i

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

ii

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

iii

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

iv

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

v

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.

viii

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

xi

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