Interdependendies in Civil Infrastructure Systems

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  • Good afternoon. I’m Miriam Heller. I’m a program director at the NSF in the area of Infrastructure and Information Systems. First I’d like to thank the NAE and the organizing committee for finding a way to reschedule this event. I’m delighted to be here to have the opportunity to share some of my ideas (note I’m not representing NSF’s). It’s also wonderful that we were able to move forward despite the devastating events of 911. I’m going to overview of how infrastructure systems have become complex beyond comprehension, with more far-reaching effects than were ever anticipated to a large degree due to automation but due to other “dependencies” as well. I would like to note that Drs. Feniosky Pena-Mora and Linda Nozick’s also talked about civil infrastructure, risk and disaster. This is a testament to the emerging concerns with infrastructure and how dependent our security and way of life is on them.
  • Just to be very clear, because it’s always good to have definitions, I’m providing a definition of Infrastructure systems: They are Networks, meaning they are representable as nodes and arcs) of facilities and institutions that Support the fow of people, energy, other resources, goods, information, and basic services Essential to human life, economic well-being, and national security.
  • Certain infrastructures were labelled as critical in Presidential Decision Directive 63. Concerns over infrastructure security had grown after the World Trade Center Bombing in 1994 and the Oklahoma City bombing in 1995. Dependencies on cyberinfrastructure were growing as Y2K approached. Not surprisingly, much work was done, primarily on cybersecurity and electrical systems, which drive the cyber systems. The newly established Office of Homeland Security is a direct outgrowth of much of this focus, with half the organization head by Dick Clark who focuses on cybersecurity.
  • Information systems hold the key to the efficient planning, design, construction, operation, maintenance, and retirement of our nation's very valuable civil infrastructure assets. Information systems are already being integrated into infrastructure operations to exploit new technologies, compensate for capacity limitations, address regulatory changes, increase efficiency, and protect against natural, accidental, and deliberate threats. Integrated information-infrastructure systems drive traffic signals and variable message signs on roadways and bridges, monitor potable water quality at treatment plants, pump water and wastewater, and activate switches in telecommunications systems that command transportation and water networks. All of these capabilities are enabled by energy and power infrastructures, which, in turn, depend on even more information infrastructure. In short, information systems can make or break civil infrastructure.
  • Integrated information systems have substantially improved unit-level and component-level operating efficiencies in transportation, water, telecommunications, and power infrastructures, just to name a few. The benefits include increased accuracy, expanded and improved services and products, reduced capacity needs, higher utilization, and lower costs. Theory suggests that further efficiencies are achievable by integrating information systems at increasingly higher levels: the subsystem level, the system level, and even across infrastructure systems. Despite this sanguine thought, history suggests, that further efficiencies from automation might be difficult to realize because of trade-offs with induced vulnerabilities. Data Sharing means Shared Databases, Reduced Redundant Resources, and Optimization at the plant level of raw water production, treatment, and distribution as well as support applications in engineering, maintenance, human resources, regulatory affairs, customer billing, and service, can communicate with one another and share information. Moreover, proprietary information exchanges on electricity consumption can be made with the local electric distribution company, who might be contracted out to read customer meters. Finally, the utility, the customers, and the vendors can access global information, such as regulations, rates and equipment, using the internet.
  • My original paper makes tangible the “interdependencies concept” using the California power system as an example, citing how rate restructuring and “deregulation” affected natural gas delivery, manufacturing, agricultural irrigation in-state, Idaho potato production out-of-state, air quality, and salmon spawning. Right after the attacks on 911, all eight critical infrastructures disrupted. Live on TV, Americans watched the air transportation infrastructure itself destroyed and subverted to destroy another structure, which housed the single most concentrated seat of banking and finance infrastructure in the world, as well as the state Department of Transportation offices, and myriad telecommunications satellite dishes and relays perched on the Towers. Strewn plane debris and the progressive collapse of Twin Towers cascaded into the collapse of building 7, which housed a ConEd substation, disrupting the densest power grid system in the world while setting aflame fuel stored in Tower 7. Bulding 7 also housed the Office of Emergency Management along with much needed data to manage the response. telecommunications services headquartered in the adjacent Verizon building were also curtailment. As debris penetrated the ground, flooding and crumbling of the Chamber Street subway station, broken water mains, and blockages of wastewater conveyance systems.
  • The size and frequency of electricity disturbances was also recently shown to obey the power law (Amin, 2001).
  • Rinaldi et al. (2001) have proposed a general framework for characterizing infrastructure interdependencies. The framework identifies infrastructure systems as CASs and provides details for developing agent-based simulations (ABSs) of complex systems. The authors identify six dimensions of infrastructure interdependencies: infrastructure environment, coupling, response behavior, failure types, infrastructure characteristics, and state of operation. Analyzing infrastructure in these terms yields new insights into infrastructure interdependencies. They also identify four types of interdependencies: physical, cyber, logical, and geographical. In a physical interdependency, the states of two infrastructures (e.g., a coal-transporting rail network and a coal-fired electrical plant that supplies the power to that rail network) depend on the material output of both. Other interesting issues are also raised, including requirements for an information architecture; data capture, storage, and privacy; and model metrics. Haimes and Jiang (2001) extend Leontief's economic input-output models to evaluate the risk of inoperability in interconnected infrastructures as a result of one or more failures subject to risk management resource constraints. Interdependence is captured in Leontief's production coefficients, which here represent the probability of an interconnected infrastructure component propagating inoperability to another component. Thus, infrastructures are interdependent through failure propagation, specified in geographical, functional, temporal, and political dimensions, and through the allocation of limited resources for risk management.   Another approach based on economics by Friesz et al. (2001) defines a spatial computable general equilibrium (SCGE) model of an economy comprised of spatially separated markets interconnected by a generalized transportation network. Interdependencies can be physical, budgetary, market-based or spatio-economically competitive, information-based, or environmental.
  • Integrated information systems have substantially improved unit-level and component-level operating efficiencies in transportation, water, telecommunications, and power infrastructures, just to name a few. The benefits include increased accuracy, expanded and improved services and products, reduced capacity needs, higher utilization, and lower costs. Theory suggests that further efficiencies are achievable by integrating information systems at increasingly higher levels: the subsystem level, the system level, and even across infrastructure systems. Despite this sanguine thought, history suggests, that further efficiencies from automation might be difficult to realize because of trade-offs with induced vulnerabilities. Data Sharing means Shared Databases, Reduced Redundant Resources, and Optimization at the plant level of raw water production, treatment, and distribution as well as support applications in engineering, maintenance, human resources, regulatory affairs, customer billing, and service, can communicate with one another and share information. Moreover, proprietary information exchanges on electricity consumption can be made with the local electric distribution company, who might be contracted out to read customer meters. Finally, the utility, the customers, and the vendors can access global information, such as regulations, rates and equipment, using the internet.
  • Colorado Springs Utilities, an innovative western water utility that has been researching multiple uses of water resources, estimates the benefits would be worth more than $30,000-50,000 per year, not including windfalls from high electricity prices (Jentgen, 2001). Their energy and water quality management system (EWQMS) is conceptually an extension of electric utilities' energy management systems (EMSs), which include power generation control and real-time power systems analysis. Some aspects of the EWQMS can be substantially more complicated than EMS. For example, in an EWQMS where hydropower is an option, decisions about pumped storage are coupled with the selection of electricity sources to exploit time-of-day electricity pricing. Alternatively, if spot market prices are exorbitant, hydropower might best be used to generate electricity for sale. Whereas EMS's power generation control has a short-term load-forecasting component, the EWQMS has two sets of demands to predict and satisfy: one for electricity and one for water. In addition, scheduling decisions must also consider what quantity of raw water from which source is subject to water rights and quantity and quality constraints, given variable pumping costs; what quantity of water to treat at which plant, given variable treatment costs; and what pumps to use for distribution, collection, and wastewater treatment and which ones to take off line for maintenance. This case study shows how shared resources can simultaneously improve efficiency and reduce vulnerability through resource reuse. Heller et al. (1999) discuss the concept of shared resources as a means of achieving regional eco-efficiency. In this context, information system boundaries are extended to coordinate the shared production, consumption, treatment, or reuse of electricity, water, and wastewater resources among regional utilities and manufacturing facilities.
  • Integrated information systems have substantially improved unit-level and component-level operating efficiencies in transportation, water, telecommunications, and power infrastructures, just to name a few. The benefits include increased accuracy, expanded and improved services and products, reduced capacity needs, higher utilization, and lower costs. Theory suggests that further efficiencies are achievable by integrating information systems at increasingly higher levels: the subsystem level, the system level, and even across infrastructure systems. I’ll share some information about a pilot effort that involved reaching some of the higher levels of integrated information at the end of the talk. Despite this sanguine thought, history suggests, that further efficiencies from automation might be difficult to realize because of trade-offs with induced vulnerabilities.
  • Dynamic or Adaptive Routing Demand Responsive Transit En-route commerce In-transit Trading Options Pricing
  • Joint solicitation and funding to further the understanding of the dynamics of complex interactive infrastructures and the development of secure operating methodologies and strategies. Collaboration between Electric Power Research Institute (EPRI) and the Office of the Director of Defense Research and Engineering (ODDR&E), with the Army Research Office (ARO) as the agent for ODDR&E.
  • Post-event analysis Putting in place community-based emergency response plans
  • Interdependendies in Civil Infrastructure Systems

    1. 1. Information Technology and Infrastructure: Benefits, Costs, and Dependencies MIRIAM HELLER, Ph.D. NATO SCIENCE PROGRAMME in conjunction with the Carnegie Bosch Institute ADVANCED RESEARCH WORKSHOP   Life Cycle Analysis for Assessing Energy and Environmental Implications of Information Technology Budapest, Hungary September 2, 2003
    2. 2. Messages <ul><li>ICT Confers Benefits To Infrastructure Systems; (Avoided) Costs May Be Easier to Quantify </li></ul><ul><li>Infrastructure Systems Differ from Other Manufacturing and Service Systems </li></ul><ul><li>Infrastructure Dependencies May Give Way to Indirect Environmental and Energy Consequences, Which Could Figure Into Life Cycle Cost/Benefit Analysis of ICT and Infrastructure System Planning and Management </li></ul>
    3. 3. TOPICS <ul><li>Infrastructure Systems </li></ul><ul><li>Infrastructure Interdependencies </li></ul><ul><li>Benefits and Costs of IT and Infrastructure Systems </li></ul><ul><li>Related IT and Infrastructure Research </li></ul><ul><ul><li>Cyber* Futures at NSF </li></ul></ul><ul><li>Challenges for Research </li></ul>
    4. 4. A Definition of Infrastructure Systems <ul><li>Networks of facilities and institutions </li></ul><ul><li>Essential to life, economic well-being, and national security. </li></ul><ul><li>Support the flow of people, energy, other resources, goods, information, and basic services </li></ul>
    5. 5. Critical Infrastructures (PDD 63) Potable & Waste Water Banking & Insurance Government Emergency Response Transportation Oil & Gas Electricity Telecom-munications
    6. 6. Integrated Information Systems Transportation Water Treatment Oil & Gas Power Information Technology & Telecom
    7. 7. ICT Benefits for Infrastructure Systems Tim e Performance and Efficiency Baseline from Core Utility Processes (Adapted from Heller et al.,1999) Automated Monitoring, Sensing, Data Acquisition Process Control / Supervision Shared Objectives Enterprise Architecture Enterprise Integration/ Optimization Shared Data Communications Architecture Product Integration/ Interoperability Industrial Ecology Community Eco-efficiency/ Sustainability Shared Resources / Environment
    8. 8. Infrastructure Systems: Some Reflections <ul><li>Differ from Manufacturing Systems </li></ul><ul><ul><li>Provide critical services / lifelines </li></ul></ul><ul><ul><li>Geographically distributed </li></ul></ul><ul><ul><li>One-offs with many degrees of freedom </li></ul></ul><ul><ul><li>Highly interconnected </li></ul></ul><ul><ul><li>Subject to uncertain and uncontrollable ambient conditions </li></ul></ul><ul><li>Life-Cycle Modeling Differences </li></ul><ul><ul><li>Uncertainty </li></ul></ul><ul><ul><ul><li>High consequence / low probability events vs. slow consequence / high probability events </li></ul></ul></ul><ul><ul><ul><li>Life-span definition (whole-life) </li></ul></ul></ul><ul><ul><li>Complexity </li></ul></ul>
    9. 9. Infrastructure Interdependencies Transportation Oil & Natural Gas E L E C T R I C I T Y Potable & Waste Water Emergency Response Government I T & T E L E C O M Banking & Finance Switches, control systems Storage, pumps, control systems, compressors e-commerce, IT Pumps, lifts, control systems Signalization, switches, control systems e-government, IT Medical equipment Water for cooling, emissions control Water for production, cooling, emissions control Fire suppression Cooling Fuel transport, shipping Fuel transport, shipping Chemicals transport Transport of emergency personnel, injured, evacuation Communications SCADA SCADA Trading, transfers SCADA Communications Location, EM contact Generator fuels, lubricants Heat Fuels, lubricants Fuels, Heat Currency (US Treasury; Federal Reserve ) DOE;DOT Regulations & enforcement FERC; DOE Personnel/Equipment (Military) Financing, regulations, & enforcement SEC; IRS FEMA; DOT DOT EPA Detection, 1 st responders, repair Financing & policies Financing & policies
    10. 10. Science of Engineered Networks K öningsberg on the Pregel River with 7 bridges. Cross each bridge exactly once and return to starting position. In 1736, Leonhard Euler the Swiss Mathematician idealized this as a system of nodes and arcs. Euler proved that it cannot be done unless every node is connected to every other with even degree.
    11. 11. <ul><li>Random networks, generated by randomly connecting a new node with an existing node, have on average, the same number of connections per node, e.g., National Highway System (Barabási, 2002). Distribution of nodes connections is normal. </li></ul><ul><li>Scale-free networks (WWW, air traffic </li></ul><ul><li>routes, social networks) arise when new nodes connect preferentially to already well-connected nodes. Most nodes have few connections: a few nodes are heavily connected hubs. Distribution of nodes connections follows a power law. </li></ul>Science of Engineered Networks: Dependencies
    12. 12. Power Grid Outages Follow Power Law Frequency (per year) of outages > N Data from NERC (Amin, 9/10/01) 10 4 10 5 10 6 10 7 10 -2 10 -1 10 0 10 1 N= # of customers affected by outage US Power outages 1984-1997 August 10, 1996
    13. 13. ICT Impacts Infrastructure Systems Example: 2001 California Power Crisis <ul><li>Disrupted fuel production, refining, and distribution, sometimes cut off fuel supplies to the very plants that should have been generating their electricity </li></ul><ul><li>Interrupted water distribution affected the state's agribusiness </li></ul><ul><li>Soaring wholesale power prices impacts rippled through the region, leading to relaxation of salmon-protection and air-quality regulations and shutdown of aluminum mills in Washington state. Idaho farmers curtailed potato production to exploit Idaho Power Company's electricity buy-back program </li></ul>
    14. 14. Coupled Systems Frameworks : Rinaldi et al., 2001 Type of Failure Infrastructure Characteristics State of Operation Types of Interdependencies Environment Coupling/ Response Behavior Natural Environment ? Loose/Tight Linear/Complex Escalating Cascading Common Cause Spatial Temporal Operational Organizational Economic Legal/ Regulatory Technical Social/ Political <ul><li>Physical </li></ul><ul><li>Cyber </li></ul><ul><li>Logical </li></ul><ul><ul><li>Geographic </li></ul></ul>Adaptive Inflexible Stressed/ Disrupted Repair/ Restoration Normal Business Public Policy Security Health/ Safety
    15. 15. State of the Water/Wastewater System <ul><li>Size </li></ul><ul><ul><li>15,000 Publicly-Owned Wastewater Treatment Plants </li></ul></ul><ul><ul><li>100,000 Pumping Stations </li></ul></ul><ul><ul><li>160,000 Public Potable Water Systems </li></ul></ul><ul><li>Operations </li></ul><ul><ul><li>Accounts for 3-7% Total US Electricity Consumption </li></ul></ul><ul><ul><li>ASCE Estimates $12 Billion Needed for Maintenance 2012 </li></ul></ul>
    16. 16. ICT Benefits for Water/Wastewater Systems Tim e Performance and Efficiency Baseline from Core Utility Processes (Adapted from Heller et al.,1999) Process Level IT (SCADA, GIS, EMS, CIS, MMS, LIMS, hydraulic, water quality, and distribution network models  Reduced Chemical and Energy Consumption, Lower Operating Costs, Improved Regulatory Compliance, Higher Reliability, and Improved Customer Service, Inventory Control, and Maintenance Management Shared Objectives Utility Business Architecture Utility Integration/ Optimization Shared Data Utility Communications Architecture Plant Integration/ Interoperability Automated Monitoring, Sensing, Data Acquisition Process Control / Supervision
    17. 17. Harnassing Complexity through Shared Resources Energy and Water Quality Management Systems (Jentgen, 2001) Energy Cost Scheduler (Electric Utility) Operations Water Quality Analyzer Water Source Analyzer Raw Water Supply/ Water Treatment Plant Pump Stations Wastewater Treatment Plant Distribution Customer Collection Consumption Forecast Program Automated Maintenance Management System Water Consumption Forecast Management Scheduler Clearance Approvals System Operating Plan Schedule & Control Operating Plan Clearance Work Orders Water Law Water Rights Water Priorities Performance Criteria Hydro Schedule Energy Cost Schedule Interruption Scheduler Signal Water Resource Schedule/Constraints Water Quality Alarms SCADA Data Water Quality Operating Constraints Water Quality Data Utility’s Historical Operating Data Performance Criteria Lab & Field Samples Operating Plan Regulations Power Supply Contract Terms/Conditions Power Suppliers’ Price Schedule Operations Planner & Scheduler System Scheduler: Surface Water Treatment Plant Pump Stations Distribution Customer Collection Wastewater Treatment
    18. 18. Potential ICT Benefits for Water/Wastewater Shared Resources / Environment Shared Data Tim e Performance and Efficiency Shared Objectives Baseline from Core Utility Processes Process Plant Utility/Facility Control / Integration/ Integration/ Supervision Interoperability Optimization (Adapted from Heller et al.,1999) Automated Monitoring, Sensing, Data Acquisition Utility Communications Architecture Utility Business Architecture Industrial Ecology Regional Eco-efficiency/ Sustainability
    19. 19. Industrial Symbiosis Example: Baytown’s Water Infrastructure (Nobel & Allen, 1998) <ul><li>21 process, 5 utility streams </li></ul><ul><li>75 feasible reuse pathways identified </li></ul>
    20. 20. Linear Program Formulation <ul><li>Exchange Feasibility </li></ul><ul><li>Based on water quality parameters (e.g., TOC, TSS, TDS) </li></ul><ul><li>Creates input for cost optimization </li></ul><ul><ul><li>feasible exchange pathways, i.e., “arcs” </li></ul></ul><ul><ul><li>“ type” of water </li></ul></ul><ul><ul><li>transportation costs </li></ul></ul>I2 GC WTP WWTP I1 I3 Fresh Reclaimed Reused Disposed
    21. 21. Industrial Symbiosis: Optimal Water Use (Nobel & Allen, 1998) Metrics Scenario mgd %  $/day %  Base Case 8.71 - 108,554 - Minimum Cost 1.05 -88% 57,165 -47% Minimum Fresh Water 0.26 -97% 85,098 -22% Fresh Water Usage Cost
    22. 22. ICT Benefits for Oil and Gas Infrastructure Example: BP’s Texas City Plant <ul><li>“ Project Future” (Bylinsky, Fortune, “Elite Factories,” 9/1/2003) </li></ul><ul><ul><li>Combined Refinery / Petrochemical Plant </li></ul></ul><ul><ul><li>$30 bbl Oil  $60 of Gasoline, Diesel, Jet Fuel, p-Xylene </li></ul></ul><ul><ul><li>2,740 Employees </li></ul></ul><ul><ul><li>2-year, $75 Million Investment in Computerization and Automation of 650 Key Valves </li></ul></ul><ul><li>Returns On Investment </li></ul><ul><ul><li>Start-up Time Reduced from 2 Weeks to 3.5 Days </li></ul></ul><ul><ul><li>Real-Time Equipment Setpoints Based on Ambient Temperature, Weather, and Product Prices </li></ul></ul><ul><ul><li>3% Less Electricity Used </li></ul></ul><ul><ul><li>10% Less Natural Gas Used </li></ul></ul><ul><ul><li>55% Increase in Productivity </li></ul></ul>} $ Millions and Tons GHG Saved
    23. 23. State of Oil and Gas Infrastructure Systems <ul><li>Size </li></ul><ul><ul><li>Ports, Refineries, Transportation </li></ul></ul><ul><ul><li>2,000 Petroleum Terminals </li></ul></ul><ul><ul><li>Almost 1 Million Wells </li></ul></ul><ul><ul><li>2,000,000 Miles of Oil Pipelines </li></ul></ul><ul><ul><li>1,300,000 Miles of Gas Pipelines and Increasing </li></ul></ul><ul><li>Operations </li></ul><ul><ul><li>Pipeline and Distribution System </li></ul></ul><ul><ul><ul><li>Leak Detection </li></ul></ul></ul><ul><ul><ul><li>Monitoring and Control Systems </li></ul></ul></ul><ul><ul><ul><li>More Efficient Use of Existing Pipe </li></ul></ul></ul><ul><ul><ul><li>Aging </li></ul></ul></ul><ul><li>Coupled Economic Models on Natural Gas and Electric Power </li></ul>
    24. 24. State of the Transportation System <ul><li>Size </li></ul><ul><ul><li>125,000 Miles of National Highway System </li></ul></ul><ul><ul><li>25,000 Miles of Public Roads </li></ul></ul><ul><ul><li>3.76 Million Miles of Other Roads </li></ul></ul><ul><li>Operations </li></ul><ul><ul><li>FHWA : > $78 Billion / Year Idled Away in Congestion </li></ul></ul><ul><ul><li>50% Total US Petroleum Consumed by Highway Vehicles </li></ul></ul><ul><ul><li>> 1/3 GHG Due to Surface Transportation </li></ul></ul><ul><ul><li>Major Source of Photochemical Smog and Other Air Pollution </li></ul></ul><ul><ul><li>> 40,000 Fatalities / Year Over Past Decade </li></ul></ul>
    25. 25. Potential ICT Benefits for Transportation <ul><li>Inform on-line buyers of environmental impacts of shipping options (NAE, 1994; Hawken et al., 1999; Sui & Rejeski, 2002) </li></ul><ul><ul><li>Ship or rail: 400-500 BTU/ton-mile </li></ul></ul><ul><ul><li>Truck : >2000 BTU/ton-mile </li></ul></ul><ul><ul><li>Air freight : > 14,000 BTU/ton-mile </li></ul></ul><ul><li>Reduce Travel: Telework, Telecommute, Teleconference, Virtual Tradeshows </li></ul><ul><li>Improve Urban Planning and Policy regarding </li></ul><ul><ul><li>Land use </li></ul></ul><ul><ul><li>Environmental quality </li></ul></ul><ul><ul><li>Social equity </li></ul></ul><ul><ul><li>Infrastructure operations and maintenance </li></ul></ul><ul><li>Increase On-Board Traveler Productivity </li></ul>
    26. 26. Potential ICT Benefits for Transportation <ul><li>Advanced Traveler Information Systems  (Real-time) Influence on Traveler Behavior and Improved Traffic Models </li></ul><ul><li>Intelligent Computer Vision Enhanced Traffic Modeling  Improved Traffic Models & Collision Avoidance </li></ul><ul><li>Real-time Emissions Monitoring  Coupled Traffic and Air Quality Models </li></ul><ul><li>Wireless Communications Networks  Improved Data Acquisition, Data Management, and Traffic Control </li></ul><ul><li>Congestion Pricing  Control Demand </li></ul><ul><li>En-route Commerce  Optimize Supply </li></ul><ul><li>Optimal and/or Dynamic Routing </li></ul><ul><li>Intermodal Models  Improved Transportation Models </li></ul>
    27. 27. State of the Electric Power Grid <ul><li>Size </li></ul><ul><ul><li>~200,000 Miles of Transmission Lines </li></ul></ul><ul><ul><li>5000 Power Plants, 800,000 Megawatts </li></ul></ul><ul><li>Transmission level (meshed network of extra high voltage, > 300 kV, & high voltage, 100-300 kV, connected to large generation units and very large customers; tie-lines to transmission networks, and to sub-transmission level) </li></ul><ul><li>Sub-transmission level (radial or weakly coupled network with some high voltage, 100-300 kV, but typically only 5-15 kV, connected to large customers and medium sized generators) </li></ul><ul><li>Distribution level (tree network of low voltage, 110-115 or 220-240 volts, and medium voltage, 1-100 kV, connected to small generators, medium- sized customers, and to local low-voltage networks for small customers) </li></ul>
    28. 28. <ul><li>Urbanization  load growth </li></ul><ul><ul><li>2.1+ % annual national growth over last 25-years  result in a 50% increase by 2014 - 2020 </li></ul></ul>State of the Electric Power Grid <ul><li>Nearly no new HV transmission lines in last 25 years </li></ul><ul><li>1988-98, 30% growth in total U.S. electricity demand is met with transmission network growth of 15% </li></ul><ul><ul><li>Re-regulation with privatization </li></ul></ul><ul><ul><li>Uncertainty ROIs </li></ul></ul><ul><ul><li>NIMBY </li></ul></ul><ul><ul><li>Right-of-way restrictions for T&D expansion </li></ul></ul><ul><ul><li>Tightening fuel supplies to meet increased demand </li></ul></ul>
    29. 29. State of the Electric Power Grid <ul><li>Operations </li></ul><ul><ul><li>8/15/03 blackout affected > 20 millions of people, water supply, wastewater conveyance, transportation, communications, hospitals, banking, and retail sales </li></ul></ul><ul><ul><ul><li>ICT safety equipment tripped to protect power plants and contain the outage causing cascading failures </li></ul></ul></ul><ul><ul><ul><li>9 nuclear power plants automatically powered down safely </li></ul></ul></ul><ul><ul><li>EPRI : $1.5 billion for July-Aug 1996 power blackouts </li></ul></ul><ul><ul><li>CEIDS : $119 billion / year in power quality disruptions </li></ul></ul>
    30. 30. Potential ICT Benefits for Electric Power <ul><li>EPRI/DoD Complex Interactive Networks Initiative </li></ul><ul><li>Goal: Develop tools that enable secure, robust and reliable operation of interdependent infrastructures with distributed intelligence and self-healing abilities </li></ul><ul><li>Systems’ approach to complex networks: advancing mathematical and system-theoretic foundations </li></ul><ul><ul><li>Target theoretical and applied results for increased dynamic network reliability and efficiency </li></ul></ul><ul><ul><li>Identify, characterize, and quantify failure mechanisms </li></ul></ul><ul><ul><li>Understand interdependencies, coupling and cascading </li></ul></ul><ul><ul><li>Develop predictive models </li></ul></ul><ul><ul><li>Develop prescriptive procedures and control strategies for mitigation or/and elimination of failures </li></ul></ul><ul><ul><li>Design self-healing and adaptive architectures </li></ul></ul><ul><ul><li>Trade-off between robustness and efficiency </li></ul></ul>
    31. 31. “ The best minds in electricity R&D have a plan: Every node in the power network of the future will be awake, responsive, adaptive, price-smart, eco-sensitive, real-time, flexible, humming - and interconnected with everything else .” — Wired Magazine, July 2001 http://www.wired.com/wired/archive/9.07/juice.html The Energy Web: “…a network of technologies and services that provide illumination…” From M. Amin, 2001
    32. 32. Enabling ICT for Electric Infrastructure <ul><li>Materials: Superconductors and wide bandgap semiconductors </li></ul><ul><li>Monitoring: WAMS, OASIS, SCADA, EMS </li></ul><ul><li>Analysis: DSA/VSA, PSA, ATC, CIM, TRACE, OTS, ROPES, TRELSS, market/risk assessment </li></ul><ul><li>Control: FACTS; Fault Current Limiters (FCL) </li></ul><ul><li>Distributed resources: Fuel cells, photovoltaics, Superconducting Magnetic Energy Storage (SMES) </li></ul><ul><li>Next generation: integrated sensor; 2-way communication; &quot;intelligent agent&quot; functions: assessment, decision, learning; actuation, enabled by advances in semiconductor manufacturing </li></ul>From M. Amin, 2001
    33. 33. Intelligent Adaptive Islanding From M. Amin, 2001 33 32 31 30 35 80 78 74 79 66 75 77 76 72 82 81 86 83 84 85 156 157 161 162 v v 167 165 158 159 155 44 45 160 166 163 5 11 6 8 9 18 17 4 3 7 14 12 13 138 139 147 15 19 16 112 114 115 118 119 103 107 108 110 102 104 109 142 37 64 63 56 153 145 151 152 136 49 48 47 146 154 150 149 143 42 43 141 140 50 57 230 kV 345 kV 500 kV
    34. 34. System Risk is a Function of System State P(H t,s ) = probability of a hazard at time t (and system state s) P(D s |H t,s ) = probability of a particular level of vulnerability of a system in state s given a hazard at time t (and system state s) E(L|D s ) = expected losses conditioned on the vulnerability of system in state s E(L) =  E(L|d s ) * P(d s |h t,s ) * P(h t,s )  h t,s d s
    35. 35. Life-Cycle Infrastructure Asset Management Life-Cycle Design Emergency Response, Diagnosis Multi-Objective Multi-stakeholder Decision-Making <ul><li>Life-Cycle Analysis </li></ul><ul><li>Internal, Direct Impacts </li></ul><ul><li>External, Indirect Impacts </li></ul><ul><li>Systems Evaluation </li></ul>Predictive Maintenance, Sensing, Monitoring, Data (Storage, Transmission, Retrieval) Modeling, Simulation, Recovery, Corrective Maintenance, Deconstruction,Reuse Detection, Preventive Maintenance, Lifetime Extension, Early Warning Prediction Planning, Training and Preparedness Social/ Cultural Values Policy/ Law Financial/ Insurance Instruments Organizational Theory Communication/ Education
    36. 36. Multi-Objective Multi-stakeholder Decision-Making <ul><li>Allocation problem over various investment options, over various stages of development (R&D, development, implementation) over time with risk/uncertainty </li></ul><ul><li>Multiple objectives : efficiency, reliability, security, resiliency, sustainability </li></ul><ul><li>Multiple stakeholders : different institutional boundaries, missions, resources, timetables, and agendas </li></ul>1 2 3 B/C ( S&M) B/C (ER) 1 ~ 2 ~ 3 : indifferent wrt ER 1 is infeasible wrt obj. S&M 2 >> 3 : 2 dominates 3
    37. 37. Challenges for Research in Life-Cycle Analysis of IT and Infrastructure <ul><li>Critical Infrastructure Inventory Data </li></ul><ul><ul><li>Scalable Environmental Knowledge Architecture </li></ul></ul><ul><li>Models of Individual Infrastructure Systems </li></ul><ul><li>Models of Coupled Infrastructure Systems </li></ul><ul><li>System Response and Resiliency </li></ul><ul><ul><li>System state /vulnerability analysis </li></ul></ul><ul><ul><li>Consequence models (boundaries, data, methods) </li></ul></ul><ul><ul><li>Extreme value statistics </li></ul></ul><ul><ul><li>Substitute services / alternate pathways </li></ul></ul><ul><li>Measures of Network Performance </li></ul><ul><li>Life-Cycle Infrastructure Asset Management Modeling </li></ul>
    38. 38. “ CyberInfrastructure” Vision <ul><li>“ Atkins report” </li></ul><ul><ul><li>Blue-ribbon panel, chaired by Daniel E. Atkins </li></ul></ul><ul><li>Calls for a national-level, integrated system of hardware, software, & data resources and services </li></ul><ul><li>New infrastructure to enable new paradigms of scientific/ engineering research and education </li></ul>http://www.cise.nsf.gov/evnt/reports/toc.htm
    39. 39. What CyberInfrastructure Means <ul><li>Infrastructure that enables distributed, reliable, real-time collaboration and analysis requiring large-scale, dynamic information storage and access </li></ul><ul><li>Examples of components to be integrated: </li></ul><ul><ul><li>Major computational processing capabilities </li></ul></ul><ul><ul><li>Unique experimental facilities </li></ul></ul><ul><ul><li>High-speed networks </li></ul></ul><ul><ul><li>Tele-participation and tele-operation tools </li></ul></ul><ul><ul><li>Networks of data collection devices </li></ul></ul><ul><ul><li>Data/metadata storage and curation </li></ul></ul><ul><ul><li>Data analysis and information extraction tools </li></ul></ul><ul><ul><li>Universal access </li></ul></ul>
    40. 40. What Makes CyberInfrastructure Unique <ul><li>Cyberinfrastructure : more than the sum of its component parts – the key is integration </li></ul>Distributing collection, storage and access across multiple locations and communities Data and resources that are collected, processed, and used by a community Transforming data into meaningful information Sharing distributed data across research groups or disciplines Playing an integrative role in a larger system Individual infrastructure components (e.g., devices that collect data, data mining as a science, or big computing resources) Unless it also involves… CyberInfrastructure isn’t just…
    41. 41. Examples of Early CyberInfrastructure <ul><li>George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES) </li></ul><ul><li>Extends national capacity for earthquake engineering through unique, shared infrastructure </li></ul><ul><li>What makes NEES CyberInfrastructure? </li></ul><ul><ul><li>Real-time video & data enable participation from remote sites </li></ul></ul><ul><ul><li>Real-time communications allow experiments to span facilities, link physical experiments with numerical simulation </li></ul></ul><ul><ul><li>15 experimental facilities linked by common network, data repository, tools, </li></ul></ul><ul><ul><li>metadata </li></ul></ul>
    42. 42. Examples: NEES’s Distributed Users and Distributed Resources Unique Laboratory Facilities Equipment Site 1 Equipment Site 2 Equipment Site 3 Equipment Site 15 . . . Other Site A Other Site B Practitioners Emergency Communities K-14 Education User Communities Earth.Eng. Researchers Data Repositories & Computational Resources NEES Consortium NEESgrid
    43. 43. Other NSF ICT-Relevant Programs <ul><li>CLEANER Small Planning Grants </li></ul><ul><ul><li>Nick Clesceri, BES, </li></ul></ul><ul><li>Sensors and Senor Networks </li></ul><ul><ul><li>Shih-Chi Liu, CMS, sliu@nsf.gov </li></ul></ul><ul><li>Information Technology Research </li></ul><ul><li>Cybertrust and Cybersecurity </li></ul>
    44. 44. Thank You For Your Attention ! ? MIRIAM HELLER, Ph.D. Infrastructure & Information Systems Program Director National Science Foundation Tel: +1.703.292.7025 Email: mheller@nsf.gov

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