Smart Grids A Grand Challenge for Complex Engineering Systems Adrian V Gheorghe C4UC and Old Dominion University Norfolk Virginia Assisted by Hal Warren The Electrical Grid A Large Fragmented ID: 294604
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Understanding Change:Smart Grids - A Grand Challenge for Complex Engineering Systems
Adrian V. Gheorghe
C4UC and Old
Dominion University
Norfolk,
Virginia
Assisted by Hal WarrenSlide2
The Electrical Grid: A Large, Fragmented, Complex Critical InfrastructureSlide3Slide4Slide5
Extraordinary ThreatsRisk PerceptionBlack Swan EventsFeral EventsLow Probabilities – High ConsequencesSlide6
Space Weather
The distortion of the Earth's magnetic field
caused by a corona mass ejection (CME) (p, e)Slide7
A Review of Power Grid Vulnerability to Solar Activity & Geomagnetic Storms
A rapidly changing geomagnetic field over large regions will induce Geomagnetically-Induced Currents (i.e. GIC a quasi-DC current) to flow in the continental interconnected Electric Power Grids
Storm causes Geomagnetic Field
Disturbances from
Electrojet
Current that
couples
to
Power SystemsSlide8
Currents in Electric Mains andGround Induced by Ionosphere Electric CurrentsSlide9
Damaged GSU
Geomagnetically
Induced Current (GIC)
flow
has
potential to cause wide-spread catastrophic damage to key
Generator Step UP (GSU) transformers Causing
Restoration Problems
Salem Nuclear Plant
GSU Transformer
Failure, March ‘89
Increased hum from
magnetostriction
(the slight change of length exhibited by a ferromagnetic object when magnetized)Slide10
Station 3 Gen Transformer 4 HV winding failure
Station 3 Gen. Transformer 5 evidence of overheating
Courtesy Eskom, Makhosi, T., G. Coetzee
Overview of South Africa EHV Transformer Failures due to Oct-Nov 2003 Geomagnetic Storms
Failures linked to Long Duration / Low Intensity GIC Exposure
Slide11
Starfish Prime HEMP (7/8/1962)Solar Coronal Mass Ejections (CME) effects
Generates an Earth-surface potential (1-10 V/km)
Drives a quasi-DC ground current (10-100A ~DC)
Duration 2-4 hours
High Altitude Electromagnetic Pulse (HEMP) from nuclear weapon effects are more intense
10X voltage (10-100 V/km)
10X current (~1000A ~DC)(0.1 Hz)
10-15 minutes/burstSlide12Slide13Slide14
Smart Grid BenefitsMore efficient transmission of electricityQuicker restoration of electricity after power disturbances caused by Space Weather, severe storms, earthquakes, and terrorist attacks, etc.
Reduced operations and management costs for utilities, and ultimately lower power costs for consumers
Reduced peak demand, which will also help lower electricity rates
Increased integration of large-scale renewable energy systems
Better integration of customer-owner power generation systems, including renewable energy systems
That is, a smarter grid will add resiliency to our electric power systemSlide15Slide16
The Smart GridSlide17
Protection of the Power Transformer using Smart Grid SwitchingSlide18
The E+I paradigm
Energy-Plus-Information
Within each company: operations, maintenance…
Along the supply chain
Prosumers
with other stakeholders
Among
prosumers
/companies
For market transactions
E
Energy
Info
E
I
(E)+(I)
support
association
isolation
blending
(E+I)
digitization
TSlide19
Smart Grid Technologies are Supported on a Platform of IC/ICSInformation Communications (IC) synonymous term for Information and Communication Systems (ICS)Slide20
NIST Smart Grid FrameworkSlide21
Smart Grid Information NetworksSlide22
Dormant Threats”If you want to hit a country severely you hit its power and water supplies. Cyber technology can do this without shooting a single bullet.”Isaac Ben-Israel
Israeli military scientist, general and politician, currently the chairman of the Israeli Space Agency and the National Council for Research and Development, both at the Israel Ministry of Science and TechnologySlide23
Consequences of Pervasive ICSICS security requirements not always explicit
Standards lagging behind (IEC, ISO 7799)
Vulnerabilities
During whole life-cycle: design process, implementation, operation, maintenance.
ICS security policies and management
Threats:
All on-line systems are exposed to malicious actions (terrorism, organized crime, activists)
Connectiveness
: gate to insider threats
Complexity: human errors, systemic failures
Use of technologies with improper protection (wireless, internet …)
©2009 A. Gheorghe All Rights ReservedSlide24
Security Requirements Undermined by Security ThreatsSlide25
Security Solution = Technologies and PoliciesSlide26
Complex Problems
“We cannot solve problems by using the same kind of thinking we used when we created them.”
Albert Einstein
That is, anyone's knowledge and understanding is limited to his own experience, training, education, and information sources
Therefore, we must continue the advancement of science and knowledge, which expands the inventory of possible solutions to any problem often in COMPLEX waysSlide27Slide28
CIP-DSS History9-11 terrorist attacks on U.S.Department of Homeland Security (DHS)Need for risk assessment and management tools to protect the nation’s critical infrastructureDesire for “spreadsheet” table showing “risks” for many different “targets” and many different kinds of “attacks/failures”
28Slide29
Critical Infrastructure Sectors
29Slide30
Infrastructure Interdependencies
30Slide31
DHS view of “Risk”Threats:weapons of mass destruction (chem/bio/nuke); physical attack/disruption/failure; cyber attack/disruption/failure; major accidents; insider/outsider malevolent attack; natural disasters
System Vulnerabilities:
p
hysical; human; cyber; intellectual; dependencies; interdependencies
Consequences:
loss
of life; economic loss; environmental degradation; loss of property; loss of reputation/morale
31Slide32
Critical Infrastructure Protection – Decision Support System (CIP-DSS)Consists of a suite of interdependent infrastructure models Simulates propagation of disruptions across infrastructures Enables analysis of consequences in a complex “system of systems”
Offers risk-informed decision support to help identify investment strategies and other options to manage risk
Source:
B. Bus
h
32Slide33
CIP-DSS Vision
Source:
B. Bus
h
33Slide34
CIP-DSS Project Architecture
Source:
B. Bus
h
34Slide35
Example: Telecom Disruption
Source:
B. Bus
h
35Slide36
C4UCA non-profit and non-partisan think tank that:1) Offers products and services to solve clients’ problems in the area of global change and risk
We provide insight to our constituents in a time of increasing complexity and decreasing understanding
We help our constituents understand the ripple effects of their actions and how specific changes, events, and phenomena affect them
We do this by building on an existing massive intellectual and financial investment in systems models and deep data assets, cross-connected by a unique software framework
We use these assets in conjunction with an advanced decision-making tool and integrated visual analytics which allows our constituents an intuitive grasp of impact, alternative paths, and implications
2
)
Conducts
independent research in partnership with other scientific organizations
Applied Research in Modeling and Simulation
Research in Global Complexity and Interconnectedness
3)
Provides education and training to raise awareness on
The value
of
wide thinking
Global change and
risks in times
of increasing complexity
and
decreasing understanding
The ripple effects of actions and how specific changes, events, and phenomena affect them
36Slide37
37
FOCUS AREAS
SERVICES
AND PRODUCTS
Client Delivery
(business sustainment / money making activities)
SERVICES
Problem formulation
Team facilitation
Decision support
Solution communication
Investigate of specific Issues
Strategic reviews to Identify formerly unseen problems on the horizon
Stress tests of strategic plans
Watch services to monitor how these problems change over time
Facilitation of access to our models & data
Subscription Service to our models and data
PRODUCTS
Software (new models)
Access to our models & data
Frameworks and approaches
R & D
Model development
Database development
Tool building and development
White papers
Applied research in modeling and simulation
Research in global complexity and interconnectedness
Education
(non-profit
activities)
Education and awareness for general public
Executive training
Training modules
Keynote and motivational speeches
C
4
UCSlide38
Nominal OrganizationC4UC team is comprised of a dedicated and accomplished team of individuals that care about the mission and the consequences of no action.
38Slide39
Dr. Richard H.F. Jackson, Chief Executive Officer Founding Director, FIATECH and former Director, Manufacturing Engineering, NIST David M. Hammond, Chief Operating Officer
Senior Program Manager, US Coast Guard, Co-Founder and Executive Board Member, buildingSMART alliance, NIBS, and Co-Chair, Emerging IT, FFC, Nat’l Academy of Science
W. Bradley Holtz,
Chief Strategy Officer
co-founder & Chief Executive Officer, Cyon Research
Dr. John Cummings,
Chief Scientist
former
Director of R&D, Critical Infrastructure Protection, Department of Homeland Security
Dr. Adrian V. Gheorghe,
Int’l Science Director
Senior Research Scientist, National Centers of System of Systems Engineering, and Editor-in-Chief, International Journal of Critical Infrastructure
Dr. Miriam Heller,
Dir. of Model and Data Integrity
Founder/Principal of
MHITech
, Systems and Adjunct Professor, Energy and Climate Program, Johns Hopkins University,
Dr. Phares Noel,
Constituent Advocate
Adjunct Professor Computer Science, U of Michigan-Flint, and former Platform Executive, Advance Manufacturing Engineering Chrysler Corporation
Dr
. David Ullman,
Director of Decision Science
founder, Robust Decisions
Carolyn Castillo,
Business
Planning
Former
Program Management Specialist, Boeing and Senior Examiner for the California Council for
Excellence
Joseph Juhnke,
Director of
Visualization
President
& Chief Executive Officer,
Tanagram
Silvana Nani
, Director of Business Development
Serial entrepreneur (domestic and international), former associate at Booz Allen, former managing partner at
Domus-USA
Don Richardson,
Outreach
former
Senior Director of Global Innovation and PLM, Microsoft
Mike Riddle,
Director of Meta-Model Architecture
author of the software on which AutoCAD was based (Interact) and co-founder, Autodesk
Brian Seitz,
Systems Engineer
former
Chief Process Manager and Architect of IBM’s marketing process, and former Architecture and Methodology Senior Technologist, Microsoft
39
Roles and ResponsibilitiesSlide40
Partnership AgreementsSandia National Labs (MOU)
Argonne National Lab (MOU)
Santa Fe Institute
Stanford University
MIT
Los Alamos National Lab (Pending)
International Partners?
…
40Slide41
Legal and StructuralMaryland Incorporation Filing [completed]
IRS EIN [completed]
D&B Number [completed]
Establish Bank Account [completed]
501 (c) (3) filing IRS Form 1023 Filing (27mos) [in progress]
Intellectual Property Agreements [in progress]
Web Presence
41Slide42
Time to Wake Up – Jeremy Grantham, GMO
Days
of Abundant Resources
and Falling
Prices Are Over Forever
The
world is using up its natural resources at an alarming rate, and this has caused a permanent shift in their
value
We
all need to adjust our behavior to this new environment. It would help if we did it
quickly
42Slide43
A Transformed World :National Intelligence
Council Global
Trends
2025
The Globalizing Economy
The Demographics of Discord
The New Players
Scarcity in the Midst of Plenty?
Growing Potential for Conflict
Will the International System Be Up to the Challenges?
Power-Sharing in a Multipolar World
43Slide44
Global Risks 2011: World Economic Forum
Three important risks in
focus:
The “macroeconomic imbalances”
nexus
The “illegal economy”
nexus
The “water-food-energy”
nexus
Five risks to
watch:
Cyber-security
Demographic
challenges
Resource
security
Retrenchment from
globalization
Weapons of mass
destruction
44Slide45
Sustainable Energy Security: Lloyd’s
The changing dynamics of energy
demand and
resource
availability
Climate change and the drive
towards renewable energy
The risks associated with a new technology
revolution
Risks to energy and transport
infrastructure
Challenges and
risks
for global businesses
45Slide46
C4UC Contribution?
Establish relationships with “deep silo knowledge” partners
Modeling and analysis
Critical data and datasets
Subject-matter experts
Build “internal” expertise
Generalists and consultants
Analysts
Subject-matter experts when needed
Operational team
Get started
Solve
some
problems
Write some papers and “thought pieces”
Seek and earn recognition
46
C
4
UC team can leverage
the collective expertise
, knowledge of the
systems and players,
and
our Vision for a viable future to provide insight to decision makers and increase awareness and improve education among all audiences !Slide47
Models and MethodsFocus on Critical infrastructure systems
Interdependencies between coupled infrastructures
Performance measures for decision-making
47
Types of Interdependencies
Type of Failure
Infrastructure Characteristics
State of Operation
Context/
Performance
Coupling/
Response
Behavior
Loose/Tight
Linear/Complex
Escalating
Cascading
Common Cause
Spatial
Temporal
Operational
Organizational
Economic
Legal
/ Regulatory
Technical
Social
/Political
Physical
Cyber
Logical
Geographic
Adaptive
Inflexible
Stressed/
Disrupted
Repair/
Restoration
Normal
Business
Public
Policy
Security
EHS
Coupled Systems Framework
(after Rinaldi et al., 2002)Slide48
Models and MethodsSystem Dynamics Models (CIPDSS)Agent Based Models
(TRANSIMS)
Economic Models
Input-Output Economic Models
Computable General Equilibrium
Supply Chain
(
SuperNetworks
)
Probability, Risk & Decision Theoretic Models
Sector Specific Models
Hydrological/Hydraulic Models
Transportation Models
Network flows
(Integrated Transportation) Land Use Models
Continuum Models
Multiscale
,
multiphysics
Models
…
48
*
*Slide49
Modeling Tools InventoryBuilding an inventory of modeling tools
Sandia models: transportation, energy, economic, financial, chemical, agriculture and food, health, or integrated
Attributes: Product Name, Type of Capability, Purpose, Use
17 active + 4 inactive models
2 active Sandia models for use: FASTMAP for situational awareness and mapping; other is workbench supporting FASTMAP; proprietary data
19 Models can be run by Sandia with caveats
Reference Management System
49Slide50
Data: Conceptually and Sandia Examples Depends on model type and sector
Measured/sensed, estimated, projected, expert opinion, etc.
Physical assets: spatial, temporal, properties, etc.
Economic: resources/goods, pricing, costs,
elasticities
, demand, use supply, etc.
Survey data: census, health, household, etc.
…
Sandia examples
Rail data: Bureau of Transportation Statistics-Commodity Flow Survey, Association of American Railroads-“Class I Railroad Statistics”
Air data: Origin and Destination Survey (DB1B) of domestic passenger airline tickets
Chemical data: Directory of Chemical Producers from SRI Consulting
Banking and finance data: FDIC institutions
geolocated
, depositors, and accounts on deposit
…
50Slide51
SimSUWER Example: Problem Background
WASTEWATER COLLECTION SYSTEMSlide52
July 2003 - M. Heller ©SimSUWER
: Causal Loop
DiagramSlide53
SimSUWER Past and FutureNSF funded $900K + City of Houston $500KSystem Dynamics Model implemented in
PowerSim
26 stocks; 42 flows: 122 auxiliaries, 56 constants and 295 links representing interactions
Six components: Inputs, Treatment, Relief Options, Finance, Indicators, User Interface
Model use and evaluation
Scenario analysis varying number of
SSOs
, annual complaints, wastewater fund behavior
Clarifier option dominated all others in all performance variables
Way ahead:
SimSUWER as foundation for Baltimore City’s SSO problem
Add climate change impacts,
TMDLs
issues, green infrastructure options
Enhance with independencies to capture water-energy nexus effects
Engage stakeholders for Robust Decision Making
53Slide54
Why run simulations?
To support making decisions.
But, cant simulation results give the optimum solution?
Maybe in your perfect world, but imperfect models are used to predict the future
The science that provides the data to the models is often uncertain
Some things are not really modelable
There are many stakeholders
“When you cannot measure it…your knowledge is of meager and unsatisfactory kind
” Lord Kelvin
“
Oh, well, if you cannot measure, measure anyhow
”. Dr. Frank Knight
“Prediction is very difficult, especially about the future”. Niels Bohr Slide55
So what if there are many stakeholders?
They all value different things. These different value sets must be honored
What does it take to get stakeholder buy-in?
To make the decision “stick” you need to develop their buy-n
The stakeholders each interpret and believe the results of the simulations in his/her own contextSlide56
C4
UC
Ecosystem
56
CLIENTS
PARTNERS
(Science Community)
PARTNERS
(Universities & Organizations)
STAKEHOLDERS
(Strategic Partners)
ORGANIZATIONS
PUBLIC
Non For Profit Activities
Sustaining Activities
Products & Services
P&S,
R&D,
White Papers
R&D, Studies
White Papers
R&D, Studies
White Papers
Education
& Training
EducationSlide57Slide58
58 THANK YOU !