by IEDs located only at the sub-stations with knowledge of the distribution systems topologyand its electrical parameters. Whenever an overcurrent event oc-curs, the system automatically provides to the operators, at theoperation center, the most probable fault points.

To illustrate the system, consider the substation arrangementdepicted in Fig. 1. An IED, connected to each medium-voltagefeeder, is responsible for monitoring voltage and current sig-nals and recording transient data whenever an overcurrent eventoccurs.

A computer, located also at the substation, is connected to thearray of IEDs and to the computer at the operation center, via acommunication channel such as dial phone line, dedicated line,radio link, tie to corporate local-area network (LAN), etc.

The fault location system consists of eight software mod-ules. This software modularity enables future software upgradeswithout the need to change the whole system. Part of these mod-ules is installed at the substations whereas the rest are installedat the operation center as illustrated in Fig. 2. The decision ofinstalling the fault location modules at the substations and at theoperation center was based on the following reasons.

Database update: The fault location system uses infor-mation stored in a database, which must be periodicallyupdated in order to reflect possible modifications in thedistribution networks. Therefore, this database and thesoftware modules that have access to it should be lo-cated at the operation center computers.

Communication channel overflow: Transferring alltransient data recorded by the IEDs to the operationcenter would probably overflow the communicationchannel that connects the substations computers tothe operation center computer. Therefore, it is conve-nient to preprocess the transient data and extract onlythe information required by the fault location system,which is transmitted to the operation center.

Fig. 2. Fault location systemsoftware modules.

A. Substation Software Modules1) Main Module: Responsible for scheduling and storing

data acquisition. It also coordinates and monitors all datatransfer among the other modules.

2) IED Interface Module: Converts the transient datarecorded by the IEDs into a COMTRADE format [7]. Thisformat is desirable to make the fault location system indepen-dent of the recording equipment in such a way that future IEDschanges will not imply in major software upgrades. The infor-mation sets included in the COMTRADE file are as follows: Detailed oscillography of the fault: phase voltages and

line currents; Additional measurements: prefault and postfault mea-

surements (active and reactive power, voltages and cur-rents), circuit-breaker operation time, etc.

3) Digital Signal Processing (DSP) Module: Preprocessesthe transient data stored in the COMTRADE file. This softwaremodule performs the tasks described below and stores the resultsin an ASCII file, which is less than 1 kb and much smaller thanthe COMTRADE file.

Determination of the fault occurrence instant: The al-gorithm developed to perform this task is based ondigital-signal-processing (DSP) techniques, which areable to identify signal transition instants.

Estimation of prefault and fault phasor quantities: TheDSP module places two data windows (one at the pre-fault region and the other at the fault region) after thefault occurrence instant is determined, and estimatesthe phasor quantities using the discrete Fourier trans-form (DFT) method.

Fault type and phases involved: The algorithm devel-oped to perform this task is based on the analysis of thesuperimposed sequence components of the currents.The DSP module compares the magnitudes and phasesof the positive-, negative-, and zero- sequence compo-nents to determine whether the fault is single line toground (AN, BN, or CN), line to line (AB, BC, or CA),double line to ground (ABN, BCN, or CAN), or threephase.


Estimation of load rejection: The DSP module esti-mates the prefault and postfault active power to deter-mine the amount of load rejection. This information isused to classify the fault.

Fault classification: Using information about the cir-cuit-breaker status, after the fault clearance, and theamount of load rejection, the algorithm is able to clas-sify the fault as:

- Permanent faults isolated by breaker operation:When the circuit breaker remains open after theovercurrent event.- Permanent faults isolated by the fuse operation:When the circuit breaker remains closed after theovercurrent event and there is load rejection (theprefault active power is bigger than the activepower measured after the fault clearance).- Transient faults: When the circuit breaker re-mains closed after the event and there is no loadrejection.

4) Communication (COMM) Module: responsible for auto-matically sending the ASCII file produced by the DSP moduleto the computer at the operation center.

B. Operation Center Modules1) Main Module: Responsible for scheduling and storing

data acquisition. It also coordinates and monitors all datatransfer among the other modules.

2) COMM Module: Responsible for receiving the data sentby the substation computer and scheduling its processingpriority.

3) WEB-based interface: Provides graphical results of thefault location procedure. The decision of using this kindof interface was based on its flexibility and widespreaduse of web-based tools. Besides, the results provided bythe system can be accessed from any computer connectedto the utilitys intranet, not only from the computers at theoperation center.

4) Fault Location Module : Performs the fault locationprocedure, based on the algorithm detailed in the nextitem, and provides the results to the web-based interface.

C. DatabaseThe fault location system has access to a database that stores

information about the topology and electrical parameters of thefeeders. This database is obtained and periodically updated fromthe electricity utilitys corporate database and contains the fol-lowing information.

Topology: The distribution feeders are described usingthe universal transverse mercator coordinates (UTM).Therefore, it is possible to integrate information pro-vided by the fault location system to any geographicinformation systems (GIS) system;

Electrical parameters: Cable types and feeder ge-ometry such as overhead, spacer, twisted, and un-derground, used to calculate the line impedances.Nominal power of the distribution transformers andconnection schemes, etc.

Fig. 3. Typical distribution feeder.

III. FAULT LOCATION ALGORITHM

Primary distribution feeders are radial networks with severallateral branches. This means that faults at different locationsmay result in the same voltage and current signals recorded atthe substation. Therefore, the algorithm should investigate allline sections in order to determine the possible fault locations.

Consider the feeder illustrated in Fig. 3, where a starting andending node identify each line section. The procedure adoptedto determine whether the th line section, generically delimitedby nodes and , has a possible fault location, consists of esti-mating the fault distance from node , where a fault wouldproduce the same voltage and current signals recorded at thesubstation. If the estimated distance is less than the sectionslength , the th line section has a possible fault location.

The methodology used to estimate the fault distance is de-scribed in item . It is based on a set of equations that dependon the fault type, and on the following phasor quantities:

and (1)

where are the voltage phasor quantities at node , during thefault, and are the current phasor quantities at line section ,during the fault, see Fig. 5.

Assuming that the fault current and the load currentsduring the fault ( , to ) are known, and can becalculated using a three-phase power-flow algorithm.

Since it is impossible to correctly calculate the load currentsduring the fault using data available only at the substation, aprocedure was developed to estimate them. This procedure con-sists of estimating the prefault complex power at each node, thenusing it to calculate the prefault voltage and current phasor quan-tities (using a three-phase power-flow algorithm), and finallycalculating the complex power at each node during the fault bymeans of modeling its behavior according to the voltage varia-tion.

The fault location algorithm is recursive, which means that anew fault distance is calculated at each step. With this dis-tance, the voltage and current phasor quantities during the faultare recalculated (considering the fault to have occurred at thenew distance). The block diagram depicted in Fig. 4 presentsthe procedure developed to locate the possible fault points. Thedetails of the block diagram are presented in items to .


Fig. 4. Fault location algorithmlogic diagram.

Fig. 5. Fault types.

The symbols used in the block diagram and in the followingequations are:

total number of nodes at the feeder;prefault complex power measured at the substa-tion;nominal power of the transformers connected tonode ;prefault complex power at node ;complex power at node during the fault;prefault voltage phasor quantity at node ;voltage phasor quantity at node during the fault;

load current phasor quantities at node , during thefault;voltage phasor quantities at the substation, duringthe fault;current phasor quantities at the substation, duringthe fault;fault current phasor quantities;load model used by the algorithm (Table I);line and mutual impedances (in ohms per kilo-meter).

A. Estimation of the Prefault Complex PowerThe first methodology used to determine the prefault com-

plex power at each node was based on a procedure presented in[8]. Basically, it consists of aggregating the representative loadcurves of all consumers connected to each node of the feeder[these curves provide the average active power consumed (inper unit) in 15-min intervals, resulting in 96 intervals each day]in order to determine the transformers loading in terms of com-plex power.

Preliminary tests, presented in item IV, indicated that minorerrors in the load estimation did not considerably affect thealgorithms accuracy and, since this methodology uses a largeamount of data to determine the complex power at each bus, asimplified methodology was developed.

It consists of assuming that all distribution transformers con-nected to the feeder operate proportionally to their nominal ap-parent power. Consequently, the total complex power measuredat the substation is distributed at each node according to theirnominal power as in

(2)

B. Prefault Power FlowThe prefault load currents and voltages at each node are

estimated using a three-phase power flow. The implementedpower-flow algorithm exploits the fact that distribution net-works are almost always radial. Therefore, it does not use theadmittance matrix.

C. Investigation of all Line SectionsAfter estimating the prefault voltage and current phasor quan-

tities, the algorithm starts investigating all line sections in orderto determine all possible fault points. First, the algorithm as-sumes that the load currents and node voltages, during the fault,are equal to the prefault ones, and the fault distance is zero (i.e.,the fault occurred at the beginning of the investigated line sec-tion).

D. Estimation of the Fault CurrentThe fault current is estimated by subtracting the fault current

phasor quantities (measured at the substation) from the load cur-rents at the feeder, during the fault, as in

(3)


TABLE ILOAD EXPONENT VERSUS LOAD MODELS

E. Power Flow During the FaultThe current and voltage phasor quantities at each node, during

the fault, are estimated using the three-phase power flow, as initem . The power-flow calculation uses the fault currents, lo-cated at a distance from node in the th line section, andthe load currents in each node. The fault currents are obtained aspresented in item and the load currents are calculated usingthe following procedure.

First, the complex load power at each node, during the fault,is calculated assuming that the loads connected to each nodedepend on voltage according to Table I and

(4)

Then, the load currents at each node can be calculated usingthe complex power previously calculated, and the voltagephasor quantities at each node as in

(5)

From (4) and (5)

(6)

Rewriting (6)

(7)

Once the load currents, during the fault, are known, the volt-ages at each node can be calculated. As presented in (7), theload currents at a certain node depend on the voltage phasorquantities at the respective node. These currents can be obtainedthrough a typical power-flow iterative process.

F. Distance CalculationThe algorithm presented in this paper is based on the solu-

tion of (8) that describes the fault condition. Fig. 5 and Table II

TABLE IIRESISTANCE VALUES FOR ALL FAULT TYPES

illustrate all possible fault types occurring in the line section de-limited by nodes and

(8)

Depending on the fault type and phases involved, a set ofequations can be written using the linear system described in(8). As an example, consider a double-line-to-ground fault, in-volving phases A and B. Equation (8) can be rewritten, resultingin (9) and (10), as follows:

(9)

(10)

The fault distance and the fault resistances ( , , and) can be calculated by separating (9) and (10) into its real and

imaginary parts and then solving the resulting linear system, asin (11), shown at the bottom of the page. All voltage and currentphasor quantities presented in (11) were calculated using thepower flow described in item .

Similar equations to all fault types are described in [11].

G. Ranking all Possible Fault LocationsAs previously mentioned, the fault location algorithm may

provide more than one possible fault point. In order to give a

(11)


Fig. 6. Distribution feeder modeled in ATP.

TABLE IIIATP SIMULATION PARAMETERS

better estimate of the fault location, the algorithm combines in-formation about the fault type and load rejection (provided bythe DSP module) with the feeders topology and electrical pa-rameters (stored in the database) to rank them by the most prob-able ones. Basically, the algorithm follows the rules describedbelow.

When the fault is permanent, isolated by breaker op-eration, the algorithm verifies which located points areprotected by fuses and ranks them as the less probableones.

When the fault is permanent, isolated by fuse opera-tion, the algorithm verifies which located points are notprotected by fuses and ranks them as the less probableones. Among those who are protected by fuses, the al-gorithm ranks as the most probable one the point thatis protected by a fuse whose opening would cause anamount of load rejection comparable to the load rejec-tion measured by the IEDs.

IV. SIMULATION RESULTSThe automated fault location system was simulated using test

data produced by Alternative Transient Program (ATP). Severalsimulations, shown in Table III, were performed using an actualfeeder, whose topology is illustrated in Fig. 6. This feeder is 25.3km long, nominal voltage of 13.8 kV and total installed load of8.1 MVA.

Table III presents the fault parameters used in the ATP simu-lations. Five fault types, with fault resistances varying from zero

up to 20 ohms, were simulated in the nodes illustrated in Fig. 6,resulting in a total of 120 simulations. Loads were modeled asconstant impedances and the branches as nontransposed lines(distributed parameters).

The system accuracy was checked against the influence in theestimation of the load currents at each node and errors in the loadmodeling. The results are presented in sections IV-AIV-C.

A. Influence of the Load DistributionThe fault location algorithm estimates the load currents by

proportionally distributing the total apparent power measuredat the substation to each node, according to their nominal ap-parent power, as in (2). However, the load distribution may notbe proportional to the nominal installed load. Therefore, a sta-tistical approach was used to determine its influence.

This approach consisted of deliberately modifying the loadgeographical distribution used by the fault location algorithm inorder to make it different from the one used in the ATP simula-tions. To accomplish this task, the prefault load power used bythe algorithm was calculated through the multiplication of theload power, actually used in the ATP simulations, by a randomnumber, chosen from a normal distribution with mean one andstandard deviation . Then, the new nominal load power ateach node was properly adjusted to fit the total prefault powermeasured at the substation, according to

(12)

(13)

whererandom number;randomly modified power at node ;load power used in ATP simulations at node ;actual load power used by the fault location algo-rithm, at node .

The difference between the load distribution used in the ATPsimulations and the load distribution used by the fault locationalgorithm increases as the standard deviation rises. Table IVpresents the error in the calculated distance as a function of(due to the modified load distribution), for a fault occurring atnode 158 (4264 m from the substation). defines the errorin the distance calculation and defines the percentageof error in the distance calculation from the substation to thelocated point.

Six different standard deviation quantities were tested andeven for large values (e.g., ), which denote that theload distribution used by the fault location algorithm was highlydifferent from the actual one, the error remained under 1%. Thisbehavior indicates that a variation in the load geographical dis-tribution does not influence significantly the algorithms accu-racy, due to the fact that in most cases, the magnitude of the loadcurrents is much smaller than the magnitude of the fault current.Therefore, errors in the load distribution do not influence the al-gorithms response.


TABLE IVERROR IN THE ESTIMATION OF THE FAULT DISTANCEFAULT BCN

TABLE VERROR IN THE ESTIMATION OF THE FAULT DISTANCEFAULT ABC

The results presented in Table IV validate the use of a sim-plified methodology for the estimation of the prefault complexpower as described in section III.

B. Influence of the Load ModelingAccording to (4) and Table I, the load exponent defines

the load model used by the algorithm. In the ATP simulations,the loads connected to each node of the feeder were modeledas constant impedances . However, with the aim ofinvestigating its influence in the accuracy of the fault locationalgorithm, different load exponents were adopted to representthe loads connected to the feeder. Table V presents the error inthe calculated distance as a function of , adopted in the faultlocation algorithm, for a fault occurring at node 158 (4264 mfrom the substation).

As can be observed, the correct load modeling does not no-ticeably influence the response of the proposed algorithm. Fivedifferent load exponents were used and the error was below 3%for almost all simulation cases.

C. Additional Simplifications to the Proposed AlgorithmThe fault location algorithm, illustrated in Fig. 4, requires a

power-flow calculation per iteration, in order to correctly esti-mate the fault location at a certain line section. However, thepower-flow algorithm is also an iterative process, since the loadcurrents at each node depend on the voltage at the respectivenode, as in (7). Due to the computational burden imposed by theprocedure described above, the estimation of all possible faultlocations may become a time-consuming task.

This item presents an analysis of the impact of implementingan additional simplification to the proposed algorithm, with thepurpose of reducing its computational burden. It consists ofreplacing the power-flow algorithm by a simple equation, re-moving the iterative process. This decision is based on the re-sults presented in sections IV-A and IV-B (as previously dis-cussed, errors in estimation of the load modeling and geograph-ical distribution do not noticeably influence the accuracy of thefault location algorithm).

Fig. 7. Error in the estimated distance.

A method to replace the power-flow algorithm is to considerthe voltage phasor quantities at each node, during the fault, equalto the voltage phasor quantities measured at the substation, alsoduring the fault . In this case, (7) can be rewrittenas

(14)

Fig. 7 illustrates the error in the estimation of the fault dis-tance for all simulation cases. These errors were obtained usingthe simplification described above and the constant impedancemodel .

It can be noticed that the error in the calculated distance wasless than 100 m for almost 70% of the simulations. The distancebetween the farthest fault location (simulated in the ATP) andthe substation is 4264 m, which means that an error of 100 m isless than 2.5% of the total distance.

The remaining simulations presented an error of more then100 m. This error level is based on the fact that the bigger thefault resistance becomes, the smaller becomes the magnitudeof the fault current. Due to the load modeling uncertainties,the error in the distance calculation tends to increase when themagnitude of the load current is comparable to the load currentmagnitude. However, faults with large fault resistance (above20 ) will not trigger the digital meter oscillography function.For short-circuits with smaller fault resistances, the errors areacceptable.

V. FIELD TESTS

A. Hardware DescriptionThe system prototype was installed at one distribution sub-

station from a Brazilian utility, similar to the one illustrated inFig. 1. It consists of two 88/13.8-kV transformers with doublesecondary windings connected to four primary feeders. There-fore, there are 16 feeders per substation (note: in Fig. 1, onlyone transformer was illustrated).

The IEDs (digital meters, model 3720 ACM Power Meterfrom Power Measurements) are located in all feeders. The oscil-lography function was configured to trigger by overcurrent andto record approximately 10 prefault and 22 postfault cycles.

This array of meters is connected to the substation computer[IBM-PC compatible, Pentium III128-b random-accessmemory (RAM)] via an Ethernet channel (10 Mb), and this


Fig. 8. Current signalEvent 1.

computer is connected to the utilitys intranet via dedicatedline.

B. Software DescriptionThe system was coded in ANSI C, except for the web-based

interface, which was coded in ASP. The database used is SQLServer. The operating system used by the utility is Windows2000.

C. Field ResultsThe prototype installation was monitored for four

monthsfrom October 2000 to January 2001. One-hun-dred-thirteen overcurrent events occurred during the evaluationperiod. Sixteen of them were permanent faults whereas the restwere transient ones.

The performance of the fault location system was checkedonly for the permanent events since it is not possible to retrieveany information about the actual location of the transient faults.The accuracy of the system was similar in all 16 permanentevents and it is detailed in the two permanent faults presentedas follows: 1) a single-line-to-ground fault, involving phase A,the fault was cleared by fuse operation and the load rejectionwas approximately 570 kW; 2) a single-line-to-ground fault, in-volving phase C and the fault was cleared by breaker operation.

Fig. 8 illustrates the current signal at line A of the first event.The fault occurred at a lateral branch protected by fuse and, asit can be observed, the fuse isolated the fault after five cycles.However, the circuit breaker opened inappropriately after an-other five cycles. The investigation of this event revealed thatthe relay misoperation was caused by an error in the implemen-tation of a new protection philosophy.

If the fault location system were not installed, it would beimpossible to detect the implementation error. Therefore, it isimportant to point out that all information provided by modernIEDs should be investigated and used in order to improve per-formance and reliability of the electrical networks.

Fig. 9 illustrates the results provided by the fault locationsystem for the first event. Four points were located, and rankedfrom number one, the most probable, to number four, the leastprobable. The actual fault distance is less than 50 m from themost probable one, calculated by the algorithm.

Fig. 10 illustrates the current signal at line C of the eventnumber two. It was a permanent fault cleared by breaker op-eration.

Fig. 9. Fault location resultsEvent 1.

Fig. 10. Current signalEvent 2.

Fig. 11. Fault location resultsEvent 2.

Fig. 11 illustrates the results provided by the system for thesecond event. Location one is the most probable since it is in themain branch of the feeder. The actual fault distance is less than90 m from the most probable one.

VI. CONCLUSIONThis work presented a complete automated fault location

system for primary distribution networks and, more specifically,an algorithm for the fault location. This system was installedat an actual substation and its performance demonstrated thatit is a powerful tool for the operation and maintenance of theelectrical distribution networks.

The most important benefits provided by the fault locationsystem proposed in this paper are as follows:

Downtime reduction: decrease in the time spent bymaintenance crews to locate the faults.


Operational costs reduction: the fast and accurate es-timation of the fault location speeds up crew work andreduces the total number of crews on stand by.

Larger profits: due to the reduction of the operationalcosts and increase in the electricity supply.

Consumer satisfaction: downtime reduction and fastersystem restoration increase customers satisfactionwith the electricity utility.

Corrective maintenance optimization: transient faults,which do not cause permanent breaker operation orfuse blowing, can be identified by the system describedin this paper. The identification of particular areas witha high number of transient faults makes it possibleto schedule corrective maintenance work, such as treetrimming or thermovision patrol.

ACKNOWLEDGMENT

The authors extend special thanks to engineers C. Fromenand U. Castellano, who cooperated with them during the firstimplementation and field tests at Eletropaulo utility, and to A.Endrigo who contributed with the implementation of the secondversion at Bandeirante utility.

REFERENCES[1] M. Lehtonen, S. Pettissalo, and J. H. Etula, Calculational fault loca-

tion for electrical distribution networks, in Proc. 3rd Int. Conf. PowerSystem Monitoring and Control (Conf. Publication no. 336), London,U.K., 1991, pp. 3843.

[2] W. Tenschert, Fault location using fault distance measurement of digitalrelays, in Proc. 12th Int. Conf. Electricity Distribution. CIRED (Conf.Publication no. 373), London, U.K., 1993, pp. 4.20.14.

[3] A. T. Johns, L. L. Lai, M. El-Hami, and D. J. Daruvala, New approach todirectional fault location for overhead power distribution feeders, Proc.Inst. Elect. Eng. C, Gen., Transm., Distrib., vol. 138, no. 4, pp. 3843,July 1993.

[4] E. C. Senger, Localizador de Faltas Para Redes de Distribuio: IIICONLADIS, 1998.

[5] P. Jrventausta, Using Fuzzy Sets to Fault Location in Distribution Net-works. New York: Physica Verlac, 1998.

[6] J. Zhu, D. L. Lubkeman, and A. A. Girgis, Automated fault locationand diagnosis on electric power distribution feeders, IEEE Trans. PowerDel., vol. 12, pp. 801809, Apr. 1997.

[7] Standard Common Format for Transient Data Exchange (COMTRADE)for Power Systems, June 27, 1991.

[8] J. A. Jardini, C. M. V. Tahan, M. R. Gouvea, S. U. Ahn, and F. M.Figueiredo, Daily load profiles for residential, commercial and indus-trial low voltage consumers; Power delivery, IEEE Trans. Power Del.,vol. 15, pp. 375380, Jan. 2000.

[9] S. H. Horowitz and A. G. Phadke, Power System Relaying. Taunton,U.K./New York: Research Studies Press/Wiley, 1992.

[10] J. L. Blackburn, Protective RelayingPrinciples and Applica-tions. New York: Marcel Dekker, 1987.

[11] G. Manassero Jr. and E. Senger, Sistema de Localizao de Faltas ParaRedes Primrias de Distribuio, Dissertao (Mestrado), So Paulo,Brazil, 2001.

Eduardo Cesar Senger was born in Brazil in 1954.He received the B.Sc., M.Sc., and Ph.D. degreesfrom the University of So Paulo, So Paulo, Brazil,in 1977, 1983, and 1990, respectively.

Currently, he is Assistant Professor in the Depart-ment of Electric Energy and Automation Engineeringat the University of So Paulo, where he has beensince 1978. His research fields are protection, moni-toring, and control of power systems.

Giovanni Manassero, Jr., was born in Brazil in1974. He received the B.Sc. and M.Sc. degrees fromPolytechnic School, University of So Paulo, SoPaulo, Brazil, in 1999 and 2001, respectively. Heis currently studying power transformer protectionusing artificial intelligence.

His research fields are power system protectionand monitoring, and software integration.

Clovis Goldemberg was born in Brazil in 1954. Hereceived the B.Sc., M.Sc., and Ph.D. degrees fromUniversidade Estadual de Campinas, So Paulo,Brazil, in 1980, 1992, and 1995, respectively.

Currently, he is Assistant Professor in TheDepartment of Electric Energy and Automation En-gineering at the University of So Paulo, So Paulo,Brazil. His research fields are industry automationand power system control and monitoring.

Eduardo Lorenzetti Pellini was born in Brazil in1975. He received the B.Sc. degree from the Poly-technic School of University of So Paulo, So Paulo,Brazil, in 2000.

His research fields are real-time simulators, powersystem control applications, hardware, and softwareintegration. The focus of his M.Sc. thesis is a real-time simulator for an application with excitation sys-tems for hydroelectric generators.

tocAutomated Fault Location System for Primary Distribution NetworkEduardo Cesar Senger, Giovanni Manassero, Jr., Clovis GoldembergI. I NTRODUCTIONA. Fault Location Algorithms

Fig.1. Substation arrangement.II. A UTOMATED F AULT L OCATION S YSTEM

Fig.2. Fault location system software modules.A. Substation Software Modules1) Main Module: Responsible for scheduling and storing data acqu2) IED Interface Module: Converts the transient data recorded by3) Digital Signal Processing (DSP) Module: Preprocesses the tran4) Communication (COMM) Module: responsible for automatically se

B. Operation Center ModulesC. Database

Fig.3. Typical distribution feeder.III. F AULT L OCATION A LGORITHM

Fig.4. Fault location algorithm logic diagram.Fig.5. Fault types.A. Estimation of the Prefault Complex PowerB. Prefault Power FlowC. Investigation of all Line SectionsD. Estimation of the Fault Current

TABLE I L OAD E XPONENT VERSUS L OAD M ODELSE. Power Flow During the FaultF. Distance Calculation

TABLE II R ESISTANCE V ALUES FOR ALL F AULT T YPESG. Ranking all Possible Fault Locations

Fig.6. Distribution feeder modeled in ATP.TABLE III ATP S IMULATION P ARAMETERSIV. S IMULATION R ESULTSA. Influence of the Load Distribution

TABLE IV E RROR IN THE E STIMATION OF THE F AULT D ISTANCE F AULTABLE V E RROR IN THE E STIMATION OF THE F AULT D ISTANCE F AULTB. Influence of the Load ModelingC. Additional Simplifications to the Proposed Algorithm

Fig.7. Error in the estimated distance.V. F IELD T ESTSA. Hardware Description

Fig.8. Current signal Event 1.B. Software DescriptionC. Field Results

Fig.9. Fault location results Event 1.Fig.10. Current signal Event 2.Fig.11. Fault location results Event 2.VI. C ONCLUSIONM. Lehtonen, S. Pettissalo, and J. H. Etula, Calculational faultW. Tenschert, Fault location using fault distance measurement ofA. T. Johns, L. L. Lai, M. El-Hami, and D. J. Daruvala, New apprE. C. Senger, Localizador de Faltas Para Redes de Distribuio: P. Jrventausta, Using Fuzzy Sets to Fault Location in DistributJ. Zhu, D. L. Lubkeman, and A. A. Girgis, Automated fault locati

Standard Common Format for Transient Data Exchange (COMTRADE) foJ. A. Jardini, C. M. V. Tahan, M. R. Gouvea, S. U. Ahn, and F. MS. H. Horowitz and A. G. Phadke, Power System Relaying . TauntonJ. L. Blackburn, Protective Relaying Principles and ApplicationsG. Manassero Jr. and E. Senger, Sistema de Localizao de Faltas

Automated Fault Location System for Primary Distribution Networks

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