42839874 improve-reliability-using-phasor-measurement-units-for-smart-grid-sajal-jain
Post on 12-May-2015
992 Views
Preview:
TRANSCRIPT
Page | 1
Improve Reliability Using Phasor Measurement
Units for Smart Grid Sajal Jain, 9028‐65‐4127, USC Viterbi School of Engineering
EE‐444 Power System Technology
Abstract
For the transmission and distribution system to become more affordable, reliable and
sustainable the grid needs to become smarter. During the past few years a considerable
number of activities have been carried out in United States to achieve a smart power grid.
Smart Grid is envisioned to use all present technologies in transforming grid intelligently in
better situational awareness and operation friendliness. At the same time blackouts in past
and reliability of grid are major issues for system engineers. This paper describes a system to
improve the security of grid against false faults and load swing. This system called,
the Phasor Measurement Unit (PMU) is an important and promising technology in making the
future grid smarter.
1. INTRODUCTION
The society depends on reliable electricity as an essential source for security, health and
welfare; communication, finance, transportation, food, water supply, heating, cooling, leisure,
computers, entertainment, education, and almost every aspect of life we could think of. People
always expect that electricity will be available when they flick on the switch. But providing
electricity with high reliability is a tough challenge with so many components and unseen
conditions. After generation of electricity, it requires a reliable, efficient and affordable
transmission system to deliver power from utility to customer.
The electricity is generated at lower voltages of about 10KV to 25KV from various sources of
generation and then stepped up to high voltage of 230KV and above for transmission to reduce
losses, transmit bulk power reliably and economically over long distances. The transmission
lines a
Fig1 Basic
of power
voltage g
to lower
residenti
Fig2 Trans
Thou
transmis
being tra
cost. The
are interco
Structure of E
r carrying lin
grid transmis
r voltages d
al (120V to 2
mission System
gh the elec
sion facility
ansmitted p
e consequen
onnected
lectric System
nes which ar
ssion lines. A
epending on
240V) and d
m Investment
tric demand
construction
er line whic
nces of these
at variou
re called as
After electri
n the sourc
istributed to
over time
d in United
n is decreas
ch creates g
e bottleneck
s switchin
grid. United
city reaches
e it has to
o customers
States has b
ing at about
rid congesti
ks become la
ng points
d States has
s its destinat
feed i.e. in
.
been increa
t 30%. Thus
on, less reli
arge and ma
to form
about 157,0
tion it is aga
dustrial (12
sing at 25%
this results
ability and
ay cause loss
Pag
m a net
000 miles of
in stepped d
KV to 115KV
% since 1990
into more p
higher elect
s of grid stab
ge | 2
twork
f high
down
V) or
0, the
ower
tricity
bility,
Page | 3
lose of power, loss of communication, etc. This situation is known as blackout or rolling
blackout.
2. BLACKOUTS
The cascading failures in a power system which result in the loss of power over a region for
considerable duration of time are referred as blackout. These have a major direct and indirect
impact on the economy and national security. Although large cascading blackouts are relatively
rare, their impact on the system results into such a high risk that it becomes necessary to
mitigate and avoid them in the best possible way.
There has been number of blackouts in United States over the time which resulted in new
transmission policies for reliability improvement every time. The major blackouts and their
causes and impact were:
2. a. November 9, 1965
One of the five 230KV line operating from Beck plant in Ontario to the Toronto area
went down due to operation of a backup protection relay. While distribution of power on the
four remaining lines, they started tripping every 2.5 seconds resulting into huge power swing
and cascading outage. It blacked out almost entire northeast affecting around 30 million
people’s life. It took about 13 hours to bring back the power for the entire region.
2. b. July 13, 1977
This blackout though concentrated to the New York City only but has major impact on
the economy and security of the people. It triggered from a total collapse of two 345 KV lines
on a common tower struck by lighting and tripping off. The utility dispatcher tried to save the
system over the next hour, but the system collapsed and resulted into blackout which affected
9 million New York City residents and lasted for about 26hrs.
2. c. July 2, 1996
In the summer of 1996 in the Western North America a line to ground fault due to a tree
resulted into flashover of a 345KV line. The protective systems detected the fault and operated
to de‐energize the line, but due to faulty operation of protective relay on a parallel transmission
line it de‐energized a second line. The loss of 2 lines from the system reduced the ability of
Page | 4
system to carry the power from generating station to load causing shut down of two out of four
generating units at the plant. This resulted into unbalance between load and supply and
frequency begin to decline. The system became unstable, automatic protection systems
initiated and outages occurred for few customers to save the entire system. It affected around
2 million customers and took from few minutes to several hours for completely re‐energizing
the system.
2. d. August 10, 1996
In the same summer of 1996 another blackout occurred. This time the system triggered
from random transmission line outages, resulting into system instability causing four electric
islands in western interconnection. It is believed that before the event the lines were heavily
loaded due to extreme demand caused by hot weather day throughout most of the western
region and also because of high electric transfers from Canada into northwest to California as
the hydroelectric plants were working in excellent condition. Again due to trees touching the
lines multiple short circuits occurred on 500kv lines resulting into cascading outages due to
overloads. It was also discovered the operators had done the adequate operating studies. It
affected around 7.5 million customers and lasted for about 9 hrs.
2. e. July 25, 1998
The blackout triggered from a lightning striking a 345KV line in Minnesota and initiating
system protection to de‐energize the line. This resulted into overloading of the low voltage lines
in the region, but the lightning struck another 345KV line and protective system de‐energized it
too. This resulted into extreme overloading of lower voltage transmission lines and system
protection began removing them from service. The cascading removal of lines continued and
entire northern MAPP region formed three islands, resulting into blackout of the northwestern
Ontario Hydro system. It affected around 152 thousand people and lasted for about 19 hrs.
2. f. August 14, 2003
The biggest blackout in the history of Northern America resulted into shutting down of 508
generating units in 265 power plants across the north east. 50 million people not only in US but
Canada too were left without electricity. It is believed that due to very high electric demand a
generating unit in Eastlake, Ohio went offline putting strain on HV transmission lines. But again
Page | 5
short circuits occurred due to overgrown trees, resulting into cascading effects ultimately
forcing to shutdown many power plants. The various direct causes and contributing factors
included:
o Failure to maintain adequate reactive power support
o Failure to ensure operation within secure limits
o Inadequate vegetation management
o Inadequate operator training
o Failure to identify emergency conditions and communicate that status to neighboring
systems
o Inadequate regional‐scale visibility over the bulk power system.
The various reports on blackouts have shown that these blackouts were preventable. Most
of the instances due to inefficiency of the system and operator to respond in such a short
period for multiple cascading effects have been the reason. Though after 1965 blackout several
regulations and recommendations were made to prevent similar situation to arise in future, still
August 2003 blackout has many similarities to the earlier ones.
For improvement of the reliability of the system we require comprehensive monitoring of
the system, training and enforcement of standards within the system, so that it could response
to critical situation, earliest possible over a larger area in the shortest possible time period with
minimum human interference required.
3. SMART GRID
According to “The Smart Grid: An Introduction” publication by US Department of Energy’s
Office of Electricity Delivery and Energy reliability, A smarter grid applies technologies, tools and
techniques available now to bring knowledge to power‐ knowledge capable of making the grid
work far more efficiently
Ensuring its reliability to degree never before possible
Maintaining its affordability
Reinforcing our global competitiveness
Page | 6
Fully accommodating renewable and traditional energy sources
Potential reducing our carbon footprint
Introducing advancements and efficiencies yet to be envisioned
It is a technology that will force the Utilities and suppliers to redesign the electric grid and
rethink its operations. It will enable to deliver electricity to the consumer from supplier using
the complete power system with ability to save energy, improve efficiency, quality and
reliability and reduce consumer cost. It will enable distributed generation grid connection, grid
energy storage for distributed generation load balancing and containing failures due to
widespread power grid cascading failures by using advanced sensing, information technology,
networks, communication techniques, control, transport and distribute electricity.
Fig3 Basic Smart Grid Ingredients
Page | 7
4. PHASOR MEASUREMENT UNITS
4.1 INTRODUCTION
A phasor is a complex number used to determine magnitude and relative angle for a voltage
and current waveform. A phasor measurement unit (PMU) also known as Synchrophasor, is a
device which in addition to voltage and current phasors can also measure simultaneously and
synchronize the associated frequency and electric power. The measurements are synchronized
through Global Positioning Satellite (GPS) using one pulse per second (1pps) as the reference.
Fig4 Phasor representation of a sinusoidal signal (a) Sinusoidal signal (b) Phasor representation
The sinusoidal waveform is represented as
x(t) = Xm cos(ωt + φ)
Then the phasor representation of the signal is given by
X = Xm/sqrt (2)*e‐jφ = Xm/sqrt (2)*(cosφ + j sinφ)
It can be noted that signal frequency ω is not states in the phasor representation. Thus the
phasor implies a stationary sinusoidal waveform. PMUs use a data window which is one period
of fundamental frequency of input signal. If the system frequency deviates PMUs uses a
frequency tracking and separate the fundamental frequency and its phasor representation.
A synchrophasor infrastructure consists of 3 layers:
1. Measurement Layer, made up of PMUs connected at transmission voltage level
Page | 8
2. Data Collection Layer, made up of phasor data concentrators to collect and synchronize
data
3. Application Layer, made of tools of PMU data for grid operators and offline analysis.
Fig5 A Representative Synchrophasors Infrastructure
4.2 APPLICATIONS
a. Power System Monitoring
Presently system is monitored using state estimator software based on models and data from
Supervisory Control and Data Acquisition (SCADA) to find out voltage magnitude and angles.
These are measured in intervals of several seconds. But with PMUs instead of estimating actual
measuring of system state could be done. The real time monitoring and time synchronization
will continuously analyze operating conditions and inform the operators about stressed grid.
Dynamic system models could be improved by detecting and analyzing inter‐area oscillation
modes and can further be used to fine tune and optimize existing system stabilizers.
Page | 9
b. Power System State Estimation
Prior to PMUs state could not be measured but just inferred using unsynchronized power flow
measurements. But now state estimation algorithms use measurements of line flows and
injections, both real and reactive power, to estimate all bus voltages and magnitude. It
improves the accuracy and robustness of bad data, faster solutions to linear system problems,
and availability of data on external network. Also PMU derived state estimation provides
possibility for 3‐phase or 3‐sequence state estimator to monitor phase unbalance due to
grounding or equipment degradation.
c. Power System Event Analysis
PMUs provide high resolution data for dynamic event analysis. Earlier data recorders and
loggers didn’t have time synchronization, making the job of understanding and reconstructing a
timeline of what happened very difficult and time consuming. But with PMUs and GPS
coordination troubleshooting time can cut down from few hours to few seconds. NERC
reported that data recorded by PMUs during 2008 Florida event helped the event analysis
tremendously.
d. Line Parameter Calculation
PMU data from ends of line can be used to calculate actual line parameters. It helps in verifying
design data based on line geometry. Line parameter monitoring and calculation continuously
can help in modeling the changes line parameter with external factors line is exposed to.
e. Real Time Congestion Management It is done to maintain real time flow across transmission lines and paths within reliable transfer
capabilities. It is an important function to manage demand in an economic manner without
challenging transmission limits. For congestion management actual flow on a line is compared
to nominal transfer capability (NTC) of the line which is pre‐calculated. This pre‐calculations
have limitation of thermal factors, voltage and stability conditions. The assumptions for NTC are
Page | 10
conservative and can result in excessive margins in congestion management. But with PMUs
highly accurate meter data in real time conditions, calculations for path limit and path flow
improves highly. The high speed real‐time algorithms provide Real Time Transfer Capability
(RTC) limits with critical stability and voltage paths.
f. Power System Protection Distance relays zone 3 or backup protections many time trips due to load encroachment during
power system disturbances. This forces protection engineers to remove backup zone, essential
for downstream protection in case of failure of protection system to remove a fault. But PMUs
avoid false failure by back up zone supervision. PMUs uses wide area measurements for
restraining back up relays to operate in case of power or load swing but coordinating with other
PMUs data and discriminating load swing and fault
g. Adaptive Protection Conventional protection system responds to faults in a predetermined manner irrespective of
the prevailing system conditions. Adaptive relaying assumes that system characteristics and
protection parameters should be coordinated according to prevailing conditions. PMUs
application for adaptive protection with out of step relays and line relays provide better
security and dependability. PMUs have much accurate measure of line impedance for actual
fault location. PMU uses data from both ends of the transmission line for fault calculation.
h. Power system Control Prior to introduction of PMUs the system control was set up locally. Many subsystems like
machines only had local control signals. But with the advent of Synchrophasors the remote
control based upon measured quantities has taken place. A time tag is associated with the
phasor data so that control of the system based on past conditions can be calculated. The
frequency of measurements every 15–60Hz i.e. 1‐4 times per second handles the control task
efficiently.
Page | 11
5. CONCLUSION
It is believed that smart grid compared to present transmission grid is something like
supercomputers are to abacus. It is more than just a power grid, with two way communication
and information technology being an integral part of it. It offers higher challenges to system
protection engineers for enhanced reliability of the grid with new standards and regulations.
Phasor measurement units have been a state of art tool that has proven its worth in solving
existing problems and better understanding of the power system. For implementation of
phasor measurement technology by utilities, identification and selection of applications
suitable for the benefit of the individual system and the interconnected grid is a must.
It is believed PMU technology is likely to be implemented initially for:
a) validation of system models, and
b) accurate postmortem analysis.
Then with experience in PMU data and real time operation, much more complex state
estimation algorithms for energy and system management could be developed. Ultimately, the
goal is to improve protection and control functions and eliminate catastrophic failures or
reduce severity of such failures from the future of power system.
Page | 12
6. REFERENCES
1. “Grid 2030: A National Vision for Electricity’s Second 100 Years”, July 2003 by United
States Department of Energy office of Transmission and Distribution
2. “The Smart Grid: An Introduction” prepared for the U.S. Department of Energy by Litos
Strategic Communication
3. “National Transmission Grid Study”, May 2002 by U.S. Department of Energy
4. “Examples of major bulk electric system power outages”, NERC website documents
5. "Final Report on the August 14, 2003 Blackout in the United States and Canada: Causes
and Recommendations," U.S.‐Canada Power System Outage Task Force, April 5, 2004
6. Farhangi, H, “The path of the smart grid” IEEE Power and Energy Magazine Volume 8
Issue 1, January‐February 2010
7. De La Ree, J. Centeno, V. Thorp, J.S. Phadke, A.G., “Synchronized Phasor Measurement
Applications in Power Systems” IEEE Transactions on Smart Grid Volume 1 Issue 1 June
2010
8. Bhatt, N.B., “Role of Synchrophasors Technology in Development of a Smarter
Transmission Grid” IEEE Power and Energy Society General Meeting 2010, 25‐29 July
2010
9. Skok, S. Ivankovic, I. Cerina, Z., “Applications Based on PMU Technology for Improved
Power System Utilization” IEEE Power Engineering Society General Meeting 2007, 24‐28
June 2007
10. Tholomier, D.; Kang, H.; Cvorovic, B., “Phasor Measurement Units: Functionality and
Applications”, Power Systems Conference, 2009. PSC '09, 10‐13 March 2009
top related