A new faulted phase identification technique for overhead distribution system

Computer Engineering and Intelligent Systems www.iiste.org
ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online)
Vol 3, No.10, 2012

A New Faulted-Phase Identification Technique for
Overhead Distribution System
Eyada A Alanzi *, Mahmoud A Younis
ELECTRICAL POWER ENGINEERING
COLLEGE OF ENGINEERING
UNIVERSITI TENAGA NASIONAL
43009 KAJANG, SELANGOR, MALAYSIA
* E-mail of the corresponding author: ealanezi@yahoo.com

ABSTRACT
An identification of faulted phase in overhead distribution System is presented in this paper. This technique is
accomplished by two steps. First, to identify the type of fault polarity (grounded or ungrounded). Then,
determine the faulted-phase type. The proposed method takes the advantage of the special features of Clarke
modal transformation and wavelet transform to explore the type of fault occurring along the distribution power
system. MATLAB software is used for implementation of modal and wavelet transformation. ATP/EMTP is
used for simulation results of the sample distribution system for demonstration and testing of the proposed
method.

Keywords: Fault-phase classification, wavelet transform, phase-shift angle and overhead distribution system

1. INTRODUCTION

Classification of fault in over head distribution system is vital for economic operation. Accurate fault classification
helps in fast repair, reduce operating costs, quick system restoration and significantly improve system availability
and reliability. Fault classification is established for two main reasons, first, identification of the faulted phase type,
e.g., single-phase-ground fault, phase-phase fault, etc. In this case the protection relays can select the suitable
algorithm element to deal with various fault conditions. The second reason is determining of the faulted phase to
maintain a single-phase tripping and auto-reclosing decisions [1]. Wavelet Transform (WT) is a valuable tool in
analyzing transient voltage and current signals related to faults both in frequency and time domain. Recent fault
classification techniques were based on the variation of the current or voltage samples of the three phases or phasor
quantities of power frequency information [2]. Wavelet transform is also used for fault classification based on
maximum detail coefficient, signal energy and ratio of energy change of three phase current signals [3]. Voltage
and current waveforms are used by wavelet transform to classify faults in a double line network for only single-
phase-ground faults [4]. Spectral energy tested at certain thresholds by wavelet transform. The current magnitude,
phase angle difference and spectral energy of coefficients are analysed for detection of fault types. The threshold
value is to be modified in each case with new actual data [5]. Also, Wavelet transform algorithm with three phase
currents at one end of the line is used with a rule base to be set for each test case. Three-phase fault was not
identified due to high impedance of the line [6]. For radial power system wavelet transform method is used to
detect phase-phase-ground faults from three phase currents at both ends of the line [7]. Another approach of
wavelet transform and generic algorithm (GA) is used with current signals collected at one end of the line. The
approach did not result with same classification accuracy for all faulted phase cases [8]. Other researchers proposed
a technique of wavelet transform with neural networks to detect faulted phase in different situations. Results of
these approaches depend highly on the accuracy of current signals extracted from the system [9, 10].

In this paper, a new fault phase identification technique for overhead distribution system is proposed using
Clarke Modal and wavelet transformations. The technique utilizes only voltage waveform (pre-fault and post-
fault) from one end of the distribution line (main substation). This will eliminate the effect of CT behaviour
during fault period on fault-phase type classification. In fact, during the fault period, current transformers do not
operate properly due to transient state and over voltage of the power system. The problem of CT saturation and
inaccurate measurement of current will increase the cost of protection of distribution system.The approach is
divided into two parts. First, identify the grounded and the ungrounded faults by the modal transform method.
Second, determine the faulty phase by Discrete Wavelet Transform (DWT).

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2. MODAL TRANSFORM

In the proposed approach, to determine whether the fault is grounded or ungrounded, the modal components are
extracted from the phase domain signals by the modal transformation matrix. In this study, all overhead
distribution line models are assumed to be fully transposed, and therefore the well known Clarke's constant and
real transformation matrix will be used for this purpose. The matrix is given by [11] and stated as follows:

T= [ ] (1)
√ √

The phase signals are transformed into their modal components by using this transformation matrix as in (2).

Smode = T Sphase (2)

where,

Smode = [ ] and Sphase = [ ]

The Smode and Sphase are the modal and phase signals (voltages or currents) vectors respectively. Clarke's
transformation is real and can be used with any transposed line. If the studied line is not transposed, then an
eigenvector based transformation matrix, which is frequency dependent, will have to be used. This matrix should
be computed at a frequency equal or close to the frequency of the initial fault transients. Recorded phase signals
are first transformed into their modal components. The first mode (mode α), is usually referred to as the ground
mode, and its magnitude is significant only during faults having a path to ground. The second mode (mode β) is
also known as the aerial mode. Therefore, the fault type problem is formulated based essentially on the ground
mode α, making use of the ground mode magnitude for the purpose of distinguishing between grounded and
ungrounded faults situations.

3. WAVELET TRANSFORM

Wavelet Transform (WT) is mathematical tool that can be used effectively for analysis of transient current and
voltage signals [2, 3]. WT has much more features than conventional signal processing methods because of the
efficient analysis of the signal in both frequency and time domains. In WT, the band of analysis can be adjusted
so that low frequency and high frequency components can be detected accurately. Results of WT provide time
and frequency information in different resolution. Discrete Wavelet Transform (DWT) is used in analyzing
transient voltage of faults on the distribution system by two scale factor. For any function (f), DWT is written as,

( ) √
∑ ( ) ( ) (3)

Where, Ψ is mother wavelet. The decomposition for three levels is shown Fig.1.
Level 1 Level 2 Level 3
HPF 2 D1

f(t ) HPF 2 D2

HPF 2 D3
LPF 2
LPF 2
A1
A2 LPF 2 A3
HPF = High Pass Filter
LPF = Low Pass Filter

Fig.1. Three level signal decomposition diagram.

In this paper, DWT is used to classify the type of fault either when fault is grounded or ungrounded. In the
grounded fault situation, faulted phases of SLG, LLG and LLLG will be distinguished. Similarly, for
ungrounded fault situation, LLF and LLLF phases will be determined.

4. PHASE-SHIFT ANGLE

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Phase shift is a change in voltage phase angle associated with fault occurrence. The characteristics of particular
faults at certain locations are determined by the type of fault in addition to other factors [12]. Phase shift during
the fault occurrence can be obtained by calculating the difference between the pre-fault voltage waveform angle
and the during-fault voltage waveform angle. A phase shift can be expressed either as a time (in milliseconds), or
as an angle (in degrees or radians), and may have a negative or positive values.

5. FAULT TYPE CLASSIFICATION

The proposed approach of fault type classification consists of two steps: (1) use of modal transformation to
identify if fault is grounded or ungrounded. (2) DWT implementation with angle phase shift to classify the
faulted phase type.

5.1. Identification of Grounded and Ungrounded Faults
After reading the faulted voltage waveforms, the signals undergo a low-pass filtration and a size reduction for
readiness to the modal transform. Next, using the faulted voltage waveforms (Va, Vb, Vc) in (2) to calculate the
modal signals (α, β, 0). Fig.3 shows the flow chart for identifying the grounded and ungrounded faults by modal
transform. For proper differentiation between grounded and ungrounded situations, a threshold value is
proposed. When absolute value of the sum of signal α is calculated, it was found that for grounded cases the
value is over 30 except for three phase-to-ground faults the value was slightly more than 0.01.On the other hand,
for ungrounded faults the values was below 0.009. As a result it was decided to set a certain threshold value (ε)
as 0.01 for definite selection between the two types.

Va, Vb, Vc

Signal Sampling
and Normalization

Modal
Transform

N Y
|  | >ε
Ungrounded Grounded
Fault Fault

Fig.2. Identification of grounded or ungrounded faults
Based on Modal Transformation of voltages signals

5.2. Determination of Fault Phase Type
The faulted phase is determined by using two types of data, results of discrete wavelet transform for each voltage
phase (Wva, Wvb , Wvc ) and the phase-shift angle (θA, θB, θC) of each recorded voltage waveforms. Therefore,
fault phase type can be determined as per the following sequence:
a. Reading/recording of voltage signals at main substation (Va, Vb, Vc).
b. Calculation of phase-shift angle for each voltage phase waveform (θA, θB, θC).
c. Apply of Discrete Wavelet transform (DWT) and use of data (Wva, Wvb, Wvc) of (db8) at level 1.
The grounded faults scheme is performed in the following steps (as shown in Fig.3):
1. If | | | | | | AND θA > θB & θC then fault type is single phase-to-ground (AG).
2. If | | | | | | AND θB > θA & θC then fault type is single phase-to-ground (BG).
3. If | | | | | | AND θC > θA & θB then fault type is single phase-to-ground (CG).
4. If | | | | | | AND θA & θB > θC then fault type is double phase-to-ground (ABG).
5. If | | | | | | AND θA & θC > θB then fault type is double phase-to-ground (ACG).
6. If | | | | | | AND θB & θC > θA then fault type is double phase-to-ground (BCG).
7. Otherwise, the fault type is three phase-to-ground fault (ABCG).

Similarly, the ungrounded faults scheme is performed in the following (as shown in Fig.4) steps:
1. If | | | | | | AND θA & θB > θC then fault type is double phase fault (AB).

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2. If | | | | | | AND θA & θC > θB then fault type is double phase fault (AC).
3. If | | | | | | AND θB & θC > θA then fault type is double phase fault (BC).
4. Otherwise, the fault type is three phase fault (ABC).

Grounded Fault

V a ,V b ,V c

Calculate Phase-Shift
Angle
(  A ,  B , C )

Wavelet Transform
( db8 , level 1)

Check for values
| Wv a |< | Wv b |&| Wv c | Y
and AG
A > B & C

N

Check for values
| Wv b | < | Wv a |&| Wv c | Y
and BG
B > A & C

N

Check for values
| Wv c | < | Wv a |& | Wv b | Y
and CG
C > A & B

N

Check for values
| Wv a |& | Wv b |<| Wv c | Y
and ABG
A & B > C
N
N

Check for values
| Wv a |& | Wv c |<| Wv b | Y
and ACG
A & C > B

N

Check for values
| Wv b |& | Wv c |<| Wv a | Y
and BCG
B & C > A

N

ABCG

Fig.3 Flowchart of identification of fault phase type for the grounded faults

Ungrounded Fault

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Va , Vb , Vc

Calculate Phase-
Shift Angle
( θ A , θB , θC )

Wavelet Transform
( db8 , level 1)
( Wva, Wvb, Wvc )

Check for values
|Wva| & |Wvb| < |Wvc| Y
AB
And
θA & θ B > θ C
N
Check for values
|Wva| & |Wvc| < |Wvb| Y
AC
And
θA & θ C > θ B

N
Check for values
|Wvb| & |Wvc| < |Wva| Y
BC
And
θB & θ C > θ A
N

ABC

Fig.4 Flowchart of identification of fault phase type for the ungrounded faults

6. SIMULATION STUDY FOR FAULT PHASE TYPE CLASSIFICATION

In this paper, estimation of fault phase type classification is performed on a power system simulation as shown in
Fig.5. The simulation of transient signals of the overhead distribution system is performed using ATP/EMTP
program [13]. The power system is consisting of single power supply of 33kv, 50Hz and a radial over head
distribution system of 20 km with three lateral branches of 5 km each and loads. The faults are simulated on 7
points (T1-T7) on the power system. Faulted phase types simulated with different fault impedances (Rf) (0Ω-
100Ω) and different inception angles (Ai) (0° 45° 90° of faults are studied. For each case, the summations of
, , )
the first level (L1) coefficients of mother wavelet (db8) are determined. It is found that even these values are
different; however, values are close for one fault type (SLG, LL, LLG, LLL or LLLG) with different impedances
and inception angles. The simulation time is 60 ms with time step 1.0μs and total of 1200 samples.
T2 T3 T4
A T1
5 KM 5 KM 5 KM 5 KM
Load

2KM 2KM 2KM

T7 T6 T5

Load Load Load

Fig.5 Overhead Distribution System used for the study
System parameters are typical to Kuwait network at Wafra area with generator source resistance 0.89Ω and
source inductance of 12.37mH. Overhead distribution line parameters for main line and lateral branches are
shown in Table.1.

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Sampling of three-phase of voltage waveforms is shown in Fig.6, Fig.7 and Fig.8 during the occurrence of
single-line-to-ground (phase-A-to-ground), double-line-to-ground (phases-AB-to-ground) and line-to-line
(phase-A-to-phase-B) faults, respectively.
4
x 10
4

3
Va
2 Vc
Vb
1

Voltage , V
0

-1

-2

-3

-4

-5

-6
0 10 20 30 40 50 60
Time, ms

Fig.6 Three phase voltage waveforms during SLG-AG
fault at T2 on the distribution system
4
x 10
4

3 Vb Vc
Va
2

1
Voltage, V

0

-1

-2

-3

-4

-5
0 10 20 30 40 50 60
Time, ms

Fig.7 Three phase voltage waveforms during DLG-ABG
4
x 10
4

3
Va
Vc
2

1
Voltage, V

0 Vb

-1

-2

-3

-4
0 10 20 30 40 50 60
Time, ms

Fig.8 Three phase voltage waveforms during Line-Line (AB)

TABLE.1
Overhead Distribution line parameters

Parameters of main line
R1 0.11763 Ω/km
R0 0.22961 Ω/km
X1 0.3712 Ω/km
X0 1.0717 Ω/km
C1 3.1 µ F/km
C0 1.5 µ F/km
Parameters of lateral branches
R1 0.227 Ω/km
R0 0.04122 Ω/km
X1 0.3654 Ω/km
X0 0.1601 Ω/km
C1 3.1 µ F/km
C0 1.3 µ F/km
7. RESULTS AND DISCUSSIONS

The data of system shown in Fig.5 is used by the proposed algorithm for classification of fault phase type
resulted at different locations on the power system. The voltage waveforms are taken from one side of the line at

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substation A for all occurred faults. MATLAB software is used for calculation of data in both methods, modal
and wavelet transforms [14].

7.1 Identification of Grounded and Ungrounded Faults

Table.2 and Table.3 show the results of modal transformation of faulted voltage waveforms for different types of
fault phases at different fault locations on the power system with fault resistance Rf = 0Ω. It is concluded from
tabulated results that the value of selected threshold is met for both schemes (grounded and ungrounded). For
grounded condition the threshold value is > 0.01and for ungrounded condition the threshold value is < 0.01.

TABLE.2
Results of Modal Transform (|Σα|) for SLG, LLLG and LLL faults
at different locations on the distribution system with Rf = 0Ω.

Fault Location
AG BG CG LLLG LLL
(Terminal #)
T1 70.396 32.197 37.760 0.0102 0.009
T2 70.055 31.996 37.611 0.0114 0.009
T3 69.704 31.785 37.459 0.0126 0.009
T4 69.342 31.563 37.304 0.0137 0.009
T5 69.688 31.775 37.452 0.0132 0.009
T6 70.040 31.987 37.604 0.0120 0.009
T7 70.381 32.188 37.753 0.0109 0.009

TABLE.3
Results of Modal Transform (|Σα|) for grounded (LLG) and ungrounded (LL) faults
at different locations on the distribution system with Rf = 0Ω.

Grounded Faults Ungrounded Faults
Fault
Location ABG ACG BCG AB AC BC
(Terminal#)
T1 37.607 32.245 69.823 0.006 0.009 0.009
T2 37.459 32.046 69.475 0.006 0.009 0.009
T3 37.311 31.839 69.120 0.006 0.009 0.009
T4 37.162 31.625 68.756 0.006 0.009 0.009
T5 37.303 31.830 69.101 0.006 0.009 0.009
T6 37.451 32.037 69.458 0.006 0.009 0.009
T7 37.599 32.236 69.806 0.006 0.009 0.009

7.2 Determination of Fault Phase Type

The results of employing the data of DWT and Phase Shift Angle are stated in this section. Table.4 shows results
data for SLG (AG) and LLG (ABG) with fault resistance Rf = 0Ω at different fault locations on the distribution
system. For AG condition it is clear from tabulated data that all values of |Wva| are less than the values of |Wvb|
and |Wvc|; and the value of phase shift angle θA is more than the values of phase shift angles θB and θC for all
fault locations. Similarly, for ABG, the values of |Wva| and |Wvb| are less than the value of |Wvc|; and the value
of phase shift angles θA and θB are more than the value of phase shift angle θC for all fault locations. In Table.5,
The results of LL (AB) faults are tabulated. It is clear that for all fault locations the values of |Wva| and |Wvb| are
less than the value of |Wvc|; and the phase shift angles values of θA and θB are more than the phase shift angle
value of θC and the condition criteria satisfied for AB ungrounded fault.

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TABLE.4
Results of Voltage Wavelet Transforms (Wv) and phase shift angles (θ)
for grounded phases (SLG and LLG) at (Rf =0Ω).
Fault
Locati
Fault
Type
on |Wva| |Wvb| |Wvc| θA θB θC
(Termi
nal#)

T1 0.0019 0.0123 0.0134 0.838 0 0.001

T2 0.0022 0.0123 0.0134 0.788 0 0.001
T3 0.0024 0.0123 0.0134 0.742 0 0.001
SLG
(AG) T4 0.0026 0.0123 0.0134 0.7 0 0.001
T5 0.0024 0.0123 0.0134 0.74 0 0.001
T6 0.0022 0.0123 0.0134 0.786 0 0.001
T7 0.0019 0.0123 0.0134 0.836 0 0.001

T1 0.0019 0.0054 0.0134 0.837 0.73 0.001

T2 0.0022 0.0056 0.0134 0.786 0.68 0.001
T3 0.0024 0.0058 0.0134 0.74 0.64 0.001
LLG
(ABG) T4 0.0026 0.0060 0.0134 0.698 0.61 0.001
T5 0.0025 0.0058 0.0134 0.738 0.64 0.001
T6 0.0022 0.0056 0.0134 0.784 0.68 0.001
T7 0.0019 0.0054 0.0134 0.835 0.73 0.001

TABLE.5
Results of voltage wavelet transforms (Wv) and phase shift angles (θ)
for ungrounded phases (LL) at (Rf =0Ω).

Fault Location
Fault Type |Wva| |Wvb| |Wvc| θA θB θC
(Terminal#)

T1 0.0049 0.0085 0.0134 0.973 0.960 0.0

T2 0.0050 0.0084 0.0134 0.908 0.862 0.0

T3 0.0050 0.0084 0.0134 0.850 0.759 0.0
LL
(AB) T4 0.0050 0.0084 0.0134 0.798 0.657 0.0

T5 0.0050 0.0084 0.0134 0.848 0.755 0.0

T6 0.0050 0.0084 0.0134 0.905 0.858 0.0

T7 0.0049 0.0085 0.0134 0.970 0.956 0.0

7.3 Testing of Performance of Proposed Technique at Different Conditions

The proposed method is tested with different parameters and shows high accuracy and meeting the condition set
for each case with different fault resistance (Rf) and inception angle (Ai), as illustrated in Tables (6 – 8). In
Table.6, the resulted data of grounded and ungrounded faults are tabulated, where in Table.7 and Table.8 the
resulted data for fault phase types based on wavelet transforms and phase shift angles for ABG and AC faults,
respectively.
TABLE.6
Results of the Modal Transform (|Σα|) for ABG and BG faults at
different locations on the distribution system with different parameters

Fault Location ABG FAULT AC FAULT
(Terminal #) (Rf =10Ω, Ai =90°) ( Ai =45°)
T1 5.242861 0.005607
T2 5.188395 0.001258
T3 5.134361 0.002632
T4 5.080795 0.003279
T5 5.131809 0.004574
T6 5.185825 0.002965
T7 5.24028 0.007969

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TABLE.7
Results of voltage wavelet transform (Wv) and phase shift angle (θ)
during ABG faults at Rf =10Ω and Ai = 90° .

Fault
Location |Wva| |Wvb| |Wvc| θA θB θC
(Terminal#)

T1 0.00307 0.00857 0.01339 0.34570 0.28622 0.00096

T2 0.00305 0.00870 0.01339 0.33446 0.27793 0.00095

T3 0.00302 0.00881 0.01339 0.32391 0.27006 0.00094

T4 0.00299 0.00893 0.01339 0.31400 0.26258 0.00093

T5 0.00302 0.00882 0.01339 0.32345 0.26972 0.00094

T6 0.00305 0.00870 0.01339 0.33397 0.27758 0.00095

T7 0.00307 0.00858 0.01339 0.34519 0.28586 0.00096

TABLE.8
Results of voltage wavelet transforms (Wv) and
phase shift angles (θ) during AC fault at Ai = 45°
.

Fault
Location |Wva| |Wvb| |Wvc| θA θB θC
(Terminal#)

T1 0.00159 0.01234 0.01075 0.76690 0.00000 0.79574

T2 0.00117 0.01234 0.01116 3.13068 0.00000 0.75277

T3 0.00081 0.01234 0.01153 3.13068 0.00000 0.71328

T4 0.00050 0.01234 0.01184 3.13068 0.00000 0.67700

T5 0.00080 0.01234 0.01154 3.13068 0.00000 0.71159

T6 0.00116 0.01234 0.01118 3.13068 0.00000 0.75094

T7 0.00157 0.01234 0.01077 0.76293 0.00000 0.79375

8. CONCLUSION

This paper presents a proposed technique for classification of fault phase types in Overhead Distribution Systems
with lateral branches. The new technique employed three methods namely, Clarke Modal Transform, Wavelet
Transform and Phase Shift Angle criteria to establish a robust result for fault phase type identification utilising
only three phase voltage waveforms at one end of the distribution line. The technique performance is
successfully tested with data obtained during computer simulations with different types of sampled data at
various situations (faulted resistance, inception angle and fault location). This proposed technique can be
implemented in real time with actual data.

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Eyada A Alanzi (M’97) received the B.E. and M.E. degrees, from Kuwait University in 1985 and 1996,
respectively. He worked in the private sector for more than 20 years on design and construction of Electrical
Projects. He is currently working on his research as PhD candidate in the Department of Electrical Power
Engineering, Universiti Tenaga Nasional (UniTen). His research interest includes protection of power systems,
neural networks, support vector machines and their application to fault locations. He is a member of IET
(Chartered Engineer) and IEEE.

Mahmoud A. A. Younis was born in Gaza, Palestine. He receives the PHD in the Department of Electrical
Engineering, UM, Malaysia 2009, the M.Sc. degree from UM Malaysia. in 2001, and B.Sc. degree from IIT,
Bangladesh in 1997. Currently he is a lecturer in the Department of Electrical Power Engineering, University
Tenaga Nasional (UNITEN), Malaysia. Dr. Mahmoud is active in Power Electronics research Group in UM and
His research interest including, Power Electronics, Renewable Energy, distributed Generation and Fuel cell
system.

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Publishing service based in the U.S. and Europe. The aim of the institute is
Accelerating Global Knowledge Sharing.

More information about the publisher can be found in the IISTE’s homepage:
http://www.iiste.org

CALL FOR PAPERS

The IISTE is currently hosting more than 30 peer-reviewed academic journals and
collaborating with academic institutions around the world. There’s no deadline for
submission. Prospective authors of IISTE journals can find the submission
instruction on the following page: http://www.iiste.org/Journals/

The IISTE editorial team promises to the review and publish all the qualified
submissions in a fast manner. All the journals articles are available online to the
readers all over the world without financial, legal, or technical barriers other than
those inseparable from gaining access to the internet itself. Printed version of the
journals is also available upon request of readers and authors.

IISTE Knowledge Sharing Partners

EBSCO, Index Copernicus, Ulrich's Periodicals Directory, JournalTOCS, PKP Open
Archives Harvester, Bielefeld Academic Search Engine, Elektronische
Zeitschriftenbibliothek EZB, Open J-Gate, OCLC WorldCat, Universe Digtial
Library , NewJour, Google Scholar

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