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AbstractRelays usually need to be tested under a variety of

fault and non-fault scenarios. In order to better achieve this goal,

relay testing simulation tools based on EMTP/ATP combined

with MATLAB/C/FORTRAN have been studied by a few

researchers. However, there is hardly a relay testing tool

designed for PSCAD/EMTDC. An advanced simulation tool

based on PSCAD and MATLAB for relay testing is proposed in

this paper. The simulation tool can not only batch test relay

performance under various scenarios automatically, but also can

solve the problem of PSCAD not being able to automatically

generate scenarios at different fault locations. Examples are

given in this paper to illustrate the application of the proposed

simulation tool in relay testing. Tips on how to use the proposed

tool for neural network training are also included.

KeywordsDigital Simulation, MATLAB, Power System,

Protective relaying, PSCAD.

I. INTRODUCTION

omputer based protection system simulation has been

studied for years and it has been proven to be an accurate

and economic way for testing relay algorithms and settings.

Especially after the advent of microprocessor and digital relay,

computer based relay testing simulation became more popular

for its convenience and flexibility. Users can easily change the

settings of the power system to be tested, change the relay

algorithms and settings and even test the relay under variousautomatically generated fault and non-fault scenarios.

For conventional relays, it may be easier to set parameters

and test if there is a graphic component pre-built in the EMTP-

like software. However, an advanced language such as

MATLAB is definitely more powerful and flexible to design

and test users own relay algorithms, especially digital relay

algorithms. For this kind of testing system, the power system

model to be tested is usually built using transient programs

such as EMTP and PSCAD. The relay algorithm can be

written in one of the several programming languages, such as

C, FORTRAN and MATLAB. The relay can be tested with

either open-loop method or closed-loop method depending on

the purpose of testing [1].EMTP has been widely used for simulating power system

transients since it was developed. Alternative Transient

Program (ATP) is a public domain licensed software based on

the EMTP [2]. Relay testing simulation systems based on

EMTP and ATP have been studied by a few researchers [1],

[3]-[6]. Some of them proposed closed-loop interactive testing

systems [1], [3], [5] and others proposed open-loop testing

Xiaolei Liu (liux@ucalgary.ca) , A.H. Osman and O.P. Malik are with theUniversity of Calgary, Alberta, Canada, T2N 1N4.

system, such as [4].PSCAD/EMTDC is another popular power system

simulator for its fast simulation speed, accuracy and easy-to-

use interface. However, there is hardly any relay testing

simulation tool based on this simulator other than the

interactive system using PSCAD and PLSA proposed in [2].

In this paper, an advanced simulation tool based on PSCAD

and MATLAB for relay open-loop batch testing is proposed.

PSCAD has a multiple-run component designed for generating

various fault and non-fault scenarios; however, the fault

location cannot be automatically changed by PSCAD. The

proposed simulation tool uses MATLAB to automatically

implement the whole process, from calling EMTDC to

generate various fault scenarios including different fault

locations, to extracting data from EMTDC output data files

and finally to testing relay algorithms or training artificial

neural networks (ANN).

II. SIMULATION TOOL FRAMEWORK

The power system simulator product PSCAD consists of

two parts, i.e. the Graphic User Interface (GUI) and the

solution system. At the early stage of this product, users use

the command line driven EMTDC system. After the invention

of the PSCAD GUI, all information required is input using the

easy-to-use GUI and EMTDC is rarely noticed anymore.

However, EMTDC stand-alone execution is still usable [7].When this mode is used, EMTDC is run from a command line

instead of from the GUI. This feature is very useful for the

open-loop system proposed in this paper.

When the power system model is input in the GUI and the

run button is pressed, PSCAD will automatically execute

three processes, i.e. compiling the project, making the project

(assembly of the associated executable files to be run by

EMTDC) and running the project (solving the performance

equations and record data). After the compiling and making

processes, a temporary folder will be created by PSCAD as

shown in the middle part of Fig. 1. Among several files in the

folder, an .exe file is created and can be used manually to

run the project in EMTDC stand-alone mode. Besides, if there

is transmission line section setup in the GUI, the input file

.tli, line constant output file .tlo and the line constant

program output file .out for the transmission line will be

created during the compiling process through the PSCAD

Line Constants Program (tline.exe).

In the system proposed in this paper, the operation

sequence is different from the normal mode. Step one, Users

design their power system model using the PSCAD GUI and

use the make button in PSCAD GUI to finish compiling and

making processes, after which the temporary folder with the

Advanced Simulation Tool for Relay TestingXiaolei Liu, Student Member, IEEE, A.H. Osman,Member, IEEEand O.P. Malik,Life Fellow, IEEE

C

978-1-4244-4283-6/08/$25.00 2008 IEEE

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above mentioned files will be created. After step one is done,

the PSCAD GUI will be no longer in use.

Fig. 1. The simulation tool scheme for open-loop relay testing

At step two, the main program written in MATLAB will

automatically finish all the tasks. It controls the whole testing

process and mainly consists of four sections, i.e. initialization

section, power system model section, data extraction sectionand digital relay algorithm section. The fault location

information is updated at each iteration of the main program.

This process is shown in the right part of Fig. 1, noted as

MATLAB main program (step 2). All the four sections are

introduced next.

A. Initialization

This section will clear MATLAB workspace variables,

initialize fault location information and the step value to

update the fault location. This section also collects the input

information, such as the name of Map file (.map) and the

name of output data file (.out), required for EMTDC stand-alone execution to be introduced in the next section.

B. Power System Model

In this section, the fault location loop starts. MATLAB

needs to call a function linecon.m written by the authors to

update line length information in the file .tli as shown in Fig.

2, at each iteration. This tli file provides all input

information required by the PSCAD Line Constants Program.

MATLAB then calls the Line Constants Program and saves

new output in the temporary folder. The last step in this

section is for MATLAB to call the .exe file in the temporary

folder, which will run EMTDC to solve the performanceequations and generate output data file, saved as .out in the

temporary folder.

Since both the Line Constants Program and the EMTDC

stand-alone program are to be executed by using .exe file,

the dos function in MATLAB is used to provide DOS

environment required to run .exe. Besides, when the

EMTDC stand-alone execution command .exe is called, a

DOS based dialog window will pop up to ask users for file

names and some other options. In order to make sure the

MATLAB main system does not have to halt for this dialog

window, DOS redirection command is used to direct all the

questions to a pre-defined IN.DAT file.

Fig. 2 Locate the line length information in the .tli file

C. Data ExtractionWhen multiple-run component is used in PSCAD GUI, the

names of output data files follow the form of

X_r00001_01.out,X_r00002_01.out,

X_r00003_01.out, where X is the user defined name for

the output data file. The function genmat.m defined by the

authors is used here to read all these data files and convert

them to .mat form which is the MATLAB data form. The

names of .mat files follow the same rule as .out files. So

X_r00001_01.mat corresponds to X_r00001_01.out. The

parameter settings, i.e. fault scenarios, which are changed each

simulation run by the multiple-run component, are saved in a

file called mrunout.out (default file name).

D. Digital Relay Algorithm

In this section, algorithms written in MATLAB are

implemented. It can be digital relay algorithm, ANN training

algorithm or any other algorithm needed to process output data

from EMTDC. In this part, variable names should be assigned

to the data extracted from EMTDC output file. When the

EMTDC generates the output data file X_r00001_01.out, it

also generates a file X_r00001.inf to save the structure of the

output data file, as shown in Fig. 3. In this example .inf file,

three variables, Va, Vb and Vc are recorded, which

corresponds to the 2

nd

, 3

rd

and 4

th

column in the data file .out,respectively. The first column in .out file is always time

information.

In the first example of the simulation tool for this paper, the

function MATrelay.m written by the authors is called in the

main program to implement a digital distance relay. The

details of the example will be introduced in a later section.

After the digital relay algorithm section, fault location

information will be updated and the program will go through

the previous three sections again with the new fault location,

i.e. new iteration.

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Fig. 3 EMTDC output structure file .inf and output data file .out

III. SIMULATION EXAMPLES

A. Simple distance relay testing example

This example demonstrates the application of the proposed

simulation tool to test a simple distance relay. The distance

protection example provided by PSCAD 4.2 is used here as an

original case, where both the power system model and the

distance relay algorithm are implemented with PSCAD GUI

only. The example is reproduced using the proposed

simulation tool, where the power system model is built in

PSCAD GUI and the digital relay algorithm is written in

MATLAB.

The power system built with PSCAD GUI is shown in Fig.

4. The relay location is at the left hand end of the transmission

line. A multiple-run component is used to change fault

inception time, fault resistance and fault type. Fault location is

changed by the MATLAB main program. Digital relay

algorithm is implemented in MATLAB too, including phasorextraction and sequence component transformation as well as

distance protection scheme part including impedance

calculation and MHO characteristics. For example, the phasor

extraction using Fast Fourier Transform [8][9] is defined as a

MATLAB function phasor_extraction.m. The relay

algorithm uses dynamic window method rather than static

window method to better reproduce the original case.

Fig. 4 Power system model build in PSCAD GUI

Firstly, the results produced by the proposed simulation

tool are the same with the original system. Various fault

scenarios including different fault types, fault inception

angles, fault resistance and fault locations are tested using the

proposed simulation tool. It is found that the trip decisions are

all the same with the original case, which proves the reliability

of the proposed simulation tool for relay testing.

For example, a permanent phase-AC-to-ground fault with

1 ohm ground resistance is simulated at 50 km away from

relay location. The trajectory of impedance calculated using

the original system is shown in Fig. 5 and the trajectory

calculated using the proposed simulation tool is shown in Fig.

6. It can be found that they are identical.

Fig. 5 Trajectory of impedance for distance relay using the original system

Fig. 6 Trajectory of impedance for distance relay using the proposedsimulation tool

Secondly, fault location has to be manually changed for the

original case while it can be automatically changed when the

proposed simulation tool is used. The proposed simulation tool

also has additional features such as displaying the detection

time and any other result in MATLAB command window as

the program is running, and generating a final statistical report

on how many percentages of faults are correctly detected, for

instance. All these extra features are due to the powerful

calculating ability of MATLAB.

Thirdly, although the digital relay algorithm part can be

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implemented either with PSCAD GUI or with MATLAB in

this example case, the algorithm is very complex or even

impossible to be implemented with PSCAD GUI under many

other situations. For example, when complex digital signal

processing is required in the relay algorithm, or complex

MHO shape is required, it has to be implemented with

MATLAB-like software. The proposed simulation tool is one

of the easiest alternatives for these situations. It also provides

an efficient tool to generate a large amount of fault scenariosor to train ANN. One example of the above mentioned

situation is shown in the following example.

B. Fault detection using Discrete Wavelet Transform example

In this example, there are at least two reasons that the

proposed simulation tool should be used. First, the wavelet

transform is more complex than Fourier transform. There is no

wavelet transform module in PSCAD and it is very difficult

for users to build their own wavelet transform module in

PSCAD GUI, since knowledge of FORTRAN language would

be required. On the other hand, MATLAB is more flexible and

powerful at mathematical calculations. The MATLAB wavelettoolbox even provides the discrete wavelet transform function

ready to use. Second, the algorithm should be tested under

various fault scenarios to verify its validation. By using the

proposed simulation tool, this process will be greatly

simplified for users. All users need to do is to build the system

model in the PSCAD GUI and input their relay algorithm in

the Digital Relay Algorithm section, as shown in Fig.1.

The power system model in this example is a 225 km long

240 kV AC transmission line. It is very similar to the system

shown in Fig. 4. For detailed parameter settings of the system

see the Appendix of [10]. A fault detection method is

proposed in [10]. Discrete Wavelet Transform is applied to

three phase currents and then the norms of the first level detailcoefficients are calculated for each phase. If any one of the

three norms exceeds a threshold, a fault is detected. For a

double-line-to-ground fault 10 km away from the relay

location, with 100 ohms ground resistance, the norms are

shown in Fig. 7. Shortly after the fault occurs at 0.19896 s,

norms for both phase A and phase B exceed the threshold (0.4

in this case) and the fault is successfully detected.

In order to make sure that the fault detection algorithm is

sensitive, it should be tested under various situations, such as

fault scenarios with different fault inception time, ground fault

resistance, fault type, fault location and under different load

angles. The combination of these situations will be an

extremely large number. The proposed simulation tool is very

efficient in dealing with this situation. After users build the

power system model (step 1) in PSCAD GUI and run the

MATLAB main program (step 2), the performance of the fault

detection algorithm can be automatically tested under tens of

thousands of fault scenarios. The detection times under some

fault scenarios are shown in Table I. It is obvious that faults

can be detected shortly after the fault inception with the

detection algorithm proposed in [10].

Fig. 7 Calculated norms for ABG fault close to relay end of the line with 100

ohms ground resistance

Table I Fault Detection time (s)under various scenarios

Fault

inception

(s)

Fault

resistance

Fault

type

Fault location

10 km 90km 170km

0.19896 1 AG 0.2021 0.2083 0.2104

ABG 0.2000 0.2031 0.2083

100 AG 0.2073 0.2094 0.2177

ABG 0.2042 0.2073 0.2146

0.20174 1 AG 0.2031 0.2094 0.2115

ABG 0.2031 0.2052 0.2094

100 AG 0.2073 0.2094 0.2177

ABG 0.2073 0.2094 0.2177

0.20452 1 AG 0.2094 0.2115 0.2188

ABG 0.2073 0.2104 0.2125

100 AG 0.2104 0.2167 0.2240

ABG 0.2104 0.2146 0.2229

Not only should the fault detection algorithm be sensitive,

it should also be reliable under no fault situations. The fault

detection algorithm should be able to distinguish line charging

(including simultaneous line charging and staggered line

charging) from regular faults. For example, when the circuit

breaker (CB) on the right hand end of the line closes on a

healthy line before the CB on the left hand end of the line

closes (staggered line charging), none of the norms exceed the

threshold 0.4, as shown in Fig. 8.

The fault detection algorithm should also be able to

distinguish closing on healthy line and faulty line. Again, the

combination of scenarios can be a huge number. With the

proposed simulation tool, it is very easy to fulfill the testing of

the detection algorithm under as many scenarios as needed.

The detection times under some scenarios are shown in Table

II. It can be found that the algorithm does not detect fault

when closing on a healthy line. When closing on a faulty line,

the fault can be detected effectively, no matter whether it is a

simultaneous line charging or staggered line charging.

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Fig. 8 Calculated norms for staggered line charging on a healthy line

Table II Fault detection time (s)under line charging on both healthy line andfaulty line

Line

charging

type

Healthy

or

faulty

line

Fault

resist

-ance

Fault location

10 km 90 km 170 km

Simul-

taneously

Healthy N.A. N.A. N.A. N.A.

BCG 1 0.2021 0.2063 0.2115

100

0.2073 0.2104 0.2188

Right CB

closes

first

Healthy N.A. N.A. N.A. N.A.

BCG 1 0.2021 0.2063 0.2115

100

0.2083 0.2104 0.2167

Left CB

closes

first

Healthy N.A. N.A. N.A. N.A.

BCG 1 0.2313 0.2333 0.2375

100

0.2365 0.2417 0.2500

C. Artificial Neural Network Training

The application of ANN in power system protection has

been studied by many researchers [11][12]. ANN training has

similar requirement with digital relay algorithms testing in the

sense that data from many scenarios are needed and the ANN

algorithms are also difficult to implement directly in PSCAD

GUI. Some of them also require data of faults at different line

locations. Therefore, the proposed simulation tool can also be

applied to ANN training.

During the training stage, the system structure is exactly the

same as the scheme shown in Fig. 1. The ANN training

program should be written within the Digital Relay

Algorithm section. If there is fault location iteration, the ANN

is trained at each iteration; the final weight of the last iteration

should be used as the initial weight for the next iteration to

carry on the training. If there is no fault location iteration

required, the training will be even simpler. Random data

should be selected for training and the file names of the

unused data should be saved to a file for future ANN testing.

Example of applying the proposed simulation tool to ANN

training is not given here since the procedure is very similar to

the first two examples.

IV. CONCLUSIONS

A powerful simulation tool for relay open-loop batch

testing using PSCAD/EMTDC and MATLAB is proposed in

this paper. The proposed simulation tool can not only generate

different fault scenarios and test relay algorithms

automatically, but also can solve the problem that PSCADmultiple-run component cannot change fault location

automatically. It can also be applied to ANN training and

some other algorithms testing too. Two simulation examples

are given to illustrate the effectiveness of the proposed

simulation tool and the procedure of applying it to relay

testing. Tips on how to use the proposed simulation tool in

ANN training are included. This paper also illustrates how

PSCAD works in a deeper level and explores PSCAD file

systems.

V. REFERENCES

[1] M. Kezunovic and Q. Chen, "A novel approach for interactive protectionsystem simulation,"IEEE Transactions on Power Delivery, vol. 12, no.2, pp. 668-674, April 1997,

[2] S.G.A. Perez, M.S. Sachdev and T.S. Sidhu, "Modeling relays for use inpower system protection studies," Proceedings, 2005 Canadian

Conference on Electrical and Computer Engineering, pp. 566-9.

[3] J. Mahseredjian, G. Benmouyall, X. Lombard, M. Zouiti, B. Bressac andL. Gerin-Lajoie, "A link between EMTP and MATLAB for user-defined

modeling," IEEE Transactions on Power Delivery, vol. 13, no. 2, pp.667-74, April 1998,

[4] N. Zhang and M. Kezunovic, "Implementing an advanced simulationtool for comprehensive fault analysis," Proceedings, 2005 IEEE/PESTransmission and Distribution Conference and Exhibition - Asia and

Pacific, pp. 1-6.

[5] X. Luo and M. Kezunovic, "Interactive Protection System SimulationUsing ATP MODELS and C++," Proceedings, 2005/2006 IEEE/PES

Transmission and Distribution Conference and Exhibition, pp. 6, 2006

[6] K.H. So, J.Y. Heo, C.H. Kim, R.K. Aggarwal, J.C. Kim and G.S. Jang,"An implementation of current differential relay and directionalcomparison relay using EMTP MODELS,"Electrical Power and Energy

Systems, vol. 28, pp.261272, 2006.

[7] PSCAD/EMTDC Runtime Manual, Manitoba HVDC Research Center,pp. 56-57, 1994.

[8] L. Wu, C. liu and C. Chen, "Modeling and testing of a digital distancerelay using MATLAB/SMULINK," Proceedings of the 37th Annual

North American Power Symposium, pp. 253-9, 2005.

[9] A.G. Phadke, J.S. Thorp, and M.G. Adamiak, "A new measurementtechnique for tracking voltage phasors, local system frequency, and rate

of change of frequency," IEEE Transactions on Power Apparatus and

Systems, vol. PAS-102, no. 5, pp 1025-38, May 1983.

[10] A.H. Osman, "Transmission Line Protection Techniques Based onWavelet Transform," Ph.D. dissertation, Department of electrical andcomputer engineering, the University of Calgary, 2003.

[11] Y.H. Song, Q.X. Xuan and A.T. Johns, Comparison studies of fiveneural network based fault classifier for complex transmission lines,

Electric Power Systems Research,vol. 43, no. 2, pp.125-32, Nov. 1997.

[12] F. Martin and J.A. Aguado, Wavelet-Based ANN approach fortransmission line protection,IEEE Transactions on Power Delivery,

vol. 18, no. 4, pp. 1572-4, Oct. 2003.

VI. BIOGRAPHIES

Xiaolei Liu (S07) received his B.Sc. from P.R. China in 2005. He is

currently pursuing the Ph.D. degree at the University of Calgary, Calgary, AB,

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Canada. His area of interests includes digital protection relaying, signal

processing, neural network and HVDC systems.

A.H. Osman (S01, M03) received his B.Sc. and M.Sc. in electrical

engineering from Helwan University, Cairo, Egypt in 1991 and 1996,respectively. In 2003 he received his PhD in electrical engineering from the

University of Calgary, Canada. Currently he is an assistant professor in

Department of Electrical and Computer Engineering at the University of

Calgary, AB, Canada. His areas of interest include power system engineering,

digital protection relaying, signal processing and power electronics.

O.P. Malik (M66SM69LF00) received the National Diploma in

electrical engineering from Delhi Polytechnic, Delhi, India, the M.E. degree in

electrical machine design from Roorkee University, Roorkee, India in 1962

and received Ph. D. degree from the University of London and D.I.C. from the

Imperial College, London, England in 1965. In 1974, he became a Professorin Department of Electrical and Computer Engineering, University of Calgary,

Calgary, AB, Canada and is presently professor emeritus there. He has

performed research work in collaboration with teams from Russia, Ukraine,China, Egypt and India. In addition to his research and teaching, he has served

in many additional capacities at the University of Calgary including Associate

Dean of Academics/Student Affairs and Acting Dean of the Faculty of

Engineering.