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ACKNOWLEDGEMENT
A journey is easier when you travel tougher. Interdependence is certainly more
valuable than independence. The real spirit of achieving a goal is through the way of
excellence and perpetual discipline. I would have never succeeded in completing my task
without the cooperation, encouragement and help provided to me by various personalities.
First of all, I render my gratitude to the almighty who bestowed self-confidence,
ability and strength in me to complete this work. Without his grace this would have never
been a reality.
With deep sense of gratitude I express my sincere thanks to my esteemed and worthy
Supervisor Dr. CHIRANJIB KOLEY, Associate Professor, Electrical Engineering
Department for his valuable guidance in carrying out this work under his effective
supervision, encouragement, enlightenment and cooperation.
I am grateful to Dr. N.K.ROY, Head of the Department Electrical Engineering for
his constant encouragement that was of great importance in the completion of this thesis.
I am also thankful to all the staff members of the department for their full cooperation and
help.
My greatest thanks to all who wished me success especially my parents and friends
whose support and care made me stay on earth.
Place: Durgapur
Date: (Rajashree Dhua)
Roll No: 10/EE/405
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NATIONAL INSTITUTE OF TECHNOLOGY, DURGAPUR
DECLARATION
I hereby declare that this submission is my own work and that, to the best of my
knowledge and belief, it contains no material previously published or written by another
person nor material which has been accepted for the award of any other degree or diploma
of the university or other institute of higher learning, except where due acknowledgement has
been made in the text.
Place: N.I.T. Durgapur Signature :
Date: Name : Rajashree Dhua
Roll No. : 10/EE/405
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NATIONAL INSTITUTE OF TECHNOLOGY, DURGAPUR
CERTIFICATE
This is to certify that Rajashree Dhua (Roll Number 10/EE/405), undergoing Master
of Technology in Electrical Engineering, with specialization in Electrical Systems has carried
out the dissertation titled “Simulation and Identification of Transmission Line Faults” and
prepared the report under my guidance and supervision.
The dissertation is submitted as a partial fulfilment of the requirement for the award
of Master of Technology in Electrical Engineering with specialization in Electrical Systems
from National Institute of Technology, Durgapur.
To the best of my knowledge, the materials in this report have not been submitted
earlier as a part of any other academic programme.
Dr. Chiranjib Koley Dr. N.K. Roy
Professor and Supervisor Professor and Head
Department of Electrical Engineering Department of Electrical Engineering
National Institute of Technology, Durgapur National Institute of Technology, Durgapur
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NATIONAL INSTITUTE OF TECHNOLOGY, DURGAPUR
CERTIFICATE OF APPROVAL
The foregoing thesis entitled “Simulation and Identification of Transmission Line
Faults” is hereby approved as a creditable study of an Engineering project carried out and
presented in a manner satisfactory to warrant its acceptance as prerequisite to the degree for
which it has been submitted. It is understood that by this approval, the undersigned do not
necessarily endorse any conclusion or opinion therein, but approved the thesis for the
purpose for which it is submitted.
……………………………………
Examiner
…………………………………...
Examiner
……………………………………
Examiner
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ABSTRACT
Though transmission lines are designed to ensure a reliable supply of
energy with the highest possible continuity, but about 85-87% of faults in power
system occur in transmission lines. Faults can occur due to external causes or
internal failures in the power system. Identification of type of faults as well as
location of faults is extremely necessary to reduce the outage time and
maintenance works. Fault identification is a difficult task because practical
experimental verification is difficult; also there is no standard method for
identification. Switching phenomenon occurring in transmission lines often
produces similar types of transients as that of faults, making the identification
task even more difficult.
The different types of faults occurring in transmission lines can be
categorized as unsymmetrical faults such as ground fault (LG), line to line fault
(LL) and double line to ground fault (LLG) and symmetrical faults such as three
phase fault (LLL) and three phase to ground fault (LLLG). Apart from the
symmetrical and unsymmetrical faults, arc faults also occur in the power
system, which may be a static arc fault or a dynamic arc fault. Switching
transients occurring in transmission lines due to various reasons also produce
similar kind of transient waveforms. The major reasons for the occurrence of
faults are external environmental conditions like storm, sudden fall of a tree
branch and also internal causes like insulation failure, breakdown of insulator,
faulty tripping of a circuit breaker.
In practical scenario fault can occur at any location, any time (any
inception angle) and the fault resistance can vary from as low as few ohms to
few hundreds of ohms, which influence the transient characteristics of the
voltage waveforms irrespective of the type of fault. This makes the fault type
identification, a difficult task. Therefore, the main objective is to identify the
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type and possible location of fault, for which an accurate digital model of a test
system becomes necessary, as practical experimentation is difficult.
In the work, a transmission line has been modelled, using distributed
parameter, as it has been found to be more accurate for high frequency
transient study. In order to make the transmission line model closer to the
actual transmission line, the parameters of the transmission line such as R, L
and C has been considered frequency dependent, instead of being constant as in
the case of the constant parameter model. The digital model of the proposed
system has been implemented with the help of Electro Magnetic Transients
Program (EMTP), which is freely available and widely used software for
transient studies.
The study of the transient characteristics of voltage waveforms at
different fault conditions, reveals that, the transient waveform for different types
of fault (with same fault parameter) are different, but variation of the fault
parameters like fault resistance, location, fault inception angle influence the
transient characteristics in a similar manner, making the fault identification a
difficult task.
As the recorded voltage waveforms for different fault condition are non-
stationary in nature, i.e. the harmonic content changes with time, the Short
Term Fourier Transform (STFT) has been performed in order to study the
variation of the transient behaviour closely in time-frequency domain. Through
time-frequency domain studies, it has been observed that arc faults and
switching transients can be easily identified from the other faults because of
their distinctly different frequencies and amplitude. Though, symmetrical and
unsymmetrical fault identification remains a difficult task, because these form a
complex relationship with interdependence and overlapping in terms of
frequencies. Finally through statistical analysis, a threshold value has been
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identified for different type of faults and the proposed work can be further
extended with the implementation of a suitable classifier through training and
testing methods.
The work takes into account most of the common disturbances that occur
in transmission lines and develops a test system for fault simulation based on
the frequency dependent transmission line model. The work also proposes a
method for identification of fault type and location using STFT.
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TABLE OF CONTENTS
ACKNOWLEDGEMENT i
DECLARATION ii
CERTIFICATE iii
CERTIFICATE OF APPROVAL iv
ABSTRACT v
TABLE OF CONTENTS viii
LIST OF FIGURES xi
LIST OF TABLES xv
PAGE NO
CHAPTER 1: INTRODUCTION
1.1 Previous work on identification of various faults 1
1.2 Objective 2
1.3 Work summary 2
1.4 Thesis organization 3
CHAPTER 2: MODELING OF TEST SYSTEM
2.1 Overview of digital fault simulators 4
2.2 Various models for fault simulation 4
2.3 Lumped parameter model for fault simulation 5
2.4 Distributed parameter model for fault simulation 6
2.5 Test system for fault simulation 9
2.5.1 Line parameters 9
CHAPTER 3: SIMULATION OF FAULTS
3.1 Comparison between transients in a distributed parameter model and a lumped
parameter (PI) model 10
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3.2 Types of faults 10
3.3 Causes of faults 11
3.4 Arc faults 11
3.5 Switching over voltages 12
3.6 Different types of fault simulation 12
3.6.1 Variation of parameters for fault simulation 12
3.6.2 Arc fault simulation 13
CHAPTER 4: TIME DOMAIN ANALYSIS
4.1 Simulation parameters 14
4.2 Simulation results for different unsymmetrical and symmetrical faults with
variation of fault resistance, fault location and fault inception angle 14
4.2.1 Observations 22
4.3 Dynamic arc fault simulation 22
4.4 Switching over voltage simulation 24
CHAPTER 5: FREQUENCY DOMAIN ANALYSIS
5.1 Power spectral density (PSD estimate) 26
5.2 Transfer function estimate 28
CHAPTER 6: TIME FREQUENCY DOMAIN ANALYSIS
6.1 Short time Fourier transform (STFT) 30
6.1.1 Continuous-time STFT 30
6.1.2 Discrete-time STFT 31
6.2 Spectrogram analysis of various fault signals 31
6.2.1 Spectrograms for line to ground(AG) fault 32
6.2.2 Spectrograms for line to line (AB) fault 36
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6.3 Dynamic arc fault spectrograms 41
6.4 Switching transients spectrogram 42
CHAPTER 7: FEATURE EXTRACTION FOR FAULT
IDENTIFICATION
7.1 Feature analysis from spectrograms 43
7.1.1 Variation of frequency of first peak with fault location 43
7.1.2 Variation of amplitude of first peak with window number 44
7.1.3 Variation of amplitude of first peak with window number for different
fault resistance 45
7.1.4 Variation of slope with fault resistance 46
7.1.5 Observations 47
7.2 Estimation of different fault parameters and feature extraction from an unknown
time domain signal 47
7.2.1 Evaluation of fault inception angle by Discrete Wavelet Analysis 47
7.2.1.1 Wavelet transform and Discrete Wavelet transform 47
7.2.2 Estimation of fault resistance and fault location 49
CHAPTER 8: RESULT ANALYSIS
8.1 Variation of Amplitude and Frequency for different type of faults 50
8.2 Statistical analysis and box plot for different symmetrical and unsymmetrical faults
CHAPTER 9: CONCLUSION AND SCOPE OF FUTURE WORK
9.1 Conclusion 55
9.2 Scope of future work 55
REFERENCES 56
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LIST OF FIGURES
Fig 2.1 Lumped parameter PI model (single section)
Fig 2.2: Unfaulted Long Transmission Line
Fig 2.3: Transmission line fed from one end
Fig 3.1 Voltage transients generated due to a ground fault (AG fault) in a distributed
parameter line and a lumped parameter (pi) modelled 100 km line
Fig 3.2 Pie chart showing percentage of occurrence of faults
Fig 4.1:Voltage waveforms for line to ground fault (AG fault) with variation of fault
resistances(1 Ω, 10 Ω, 50 Ω and 100 Ω) for fault inception angle 20 ° and fault location
20 km
Fig 4.2: Voltage waveforms for line to ground fault for fault resistance 1 Ω and fault
inception angle 20° with variation in fault location(20km,40 km,60 km,80 km and 100
km)
Fig 4.3: Voltage waveforms for a line to ground fault at 20 km length of the
transmission line and fault resistance (Rf)=1Ωwith variation in fault inception
angle(20°,90° and 135°)
Fig 4.4: Voltage waveforms for a line to line fault (AB fault) at 20 km length and fault
inception angle (FIA) =20° with variation of fault resistance (10Ω, 50Ω, 100 Ω and 200
Ω)
Fig 4.5:Voltage waveforms for a line to line fault for fault resistance 10 Ω and fault
inception angle 20° with variation in fault location (20 km,40 km,60 km,80 km and 100
km)
Fig 4.6: Voltage waveforms for a line to line fault at 20 km and fault resistance10 Ω with
variation in fault inception angle as(20°,90°,180° and 225°)
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Fig 4.7: Voltage waveforms for a double line to ground (ABG fault) at 20 km length and
fault inception angle (FIA) =20° with variation of fault resistance (10 Ω, 50Ω, 100 Ω and
200Ω)
Fig 4.8:Voltage waveforms for a double line to ground fault for fault resistance 50 Ω
and fault inception angle 20° with variation in fault location (20 km,40 km,60 km,80 km
and 100km)
Fig 4.9: Voltage waveforms for a double line to ground fault at 20 km and fault
resistance 50 Ω with variation in fault inception angle as(20°,90°,180° and 225°)
Fig 4.10: Voltage waveforms for a three phase fault (ABC fault) at 20 km length and
fault inception angle (FIA) =20° with variation of fault resistance (10 Ω, 50Ω, 100 Ω and
200Ω)
Fig 4.11:Voltage waveforms for a three phase fault for fault resistance 100 Ω and fault
inception angle 20° with variation in fault location (20 km,40 km,60 km,80 km and
100km)
Fig 4.12: Voltage waveforms for a three phase fault at 20 km and fault resistance100 Ω
with variation in fault inception angle as(20°,90°,180° and 225°)
Fig 4.13: Voltage waveforms for a three phase to ground fault (ABCG fault) at 20 km
length and fault inception angle (FIA)=20° with variation of fault resistance (10
Ω,50Ω,100 Ω and 200Ω)
Fig 4.14:Voltage waveforms for a three phase to ground fault for fault resistance 100 Ω
and fault inception angle 20° with variation in fault location (20 km,40 km,60 km,80 km
and 100km)
Fig 4.15: Voltage waveforms for a three phase to ground fault at 20 km and fault
resistance100 Ω with variation in fault inception angle as(20°,90°,135° and 225°)
xiii
Fig 4.16: Line to ground voltage of phase A at the load end showing the dynamic arc
fault characteristics for a line to ground fault (AG fault) at 50 km (Tdynamic=3
ms,Lstatic=0.1m)
Fig 4.17: Line to ground voltage of phase A at the load end showing the dynamic arc
fault characteristics for a line to ground fault (AG fault) at 50
km(Tdynamic=0.25ms,Lstatic=0.2m)
Fig 4.18: Line to ground voltage of phase A at the load end showing the dynamic arc
fault characteristics for a line to ground fault (AG fault) at 50 km(Tdynamic=0.625
ms,Lstatic=3.4m)
Fig 4.19: Network for simulation of switching over voltages due to 350 MW load shed
Fig 4.20: Switching over voltages of phase A, B and C due to sudden load rejection
Fig 5.1 Power spectral density estimate of AG fault voltage signal for different fault
location of 25 km, 50 km and 75 km
Fig 5.2 Power spectral density estimate of AB fault voltage signal for different fault
location of 25 km, 50 km and 75 km
Fig 5.3 Transfer function estimate of AG fault
Fig 5.4 Transfer function estimate of AB fault
Fig 6.1 STFT time-frequency representation
Fig 6.2 Spectrogram for AG fault at 25 km, Rf =1 ohm and inception angle=90°
Fig 6.3 Spectrogram for AG fault at 50 km, Rf =1 ohm and inception angle=90°
Fig 6.4 Spectrogram for AG fault at 75 km, Rf =1 ohm and inception angle=90°
Fig 6.5 Spectrogram for AG fault at 50 km, Rf =10 ohms and inception angle=90°
Fig 6.6 Spectrogram for AG fault at 50 km, Rf =50 ohms and inception angle=90°
xiv
Fig 6.7 Spectrogram for AG fault at 50 km, Rf =1 ohm and inception angle=20°
Fig 6.8 Spectrogram for AG fault at 50 km, Rf =1 ohm and inception angle=135°
Fig 6.9 Spectrogram for AB fault at 25 km, Rf =10 ohms and inception angle=60°
Fig 6.10 Spectrogram for AB fault at 50 km, Rf =10 ohms and inception angle=60°
Fig 6.11 Spectrogram for AB fault at 75 km, Rf =10 ohms and inception angle=60°
Fig 6.12 Spectrogram for AB fault at 50 km, Rf =50 ohms and inception angle=90°
Fig 6.13 Spectrogram for AB fault at 50 km, Rf =100 ohms and inception angle=90°
Fig 6.14 Spectrogram for AB fault at 50 km, Rf =200 ohms and inception angle=90°
Fig 6.15 Spectrogram for AB fault at 50 km, Rf =10 ohms and inception angle=20°
Fig 6.16 Spectrogram for AB fault at 50 km, Rf =10 ohms and inception angle=135°
Fig 6.17 Spectrogram for AB fault at 50 km, Rf =10 ohms and inception angle=225°
Fig 6.18 Spectrogram for dynamic arc fault (AG fault) at 50 km (Tdynamic=3 ms,
Lstatic=0.1m)
Fig 6.19 Spectrogram for dynamic arc fault (AG fault) at 50 km (Tdynamic=0.25
ms,Lstatic=0.2m)
Fig 6.20 Spectrogram for dynamic arc fault (AG fault) at 50 km (Tdyanmic=0.625 ms,
Lstatic=3.4m)
Fig 6.21 Spectrogram of switching transient due to load rejection at 10 ms
Fig 7.1 Variation of frequency of first peak with fault location: RF = 10Ω for AG, ABG,
ABCG and AB faults and RF=20Ω for ABC fault
Fig 7.2 Variation of frequency of first peak with fault location: Rf= 50Ω for all faults
Fig 7.3 Variation of amplitude of first peak with window number: Fault location=50
km, Rf=10Ω and FIA=90° for AG, ABG, ABCG, AB fault and fault location=50 km,
Rf=10Ω and FIA=60° for ABC fault
xv
Fig 7.4 Variation of amplitude of first peak with window number: Fault location=50
km, Rf=50Ω and FIA=90° for AG, ABG, ABCG, AB fault and fault location=50 km,
Rf=50Ω and FIA=60° for ABC fault
Fig 7.5 Variation of amplitude of first peak with window number for different fault
resistance: ABC fault at fault location=50 km, fault inception angle=60°
Fig 7.6 Slope calculation ABC fault at fault location=50 km, fault inception angle=60° at
different fault resistances
Fig 7.7: Variation of slope with fault resistance
Fig 7.8 Analysis of a signal using wavelet transform
Fig 8.1 Variation of amplitude with frequency for switching transients, arc faults and
various symmetrical and unsymmetrical faults
Fig 8.2 Variation of amplitude with frequency for symmetrical and unsymmetrical
faults
Fig 8.3 Variation of amplitude with frequency for all faults involving ground
Fig 8.4 Variation of amplitude with frequency for faults not involving ground
Fig 8.5 Box plot for different faults
LIST OF TABLES
TABLE 8.2.1: Statistical data for faults involving ground
TABLE 8.2.2: Statistical data for faults not involving ground