Power System Faults Fault Detection Project-3

Presented by: INDRAJEET PRASAD

SHIVANANDA PUKHREM

JOAN JIMIENEZ ANGELES

2011-‘12

WROCLAW UNIVERSITY OF TECHNOLOGYWROCLAW UNIVERSITY OF TECHNOLOGYWROCLAW UNIVERSITY OF TECHNOLOGYWROCLAW UNIVERSITY OF TECHNOLOGY

FACULTY OF ELECTRICAL ENGINEERINGFACULTY OF ELECTRICAL ENGINEERINGFACULTY OF ELECTRICAL ENGINEERINGFACULTY OF ELECTRICAL ENGINEERING

[POWER SYSTEM FAULT POWER SYSTEM FAULT POWER SYSTEM FAULT POWER SYSTEM FAULT

PROJECT NOPROJECT NOPROJECT NOPROJECT NO----3 (FAULT 3 (FAULT 3 (FAULT 3 (FAULT DETECTION).DETECTION).DETECTION).DETECTION).]

Prof. Dr. Hab. Inż Jan Iżykowski

2 Presented by: INDRAJEET PRASAD, SHIVANANDA PUKHREM, JOAN JIMIENEZ ANGELE

PROJECT NO-2 POWER SYSTEM FAULT

INDEX:

1. Introduction…………………………………………………………………………………………….. 3

2.Variables used in the line code program………………………………………………….. 4

3.Program code…………………………………………………………………………………………. 5

4. Graphics …………..……………………………………………………………………………………. 8

5. Graphics Description…….………………………………………………………………………… 9

6. Conclusion……………………………………………………………………………………………… 10



1.INTRODUCTION:

With this report we will try to familiarize with some code lines of Matlab Program.

Since we detected the fault in the system in the 1st and

2nd

projects, here in this

project we are detecting the power system fault through statistical method.

On the basis of delivered description of the fault detection method, we will

develop a MATLAB program to give the simulation results in time domain, and

three phase current and voltage in the system.

Here we are using two statistical methods for fault detection. They are called

sample-bysample(SBS) and cycle-by-cycle (CBC) methods,by defining threshold

value in MATLAB. This threshold must be lowenough to detect faults but also high

enough to avoid falsedetections.



2. VARIABLES USED IN LINE CODE PROGRAM:

theta_i=1;

theta_v=1;

n=20;

dT=2*pi/n;

FF=-2*FF/n;

x=readpl452;

size(x);

y=x';

size(y),

iS_af(1,:)=theta_i*filter(FF,1,y(2,:));

iS_bf(1,:)=theta_i*filter(FF,1,y(3,:));

iS_cf(1,:)=theta_i*filter(FF,1,y(4,:));



3. PROGRAM CODE:

clear all;

theta_i=1; % CT ratio

theta_v=1; % VT ratio

n=20; % number of samples in a single fundamental frequency period

% sampling frequency: 1000 Hz

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Standard full-cycle FOURIER FILTRATION:We need to calculate magnitud of

%fault current and voltege. We need to pass the digital filter called FF.

dT=2*pi/n;

for k=1:n,

alfa=dT/2+(k-1)*dT;

FF(k)=cos(alfa)+sqrt(-1)*sin(alfa);

end;

FF=-2*FF/n;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% READING AND TRANSPOSING *.PL4 FILES.

%If the readpl4 doesn`t work we can put the other file.

%x=readpl4;

x=readpl452;

size(x),

%if we want the columns for rows we are doing the transposed matrix.

y=x';

size(y),



% (S)means Sending, (a) the phase and (f) filtration. Later on we are

%using the filter that is a matlab function (help filter to know how it`s works).

%FF is the name of the filter(FF:Fourier Filter,1: is the gain,y: is the

%input signal from 2 till (:) that menas all the range of samples).

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

iS_af(1,:)=theta_i*filter(FF,1,y(2,:)); % Side S - phase 'a' current after filtration

iS_bf(1,:)=theta_i*filter(FF,1,y(3,:)); % Side S - phase 'b' current after filtration

iS_cf(1,:)=theta_i*filter(FF,1,y(4,:)); % Side S - phase 'c' current after filtration

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Threshold= 1.2*2*abs(iS_af(1,21)*sin(0.5*100*pi*0.001))

isa= y(2,:)*theta_i;

isb= y(3,:)*theta_i;

isc= y(4,:)*theta_i;

for n=2:120;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

SbyS_Sa(n)=abs(isa(n)-isa(n-1));

SbyS_Sb(n)=abs(isb(n)-isb(n-1));

SbyS_Sc(n)=abs(isc(n)-isc(n-1));

ifSbyS_Sa(n)>=Threshold

FLT_Sa(n)=1;

elseFLT_Sa(n)=0;

end;

Threshold(n)= 1.2*2*abs(iS_af(1,21)*sin(0.5*100*pi*0.001));

end;



figure(1);

plot(FLT_Sa,'ro');

grid on;

title('Fault detection[if 0=no fault,if 1=fault]');

xlabel('Time [ms]'); ylabel('fault detection');

figure(2);

plot(SbyS_Sa,'r-');

title('Sample by Sample');

xlabel('Time [ms]'); ylabel(‘Current[Amperes]’);

grid on;

hold on;

plot(Threshold,'g-');

%cycle by cycle method

for n=21:120;

Cbc_sa(n)=isa(n)-isa(n-20);

end

figure(3);

plot(Cbc_sa,'r-');

title(‘Cycle by Cycle');

xlabel('Time [ms]'); ylabel('Current[Amperes]’);

grid on;

hold on;

for n=21:120;

Cbc_saa(n)=abs(isa(n)-isa(n-20));

end

figure(4);

plot(Cbc_saa,'g-');

title(‘Absolute value of phase current');

xlabel('Time [ms]'); ylabel(‘Current[Amperes]’);

grid on;

end.

8 Presented by: INDRAJEET PRASAD, SHIVANANDA PUKHREM, JOAN JIMI

4. GRAPHICS RESULTS:

The graphics obtained from the program are showed down:

Fig : Task :Fault detection.

Presented by: INDRAJEET PRASAD, SHIVANANDA PUKHREM, JOAN JIMI

POWER SYSTEM FAULT

GRAPHICS RESULTS:

The graphics obtained from the program are showed down:

:Fault detection.

Presented by: INDRAJEET PRASAD, SHIVANANDA PUKHREM, JOAN JIMIENEZ ANGELE




5.GRAPHICS DESCRIPTION

From the above figures,

In figure 1 as we observed,till 60ms there is no fault because as we can see in the

legend of the graphic for no faults we are using {o}. During the rest of the period

which contains another 60 ms appears a fault and that is denoted by {o} symbol at

1 level of the Y axis.

Thefigure 2 depicts the sample by sample method.This method shows a sinusoidal

wave as a result of the rest of each component and the previous one which is

shown in red waveform.And the green line shows the threshold value. Here at 60

ms, the sample difference between the fault inception sample and the post fault

sample exceeds the threshold value and as a result the fault is detected after 60

ms.

The figure 3 depicts the cycle by cycle method that exceeds the threshold value at

60 ms.As we can see in the MATLAB, threshold value is equal to 1.2 of the absolute

value of the current. Because of this, during the first 60 ms the values are {0}, so

these values doesn’t exceeds the threshold value.

And figure 4 depicts the absolute value of the phase current.



6.CONCLUSION:

Through this particular project we are able to detect the power system fault using

a traditional statistical approach of fault detection which is more precious fault

detection algorithm. By simulating in MATLAB, we are able to calculate the time

period in which the fault occurs and the absolute value of the fault current at that

period of time.

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Power System Faults Fault Detection Project-3