IEEE Power & Energy Magazine - January/February 2014 - 57

Smart Restoration

70
Load Lost (GW)

from a complete or partial blackout. the lessons learned from
these drills have demonstrated the difficult challenges of managing electric islands. this has served as a catalyst for new
ideas about how smart grid technologies may be able to automate and expedite future system restoration procedures.

2003 NE

60
50
40
30

1996 WSCC

20

1965 NE

1996 WSCC

"decision support tools must be highly flexible and adaptive
1982 WSCC
1977 NYC
to allow ever-changing power grid conditions to be reflected
0
10
20
30
40
50
60
through seamless collaboration between human operators and
Duration (h)
computer-based optimization tools," says chen-ching liu, of
washington state university. power system restoration follow- figure 2. Major blackout events in the United States and
ing a widespread outage is a highly complex task for both plan- their associated impacts in terms of load lost. NE = Northeast;
ners and operators. decision-making or decision support tools NYC = New York City; WSCC = West Coast; MW = Midwest.
are therefore in great need for both online and off-line purposes.
decision making for power system restoration was among the
earliest applications of intelligent system techniques. the prog- decision support tools relieve the dispatchers from tedious tasks
ress of such tools has been slow, however, particularly for the and ensure that detailed simulations are performed before decionline environment. one major hurdle is that the decision-mak- sions are made. we believe that the grM decision support softing tools may not have sufficient information about the status ware tools represent a breakthrough in concept and technology
of power grid elements as system restoration progresses. as a development for smart restoration.
the grM concept provides a methodology for developresult, the recommendations from the decision-making tools
may be inaccurate or obsolete. a simple example is the status ing smart software tools for decision support during power
of unmonitored manual switches or breakers. dispatchers are system restoration. the actual implementation will be enabled
in contact with field crews, so the status of these devices is by emerging smart grid technologies. although power system
known to them-but there is no mechanism for updating the restoration involves a large number of generators, transmisstatus for the software decision-making tools in a timely man- sion and distribution facilities, loads, and system constraints,
ner. it is important that software tools play the role of decision the actual restoration process can be broken down into a numsupport while the decisions themselves are made by dispatch- ber of distinct phases. each of the phases and the associated
ers. in other words, software tools provide computational and technologies that enable smart restoration is reviewed below.
logic-reasoning information for
the various options dispatchers are
considering. Making this adjustment requires closer collaborations
Secure
among dispatchers, restoration planNormal
State
ners, and smart restoration tools.
Preventive Control
the other challenge of designing
smart restoration tools is including
Insecure
Restorative
Normal
the capability to adapt to different
Control
State
power systems and their respective
Corrective
system restoration strategies. even
Control
for the same power grid, the outage conditions and the availability
Emergency
of power system facilities can vary
Control
significantly. a smart restoration
decision support tool must be able
Emergency
Restoration
to meet the needs of different power
State
State
systems and various grid operating
conditions. based on the results of
recent epri projects, the concept
Cascade Events
of generic restoration milestones
(grMs) has been developed, and
Transition Due to Control Action
Transition Due to a Disturbance
the corresponding software modules have been tested with scenarios from large power grids. these figure 3. The operation states of a power system.
january/february 2014

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ieee power & energy magazine

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Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - January/February 2014

IEEE Power & Energy Magazine - January/February 2014 - Cover1
IEEE Power & Energy Magazine - January/February 2014 - Cover2
IEEE Power & Energy Magazine - January/February 2014 - 1
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IEEE Power & Energy Magazine - January/February 2014 - 112
IEEE Power & Energy Magazine - January/February 2014 - Cover3
IEEE Power & Energy Magazine - January/February 2014 - Cover4
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