Algorithmic Decision Theory and
the Smart Grid
Fred Roberts, Rutgers
University
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Algorithmic Decision Theory
•Today’s decision makers in fields
ranging from engineering to
medicine to homeland security have
available to them:
−Remarkable new technologies
−Huge amounts of information
−Ability to share information at
unprecedented speeds and
quantities
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Algorithmic Decision Theory
•These tools and resources will enable better
decisions if we can surmount concomitant
challenges:
−The massive amounts of data available are
often incomplete or unreliable or distributed and
there is great uncertainty in them
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Algorithmic Decision Theory
•These tools and resources will enable better
decisions if we can surmount concomitant
challenges:
−Interoperating/distributed decision makers and
decision-making devices need to be coordinated
−Many sources of data need to be fused into a
good decision, often in a remarkably short time
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Algorithmic Decision Theory
•These tools and resources will enable better
decisions if we can surmount concomitant
challenges:
−Decisions must be made in dynamic environments
based on partial information
−There is heightened risk due to extreme consequences
of poor decisions
−Decision makers must understand complex, multidisciplinary problems
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Algorithmic Decision Theory
•In the face of these new
opportunities and challenges, ADT
aims to exploit algorithmic methods
to improve the performance of
decision makers (human or
automated).
•Long tradition of algorithmic
methods in logistics and planning
dating at least to World War II.
•But: algorithms to speed up and
improve real-time decision making
are much less common
Pearl Harbor
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Algorithmic Decision Theory
•The goal of the Special Focus on ADT and of the
field of ADT is to explore and develop algorithmic
approaches to decision problems arising from a
variety of application areas.
•This requires collaborations:
−Computer scientists with decision theorists
−Statisticians with economists
−Mathematicians with behavioral scientists
−Operations researchers with public health
professionals
•The SF on ADT aims at stimulating such
collaborations
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DIMACS Special Focus on
Algorithmic Decision Theory
•The SF is the classic DIMACS approach to
exploring and developing new areas of science
•Approach
−Workshops
−Working groups
•Foundational Topics
•Applied Topics
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Special Focus on Algorithmic
Decision Theory
•Foundations WSs and WGs
−Risk-averse adversarial decision
making
−Risk measures and incorporating
them into ADT
Risk topics
Cosponsored by
CCICADA
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Special Focus on Algorithmic
Decision Theory
•Foundations WSs and WGs
−The science of expert opinion
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Special Focus on Algorithmic
Decision Theory
•Foundations WSs and WGs
−Evidence-based policy making
December 2-3 in Paris
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Special Focus on Algorithmic
Decision Theory
•Foundations WSs and WGs
−Recommender systems
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Special Focus on Algorithmic
Decision Theory
•WSs and WGs on Applied Topics
−Electric power systems (smart grid)
−Health care
−Epidemiology
Note: Long-term DIMACS
SF on epidemiology; planned SF
on Algorithms and Energy
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Special Focus on Algorithmic
Decision Theory
•WSs and WGs on Applied Topics
−Ecology
−Port Security
−Urban policy making (“smart cities”)
Note: long term
DIMACS project on
inspection algorithms
for ports – relevant to
testing state of the
smart grid
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Special Focus on Algorithmic
Decision Theory
•SF-ADT arose from a joint project on Computer
Science and Decision Theory between DIMACS
and LAMSADE (Laboratoire d’Analyse et
Modelisation de Systeme pour l’Aide a la
Decision, U. of Paris Dauphine)
−Special issue of Annals of Operations
Research, Vol. 163, 2008
−Special issue of Mathematical Social Sciences,
Vol. 57, 2009
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Special Focus on Algorithmic
Decision Theory
•The European Cooperation in
Science and Technology
(COST) funded a 4-year
project on ADT that included
the First International
Conference on ADT, Venice
2009.
•The second International
Conference on ADT will be
held at DIMACS in October
2011.
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Special Focus on Algorithmic
Decision Theory
•The DIMACS SF on ADT is sponsored by:
−National Science Foundation
−Department of Homeland Security
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ADT and Smart Grid
Many of the following ideas are borrowed from a
presentation by Gil Bindewald of the Dept. of Energy to
the SIAM Science Policy Committee, 10-28-09
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ADT and Smart Grid
•Today’s electric power systems have grown up
incrementally and haphazardly – they were not
designed from scratch
•They form complex systems that are in constant
change:
−Loads change
−Breakers go out
−There are unexpected disturbances
−They are at the mercy of uncontrollable
influences such as weather
Note: DIMACS project on
Climate & health: heat events
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ADT and Smart Grid
•Today’s electric power sytems operate under
considerable uncertainty
•Cascading failures can have dramatic
consequences.
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ADT and Smart Grid
•Challenges include:
−Huge number of customers, uncontrolled
demand
−Changing supply mix system not designed for
Complexity of the grid
−Operating close to the edge and thus
vulnerable to failures
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ADT and Smart Grid
•Challenges include:
−Interdependencies of electrical systems create
vulnerabilities
−Managed through large parallel computers/
supercomputers with the system not set up for
this type of management
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ADT and Smart Grid
•“Smart grid” data sources enable real-time
precision in operations and control previously
unobtainable:
−Real-time data from smart meter systems will
enable customer engagement through demand
response, efficiency, etc.
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ADT and Smart Grid
•“Smart grid” data sources enable
real-time precision in operations and
control previously unobtainable:
−Time-synchronous phasor data,
linked with advanced computation
and visualization, will enable
advances in
state estimation
real-time contingency analysis
real-time monitoring of
dynamic (oscillatory) behaviors in
the system
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ADT and Smart Grid
•“Smart grid” data sources enable real-time
precision in operations and control previously
unobtainable:
−Enhanced operational intelligence
−Integrating communications, connecting
components for real-time information and control
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ADT and Smart Grid
•“Smart grid” data sources enable real-time
precision in operations and control previously
unobtainable:
−Sensing and measurement technologies will support
faster and more accurate response, e.g., remote
monitoring
−Advanced control methods will enable rapid
diagnosis and precise solutions appropriate to an
“event”
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ADT and Smart Grid: Phasor
Measurements
•Phasor measurements will provide “MRI
quality” visibility of the power system.
•Traditional SCADA measurement provides
−Bus voltages
−Line, generator, and transformer flows
−Breaker Status
−Measurement every 2 to 4 seconds
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ADT and Smart Grid: Phasor
Measurements
•Phasor technology and phasor measurements
provide additional data:
−Voltage and current phase angles
−Frequency rate of change
−Measurements taken many times a second
−This gives dynamic visibility into power system
behavior
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ADT and Smart Grid: Phasor
Measurements
•Phasor technology and phasor measurements
provide additional data:
−New algorithmic methods to understand,
process, visualize data and find anomalies
rapidly are required.
−Such measurements will allow rapid
understanding of how customers are
using electricity.
−Raise privacy issues.
−Another area for research.
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ADT and Smart Grid: Phasor
Measurements
•Some phasor applications:
−Monitoring
Visibility beyond local controls
Frequency instability detection
Triangulation to estimate location of generator dip
or hard drop
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ADT and Smart Grid: Phasor
Measurements
•Some phasor applications:
−Analysis/Assessment: improved state estimation
−Planning
Dynamic model validation
Forensic analysis through time tagging and
synchronization of measurements
−Protection and control: automatic arming of
remedial action schemes
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ADT and Smart Grid
Other problems/opportunities requiring ADT:
•Grid robustness: How will the grid respond to
disturbances and how quickly can it be restored to its
healthy state?
•Transmission reliability:
−Wide area situational awareness and advanced
computational tools can help with quick
response to dynamic process changes, e.g.,
using automatic switching.
−Sample challenge: How far are we from the
edge? When voltages drop too fast, the entire
power system can collapse.
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ADT and Smart Grid
Some Challenges:
•Need to develop reliable, robust models to help us
achieve system understanding.
•Need a new mathematics for characterizing
uncertainty in information created from the large
volumes of data arising from the smart grid.
•Need new methods to enable the use of highbandwidth networks by dynamically identifying
only the data relevant to the current information
need and discarding the rest.
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ADT and Smart Grid
Some Challenges:
•Security of new software is a priority
•Cyber attacks on the electric power grid are a
major concern. Needed are methods for
−Prevention
−Response
−Recovering
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ADT and Smart Grid
Some Challenges:
Cybersecurity Continued:
“Cyberspace” is
•Insecure
•Faced with attacks by adversaries who wish to
take advantage of our dependence on it
•Use of cyberspace subjects us to:
−Loss of information
−Loss of money
−Disruption, destruction, or interruption of
critical services
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ADT and Smart Grid
•
•
•
•
Some Challenges:
Cybersecurity Continued:
Adversaries can launch sophisticated
“information warfare”
Can destroy critical infrastructure
E.g., Russian cyberattacks on Estonia
E.g., “botnet” attacks on South Korean
government and private industry sites.
Note: DIMACS project on detection of
botnet attacks; planned DIMACS SF
on cybersecurity.
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ADT and Smart Grid: Summary
Relevance of ADT
Algorithmic methods needed to:
•Improve security of energy system in light of its
haphazard construction and dynamically changing
character
•Find early warning of a changed state – anomaly
detection
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ADT and Smart Grid: Summary
Relevance of ADT
Algorithmic methods needed to:
•Identify and overcome vulnerabilities in the
system
•Protect the privacy of individuals under new data
collection methods
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ADT and Smart Grid: Summary
Relevance of ADT
Algorithmic methods needed to:
•Protect systems operating “close to
the edge”
•Find new ways to characterize
uncertainty in information about the
health of the system
•Find ways to protect against cyber
attacks that take advantage of
vulnerabilities created by dependence
on massive amounts of data generated
through the smart grid.
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K.R. Krishnan
Linda Ness
Tom Reddington
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