WIDE
protection and monitoring
As interconnected power system size grew over the years, the magnitude of system-wide disturbances in power systems
grew as well. Protection and control actions are needed to arrest the propagation of large power disturbances, stop
the power system degradation and restore the system to a normal state. Control centers have the obligation to act,
AREA
with limited information, on a very complex situation and often use heuristics and pre-defined procedures to be able
to normalize the situation quickly. Local protection systems, which only rely on locally available measurements, are not
capable to protect the entire power system.
Miroslav Begovic, Georgia Institute of Technology, USA
by Miroslav Begovic, Georgia Institute of Technology, USA
Wide Area Protection
cover story
20
Miroslav Begovic
is Professor in the
School of Electrical and Computer
Engineering at
Georgia Institute
of Technology,
Atlanta.
He received his
BSEE and MSEE
from Belgrade
University and
PhDEE from
Virginia Tech
University. Miroslav
is a Fellow of IEEE,
a member of the
Power System
Relaying and
Dynamic
Performance
Committees,
and serves in
different IEEE leadership positions.
Development of new SIPS
will provide for superior
management of system
disturbances.
Oper ating on tight margins and with less
redundancy, power systems are sometimes just a
couple of unexpected (and unlikely) contingencies away
from a blackout, as the experience from the years past has
repeatedly shown. Transformation of power networks into
modern structures makes them harder to protect, through
addition of non-utility generators, heavy tie line transfers in
a growingly competitive environment, and deployment of
fast control devices. The need is great for automated systems
with advanced monitoring and better real-time interfaces for
operator interactions. Advancements of measurement devices
and communication technology in wide-area monitoring and
controls, FACTS devices, and new procedures provide for
more efficient ways to detect and control large disturbances.
System integrity protection scheme (SIPS) is a concept
of using local as well as selected remote measurements and
sending the necessary system information to a processing
location to formulate the emergency control and protective
actions for the power system. With new technologies,
more "intelligent" equipment is deployed at the local level
to formulate an efficient response to ongoing disturbances.
Traditional contingency / event based remedial action
systems can be made to act with proper local supervision for
security.
Decentralized subsystems make local decisions based on
local measurements and assorted remote information. They
can send pre-processed information to higher hierarchical
levels. A major feature of the SIPS is their ability to receive
remote information and commands and to send selected local
information to the other locations in the system.
Modern Protection Infrastructure
Experience reveals similar patterns in genesis of such
disturbances. Among common causes are:
Unfavorable pre-existing conditions (i.e. generator/line
maintenance)
Tendency of cascading overloads to spontaneously
develop under heavily loaded, contingency-challenged system
conditions
Inadequate VAr support
Poor right-of-way maintenance
Incomplete or misleading alarms
Inability of operators to respond due to the lack of
training or limitations of resources at their disposal
Inadequate planning/operation studies
Unavailability of automated actions to initiate
appropriate response, such as automatic and pre-planned
separation of the power system
PAC.AUTUMN.2009
While it is not practically possible to completely eliminate
blackouts, with reasonable means probability of the blackouts
could be substantially reduced.
Improved communication facilities and better data
handling capability have greatly enhanced modern SCADA/
EMS systems. Availability of critical functions of 99.99%
or better is expected for reliable system operation. Alarm
monitoring systems should always be in top operating
condition. New alarm processing techniques should be
deployed to deal with the avalanche of data during major
disturbances.
Phasor measurement units (PMUs) and high bandwidth
and high-speed communication networks can provide
time-tagged measurements from the entire system, enabling
improved, faster and more accurate state estimators.
Development of SIPS may provide for superior management
of system disturbances. Those schemes are designed to
operate on pre-planned, automatic corrective actions, as a
result of system studies. The primary goal of SPS schemes
is to improve security of the power system. Periodic studies
should be done and protection designs reviewed to prevent
misoperation. As a tradeoff between dependability and
security, designers can increase the security of protection
design in the areas vulnerable to blackouts. As an example,
transmission line pilot protection Permissive Overreach
Transfer Trip scheme (POTT), which is more secure, could be
used instead of the more dependable Directional Comparison
Blocking (DCB).
Design and Architectures
The SIPS encompasses Special Protection Schemes (SPS),
Remedial Action Schemes (RAS), as well as additional
schemes such as underfrequency (UF), undervoltage (UV),
out-of-step (OOS), etc. These additional schemes are not
used in the conventional North American definition of SPS
and RAS.
A traditional protection scheme is focused on a specific
piece of equipment (line, transformer, generator, bus bar, etc.).
SIPS is applied to the overall power system (or a strategic part)
and may require multiple detection and actuation devices and
communication infrastructure. The scheme architecture can
be defined by the location of the sensing, decision making,
and control devices and the impact the SIPS has on the
electrical system. Impact classifications are:
1) Local (Distribution System) – All sensing and
control devices are typically located within one distribution
substation. Operation generally affects only a very limited
portion of the distribution system.
2) Local (Transmission System) - All sensing and control
devices are typically located within one transmission
substation. Operation affects only a single small power
company, or portion of a larger utility. This category includes
SIPS with impact on power plants.
3) Subsystem - More complex, involving sensing of
multiple power system parameters and states. Information
can be collected both locally and from remote locations
while decision-making is performed at one location.
21
Telecommunications facilities are used to transfer information
and remote corrective actions. The operation has a significant
impact on an entire large utility or balancing authority area.
4) System wide - The most complex, with multiple levels
of arming and decision making and communications. Local
and telemetry data are obtained from multiple locations and
can initiate multi-level corrective actions. Multi-level logic
is used for different types of power system contingencies.
Operation has a significant impact on an entire interconnected
system. Design of the SIPS may involve redundancy or backup
functions, and may involve some form of voting or vetoing
decisions.
There are two main types of SIPS architectures: flat and
hierarchical.
1) Flat Architecture - the measurement and operating
elements are co-located. The decision and corrective actions
may need a communication link for remote information and/
or to initiate actions.
2) Hierarchical Architecture - There may be several
steps in the corrective action. Local measurements may be
transmitted to multiple control locations. Immediate action
can be followed by further analysis. Typical logic involves use
of operating nomograms, state estimation and contingency
analysis.
The design of the System Protection Terminal (SPT)
addresses standard requirements for protection terminals.
The terminal is connected to the substation control system.
For time tagging applications, a GPS-based synchronization
function is used. SPT uses a high-speed communication
link to transfer data between the terminal databases, which
contain all updated measurements and binary signals recorded
in the substation. The decision-making logic contains all
the algorithms necessary to derive appropriate output
control signals, such as circuit-breaker trip, AVR-boosting,
and tap-changer action, to be performed in the substation.
The input data is stored in the database. A low speed
1 System Protection Terminal
Power System
Substation Control System
Power System Transducers and
Measurement Devices
Power System
Actuators
Local and Remote Signals and
Measurement
Local or Remote Control
Signals
SPT
Input Interface
SPT
GPS
Time
Synchronization
System
Protection
SPT
Output Interface
Terminals
SPT
Decision Making Logic
(SPT) could
concurrently
Power System
Variables
Database
Supervision
Service,
Maintenance and
Update Interface
facilitate
Parameter
Setting
Database
multiple SIPS
actions.
Other SPT
Device
High Speed
Communication
Interface
Other SPT
Device
Low Speed
Communication Interface
Other Interface
PAC.AUTUMN.2009
Wide Area Protection
cover story
22
Soon to be
published
report of the
IEEE Power
Systems
Relaying
Committee will
report on
world wide
industry
experiences
with various
types of SIPS.
communication link for SCADA communication and
operator interface is also available as an enhancement for
the SCADA state estimator. Actions initiated by SCADA/
EMS, such as optimal power flow, could be activated via the
system protection terminal. The power system operator
should also have access to the terminal, for supervision,
maintenance, update, parameter setting, change of setting
groups, disturbance recorder data collection, etc. The most
appropriate types of SIPS actions are:
Generator Rejection
Load Rejection
Under-Frequency Load Shedding
Under-Voltage Load Shedding
Adaptive Load Mitigation
Out-of-Step Tripping
Voltage Instability Advance Warning Scheme
Angular Stability Advance Warning Scheme
Overload Mitigation
Congestion Mitigation
System Separation
Shunt Capacitor Switching
Tap-Changer Control
SVC/STATCOM Control
Turbine Valve Control
HVDC Controls
Power System Stabilizer Control
Discrete Excitation
Dynamic Breaking
Generator Runback
Bypassing Series Capacitor
Black-Start or Gas-Turbine Start-Up
AGC Actions
Busbar Splitting
In 1996, joint Working Groups of IEEE and CIGRE
published a noted article. The objective was to investigate the
worldwide use of special protection schemes and to report
on their designs, functional specifications, reliability, costs
and operating experiences. The report encompassed over
100 schemes and provided a wealth of information on the
direction the industry was taking in coping with increasingly
complex disturbances.
In 2004, the System Protection Subcommittee of the IEEE
Power System Relaying Committee started an initiative to
update the industry experience on SPS and SIPS by creating
a new worldwide survey. The survey is divided into two
parts: Part 1 identifies the purpose of the schemes with
subsections of "Type" and "Operational Experience". Part 2
concerns engineering, design, implementation, technology,
and cyber security. The survey inquires about design and
implementation, as well as the operation experience.
Information is collected on the application, design,
implementation, operation, and maintenance of new and next
generation SIPS and providing reasonable countermeasures
to slow and/or stop cascading outages caused by extreme
contingencies (safety net). The results of the survey,
containing almost one thousand different schemes obtained
from all over the world will soon be published as a special
Before blackout
2003 Blackout images courtesy of NOAA.
report of the IEEE PES Power System Relaying Committee
and also summarized as a journal article for wider engineering
readership.
Wide area monitoring with PMUs
While true wide area SIPS are very demanding systems
in terms of infrastructure support (fast data acquisition,
communication networks with guaranteed bandwidth, fast
and reliable actuation), monitoring of system-wide events can
be accomplished with much fewer resources, especially when
it is done as part of the forensic analysis of the disturbances. It
may be considered as a transitional step to developing a better
understanding of the system behavior and formulating a target
list of applications which could cost-effectively share the
same infrastructure (such as state estimation, voltage stability
protection and emergency control, dynamic line ratings, etc.)
Developing a portfolio of possible applications would lead to
a more cost-effective sharing of resources as long as they are
integrated to satisfy the most demanding aspects of every
application planned to be used concurrently. Most designs
for such systems are built around the networks on phasor
measurements, which can also be used in non-networked
configuration for ex-post tracking of system wide events.
The concept of phasor measurement is a spin-off of the
symmetrical component distance relay, one of the early
microprocessor-based relay designs. The first prototypes of
2 Propagation of disturbances
Frequency (active power imbalance) disturbances spreading across power
networks is akin to propagation of ripples in laminar fluids
PAC.AUTUMN.2009
picture courtesy of Adam Hart-Davis
23
Networks of synchronized phasor measurements
are able to accurately track the propagation
of disturbances in large power systems.
PV and wind generation are becoming more common
Wider use
of PV
and wind
generation
will create
After blackout
more
frequency
phasor measurement units (PMUs) were
designed and built by the research team of disturbanProfessor Arun Phadke at Virginia Tech in
the mid-80s. Built on the hardware platform ces.
using Motorola 68020 microprocessors and
VME bus, early PMUs were synchronized
using the outrageously expensive stand-alone GPS receivers
then available. They provided the single pulse per second
synchronization signal which was used to enable the 720 Hz
sampling rate needed by PMUs to obtain phasors from 60 Hz
voltages and currents. The sampling rates used at the time
were dictated by the relative simplicity of calculations needed
to obtain phasors from a sliding window of data containing
12 samples per cycle.
The first tests of PMUs (in the late 80s and 90s) were done
by several US utilities (BPA, AEP, NYPA, Georgia Power Co.,
FP&L, etc.) in stand-alone configuration, due to the limited
infrastructure availability. Consequently, various uses were
developed for non-networked groups of PMUs strategically
placed across the power system. Many of them were really
deploying PMUs as highly performing disturbance recorders.
The data obtained from the first PMUs were very
sufficiently detailed to estimate the phase angle dynamics
across the system using ex post estimation. Among the
first field tests were those performed at the Georgia-Florida
interconnection, known for its challenging dynamics. Over
the years, the capabilities of the equipment allowed for many
more innovative uses of the PMU equipment.
Different classes of disturbances provide different
signatures in the network. In general, power/frequency
disturbances produce system wide effects and allow to
observe the propagation of the disturbance across the
network. Figure 2 shows the propagation of ripples created by
a drop of water, which are often used to visualize the spreading
of the frequency perturbations through vast distances in
power networks. Disturbances caused by relatively minor
active power imbalances are possible to track if a number of
strategically positioned PMUs are used to provide information
about timing and nature of the initial transients. Figure 3
illustrates such an event which occurred in the San Francisco
area in 1999 and was captured by a number of PMUs installed
across the WSCC system. The ease with which active power/
frequency disturbances may be observed spreading across large
networks have led to proposals to use networks of frequency
recorders to track such events. It has also contributed to
proposals to develop deeper understanding of how frequency
perturbations propagate through electrical networks.
It is believed that very minor active power disturbances
can produce system wide effects. Power excursions of 0.276
Hz (Figure 4) have preceded the loss of a major transmission
line during genesis of the system wide blackout in WSCC
on August 10, 1996. The entire system has collapsed within
6 minutes from the occurrence of that disturbance, believed
to have been caused by spontaneous arcing between the
transmission line and a tree in the right-of-way. If that
speculation is true, then it could be seen as demonstration
that, in the realm of large power networks, the flapping of
butterfly wings in certain places can literally produce a storm
in the remote corners of the system.
Even when the amount of load drop is only 0.5% of
the system load (Figure 4), it may reveal facts about the
disturbance: sudden changes in frequency indicate switching
events, initial frequency upswing indicates a surplus of
generation (loss of load) whose magnitude reflect the
amount of load lost in the disturbance. Subsequent larger
oscillations are the consequences of generator trips. Very
small disturbances may have complicated evolution and
consequences, and ex-post analysis may require a large
number of measurements, precise time tagging of different
events and additional information. It may not be easy to
propose general rules for analysis of system disturbances via
non-EMS networks of PMUs.
Frequency disturbances will become more frequent
(and important) with deeper penetration of renewable
generation resources, especially photovoltaic and wind. Both
are dependent upon stochastic inputs (as Figure 5 illustrates
using field data from the system installed since 1996 on Georgia
Institute of Technology campus). Some countries, like Spain,
already have 11 percent of their available generation capacity
in wind resources. In contrast, voltage disturbances areas
are usually localized around the point of inception of the
disturbance, especially in strong systems. Analysis of such
events is more effective through use of EMS based techniques,
PAC.AUTUMN.2009
In the realm
of large power
networks,
'flapping of the
butterfly wings'
in some places
can
literally produce
a 'storm' in the
remote parts of
the system.
3 Frequency deviations
4 Malin-round mountain #1 MW
I
15: 48: 51
Out-of-Step separation
15: 42: 03
Keeler-Allston trips
I
I
1400
1300
0.276 Hz
I
0.264 Hz
3.46% damping
1200
I
-0.02
0.252 Hz
I
0.00
15: 47: 36
Ross-Lexington time trips/
McNary generation drops off
I
I
0.04
0.02
1500
I
0.06
I
0.08
WSCC PDC Units, 12/08/99
reference time = 08:14:30.1
sample rate = 30 sps
I
0.10
Dittmet Control Center
Vancouver WA - sample rate - 20 per sec.
I
P4: Summary Plot for SF_9812081614B
caseID = SF_9812081614B casetime = 09/23/99_09:14:06
I
Figure 4:
Power oscillations
at 0.276 Hz have
developed prior
to the KeelerAllston line trip
which unchained
the system wide
blackout in the
WSCC system in
1996.
The oscillations are
believed to have
been triggered by
the arcing between
the tree and a
transmission line.
but it is possible to identify certain signatures of problematic
situations by using special monitoring strategies. Very often,
voltage disturbances such as loss of a shunt capacitor bank,
are only detected in the first few tiers of buses surrounding
the point of inception of the disturbance (tier #1 consists of
buses directly connected to the point of disturbances, tier #2
are buses connected to tier #1, etc.)
Direct Tests
Direct (staged) tests are an excellent way to explore the
system dynamics. Broadly, they can be classified as Topology
Switching Tests (simple opening or closing of the breakers);
Tests with large inputs (using controllers capable of producing
GW scale disturbances, such as dynamic brakes, SVCs,
thyristor-controlled series capacitors (TCSCs) or similar
devices); Tests with medium-level inputs (using injectors
such as HVDC controllers, which may be used to inject the
disturbances of the order of 0.1 % of the system load); Tests
with low-level random and pseudo-random inputs (signals
as small as 0.01—0.05% of the system load may be sufficient
to drive the system dynamic response).
Example: Control of Inter-area oscillations
The frequency of inter-area disturbances has increased
significantly in recent years (in some systems reaching
hundreds annually). The variety of circumstances surrounding
the onset of power oscillations needs an adaptive approach
to ensure fast detection and effective mitigation. Knowing
generator coherency in real-time is important in such
cases. Phasor measurement based technologies have the
potential to significantly enhance SIPS (system integrity
protection schemes). A new method for generator coherency
determination determines generator coherency based on
real-time tracking of generator speeds in the network.
The new method establishes the coherency faster than
conventional angle monitoring due to its lower sensitivity
to transient distortion. The low frequency spectra of inter
area oscillations tend to produce phase-aligned peaks in
coherent machines. Their accurate determination requires
use of advanced DSP techniques. Once coherent groups are
determined, separation schemes may be initiated. Important
issues involve the geographical structure of the scheme, wide
area data processing and the choice of remedial actions.
Figure 6 demonstrates the application of such
instantaneous measurements for identification of the
coherent groups of generators during development of
inter-area oscillations in the system. The initiating disturbance
on a 68-bus, 16-machine test system is a line outage. The
consequence is development of inter area oscillations which
develop over time and can be tracked on any one of the
generators by calculating time evolution of the low frequency
spectrum of its speed and identifying the dominant modes
of oscillation (0.22 Hz, 0.36 Hz and 0.60 Hz). The machines
which have identical phase angles corresponding to the peaks
of any oscillation modes are forming coherent groups, which
can be identified in real-time by tracking the low frequency
spectra of the machine speeds as the disturbance evolves.
Subsequent control actions may be designed around such
real-time monitors and allow for an adaptive scheme for
system separation.
Example: Voltage Collapse Analysis
Voltage instabilities are often investigated using static
bifurcation model. This model assumes that the power
system is described with a set of differential equations. As
system loading varies slowly, the stable equilibrium moves
in the state space and can become unstable or even disappear.
In both cases, the system loses its stability. In the latter case,
it means that the systems with heavy, increasing loads tend
to suffer declining voltages and progressively larger reactive
losses up to the point when the voltages suddenly collapse,
driving the entire system into a blackout. If the equilibrium
point becomes unstable, the system loses its stability through
I
Figure 3:
Frequency
deviations in
response to a 600
MW load loss in the
San Francisco area
observed through
a network of PMUs,
some of which
thousand or more
miles away.
New monitoring and
protection technologies will
promote speed and accuracy
enhancement to network
functions.
I
Wide Area Protection
cover story
24
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50
PAC.AUTUMN.2009
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55
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60
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65
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70
Time in Seconds
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75
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80
1100
Reference time = 15: 35: 30 PDT
50
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400
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500
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600
Time in Seconds
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700
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800
25
5 PV system daily power generation
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Power [kW]
200
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Power [kW]
Figure 5:
The DC and AC
power outputs
150
during daily
150
operation of
100
the 340 kW
100
photovoltaic
50
system on
50
Georgia Institute
05 April 2009
31 March 2009
of Technology
0
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0
00:00
6:00
12:00
18:00 00:00
6:00
12:00
18:00 campus on a clear
DC power [kW]
AC power [kW]
sunny day (left)
and intermittently
may mean that the mitigation is applied to a system which
cloudy day (right).
has changed by the time of actuation, and that the assessment
Similar fluctuations
cannot be done fast enough to deal with fast transient aspects
are observed in
of voltage dynamics.
daily operation of
Finally, only a network of PMUs covering the entire system
large wind farms.
redundantly (and equipped with a reliable and redundant
200
information exchange infrastructure) could provide a fast and
accurate medium for monitoring and transfer of information,
which could be used to formulate the real-time monitoring
and control strategies not only for quasi-steady-state types
of voltage instabilities, but also be used for mitigation
of dynamic voltage dips using SVCs and other dynamic
reactive support devices. In addition, such a network would
be fast enough to be used for other applications, such as
defense against transient and cascading instabilities in the
transmission network, which require fast response times not
afforded by currently available alternatives to PMUs. PMUs
would also allow shortening the refresh times for various
network optimization functions, such as active and VAr
loss minimization optimal power flows, which would help
accomplish better tracking of the optimal states and reduce
the cost of system operation. Considered in conjunction
with a portfolio of complementary applications, PMUs offer
unprecedented speed and accuracy enhancement to network
functions, which make a proposal for their implementation
much easier to justify.
0.04
/
0.02
/
0.01
/
0.03
/
0.05
/
0.06
/
6 Evolving spectra in development of inter-area oscillations
Magnitude [pu]
either abrupt appearance of self-sustained oscillations or
a growing oscillatory transient. This type of oscillatory
instability is called Hopf bifurcation (HB), and can possibly
explain a number of events observed in power systems world
wide, when unexplained self-sustained oscillations develop,
sometimes without any obvious cause.
Bifurcation does not account for the large disturbances
found in some voltage collapses. However, some concepts of
bifurcations can be reused to study large, sudden disturbances
as well. One key idea is to split dynamics into fast and slow
dynamics. When studying the slow dynamics, the fast
dynamics can be approximated as instantaneous. During
the fast transients, the slow variables can be considered as
practically constant.
Voltage stability of the system can be improved by
implementing various remedial measures, such as adding
reactive compensation near load centers (e.g., shunt capacitor
banks, Static Var Compensators (SVCs), synchronous
condensers, etc.), strengthening the system by building new
transmission lines, varying the operating conditions, such as
voltage profile and generation dispatch, coordinating relays
and controls (e.g., control of transformer tap changers), etc.
The factors that influence the choice of the measure are the
dynamic characteristics of the collapse, the state of the system
parameters, and the system sensitivity to a certain measure.
Are PMUs needed or not for voltage stability monitoring
and protection? The answer depends on sensitivity to
inaccuracy of the implemented scheme. Voltage stability is
an inherently system phenomenon. The complete model
assumes the knowledge of the complete state vector, obtained
as the system is undergoing changes. That is not possible in
conventional installations, where state estimation is refreshed
relatively infrequently (every several minutes).
The conventional approach to defense would be an
under-voltage (UV) load shedding with fixed set points.
UV relays are widely available; they are often implemented
in transmission networks. The advantage is simplicity and
robustness of the scheme, which relies on local voltage
measurements only. The disadvantage is also the simplicity
– the relay settings are not adapted to changing network
conditions, which, depending on the loading levels and the
level of reactive support, may vary within a wide range. That
may, under some circumstances, render the scheme useless,
or even trigger the protection under normal and secure
operating regimes with depressed voltages.
The accurate model of voltage collapse requires the
complete state vector (phasors across the entire network).
Under such circumstances, deployment of the advanced
analysis techniques (direct, iterative, or continuation
methods) could be used to assess the margin or sensitivities
of the system to voltage collapse, identify the critical
contingencies, and formulate the optimal remedial actions.
There are a number of EMS packages currently in use which
claim to accomplish some, or all of those functions. The
limitation of this approach is that the evaluation is tied to a
latency time of the underlying monitoring system, which
0.00
40
30
Time [s]
20
0.8
0.7
0.6
0.5
0.4
Frequency [Hz]
0.3
PAC.AUTUMN.2009
Figure 6:
Time-frequency
distributions on one
of the generators’
speeds during
development of an
inter-area oscillation
in a simulated 68bus, 16-generator
system model.
Horizontal axes are
time and frequency
(corresponding
to different time
instants).