A Smarter Grid for Improving System Reliability
and Asset Utilization
D. Divan and H. Johal
Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, USA
deepak.divan@ece.gatech.edu
Abstract The power grid is aging and under stress.
Unlike other modern networked systems, the grid lacks
intelligence and automation. This paper has presented a new
look at the way a Smart Grid can be implemented. The
conventional approach has been to first obtain real time
information on critical parameters, and then by controlling
VAR resources, tap changers, and FACTS devices to
achieve the desired control. A simpler approach is presented
here based on using highly interconnected meshed
networks. Such networks have been used in high density
urban areas for many years for the high reliability
achievable, but suffer from poor line utilization and lack of
flexibility under contingency or load growth conditions. The
use of a large number of Current Limiting Conductor or
CLiC modules provides a simple and cost-effective
approach for realizing a controllable meshed network,
maximizing network capacity under diverse contingencies
and load growth scenarios. Using a low-tech approach, it is
seen that basic network performance and reliability are
dramatically increased. It is also seen that the distributed
nature and inherent redundancy in the deployment of large
numbers of CLiC modules, results in high system reliability.
Keywords- Transmission lines; Loadflow control; Intelligent
sensors
I.
INTRODUCTION
The global electricity infrastructure represents perhaps
the most complex edifice built by man. In the US, for
instance, the grid is in excess of 50-60 years old, spans the
entire continent with over 800,000 miles of high voltage
transmission lines, and has a minimal level of monitoring
and/or automation. Over the last two decades, electricity
consumption and generation have continually grown at an
annual rate of around 2.5% [1]. At the same time,
investment in the T&D infrastructure has steadily
declined. Further, it has become increasingly difficult and
expensive to permit and build new power lines. As a result
the aging power grid is congested and under stress,
resulting in compromised reliability and higher energy
costs. To compound the situation, the utilities often do not
possess detailed information on the status and operating
margins on their various geographically-distributed
power-line assets, resulting in sub-optimal use. In today's
competitive environment, the ability to use its assets
This project has been done under the Intelligent Power Infrastructure
Consortium at Georgia Tech under research funding by Tennessee
efficiently becomes an important component of a utility's
profitability.
While radical changes in infrastructure may seem
attractive, and in line with transformations that have
occurred in the telecom and Internet areas, the analogies
are likely to be misleading at best. Unlike in telecom
where society's bandwidth requirements have grown
exponentially, no metrics can be identified in the powerdelivery industry where performance has improved by
several orders of magnitude over the last decade. With the
exception of a few high growth opportunities, e.g. China
and India, where building new infrastructure is a priority,
enormous legacy investments exist in the existing power
delivery infrastructure and one can only posit incremental
improvements on the existing infrastructure.
A few critical requirements can clearly be defined.
System reliability is sacrosanct and cannot be
compromised. Utility system planners are moving away
from radial systems towards networked systems to achieve
higher reliability, especially under contingency conditions.
While enhancing reliability, this degrades controllability
of the network, as current flow along particular lines
cannot easily be controlled. The situation is exacerbated
when a contingency such as loss of a line or generator
results in overload and tripping of lines, increasing the
possibility of a cascading blackout. Finally, rapid load
growth leads to congestion on key lines connecting lowcost generation to load centers, leading to an inefficient
operation of energy markets and 'gaming' [2].
The answer seems to lie in the implementation of a
'Smart Grid', that is reliable, self-healing, fully
controllable and asset efficient [3]. Continuous advances
and cost-reductions in sensing, communications, power
electronics and systems technology are at the heart of the
Smart Grid of the future as envisioned. Components of
tomorrow's grid include Flexible AC Transmission
Systems (FACTS) devices rated at >100 MVA, HVDC
Lite, Smart Wires, PMU's, and power line sensometworks
[4]-[5]. Of the various technologies under development,
smart sensing is clearly an important component.
However, much more critical is the ability to statically and
dynamically control critical grid operating parameters,
such as line current, voltage, phase angle, and power flow.
This paper discusses some of the more promising
technologies that allow real-time control of grid
operations and that will help to create the Smart Grid.
Valley Authority
1-4244-0449-5/06/$20.00 ©02006 IEEE
IPEMC 2006
IMPROVING POWER GRID RELIABILITY AND
UTILIZATION
System reliability is the paramount mission for a utility.
Older systems are radial in structure, primarily because
they provide a cost-effective and fully controllable
system. However, radial systems suffer from poor
reliability, because a fault results in an extended outage
for all downstream customers, severely compromising
system reliability. Utilities are moving from radial
systems to meshed networks or 'networks' at the
distribution, sub-transmission and transmission levels, in
an effort to enhance system reliability. In a network, a
fault results in the isolation of a single line segment, with
alternate paths maintaining power to all other customers.
This results in significantly higher reliability levels. Many
urban centers, such as New York, have vast networks at
the distribution level, and consistently deliver some of the
most reliable power in the US [6]. Even at the
II.
transmission level, interconnections between major
transmission lines are common, and provide alternate
paths for power flow under contingency conditions.
The biggest drawback of networks is the inability to
control how current flows on individual lines in the
network. Balancing power flows dynamically under
changing load and source conditions is not possible as the
system is passive and has few 'handles' for control. Even
if expensive phase angle controllers were used on each
line, finding an optimal control strategy would be a
daunting task. As a result, the reliability comes at a
significant price. Inability to control power flow results in
loop flows, congestion, and poor line utilization [7]. In a
network, the first line that reaches a thermal limit
constrains the power transfer capacity of the entire
network, even though all the other lines may be operating
substantially below their thermal capacity. Fig. 2 shows
the utilization of a part of the IEEE 39 bus system (Fig. 1),
when the first line in the system (Line 22 21) hits the
thermal limit. It is observed that individual line utilization
varies from 5% to 100%, with an average of 59%. The
real situation is even worse as it is driven by the need to
have spare system capacity and to ensure system integrity
and reliability under (N-1) or (N-2) contingency
conditions. This reduces the allowed line current levels
under normal operating conditions to well below nominal
thermal limits, and further degrades system utilization.
Another compounding factor is the dynamic thermal
limit of the line under prevailing weather conditions.
System operators generally approach the line rating issue
conservatively, with limits established under the highest
ambient temperature and zero-wind conditions.
Sometimes, prevailing winds and ambient temperature
forecasts are factored into setting the limits. EPRI and
others have proposed the use of line sensors located on a
pre-identified 'critical span' to assess the dynamic thermal
capacity of the line [8]. While this appears to be promising
at first glance, lack of knowledge of micro-climate
conditions, especially for long lines, raises a concern as to
whether the identified span is truly the critical span under
current operating conditions [9]. This once again limits the
system operator's ability to truly use any dynamic line
capacity information that he may have.
j 4....] 28
iZ
~
tt3
le
v
GI
is
t
. $ j,7
12
I~
11 .j~
r
s
21
^_32
GS
.22
L!!
G4
Fig. 1. IEEE 39 Bus System
Network Performance Without CLiC
._,
,2
a
E
c)
0
100
80
60
40
20
0
Power Lines
Fig. 2. Network utilization when the first line reaches thermal limit
Another important and related issue is transmission line
congestion that limits the ability of end-users to freely
access low-cost generation. Load growth and lack of
incentives for transmission investment can result in
increasing levels of congestion. When a transmission line
reaches a constraint (thermal or stability), and limits the
power that can be supplied, say to a load in region 2 from
a low-cost generator in region 1, then an out-of-merit
generator in region 2 is used to supply the power at a
higher rate. This results in higher cost for all consumers in
region 2. The insufficient transmission capacity also
results in islanded networks that require higher level of
generation reserves within each region to ensure system
reliability. All these factors result in a cost increase for the
consumers [10].
It is seen that system reliability and utilization seem to
move power system designers in opposite directions. Cost
and system-utilization can be more effectively controlled
in radial systems, whereas reliability of meshed networks
is substantially higher. Today's modern digital economy
requires more reliable and higher quality power than ever
before. Our total dependence on electronics appliances
and industrial automation brings our everyday life to a
halt, even for short interruptions in our electricity service.
Except in remote rural areas, the trend is towards higher
reliability achieved through an increasing use of networks.
It is important to explore techniques for cost-effectively
enhancing the reliability and utilization of meshed
networks.
III.
EXISTING SOLUTION
The traditional solution for overloaded lines and
transmission congestion has been to build new lines. In a
radial system, this is possibly the only solution. In a
network, that may not be the case, as there are likely to be
a number of under-utilized lines, as can be seen in Fig.
l(b). New lines are expensive to build, and are subject to
delays in permitting, siting and obtaining rights of way
(ROW). In the US, some transmission lines have been
delayed for more than 20 years because of ROW issues.
Further, it should be noted that a new line is likely to be
lightly loaded and can make the overall grid utilization
even worse [11].
Several important technologies are in use today for
improving grid reliability and utilization. Some of these
technologies are discussed below. A widely used approach
is the use of shunt VAR compensation to provide voltage
support. Shunt compensation techniques include electromechanically switched capacitor banks, static VAR
compensators (SVC) and STATCOMs [12]. Capacitors
are used to compensate for voltage drop along the line
reactance, and provide only steady state VAR support.
SVCs use thyristor controlled reactors (TCR) in parallel
with shunt capacitors to realize reasonably fast control of
shunt VARs, and to provide dynamic control of voltage.
For sub-cycle response to prevent voltage collapse in the
presence of faults on the system, it is necessary to have
faster response capability using STATCOMs.
STATCOMs are rated in the 20-100 MVA range, and
utilize inverters to draw leading or lagging reactive current
from the line. While shunt compensation is universally
used, the value is primarily in voltage regulation on the
system. The impact on system power flow control is
extremely weak.
In order to achieve power flow control on the grid,
series VAR compensation or phase angle control is
required. Series capacitor compensation is often used to
mitigate sub-synchronous resonance issues encountered
with long lines, and to allow power flow over long haul
transmission lines. Similarly, phase-angle controllers,
essentially phase shifting transformers with tap-changers,
are used to balance power flow on interconnected
transmission systems. Both techniques are expensive and
are typically applied only at 345 kV and higher. Also,
neither technique offers dynamic control capability as far
as grid power flow control is concerned. What is needed is
the ability to dynamically control power flow, so that
under contingency and/or overload conditions, the current
can be redirected to under-utilized paths, thus averting a
serious cascading blackout.
Several techniques are available that allow dynamic
power flow control on the grid. These include Unified
Power Flow Controllers (UPFC) and Synchronous Static
Series Compensators (SSSC) [13]. Most of these fall into
the category of Flexible AC Transmission or FACTS
devices, as do SVCs and STATCOMs. Fig. 3. shows block
schematics of various FACTS devices. The UPFC
provides the highest level of flexibility, providing both
series and shunt compensation, including implementation
of STATCOM and SSSC functionality, but with the
additional ability to exchange real power between the
series and shunt inverters. The inverters use GTOs or
IGCTs, are custom designed and built, are rated at up to
100 MVA, and are connected to the transmission line
using transformers. The series connected transformer, in
particular, has stringent design issues, including the ability
to handle fault currents of up to 65,000 Amperes, and core
saturation that can occur under certain types of transients
and start-up conditions. The BIL issues related to a 345 kV
line add further cost and complexity.
Svc
STATCOM
VsL
I~~~~~~~~~~~~~~~~~~~~~~~~D
sssc
UPFC
vsi
-E--cl-
T-
Fig. 3. Common FACTS devices: (a). SVC, (b). STATCOM, (c).
SSSC, (d). UPFC
FACTS technology has been around for over 15 years,
with several highly visible and successful demonstration
projects that showcase the capability of the technology.
The Marcy UPFC project in New York, representing 200
MVA of total control capability at the 345 kV level built
at a cost of $54 million, exemplifies the capabilities of
existing FACTS technology [14]. It is interesting to note
that although FACTS devices have been commercially
available for many years, there has been virtually no
market penetration, especially in the area of grid power
flow control.
Discussions with utility personnel suggest the following
reasons. It is perceived that the first cost and life cycle
costs for FACTS devices are high, while the uptime and
reliability have not yet reached desired levels. Also,
building a large centralized device results in susceptibility
to a single point of failure, and the device complexity and
unique components results in a mean time to repair that is
much longer than desired. Finally, the utility personnel are
not qualified to maintain and repair the FACTS devices.
Another interesting issue revolves around the cost
differential between compensators that can influence
steady state behavior, and those that can provide fast
dynamic compensation. For example, STATCOMs are
faster than capacitors or SVCs but cost a lot more.
STATCOMs provide unique value only during infrequent
transmission level system faults, while capacitors provide
value on a continuous basis. This suggests that the return
on investment from a market perspective for a steady state
compensator may be easier than for a dynamic
compensator that provides unique value only under
occasional faults. This is particularly true for a steady state
series VAR compensator that can enable additional MW
flow along congested lines, that a customer is willing to
pay for. However, there are few commercial technologies
and solutions that are presently available that can provide
cost-effective power flow control in networked systems,
especially at the distribution level, so as to enhance system
reliability and utilization.
IV.
DISTRIBUTED SOLUTION FOR IMPROVING GRID
RELIABILITY AND UTILIZATION
It is clear that a meshed network provides the highest
level of reliability, albeit at apparently higher cost and
with poor asset utilization. This results purely from the
inability to control how current flows on individual lines
in the network. Utility operations are based on an
assumption that it is difficult to control current in
individual lines in a network. This has resulted in a
preference for radial networks wherever possible, and
with vastly under-utilized systems where networks were
unavoidable to meet urban distribution and reliability
needs.
Fig. 4 shows an example of a meshed network, with
controllable voltages at major buses. In an optimal
situation, the amplitude and phase angle of the voltage at
the various buses could be controlled so as to balance the
individual line currents. This would require a real-time
computation of the power flows in the network, with a
calculation of voltage magnitude and angle at each of the
controllable nodes to provide an optimal operating set
point. This process would need to be continuously
repeated as the load or any of the sources varied. For
proper operation, this would also require a fast
communication link between all nodes, with full visibility
to the 'state' of the network/system. This is akin to the
technique by which a larger power system is controlled,
where system operators at the area control centers can
dispatch generators, set VAR compensator tap changer
operating points, etc. to optimize the load flow. Fast and
reliable communications, information on the current in
individual lines, and an accurate knowledge of the
network topology at any given time is required for such a
control strategy to work. Clearly, while this is
theoretically possible, it would add substantially to the
complexity and cost of the implementation. Further, under
a contingency, such as an unanticipated line, generator or
transformer outage, the set points have to be rapidly
recalculated if outages and the potential for cascading
blackouts are to be avoided. While this approach may be
acceptable for the transmission grid, it is too expensive
and unwieldy to implement at the distribution level. As a
result, interconnected and meshed networks are
infrequently used in distribution, unless reliability is an
overriding priority.
Meshed Power Network with
Controllable Bus Voltages and Angles
VI argO,
I
*
S
0*
*
0
*
S
*
0
0*
*
0
Fig. 4. Meshed network with controllable voltages and phase angles
The fundamental issue with networks is that individual
lines get overloaded as a result of load growth, line
outages and source outages. The interconnectedness of the
network, invaluable for reliability, now makes it difficult
to predict how the current will distribute in the network,
and which lines will be overloaded. Even if this
information were known, there are no simple control
handles that would allow us to limit the current without
some form of load-shedding. What is clearly required is
some form of 'throttle' control that would 'dial back' the
current in an overloaded line. A recently proposed
technique - 'Current Limiting Conductors'- provides a
cost-effective method for implementing such control on
lines that can potentially be subject to overload, offering a
new approach to the implementation of meshed networks
that promise high reliability, with high asset utilization
and low cost [15].
V.
CURRENT LIMITING CONDUCTORS
Recently, the concept of Current Limiting Conductor
(CLiC) modules, a special implementation of the generic
family of Distributed Series Impedance devices, has been
proposed as a means of varying the impedance of existing
transmission and distribution lines. CLiC modules clamp
on to power lines, floating mechanically and electrically
on the power line as shown in Fig. 5. Fig. 6 shows a
schematic of a CLiC module, including a single turn
transformer (STT) with a normally closed relay that
bypasses the transformer impedance. The STT turns ratio
is chosen to reduce the relay current, under nominal and
fault conditions, to a reasonable value. A control circuit is
powered parasitically off the line, and monitors the line
current. When the current in the line reaches a
predetermined threshold, the relay is opened inserting the
magnetizing inductance of the transformer in series with
the line impedance. Multiple CLiC modules are used
together on a line, with individual module current trip
thresholds tuned slightly apart from each other. At the line
level, as the current rises, the impedance of the line
gradually increases. If the current in other lines has not yet
reached this threshold, then the increasing impedance will
force the current to preferentially flow in other lines that
have lower impedance.
all lines operate within their thermal limit. Further, it is
seen that loss of lines and or sources does not result in
system collapse. This is illustrated in Fig. 8, where a
contingency condition is simulated by taking Gen. 7 (G7)
off. The current through Line 22_23 is seen to jump to a
very high value of 940 A from an initial operating point of
43 A. However, with the CLiC modules turned on, the
current is brought down to a safer level of 643 A. Thus
system reliability is ensured even under contingency
conditions.
Network Performance With CLiC
100
7G~~~~~~~~~~~~~~~~~~~~~~~~~~~~
80
60
40
*---a Lirto curmnts vwith CLiC
+---* Line currents vAthout CLiC
Power Line
Power Lines
Fig. 7. Improvement in line utilization with CLiC modules
Power
_
_
~
#ilSpp19
$sm
__
19
~~~~~~~~~
I
Current Profile With CLiC Modules
I
Current Without CLiC Modules
940 A
l~~~~~~~~~~~~~~~~~~~~~~~~~~~~
I~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
940 A
08
Control t- - - --6 _ _
Current With CLiC Modules
06
643 A
Fig. 6. Circuit schematic of CLiC
The CLiC module implementation is very simple, using
readily available low-cost components. Control is purely
based on locally measured parameters (line current),
although communications can be used to augment the
performance. A single CLiC module weighing
approximately 55 kg can be suspended from most power
lines, and can inject approximately 9-11 volts at 6001000 Amperes. The CLiC modules operate according to
an algorithm that turns the device on or off with the
appropriate current-delay characteristics.
One can explore what the impact of CLiC modules
would be on system capacity and asset utilization. As
current in a line increases to a value above the predefined
threshold, as a result of load increase or a contingency, the
impedance increases causing the current to redistribute to
those lines where the impedance is unchanged- i.e. lines
that are not seeing the same increase in current. This is a
natural redistribution that does not require any coordinated
control or action, or any communications. It is possible to
analyze potential overloads under anticipated load
increases and/or contingencies, and to only deploy the
number of CLiC modules that would be needed to save
the susceptible lines from overloads. Fig. 7 shows
improvement in the network utilization ofthe IEEE 39 bus
system, when operated with CLiC modules. It is seen that
system utilization is increased from 59% to over 93.3%,
showing an increase of more than 33% in system capacity
without any addition of new lines and while ensuring that
,04
0.2 -Generato
Taken Off
0
0.5
l
1.5
1
CLiC Active
2
2.5
Time (s)
Fig. 8. Performance under contingency condition (generator outage)
The approach can be clearly applied to distribution as
well as sub-transmission and transmission networks.
Tightly meshed systems with short lines, typical at the
distribution level, should show the most significant
improvement in reliability and asset utilization. The CLiC
modules can be incrementally deployed only on those
lines where they are needed, and can handle a variety of
contingencies without any need for real time computation.
Further, the ability to keep operating even as a few of the
modules fail indicates high reliability and availability at a
system level. The ability to replace failed units in the field
also promises a small mean time to repair. Finally, the use
of standard CLiC modules promises low cost.
The introduction of new technology on the grid always
raises a myriad of questions. Front and foremost are issues
of fault current handling and impact on protective
relaying. The CLiC module (Fig. 6) is designed with a
thyristor pair in parallel to the NC relay. Under fault
current conditions, the thyristor pair is rapidly triggered on
(within 1/4 cycle), effectively reverting the line to its
normal impedance state. This serves two important
functions. Firstly, it allows the CLiC module to ridethrough the fault. Secondly, it allows existing protective
relays to operate normally. This is clearly an issue that
needs to be validated before significant level of
deployment can occur. Other issues include the
environmental susceptibility of the unit, and the ability to
deploy or remove the CLiC module on a live line. These
issues have been addressed in previous papers. An
extension of the Distributed Series Impedance modules to
realize a Distributed Series Static Compensator or DSSC,
was reported in [16]. Fig. 9 shows that the device clamps
on to power lines, and shows a schematic of the
implementation. Fig. 10 shows operating waveforms,
demonstrating the ability to inject leading or lagging
impedance into the line.
Fig. 9. Laboratory demonstration of DSSC on a power line
800
I total/2
-I _1
(DSSC)
2 (uncontrolled)
I
V DSSC*I00
600
200
0
-200
-400
-600
-800
-0.015
-0.01
-0.005
0
0.005
0.01
0.015
0.02
Time (s)
I total/2
I
_1 (DSSC)
I
600
o
2 (uncontrolled) -V DSSC*I00
A
400
o200
0
-200
-400
-600
-800
-0.015
POTENTIAL VALUE TO UTILITIES
A controllable meshed network can of course be
implemented with existing networked systems. However,
the more interesting possibility is that new power grid
build-outs could be designed using a meshed network
architecture to realize high reliability and asset utilization
at low cost. In both cases, significant benefits are seen to
accrue. The benefits are also seen to be realized for
transmission as well as distribution networks. These
include:
* Enhancement in reliability and operation of existing
and new networks under (N-1) and (N-2)
contingencies by automatically routing current from
overloaded lines to lines with available capacity,
without impacting system performance or losses
under normal conditions.
* Improvement in line utilization significantly,
especially for shorter length lines typical of
distribution meshes, thus enhancing system capacity.
* Enhanced system performance based on local
measurements, without the need for a
communications link. Performance can be further
enhanced with a low speed communications link.
* Ability to share generation reserves across wider part
of the existing network.
* Distributed scalable solution allows strategic,
targeted and incremental deployment.
* Reduction in the overall cost of energy by providing
access to lower cost generation sources.
* Improvement in asset utilization of existing lines and
deferment of investments in new lines.
* Maintaining and operating CLiC system using
existing utility staff without the need for new skill
sets.
400
800
VI.
-0.01
-0.005
0
0.005
0.01
0.015
0.02
Time (s)
Fig. 10 Operating waveforms. (a). Injection of leading voltage
(inductive impedance), (b). Injection of lagging voltage (capacitive
impedance)
VII. CONCLUSIONS
This paper has presented a new look at the way a Smart
Grid can be implemented. The conventional approach has
been to first obtain real time information on critical
parameters, and then achieve the desired performance by
using VAR resources, tap changers, and FACTS devices.
A simpler approach is presented here based on using
highly interconnected meshed networks. Such networks
have been used in high density urban areas for many years
for the need of high reliability, but suffer from poor line
utilization and inflexibility under contingency or load
growth conditions.
The use of Current Limiting Conductor or CLiC
modules shows a simple and cost-effective approach for
realizing a controllable meshed network, maximizing
network capacity under diverse contingencies and load
growth scenarios. Using a low-tech approach, it is seen
that basic system performance and reliability are
dramatically increased. While performance can be further
enhanced using communications, the device operates
based on locally measured parameters, and continues to
deliver most of the improvement even without any
communications. It is also seen that the distributed nature
and inherent redundancy in the deployment of large
numbers of CLiC modules, results in high system
availability.
Delivery, IEEE Transactions on, July 1996, vol. 11, issue: 3, pp:
1407-1418.
[9]
ACKNOWLEDGMENT
This project has been done under the Intelligent Power
Infrastructure Consortium at Georgia Tech under research
funding by Tennessee Valley Authority.
[10]
REFERENCES
[1] National Transmission Grid Study, US Department of Energy.
[Online].
[2] B. C. Lesieutre and J. H. Eto, "Electricity Transmission
Congestion Costs: A Review of Recent Reports," [Online].
f .
Available:
H
b
[3] S. A. Massoud and B. F. Wollenberg, "Toward a smart grid:
power delivery for the 21st century," IEEE Power and Energy
Magazine, vol. 3, issue 5, Sept-Oct 2005, pp. 34-41.
[4] D. Divan, " Distributed Intelligent Power Networks - A New
Concept for Improving T&D System Utilization and
Performance," T&D Workshop, CMU, Dec 15-16, 2004. [Online].
Available.http: www.ece.cmu.edu/electriconf/old2004/divan.pdf
[5] Y. Yang, D. Divan, R. G. Harley and T. Habetler, "Power Line
Sensornet - A New Concept for Power Grid Monitoring," to be
presented at the IEEE PES General Meeting 2006.
[6] M. J. Museler, President and CEO of the New York Independent
System Operator (NYISO), presentation May 22, 2003. [Online].
Available:
[11]
[12]
[13]
[14]
[15]
http.//www.nyiso.com/topics/articles/news releases/2003/pa3_pre
sentation.pdf
[7] Kojo Ofori-Atta, Elliot Roseman, Bansari Saha, Scott Stuart, Marc
Lipschultz and Jonathan Smidt, "Profiting From Transmission
Investment," Public Utilities Fortnightly, Oct. 2004, pp 72-77.
[8] D.A. Douglass and A. A. Edris, "Real-time monitoring and
dynamic thermal rating of power transmission circuits," Power
[16]
S. D. Foss, S. H. Lin, R. A. Maraio and H. Schrayshuen, "Effect of
variability in weather conditions on conductor temperature and the
dynamic rating of transmission lines," Power Delivery, IEEE
Transactions on, Oct. 1988, vol. 3, issue 4, pp:1832-1841.
Harjeet Johal and Deepak Divan, "Calculating Economic Impact
of Congestion Mitigation Using Distributed Series Impedances,"
under review for IEEE PES, Power System Conference and
Exposition 2006, Atlanta
W. W. Hogan, " Transmission Capacity Rights for the congested
Highway: A Contract Network Proposal," Submitted to Federal
Energy Regulatory Commission.
[Online]. Available:
http: //ksghome.harvard.edu/whogan/ferc691r.pdf
N. G. Hingorani, "FACTS Technology and Opportunities," IEEE
Colloquium on Flexible AC Transmission (FACTS)- The Key to
Increased Utilization of Power Systems, Digest No.1994/005, 12
Jan. 1994, pp. 4/1-4/10.
L. Gyugyi, C. D. Schauder, and K. K. Sen, "Static Series
Compensator: a Solid-State Approach to the Series Compensation
of Transmission Lines," IEEE Transactions on Power Delivery,
Vol. 12, No. 1, Jan 1997, pp. 406-407
NYPA MARCY FACTS Project - Phase II. [Online]. Available.
http://www.nyiso.com/public/webdocs/market data/reports info/o
per_studies_sys_perf reports/ipfcmp6report_oc_final_approved.p
df
Harjeet Johal and D. Divan, "Current Limiting Conductors: A
Distributed Approach for Increasing T&D System Capacity and
Reliability," IEEE PES, Transmission and Distribution
Conference 2005-06, Dallas, Texas.R. Nicole, "Title of paper with
only first word capitalized", J Name Stand. Abbrev., in press.
D. Divan, W. Brumsickle, R. Schneider, B. Kranz, R. Gascoigne,
D. Bradshaw, M. Ingram, and I. Grant, "A Distributed Static
Series Compensator System for Realizing Active Power Flow
Control on existing Power Lines," IEEE PSCE Conference
Records, Oct 2004.