This document discusses using synchronized phasor measurements from Phasor Measurement Units (PMUs) to locate faults in interconnected power networks. It addresses the challenge that it is not economical to install PMUs at all network buses. The paper proposes using the Tree Search Method (TSM) to determine a near-optimal placement of PMUs that allows fault location. It presents simulation results applying TSM to standard test systems and a real network, showing the ability to accurately locate different fault types. Mathematical formulations for calculating fault distances are also discussed.

1. 1
Fault Location in SEC Interconnected Network Based on Synchronized Phasor
Measurements
A. H. AL-MOHAMMED*, M. M. MANSOUR**, M. A. ABIDO**
*Saudi Electricity Co., **King Fahd University of Petroleum & Minerals
Saudi Arabia
SUMMARY
This paper addresses the subject of fault location in interconnected networks using the Phasor
Measurement Units (PMUs). As it is not economical to install PMUs in all the network buses,
this paper also highlights a PMU placement technique based on the so-called Tree Search
Method (TSM) to determine a near-optimal solution for the PMU placement problem. TSM
application to IEEE-14 bus, IEEE-57 bus and a 115 kV system selected from the Saudi
Electricity Company (SEC) network will then be presented. Mathematical formulation to
calculate the fault distance will be discussed. Simulation results obtained from both
PSCAD/EMTDC and MATLAB to determine the location of different types of faults will be
presented and discussed.
KEYWORDS
Phasor Measurement Unit (PMU), Synchrophasor, PMU Placement Problem, Fault Location
21, rue d’Artois, F-75008 PARIS C4-205 CIGRE 2012
http : //www.cigre.org

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1. INTRODUCTION
The phasor measurement unit (PMU) has the potential to revolutionize the way electric power systems
are monitored and controlled. This device has the ability to measure current, voltage, and calculate the
angle between the two. Phase angles from buses around the system can then be calculated in real time.
This is possible because of two important advantages over traditional meters; time stamping and
synchronization. The algorithms behind phasor measurement date back to the development of
Symmetrical Component Distance Relays (SCDR) in the 1970’s. The major breakthrough of SCDR
was its ability to calculate symmetric positive sequence voltage and current using a recursive Discrete
Fourier Transform. The recursive algorithm continually updates the sample data array by including the
newest sample and removing the oldest sample to produce a constant phasor. The advent of the Global
Positioning System (GPS) in the 1980’s was the second breakthrough that enabled the modern PMU.
Researchers at Virginia Tech’s Power Systems Laboratory in the mid-1980’s were able to use the
pulses from the GPS satellites to time stamp and synchronize the phasor data with an accuracy of 1.0
μs. With the addition of effective communication and data collection systems, voltage and current
phasors from different locations could be compared in real-time. [1]
At present, PMUs have come out of their academic infancy with commercial viability. They are now
commercially produced by all major IED providers in the power industry. To aid the maturing of the
industry, an important standard has been developed by the IEEE. The IEEE synchrophasor standard,
c37.118-2005, ensures PMUs from different manufacturers operate well together. Initial cost of PMUs
in the early 90’s was about $20k. The price has since dropped to $3k for the simplest units. However,
installation costs remain high, between $10k-50k depending on the utility and location. [1]
Monitoring real-time angle differences has many potential applications in power systems. Simply
placing PMUs in various substations can help prevent blackouts by real-time monitoring by system
operators. System operators can be warned of potential problems more quickly during critical
situations, where seconds can make all the difference in detecting and dealing with dangerous
cascading events. Operators neighboring a highly stressed system would also be more alert to potential
dangers originating outside of their control area. If a cascading problem were to arise, PMUs would be
very useful in determining where and how to perform system separation to limit the effect of the
system disturbance. [1]
One application of PMU in power systems is in fault location. Fault detection/location on transmission
lines is a very well-known problem that has been studied for a long time. An accurate fault
detection/location technique is of special importance in improving power system reliability including
relaying, analysis for line inspection, and routine maintenance. The importance of fault
detection/location of power transmission lines is dramatically increasing in recent decades. EHV and
UHV transmission network plays essential roles in transmitting electrical power from the generating
plants to the end users. Any occurrences of fault in transmission network usually cause multimillion
dollars losses to the economic. To avoid such event, power providers have to guarantee the quality and
stability of the power feeding. Therefore, ensuring the reliability of the transmission lines is crucial.
Once an occurrence of fault is happened in the transmission network, a fault detection and location
systems estimate the fault location of transmission lines, then a transmission line protection system
isolates the fault region from the entire transmission network by cutting the power feeding at some
relaying points around the fault region. Any reason that causes the response times of the fault
detection/location/protection system failing to respond promptly, more transmission lines will be
affected, and finally, the entire transmission network collapses.
2. LITERATURE SURVEY
In paper [2], application of PMU for fault location is conducted through a driven algorithm and is
applied to different study systems through computer numerical simulation. The algorithm estimates
the fault location based on synchronized phasors from both ends of the transmission line whether
PMUs are installed to both ends or to only one end and the other end is calculated from synchronized
phasors from another side. This algorithm allows for accurate estimation of fault location irrespective
of fault resistance, load currents, and source impedance. A computer simulation using PSCAD

3. 3
program of the transmission line under study with various fault types and different locations is carried
out. A modal transformation is used in the algorithm. Different fault types are simulated with different
fault locations to more than one line in the Egyptian network, which has PMUs installed according to a
selected allocating technique. The results obtained show high levels of accuracy in locating the fault of
different faults types.
Paper [3] presents a concept of fault-location observability and a new fault-location scheme for
transmission networks based on PMUs. Using the proposed scheme, minimal PMUs are installed in
existing power transmission networks so that the fault, if it occurs, can be located correctly in the
network. The scheme combines the fault-location algorithm and the fault-side selector. Extensive
simulation results verify the proposed scheme.
A new adaptive fault location technique based on PMU for transmission line is presented in [4].
Voltage and current phasors of both terminals of the transmission line are obtained through PMU. The
online parameter-calculation algorithm is adopted to obtain the practical operating parameters when
fault occurs, solving the problems that parameters provided by electric power company is different
from the practical parameters because of the running environment and the operation history. The
suddenly changed voltage and current are utilized to obtain suddenly changed positive voltage and
current components to solve the system’s impedance at the fault time. The on-line calculated system’s
impedance and parameters of the line are employed in the fault location equation and the fault location
accuracy is high. The proposed fault location method is applied in single transmission line, parallel
transmission line as well as teed transmission line. Extensive EMTP simulations as well as practical
system data testing results have shown that the proposed technique accurately locate the fault point
adaptively, not influenced by factors such as operation mode, fault resistance at fault point, fault type,
pre-fault load and fault distance.
Paper [5] and [6] present a new method to find minimum number of PMUs to determine the fault
location of all the transmission network lines. Considering the installation cost of PMUs, it is
important to investigate the placement scheme of the PMUs at minimal locations on the network in the
sense that the fault location observability can be achieved over the entire network. A new algorithm is
introduced to find an optimization problem for determining the place and minimum number of PMUs
in order to find accurate place of any fault in power systems. The accuracy of suggested algorithm is
independent from the fault type and its resistance. Optimization problem is solved by genetic
algorithm method in [5] and branch and bound method in [6]. A real 41-bus 230 kV Tehran
Transmission Regional Electric Network is used to test the method.
In the study conducted under the work of paper [7], a system combining an adaptive PMU based fault
detection/location approach and an adaptive computer network routing algorithm is presented. The
fault detection/location index D, and its factors M and N are also computed to serve as fault detector
and locator simultaneously. The data used to verify the proposed system in the simulation are
generated by EMTP. Hardware errors, system noises are also considered in the simulation. Different
types of fault, different fault resistances, different synchronization errors, various power flow
conditions, and inception angles of the fault occurrence were considered. In the simulation, a 345 kV,
100 kilometers transposed transmission line is simulated. The required computational time is 1-cycle
of the system frequency, which is around 16 ms regardless of delay time caused by communication
network. Because each GPS-PMU device generates data packets to the communication network very
rapidly, higher network traffic loading causes longer transmission delay for the measured data to reach
to the monitoring center. Consequently, the fault detection/location system takes longer time to
calculate the location index D. The cooperative adaptive network routing algorithm is also integrated
with the fault detection/location algorithm to test the response time of the enhanced fault
detection/location system. Various numbers of monitoring nodes with different network topologies
were used in the simulation. The simulation results show that the maximal delay of the communication
network sized 20 nodes was lesser than 2 ms. Even if some links in the communication networks were
suddenly disconnected from the network, the adaptive routing algorithm can converge to another
optimal routing table in the matter of about 25 ms, which provides a very efficient and stable
communication platform for GPS-PMU based fault detection/location algorithm to indicate the
location of the faults in a very short time.

4. 4
A new adaptive fault location technique based on PMU for double circuit transmission lines is
presented in [8]. Voltages and currents of the transmission line obtained through PMU are used for on-
line estimation of line parameters such as line impedance and capacitance. According to the fault
feature of double circuit transmission lines, six-sequence fault component method is employed to
implement fault location for parallel lines. For extremely long transmission lines, distributed
capacitance has great influence on the accuracy of fault location. In the fault location method used, the
distributed capacitance is allocated to the two terminals of the transmission line as lumped parameter
in order to achieve higher accuracy. Extensive EMTP simulation results show that the proposed
algorithm is independent of fault distance, fault type, fault resistance, uncertainty of parameters of
transmission and asymmetry of parallel line.
3. PMU IN POWER SYSTEMS
Phasors are considered as basic tools of ac circuit analysis, usually introduced as a means of
representing steady state sinusoidal waveforms of fundamental power frequency. Even when a power
system is not quite in a steady state, phasors are often useful in describing the behavior of the power
system. For example, when the power system is undergoing electromechanical oscillations during
power swings, the waveforms of voltages and currents are not in steady state, and neither is the
frequency of the power system at its nominal value. Under these conditions, as the variations of the
voltages and currents are relatively slow, phasors may still be used to describe the performance of the
network, the variations being treated as a series of steady state conditions. Recent developments in
time synchronizing techniques, coupled with the computer-based measurement technique, have
provided a novel opportunity to measure the phasors, and phase angle differences in real time. [2]
To shed some light on phasor measurement, let us consider the steady-state waveform of a nominal
power frequency signal as shown in Figure-1. If we start our observation of this waveform at the
instant t = 0, the steady-state waveform may be represented by a complex number with a magnitude
equal to the rms value of the signal and with a phase angle equal to the angle (a).
Figure-1: Phasor representation of a sinusoidal waveform
In a digital measuring system, samples of the waveform for one (nominal) period are collected,
starting at t = 0, and then the fundamental frequency component of the Discrete Fourier Transform
(DFT) is calculated according to the relation:
(1)
where N is the total number of samples in one period, X is the phasor, and Xk is the waveform samples.
This definition of the phasor has the merit that it uses a number of samples N of the waveform, and is
the correct representation of the fundamental frequency component, when other transient components
are present. When the input signal frequency is different from the nominal frequency, an error is
introduced in the magnitude and the phase angle of the phasor. [2]
When several voltages and currents in a power system are measured and converted to phasors in this
fashion, they are on a common reference if they are sampled at precisely the same instant. This is easy
to achieve in a substation, where the common sampling clock pulses can be distributed to all the

5. 5
measuring systems. However, to measure common-reference phasors in substations separated from
each other by long distances, the task of synchronizing the sampling clocks is not a trivial one. Over
the years, recognizing the importance of phasors and phase angle difference measurements between
remote points of a system, many attempts have been made to synchronize the phasor measurements.
None of these early attempts were too successful, as the technology of the earlier era is very limited on
what could be accomplished. It is only in recent years that the technology has reached a stage,
whereby we can synchronize the sampling processes in distant substations economically, and with an
error of less than 1 µs which translates into 0.021o
for a 60 Hz system and 0.081o
for a 50 Hz system
and is certainly more accurate than any presently conceived application would demand. [2]
Synchronized signals could be distributed over any of the traditional communication media being used
in power systems. Most communication systems, such as leased lines, microwave, or AM radio
broadcasts, place a limit on the achievable accuracy of synchronization, which is too coarse to be of
practical use. Fiber-optic links, where available, could be used to provide high-precision synchronized
signals, if a dedicated fiber is available for this purpose. If a multiplexed fiber channel is used,
synchronization errors of the order of 100 µs are possible, and are not acceptable for power system
measurements. GOES satellite systems have also been used for synchronization purposes, but their
performance is not sufficiently accurate. The technique of choice at present is the GPS satellite
transmissions. This system is designed primarily for navigational purposes, but it furnishes a common-
access timing pulse, which is accurate to within 1 µs at any location on earth. [2]
Since the introduction of PMUs in mid-1980s, the subject of wide-area measurements in power
systems using PMUs and other measuring instruments has been receiving considerable attention from
researchers in the field. PMUs using synchronization signals from the GPS satellite system have
evolved into mature tools and are now being manufactured commercially. Figure-2 shows a functional
block diagram of a typical PMU. The GPS receiver provides the 1 pulse-per-second (pps) signal, and a
time tag, which consists of the year, day, hour, minute, and second. The time could be the local time,
or the UTC (Universal Time Coordinated). The l-pps signal is usually divided by a phase-locked
oscillator into the required number of pulses per second for sampling of the analog signals. In most
systems being used at present, this is 12 times per cycle of the fundamental frequency. The analog
signals are derived from the voltage and current transformer secondary sides. The microprocessor
determines the positive sequence phasors according to the recursive algorithm given by (1), and the
timing message from the GPS, along with the sample number at the beginning of a window, is
assigned to the phasor as its identifying tag. The computed string of phasors, one for each of the
positive sequence measurements, is assembled in a message stream to be communicated to a remote
site. [2]
Now, let us consider the problem of measuring the positive sequence voltages at two substations
separated by many miles. If the data samples used at the two stations were synchronized precisely, and
the absolute time of the sampling process recorded, then one could send the measurement to a remote
location with the accompanying time stamp, and by aligning the time stamp of the measurements
obtained from different stations one would obtain simultaneous positive sequence measurements very
few cycles. [2]
Figure-2: Phasor measurement unit block diagram

6. 6
Synchronized phasor measurements have become a practical proposition. As such, their potential for
use in power system applications has not yet been fully realized. Below are some potential
applications of PMUs in power system [2]:
 Instability prediction
 Adaptive relaying
 State estimation
 Measuring frequency and magnitude of phasors
 Improved control
 Fault recording applications
 Disturbance recording applications
 Transmission and generation modeling verification applications
 Wide Area Protection
 Fault location
In section-5, application of PMU for fault location in power systems will be discussed in details.
4. PMU PLACEMENT USING TREE SEARCH METHOD
PMU placement is the art of connecting bus-bars of the electrical power network to make use of a
universal space monitoring communication system in control and protection. PMU placement in each
substation allows direct measurement of the state of the network. However, a ubiquitous placement of
PMUs is rarely conceivable due to cost and/or non-existence of communication facilities in some
substations. [9]
Many techniques have been applied to solve the PMU placement problem in power systems. Examples
include genetic algorithm, tabu search, simulated annealing, linear programming, particle swarm and
tree search method (TSM). Interested reader may refer to [9] for more details on TSM and the concept
of system unobservability level.
Two IEEE standard systems have been selected, namely 14-bus and 57-bus IEEE test systems. Table-1
summarize the simulation results obtained when TSM was applied for these two systems. Simulation
output is just the set of buses at which a minimum number of PMUs shall be installed so that the
desired depth of system unobservability is satisfied. In all the simulations made for these two systems,
the desired unobservability depth is considered as 1 and all buses are assumed to have the necessary
communication facilities.
Power System
PMU allocation Using TSM
Number Location
IEEE 14-bus 2 6, 4
IEEE 57-bus 8 3, 13, 23, 25, 29, 34, 36, 45
Table-1: PMU Placement for IEEE systems using TSM
An interconnected system depicted from the Saudi Electricity Company (SEC) network in the Eastern
region has been selected. The system's base MVA and base voltage are considered as 100 MVA and
115 kV respectively. Figure-3 shows the one line diagram of this system. The system consists of 38
substations and 39, 115 kV transmission lines with an approximate total length of 500 kilometers.
Bus-1, 17, 21 and 38 are considered as generation buses. TSM was applied to this system and
simulation results are shown in Table-2.
Power System
PMU allocation Using TSM
Number Location
SEC System 7 5, 9, 27, 30, 34, 35, 36
Table-2: PMU Placement for 115 kV SEC system using TSM

7. 7
1
2
3
4
5
6
7 8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
3435
36
37
38
Figure-3: One line diagram of 115 kV SEC depicted system
5. PMU FOR FAULT LOCATION
In this section, application of PMU for locating faults in power systems will be discussed. The
numerical simulation results obtained using both PSCAD/EMTDC and MATLAB to determine the
location of different types of faults assumed to occur in the 115 kV SEC system will then be
presented.
5.1 Theory
Based on [2] we shall now present a concept of fault-location observability and a fault-location
scheme for transmission networks based on synchronized PMUs. Using this scheme, minimal PMUs
are installed in existing power transmission networks so that the fault, if it occurs, can be located
correctly in the network. The scheme combines the fault-location algorithm and the fault-side selector.
The three-phase synchronized phasors of voltages and currents are measured simultaneously by
PMUs. The phasor quantities are then decoupled into sequence components using symmetrical
transformation and the symmetrical components are used as the input data for further computations.
The fault-location algorithm developed here is based on symmetrical components of voltages and
currents rather than directly using phase values since the former allows the three-phase system to be
treated like three single circuits.
Since the fault detector can not discriminate the true fault side between line (i) and line (k), two
identical subroutines (subroutine1 and subroutine 2) are used to calculate the fault location in line (i)
and line (k), respectively. Then, the proposed fault-side selector is used to identify the correct fault
side and fault location. Finally, the correct fault side and fault location are confirmed and displayed to
operators.
Figure-4: Faulted transmission line with PMUs installed
For the sub-network in Figure-4 above, three phase voltages (Vk & Vi) and currents (Iij & Ikj) of buses i
& k are obtained from the PSCAD/EMTDC simulator. The phasor quantities are then decoupled into

8. 8
modal components using Karrenbauer transformation and the modal components are used as the input
data for further computations to calculate the voltage and current of bus j from the following
equation:
(2)
where; Zi is line i impedance per unit length
(3)
(4)
Assuming Ijk equals Iij as shown in Figure-4, then equation (4) will be:
(5)
Subtracting equations (3) and (5), we get:
(6)
Hence the fault distance from bus k is:
(7)
Calculating the distance from the other side, that is to say from bus i, the distance will be calculated
from the following equation
(8)
And since Iij = - Iji, therefore the distance is infinity as we divide by zero. This case gives "no answer".
Karrenbauer modes (0, 1 and 2) are obtained using the following transformation:
(9)
(10)
5.2 Numerical simulation
SEC 115 kV system was represented in PSCAD/EMTDC and different types of faults assumed to take
place along the line connecting bus-38 to bus-30 and various distances from bus-38. Figures 5 to 8
show phase voltages and currents of the system at steady state. Figures 9 to 12 show sample results
obtained for a line to line fault occurred 5 km from bus-38.
SEC-EOA 115 kV System- Steady State
0.050 0.060 0.070 0.080 0.090 0.100
-120
120
y
Vabua Vabub Vabuc
SEC-EOA 115 kV System- Steady State
0.050 0.060 0.070 0.080 0.090 0.100
-120
120
y
Vsha Vshb Vshc
Figure-5: SS phase voltages of bus-29 Figure-6: SS phase voltages of bus-38

9. 9
SEC-EOA 115 kV System- Steady State
0.050 0.060 0.070 0.080 0.090 0.100
-0.200
0.200
y
Iahjsa Iahjsb Iahjsc
SEC-EOA 115 kV System- Steady State
0.050 0.060 0.070 0.080 0.090 0.100
-0.400
0.400
y
Ishjsa Ishjsb Ishjsc
Figure-7: SS phase currents from bus-29 to bus-30 Figure-8: SS phase currents from bus-38 to bus-30
SEC-EOA 115 kV System
0.050 0.060 0.070 0.080 0.090 0.100
-120
120
Vabua Vabub Vabuc
SEC-EOA 115 kV System
0.050 0.060 0.070 0.080 0.090 0.100
-120
120
Vsha Vshb Vshc
Figure-9: Phase voltages of bus-29 Figure-10: Phase voltages of bus-38
SEC-EOA 115 kV System
0.050 0.060 0.070 0.080 0.090 0.100
-0.200
0.200
Iahjsa Iahjsb Iahjsc
SEC-EOA 115 kV System
0.050 0.060 0.070 0.080 0.090 0.100
-35.0
35.0
Ishjsa Ishjsb Ishjsc
Figure-11: Phase currents from bus-29 to bus-30 Figure-12: Phase currents from bus-38 to bus-30
Table-3 below summarizes the results obtained. It shall be noted that the average distance is the
average of D0, D1 and D2. Also, the percentage error is calculated using the following equation:
(11)
Type of
fault
Actual fault
location from
bus-38
D0 (km) D1 (km) D2 (km)
Average
distance
(km)
Error (%)
3Ф
5
5.0037 4.9972 5.00045 0.0017
LG 4.7785 5.0247 5.2044 5.0025 0.0097
LLG 4.7788 5.2649 4.9728 5.0055 0.0211
LL 5.3644 4.6811 5.0227 0.0875
3Ф
10
10.0087 9.9889 9.9988 0.0046
LG 9.6790 9.9634 10.3502 9.9975 0.0094
LLG 9.6796 10.4585 9.8766 10.0049 0.0189
LL 10.6870 9.3880 10.0375 0.1442
3Ф
15
15.0124 14.9799 14.9962 0.0148
LG 14.5927 14.9035 15.4739 14.9900 0.0383
LLG 14.5932 15.6298 14.7931 15.0054 0.0206
LL 15.9773 14.1354 15.0564 0.2167
3Ф
20
20.0150 19.9708 19.9929 0.0273
LG 19.5211 19.8462 20.5768 19.9814 0.0717
LLG 19.5217 20.7767 19.7200 20.0061 0.0236
LL 21.2304 18.9198 20.0751 0.2888
Table-3: Calculation of fault distance

10. 10
6. CONCLUSION
It can be seen from the simulation results that the applied method was very accurate in determining the
fault location as the percentage error was less than 0.3 %. The minimum error recorded was for the
case of three-phase fault and the maximum was for the case of line-to-line fault. For most of the cases,
it was found that the percentage error increases as the fault distance increases but the error remains
within very much acceptable limits.
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