Pivotal Technologies to Enable the Intelligent...
Transcript of Pivotal Technologies to Enable the Intelligent...
UNIVERSITY OF MINNESOTAINSTITUTE OF TECHNOLOGY Copyright © 2006 No part of this presentation may be
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Pivotal Technologies to Enable the Intelligent Infrastructure
presentation at theEPRI 2006 Summer Seminar
Advancing Energy Efficiency and End-Use Technologies: “Prices to Devices”
August 7, 2006Massoud Amin, D.Sc.CDTL Director and H. W. Sweatt Chair in Technological LeadershipProfessor, Electrical & Computer EngineeringSome of the material and findings for this presentation were developed while the author was at the Electric Power Research Institute (EPRI) in Palo Alto, CA. EPRI’s support and feedback is gratefully acknowledged.
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Context: Economics, Efficiency, Environment, Electric Power, Communications & Adaptive Dynamic Systems
Dynamic Systems
EconomicsEfficiencyIncentives
Private Good
Electric PowerReliability
Public Good
-- Complex, highly nonlinear infrastructure -- Rules being modified: evolving development of markets, rules and designs “if you measure it you manage it if you price it you manage it”…Tech & options risk/valuation
“Prices to Devices”
Society (incl. Policy & Environment)
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Recent Directions: EPRI/DOD Complex Interactive Network/Systems Initiative (CIN/SI)
Complex interactive networks:• Energy infrastructure: Electric power
grids, water, oil and gas pipelines• Telecommunication: Information,
communications and satellite networks; sensor and measurement systems and other continuous information flow systems
• Transportation and distribution networks• Energy markets, banking and finance
1999-2001: $5.2M / year —Equally Funded by DoD/EPRI
“We are sick and tired of them and they had better change!”Chicago Mayor Richard Daley on the August 1999 Blackout
Develop tools that enable secure, robust and reliable operation of interdependent infrastructures
with distributed intelligence and self-healing abilities
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FailureAnalysis
Information&
Sensing Vulnerability Assessment
Self Healing Strategies
StrategyDeployment
GPS
Sate
llite
LE
O
Sate
llite
Intr
anet
Inte
rnet
Dynamic Systems: Complex Interactive Networks
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Dynamic Systems: Network Centric Warfare
Direct Fire Function *
Infantry Carrier Function
Indirect Fire Function*
Sensor Function*
* Manned or unmanned
Organic & inorganic
RSTA
Networked Comms
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Dynamic Systems: CIN/SI Funded Consortia
• U Washington, Arizona St., Iowa St., VPI
• Purdue, U Tennessee, Fisk U, TVA, ComEd
• Harvard, UMass, Boston, MIT, Washington U.
• Cornell, UC-Berkeley, GWU, Illinois, Washington St., Wisconsin
• CMU, RPI, UTAM, Minnesota, Illinois
• Cal Tech, MIT, Illinois, UC-SB, UCLA, Stanford
107 professors in 28 U.S. universities are funded: Over 360 publications, and 19 technologies extracted, in the 3-year initiative
- Defense Against Catastrophic Failures, Vulnerability Assessment
- Intelligent Management of the Power Grid
- Modeling and Diagnosis Methods
- Minimizing Failures While Maintaining Efficiency / Stochastic Analysis of Network Performance
- Context Dependent Network Agents
- Mathematical Foundations: Efficiency & Robustness of Distributed Systems
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Tools: EPRI/DOD Complex Interactive Network/Systems Initiative (CIN/SI)Tools:• Dynamical systems• Statistical physics• Information & communication science• Computational complexity
To measure and model coupled large-scale systems including:• Electricity Infrastructure• Telecommunication networks• Economic markets• Cell phone networks and the Internet• Other complex systems
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Background:Dynamical Systems and The Self Healing Grid
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Background: The Case of the Missing Wing
NASA/MDA/WU IFCS: NASA Ames Research Center, NASA Dryden Flight Research Center, Boeing Phantom Works, and Washington University in St. Louis.
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Goal: Optimize controls to compensate for damage or failure conditions of the aircraft*
NASA/MDA/WU IFCS
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Roll Axis Response of the Intelligent Flight Control System
=
0 0 .5 1 1 .5 2 2 .5 3 3 .5 4 4 .5-4 -2 0 2 IF C S D A G 0 fu l l la te ra l s t ic k ro l l a t 2 0 ,0 0 0 f t , 0 .7 5 M a c h , F l t 1 2 6
0 0 .5 1 1 .5 2 2 .5 3 3 .5 4 4 .5
-2 0 0 -1 0 0
0
t im e [s e c ]
C o m m a n d e dO b ta in e d
la te ra l s t ic k( in c h e s )
ro ll ra te (d e g /s e c )
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Accomplishments in the IFCS program
• The system was successfully test flown on a test F-15 at the NASA Dryden Flight Research Center:
– Fifteen test flights were accomplished, including flight path control in a test flight envelope with supersonic flight conditions.
– Maneuvers included 4g turns, split S, tracking, formation flight, and maximum afterburner acceleration to supersonic flight.
• Stochastic Optimal Feedforward and Feedback Technique (SOFFT) continuously optimizes controls to compensate for damage or failure conditions of the aircraft.
• Flight controller uses an on-line solution of the Riccati equation containing the neural network stability derivative data to continuously optimize feedback gains.
• Development team: NASA Ames Research Center, NASA Dryden Flight Research Center, Boeing Phantom Works, and Washington University.
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Dynamic Systems and Communications: Present scheme for control of a power system
• All real time information is gathered and sent to a central site
• Central site maintains data base to model the power system network (updated by hand)
• Software applications control system through commands sent back down to the plants and substations
University of Minnesota Center for Smart Grid Technologies
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Communication RequirementsPower System Tasks Bandwidth Current
Requirement Response TimeLoad Shedding (Local Decision) Low SecondsAdaptive Relaying (e.g., Blocking relay) Low Not AvailableHierarchical Data Acquisition and Transfer High Seconds (e.g., 2-12
seconds / scan for RTUs)
Line / Bus Reconfiguration Low Minutes (manual)
Control Devices (e.g., FACTS, Transformer,… ) Medium Seconds (by manual)
Fault Event Recorder Information Medium Minutes
Generator Control Low SecondsPower Infrastructure Defense & High Not ApplicableCoordination with Control Centers (EPRI/DoD CINSI)
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Protection Schemes & Communication Requirements
Type of relay Data Volume (kb/s) Latency
Present Future Primary (ms)
Secondary (s)
Over current protection 160 2500 4-8 0.3-1
Differential protection 70 1100 4-8 0.3-1
Distance protection 140 2200 4-8 0.3-1
Load shedding 370 4400 0.06-0.1 (s)
Adaptive multi terminal 200 3300 4-8 0.3-1
Adaptive out of step 1100 13000 Depends on the disturbance
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Communication, Controls, Dynamical systems and Information Technology (e.g. unrelenting “Moore’s Law”)
Source: Intel’s Silicon Showcase, http://www.intel.com/research/silicon/mooreslaw.htmThe promise of nano includes keeping Moore’s Law moving along
Gordon Moore• Principles of operation for power systems were established in the 1960s prior to the emergence of extensive computer and communication networks.
• Computation is now heavily used in all levels of the power network-for planning and optimization, fast local control of equipment, processing of field data.
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Future of End-Use Technologies
•End-Use Technology and Access Evolution
•The Emergence of Always On
•Powering Evolution:Batteries and Nanotech… plastic batteries with up to 8 times its nominal capacity charged in less than a minute.
•Processing Evolution:On a single fiber optic you can carry all the information in the World! Shannon’s theory applies to single channel, not to a cellular fiber optic network. N+1 receivers are separated by ½ a wavelength, can separate interference by boosting processing power
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Smart dynamic system scheme
• Each device has its own processor which can act as an independent agent
• Each device knows what other devices it is connected to and can communicate with those devices’ processors
• Central site data base updated automatically when new devices are connected
• Fast control can be achieved when necessary through agents’ local decisions
University of Minnesota Center for Smart Grid Technologies
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Each device has its own processor: Smart, adaptive, network addressable devices
University of Minnesota Center for Smart Grid Technologies
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Processors are connected by secure communications
University of Minnesota Center for Smart Grid Technologies
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Addition of new device
University of Minnesota Center for Smart Grid Technologies
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New device is also connected to information layer
University of Minnesota Center for Smart Grid Technologies
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S&T Assessment, Scan and Map(April 2005-Feb 2006; Galvin Electricity Initiative, Task 3, Phase 1)
Objectives:• Identify the most significant Science &
Technology innovations which would meet energy service needs over the next 10 or 20 years.
• Determine Science & Technologies areas and concepts which address customer aspirations and hopes:– Technologies that encourage job creation and address
the needs of the society;– An energy system so robust and resilient that it will not
fail; – A totally reliable, secure communication system that will
not fail.Source: Galvin Electricity Initiative www.galvinelectricity.org
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Technology Scanning Process - Evaluation
Information Science
Physical Science
Life Science.
.
Leading
Capable
Strong
High
Medium
Low
Power Zone
Strategic Selection in Technology
Space
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Examples of Technology strengths of the industry today
Information Science
Physical Science
leading
strong
capable
14
Industry Application Status
Industry’sTechnology
PowerZone™™
Examples of Technology strengths of the industry today include:1.Power Electronics2.Adv. Electric motors3.Wind generation4.Nuclear Power5.Solar power6.Systems integration7.Real-time systems control8.Personal storage devices9.Power conditioning10.Efficient illumination11.Emission control12.Turbine generation13.Adv. Materials technology14.Security technology
3
2
1
6
4
7
5
9
812
10
13
11
Bio- and Life Sciences
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Expanding the Power Zone
Physical Biological
InfoA. Distributed controlB. Electronic power commerceC. Distributed generation/storageD. Integrated common infrastructureE. Integrated/Embedded PV
AB
C
D
E
F Wireless backupG Granular Semi-autonomous ArchitectureH Fractal Grid Lego ModelI Lego ModelJ Plug and play appliancesF
G
J
H
I
Technology Map for the Granular Semi-Autonomous Architecture
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Expanding and Transforming the Power Zone
Information Science
Physical Science
Bio./LifeScience
17
2 5
63
8
4
Bench-marking
Existing Power Zone
ExtendedPower Zone
Technology Map for Bio-fuel Systems, Distributed Gen and Storage systems integrated with Advanced Information Systems for Network Management
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R& D Strategies and Examples of Technology areas
Develop into
Products
Identify Real Applications to Pull Technology
High Potential --Elaborate,
Expand, Drive Investment
Alliances, Government,
University
Not strategic - evaluate as
separate opportunity
Sustain and Grow-Industry and other
resources
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Toward High Reliability Infrastructures: We have a bright future if we challenge the best minds and marshal their talents…
• Integrated System Assessment, Efficiency, Security & Interoperability Integrated Secure Communication
• Intelligent data management and adaptive use• Realistic and scalable models, estimation and
control• Transformation of the meter and end-use devices
into a two-way energy/information dynamic systemsIncreased dependence on sensing, IT and software
• Dependability/security/robustness is the key… V&V remains a big challenge
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Toward High Reliability Infrastructures: We have a bright future if we challenge the best minds and marshal their talents…
• Intelligent sensors as elements in real-time data base; seek appropriate high level query tools for such a database? Sensor interface to models? Metrics? Business case and impact.
• Coupling to smart devices/sensors, state estimation, dynamic monitoring, simulation, identification, disturbance analysis
• Wide-area layered fail-safe control, sensing, communication and control mix/placement
• Integration of distributed energy resource into the network
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Research Challenges: Need new technologies analogous to putting the “man on the moon,” with the urgency of the Manhattan Project
• Broad range of R&D including Dynamical Systems with impact of all pertinent interactive layers:– Dynamic Coupled Systems: Fuel options, distributed
generation, T&D, Secure Communication and Protection layers
– Electricity Markets and Policy/Regulatory layers– Ownership and investor layer (investment signals);
economic evaluations– Customers layer (demand response, smart meters,
reliability/security/quality)
– System and End-use efficiency, including technologies and the built environment, urban and building design
– Environment: Adaptation measures and costs
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