1.
APPLICATIONS OF
GPS IN POWER
ENGINEERING

2.
What is GPS?
 GPS or Global Positioning Systems is a highly
sophisticated navigation system developed
by the United States Department of Defense.
This system utilizes satellite technology with
receivers and high accuracy clocks to
determine the position of an object.

3.
Global Positioning Systems (GPS) Applications
in Power Systems

4.
Power companies and utilities have
fundamental requirements for time and
frequency to enable efficient power
transmission and distribution.
Repeated power blackouts have
demonstrated to power companies the need
for improved time synchronization
throughout the power grid. Analyses of
blackouts have led many companies to
place GPS-based time synchronization
devices in power plants and
substations

5.
Why GPS For power Eng
It furnishes a common-access timing pulse
which is accurate to within 1 microsecond at any
location on earth.
A 1-microsecond error translates into 0.021°
for a 60 Hz system and 0.018 ° for a 50 Hz
system and is certainly more accurate than
any other application

6.
GPS time synchronization
By synchronizing the sampling processes for
different signals – which may be hundreds
of kilometers apart – it is possible to put
their phasors in the same phasor diagram

7.
V
V
V1
V2
Substation 1
Substation 2
t1 t2 t3 t4 t5 t6 t7
GPS time synchronized
pulses
V1
V2
Ψ
FFT or any other
technique gives:
•Magnitude
•Phase angle
With respect to GPS
GPS time synchronization

8.
Absolute Time Reference
Across the Power System

9.
Synchronized phasor
measurements (SPM) have
become a practical
proposition.
As such, their potential use in
power system applications has
not yet been fully realized by
many of power system engineers.
Phasor Measurement Units PMUs

10.
Phasor Measurement Units
(PMU)
[or SYNCHROPHASORS]

11.
Phasor Measurement Units
)PMU)
They are devices which use
synchronization signals from the
global positioning system (GPS)
satellites and provide the phasor
voltages and currents measured at a
given substation.
Phasor Measurement Units PMUs

12.
Secondary
sides of the
3Φ P.T. or
C.T.
Corresponding
Voltage or
Current phasors
input output
PMU
Phasor Measurement Units PMUs

13.
Sampling at Fixed Time Intervals Using an
Absolute Time Reference
Time
Synch
GPS
Clock
A/D
LPF
Synchronized
Phasor
¦s
v

14.
The GPS receiver provides the 1 pulse-per-
mcrsecond (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's.

15.
The Birth of the PMUs
 Computer Relaying developments in 1960-70s.
ABB

16.
 Now
RES 521
SEL-421
ABB

17.
Phasor Measurement Unit’s

18.
central data
collection
Phasor Measurement Units PMUs

19.
CONCLUSIONS AND FUTURE WORKS
 thanks to GPS for their multiple advantages,
nowadays, the technologies based on synchronized
phasor measurements have proliferated in many
countries worldwide (USA, Canada, Europe, Brazil,
China, Egypt !,..).
 up to now most applications based on synchronized
phasor measurements have concerned mainly off-line
studies, on-line monitoring and visualization, and to a
less extent the real-time control, Protection, and the
emergency control.
19

20.
Off-line SPM-based applications
 software simulation validation
 SPM-based technologies can be very useful to help the validation of
(dynamic) simulation software
 system parameter/model identification (e.g. for loads, lines,
generators, etc.)
 the identification of accurate model/parameter is a very important
and tough task for the power system analysis and control.
 difficulty: large number of power system components having time-
varying characteristics.
 synchronized disturbances record and replay
 this task is like that of a digital fault recorder, which can memorize
triggered disturbances and replay the recorded data if required.
 the use of SPM allows more flexibility and effectiveness.
21

21.
Real-time monitoring SPM-based applications
 fault location monitoring
 accurate fault location allows the time reduction of maintenance of the transmission
lines under fault and help evaluating protection performance.
 power system frequency and its rate of change monitoring
 the accurate dynamic wide-area measured frequency is highly desirable especially in the
context of disturbances, which may lead to significant frequency variation in time and
space.
 generators operation status monitoring
 this function allows the drawing of generator (P-Q) capability curve.Thus, the generator
MVAr reserve, can be supervised.
 transmission line temperature monitoring
 the thermal limit of a line is generally set in very conservative criteria, which ignores the
actual cooling possibilities.The use of SPM allows the higher loading of a line at very low
risk.
 on-line "hybrid" state estimation
 the SPM can be considered, in addition to those from the RemoteTerminal Units (RTU)
of the traditional SCADA system, in an on-line "hybrid" state estimation.
 SPM-based visualization tools used in control centers
 display: dynamic power flow, dynamic phase angle separation, dynamic voltage
magnitude evolution, real-time frequency and its rate of change, etc.
22

22.
Real-time (emergency) control SPM-based applications
 automatic (secondary and tertiary) voltage control
 aim: optimize the var distribution among generators, controllable ratio transformers
and shunt elements while keeping all bus voltage within limits.
 in the context ofWAMS application, the solution of this optimization problem can be
used to update settings of those reactive power controllers, every few seconds.
 damping of low frequency inter-area oscillations (small-signal angle
instability)
 low frequency inter-area oscillations (in the range of 0.2 – 1 Hz) are a serious concern in
power systems with increasing their size and loadability.
 In Europe, in particular, many research studies have been performed to reveal such
oscillations as well as provide best remedial actions to damp them out.
 transient angle instability
 since such instability form develops very quickly, nowadays, Special Protection Systems
(SPS), also known as Remedial Action Schemes (RAS), are designed to act against
predefined contingencies identified in off-line studies while being less effective against
unforeseen disturbances.
23

23.
Real-time (emergency) control SPM-based applications (cont’d)
 short- or long-term voltage instability
 a responde-based (feedback)Wide-Area stability and voltage Control System (WACS) is
presently in use by BPA.
 this control system uses powerful discontinuous actions (switching on/off of shunt
elements) for power system stabilization.
 frequency instability
 the underfrequency load shedding has its thresholds set for worst events and may lead
to excessive load shedding.
 new predictive SPM-based approaches are proposed aiming to avoid the drawbacks of
the conventional protection.
24

24.
Conclusions:
• A new modified DPSO technique is developed to determine the
optimal number and locations for PMUs in power system
network for different depths of unobservability. It gives the
optimal PMUs' allocation for different depths of unobservability
comparable to other techniques
• The developed DPSO is tested on both 14-bus and 57-bus
IEEE standard systems.
• For small power systems, DPSO gives either equivalent or
better results. However for large power systems, it gives
almost better locations and sometimes less number of PMUs
for large power systems.
• DPSO determines the optimal PMUs' allocation for complete
observability of the large system depicted from the Egyptian
unified electrical power network.
A- Discrete Particle Swarm Optimization Technique:

25.
Conclusions (continued):
• The phasors readings of PMUs are taken into consideration in a
new hybrid state estimation analysis to achieve a higher
degree of accuracy of the solution.
• The effect of changing the locations and numbers of PMUs
through the buses of the power network on the system state
estimation is also studied with a new methodology.
• The hybrid state estimation technique is tested on both 14-bus
and 57-bus IEEE standard systems. It is also applied to a large
system depicted from the Egyptian unified electrical power
network.
• PMUs' outputs affect the state estimation analysis in a precious
way. It improves the response and the output of the traditional
state estimation.
B- Hybrid State Estimation Technique:

26.
Conclusions (continued):
• The locations of PMUs according to state estimation
improvement do not need to be similar to those locations
according to observability depth.
• The system parameters, system layout and power flow affect
the PMUs' positioning for optimal state estimation.
• For each system there is a certain number of PMUs with
certain connections that reduces the estimation error
significantly. As the number of PMUs' increases over the
optimal solution, the estimation analysis begins to magnify the
measurements error of the other devices.

27.
Conclusions (continued):
• The readings of the allocated PMUs are to be utilized using a
newly developed technique for on-line voltage instability
alarming predictor.
• The predictor gives two types of alarms, one for voltage limit
violation (10% voltage decrease) and the other for voltage
collapse prediction according to the maximum permissible
angle difference between bus voltages for certain bus loading
angle.
• The time taken by the alarming predictor is small, and is
determined by the speed of PMUs and the used computational
system.
• The voltage instability alarming predictor concept is tested on
both 14-bus IEEE standard system. It gives effective results.
• The alarming predictor is applied to the large system depicted
from the Egyptian unified electrical power network, with the
aid of the voltage instability limits calculation of the system.
C- On-line Voltage Instability Alarming Predictor: