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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.

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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

Information Technology and Infrastructure: Benefits, Costs, and Dependencies

messages
Messages
  • ICT Confers Benefits To Infrastructure Systems; (Avoided) Costs May Be Easier to Quantify
  • Infrastructure Systems Differ from Other Manufacturing and Service Systems
  • 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
topics
TOPICS
  • Infrastructure Systems
  • Infrastructure Interdependencies
  • Benefits and Costs of IT and Infrastructure Systems
  • Related IT and Infrastructure Research
    • Cyber* Futures at NSF
  • Challenges for Research
a definition of infrastructure systems
A Definition of Infrastructure Systems
  • Networks of facilities and institutions
  • Support the flow of people, energy, other resources, goods, information, and basic services
  • Essential to life, economic well-being, and national security.
critical infrastructures pdd 63
Critical Infrastructures (PDD 63)

Potable & Waste Water

Transportation

Banking & Insurance

Telecom-munications

Government

Electricity

Emergency Response

Oil & Gas

integrated information systems
Integrated Information Systems

Oil & Gas

Power

Information Technology & Telecom

Transportation

Water Treatment

ict benefits for infrastructure systems
ICT Benefits for Infrastructure Systems

Enterprise

Integration/

Optimization

Community

Eco-efficiency/

Sustainability

Process

Control /

Supervision

Product

Integration/

Interoperability

Shared

Resources /

Environment

Shared

Objectives

Industrial

Ecology

Shared

Data

Enterprise Architecture

Communications Architecture

Automated Monitoring, Sensing, Data Acquisition

Performance

and

Efficiency

Baseline from

Core Utility

Processes

Time

(Adapted from Heller et al.,1999)

infrastructure systems some reflections
Infrastructure Systems: Some Reflections
  • Differ from Manufacturing Systems
    • Provide critical services / lifelines
    • Geographically distributed
    • One-offs with many degrees of freedom
    • Highly interconnected
    • Subject to uncertain and uncontrollable ambient conditions
  • Life-Cycle Modeling Differences
    • Uncertainty
      • High consequence / low probability events vs. slow consequence / high probability events
      • Life-span definition (whole-life)
    • Complexity
infrastructure interdependencies
Infrastructure Interdependencies

Financing & policies

SEC; IRS

E

L

E

C

T

R

I

C

I

T

Y

I

T

&

T

E

L

E

C

O

M

Banking & Finance

Trading, transfers

e-commerce, IT

Regulations & enforcement FERC; DOE

Currency (US Treasury; Federal Reserve )

Government

e-government,

IT

Communications

Financing & policies

Personnel/Equipment (Military)

Detection, 1st responders,

repair

Medical equipment

Emergency Response

FEMA; DOT

Location, EM contact

Fuel transport, shipping

Fire suppression

Transport of emergency personnel, injured, evacuation

Signalization, switches,

control systems

Transportation

DOT

SCADA

Fuel transport, shipping

Fuels, lubricants

Fuels, Heat

Generator fuels, lubricants

Financing, regulations, & enforcement

Storage,

pumps,

control systems, compressors

Oil & Natural Gas

DOE;DOT

Communications

SCADA

Chemicals

transport

Water for production, cooling, emissions control

Water for cooling, emissions control

Potable & Waste Water

EPA

Heat

SCADA

Pumps, lifts, control systems

Cooling

Switches, control systems

science of engineered networks
Science of Engineered Networks

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.

Köningsberg on the Pregel River with 7 bridges.

Cross each bridge exactly once and return to starting position.

science of engineered networks dependencies
Science of Engineered Networks:Dependencies
  • 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.
  • Scale-free networks (WWW, air traffic

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.

power grid outages follow power law
Power Grid Outages Follow Power Law

1

10

0

10

US Power outages

1984-1997

-1

10

August 10, 1996

-2

10

4

5

6

7

10

10

10

10

N= # of customers affected by outage

Frequency (per year) of outages > N

Data from NERC

(Amin, 9/10/01)

ict impacts infrastructure systems example 2001 california power crisis
ICT Impacts Infrastructure SystemsExample: 2001 California Power Crisis
  • Disrupted fuel production, refining, and distribution, sometimes cut off fuel supplies to the very plants that should have been generating their electricity
  • Interrupted water distribution affected the state's agribusiness
  • 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
coupled systems frameworks rinaldi et al 2001
Coupled Systems Frameworks : Rinaldi et al., 2001

Escalating

Cascading

Common Cause

Spatial

Temporal

Operational

Organizational

Loose/Tight

Linear/Complex

Normal

Adaptive

Inflexible

  • Physical
  • Cyber
  • Logical
    • Geographic

Business

Public

Policy

Security

Health/

Safety

Stressed/

Disrupted

Repair/

Restoration

Economic

Legal/

Regulatory

Technical

Social/

Political

Type of Failure

Infrastructure Characteristics

Coupling/

Response

Behavior

State of Operation

Natural

Environment ?

Types of Interdependencies

Environment

state of the water wastewater system
State of the Water/Wastewater System
  • Size
    • 15,000 Publicly-Owned Wastewater Treatment Plants
    • 100,000 Pumping Stations
    • 160,000 Public Potable Water Systems
  • Operations
    • Accounts for 3-7% Total US Electricity Consumption
    • ASCE Estimates $12 Billion Needed for Maintenance 2012
ict benefits for water wastewater systems
ICT Benefits for Water/Wastewater Systems

Utility

Integration/

Optimization

Process

Control /

Supervision

Plant

Integration/

Interoperability

Shared

Objectives

Shared

Data

Utility Business Architecture

Utility Communications Architecture

Automated Monitoring, Sensing, Data Acquisition

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

Performance

and

Efficiency

Baseline from

Core Utility

Processes

Time

(Adapted from Heller et al.,1999)

slide17
Harnassing Complexity through Shared ResourcesEnergy and Water Quality Management Systems (Jentgen, 2001)

Operations Planner & Scheduler

System Scheduler:

Surface Water Treatment Plant

Pump Stations

Distribution

Customer

Collection

Wastewater Treatment

Water Consumption Forecast

Power Supply

Contract Terms/Conditions

Energy Cost Scheduler (Electric Utility)

Interruption

Scheduler

Signal

Power Suppliers’

Price Schedule

Energy

Cost

Schedule

Hydro

Schedule

Performance Criteria

Consumption Forecast Program

Operating Plan

Schedule & Control

Management Scheduler

Raw Water Supply/ Water Treatment Plant

System Operating Plan

Operations

Clearance Approvals

Pump Stations

Automated Maintenance Management System

Operating Plan

Distribution

Water Quality

Operating

Constraints

Water Resource

Schedule/Constraints

Customer

Regulations

Clearance Work Orders

Collection

Water Source Analyzer

Water Quality Analyzer

Water Law

Water Rights

Water Priorities

Water Quality

Alarms

Wastewater Treatment Plant

Water Quality

Data

SCADA

Data

Lab & Field

Samples

Utility’s Historical Operating Data

Performance Criteria

potential ict benefits for water wastewater
Potential ICT Benefits for Water/Wastewater

Regional

Eco-efficiency/

Sustainability

Industrial Ecology

Utility Business Architecture

Utility Communications Architecture

Automated Monitoring, Sensing, Data Acquisition

Process Plant Utility/Facility

Control / Integration/ Integration/ Supervision Interoperability Optimization

Shared

Resources /

Environment

Performance

and

Efficiency

Shared

Objectives

Shared

Data

Baseline from

Core Utility

Processes

Time

(Adapted from Heller et al.,1999)

industrial symbiosis example baytown s water infrastructure nobel allen 1998
Industrial Symbiosis Example:Baytown’s Water Infrastructure (Nobel & Allen, 1998)
  • 21 process, 5 utility streams
  • 75 feasible reuse pathways identified
linear program formulation
Linear Program Formulation

GC

I1

WWTP

WTP

I2

I3

Fresh

Reclaimed

Reused

Disposed

Exchange Feasibility

  • Based on water quality parameters (e.g., TOC, TSS, TDS)
  • Creates input for cost optimization
    • feasible exchange pathways, i.e., “arcs”
    • “type” of water
    • transportation costs
industrial symbiosis optimal water use nobel allen 1998
Industrial Symbiosis: Optimal Water Use (Nobel & Allen, 1998)

Fresh Water

Cost

Metrics

Usage

D

D

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%

ict benefits for oil and gas infrastructure example bp s texas city plant
ICT Benefits for Oil and Gas Infrastructure Example: BP’s Texas City Plant
  • “Project Future” (Bylinsky, Fortune, “Elite Factories,” 9/1/2003)
    • Combined Refinery / Petrochemical Plant
    • $30 bbl Oil  $60 of Gasoline, Diesel, Jet Fuel, p-Xylene
    • 2,740 Employees
    • 2-year, $75 Million Investment in Computerization and Automation of 650 Key Valves
  • Returns On Investment
    • Start-up Time Reduced from 2 Weeks to 3.5 Days
    • Real-Time Equipment Setpoints Based on Ambient Temperature, Weather, and Product Prices
    • 3% Less Electricity Used
    • 10% Less Natural Gas Used
    • 55% Increase in Productivity

}

$ Millions and

Tons GHG Saved

state of oil and gas infrastructure systems
State of Oil and Gas Infrastructure Systems
  • Size
    • Ports, Refineries, Transportation
    • 2,000 Petroleum Terminals
    • Almost 1 Million Wells
    • 2,000,000 Miles of Oil Pipelines
    • 1,300,000 Miles of Gas Pipelines and Increasing
  • Operations
    • Pipeline and Distribution System
      • Leak Detection
      • Monitoring and Control Systems
      • More Efficient Use of Existing Pipe
      • Aging
  • Coupled Economic Models on Natural Gas and Electric Power
state of the transportation system
State of the Transportation System
  • Size
    • 125,000 Miles of National Highway System
    • 25,000 Miles of Public Roads
    • 3.76 Million Miles of Other Roads
  • Operations
    • FHWA : > $78 Billion / Year Idled Away in Congestion
    • 50% Total US Petroleum Consumed by Highway Vehicles
    • > 1/3 GHG Due to Surface Transportation
    • Major Source of Photochemical Smog and Other Air Pollution
    • > 40,000 Fatalities / Year Over Past Decade
potential ict benefits for transportation
Potential ICT Benefits for Transportation
  • Inform on-line buyers of environmental impacts of shipping options(NAE, 1994; Hawken et al., 1999; Sui & Rejeski, 2002)
    • Ship or rail: 400-500 BTU/ton-mile
    • Truck : >2000 BTU/ton-mile
    • Air freight : > 14,000 BTU/ton-mile
  • Reduce Travel: Telework, Telecommute, Teleconference, Virtual Tradeshows
  • Improve Urban Planning and Policy regarding
    • Land use
    • Environmental quality
    • Social equity
    • Infrastructure operations and maintenance
  • Increase On-Board Traveler Productivity
potential ict benefits for transportation1
Potential ICT Benefits for Transportation
  • Advanced Traveler Information Systems  (Real-time) Influence on Traveler Behavior and Improved Traffic Models
  • Intelligent Computer Vision Enhanced Traffic Modeling  Improved Traffic Models & Collision Avoidance
  • Real-time Emissions Monitoring  Coupled Traffic and Air Quality Models
  • Wireless Communications Networks  Improved Data Acquisition, Data Management, and Traffic Control
  • Congestion Pricing  Control Demand
  • En-route Commerce  Optimize Supply
  • Optimal and/or Dynamic Routing
  • Intermodal Models  Improved Transportation Models
state of the electric power grid
State of the Electric Power Grid
  • Size
    • ~200,000 Miles of Transmission Lines
    • 5000 Power Plants, 800,000 Megawatts
  • 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)
  • 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)
  • 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)
slide28

State of the Electric Power Grid

  • Urbanization  load growth
    • 2.1+ % annual national growth over last 25-years  result in a 50% increase by 2014 - 2020
  • Nearly no new HV transmission lines in last 25 years
  • 1988-98, 30% growth in total U.S. electricity demand is met with transmission network growth of 15%
    • Re-regulation with privatization
    • Uncertainty ROIs
    • NIMBY
    • Right-of-way restrictions for T&D expansion
    • Tightening fuel supplies to meet increased demand
state of the electric power grid1
State of the Electric Power Grid
  • Operations
    • 8/15/03 blackout affected > 20 millions of people, water supply, wastewater conveyance, transportation, communications, hospitals, banking, and retail sales
    • ICT safety equipment tripped to protect power plants and contain the outage causing cascading failures
    • 9 nuclear power plants automatically powered down safely
  • EPRI : $1.5 billion for July-Aug 1996 power blackouts
  • CEIDS : $119 billion / year in power quality disruptions
potential ict benefits for electric power
Potential ICT Benefits for Electric Power
  • EPRI/DoD Complex Interactive Networks Initiative
  • Goal: Develop tools that enable secure, robust and reliable operation of interdependent infrastructures with distributed intelligence and self-healing abilities
  • Systems’ approach to complex networks: advancing mathematical and system-theoretic foundations
    • Target theoretical and applied results for increased dynamic network reliability and efficiency
    • Identify, characterize, and quantify failure mechanisms
    • Understand interdependencies, coupling and cascading
    • Develop predictive models
    • Develop prescriptive procedures and control strategies for mitigation or/and elimination of failures
    • Design self-healing and adaptive architectures
    • Trade-off between robustness and efficiency
slide31

“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 2001http://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

enabling ict for electric infrastructure
Enabling ICT for Electric Infrastructure
  • Materials: Superconductors and wide bandgap semiconductors
  • Monitoring: WAMS, OASIS, SCADA, EMS
  • Analysis: DSA/VSA, PSA, ATC, CIM, TRACE, OTS, ROPES, TRELSS, market/risk assessment
  • Control: FACTS; Fault Current Limiters (FCL)
  • Distributed resources: Fuel cells, photovoltaics, Superconducting Magnetic Energy Storage (SMES)
  • Next generation: integrated sensor; 2-way communication; "intelligent agent" functions: assessment, decision, learning; actuation, enabled by advances in semiconductor manufacturing

From M. Amin, 2001

intelligent adaptive islanding
Intelligent Adaptive Islanding

230 kV

345 kV

500 kV

35

33

32

30

31

74

80

79

66

75

78

72

76

v

v

77

82

81

84

85

86

83

162

112

161

156

157

114

11

5

167

155

165

44

159

158

6

45

160

115

166

163

18

17

118

13

8

12

7

108

119

138

139

109

9

107

14

37

110

104

63

64

103

147

3

143

4

154

146

102

142

56

48

153

151

145

136

49

47

140

152

19

150

141

149

57

42

43

50

16

15

From M. Amin, 2001

system risk is a function of system state
System Risk is a Function of System State

P(Ht,s) = probability of a hazard at time t (and system state s)

P(Ds|Ht,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|Ds) = expected losses conditioned on the vulnerability of system in state s

E(L) = S S E(L|ds) * P(ds|ht,s) * P(ht,s) 

ht,s

ds

life cycle infrastructure asset management
Life-Cycle Infrastructure Asset Management

Communication/ Education

Social/ Cultural Values

Financial/ Insurance Instruments

Organizational Theory

Policy/ Law

Detection, Preventive Maintenance,

Lifetime Extension, Early Warning

Emergency Response, Diagnosis

Planning, Training and Preparedness

Recovery, Corrective Maintenance, Deconstruction,Reuse

Modeling, Simulation,

Multi-Objective Multi-stakeholder Decision-Making

Prediction

Predictive Maintenance, Sensing, Monitoring, Data (Storage, Transmission, Retrieval)

  • Life-Cycle Analysis
  • Internal, Direct Impacts
  • External, Indirect Impacts
  • Systems Evaluation

Life-Cycle Design

multi objective multi stakeholder decision making
Multi-Objective Multi-stakeholder Decision-Making

1

2

3

1 ~ 2 ~ 3 : indifferent wrt ER

1 is infeasible wrt obj. S&M

2 >> 3 : 2 dominates 3

B/C ( S&M)

B/C (ER)

  • Allocation problem over various investment options, over various stages of development (R&D, development, implementation) over time with risk/uncertainty
  • Multiple objectives : efficiency, reliability, security, resiliency, sustainability
  • Multiple stakeholders : different institutional boundaries, missions, resources, timetables, and agendas
challenges for research in life cycle analysis of it and infrastructure
Challenges for Research in Life-Cycle Analysis of IT and Infrastructure
  • Critical Infrastructure Inventory Data
    • Scalable Environmental Knowledge Architecture
  • Models of Individual Infrastructure Systems
  • Models of Coupled Infrastructure Systems
  • System Response and Resiliency
    • System state /vulnerability analysis
    • Consequence models (boundaries, data, methods)
    • Extreme value statistics
    • Substitute services / alternate pathways
  • Measures of Network Performance
  • Life-Cycle Infrastructure Asset Management Modeling
cyberinfrastructure vision
“CyberInfrastructure” Vision
  • “Atkins report”
    • Blue-ribbon panel, chaired by Daniel E. Atkins
  • Calls for a national-level,integrated system of hardware, software, & data resources and services
  • New infrastructure to enable new paradigms of scientific/ engineering research and education

http://www.cise.nsf.gov/evnt/reports/toc.htm

what cyberinfrastructure means
What CyberInfrastructure Means
  • Infrastructure that enables distributed, reliable, real-time collaboration and analysis requiring large-scale, dynamic information storage and access
  • Examples of components to be integrated:
    • Major computational processing capabilities
    • Unique experimental facilities
    • High-speed networks
    • Tele-participation and tele-operation tools
    • Networks of data collection devices
    • Data/metadata storage and curation
    • Data analysis and information extraction tools
    • Universal access
what makes cyberinfrastructure unique
What Makes CyberInfrastructure Unique
  • Cyberinfrastructure : more than the sum of its component parts – the key is integration
examples of early cyberinfrastructure
Examples of Early CyberInfrastructure
  • George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES)
  • Extends national capacity for earthquake engineering through unique, shared infrastructure
  • What makes NEES CyberInfrastructure?
    • Real-time video & data enable participation from remote sites
    • Real-time communications allow experiments to span facilities, link physical experiments with numerical simulation
    • 15 experimental facilities linked by common network, data repository, tools,

metadata

examples nees s distributed users and distributed resources
Examples: NEES’s Distributed Users and Distributed Resources

Unique Laboratory

Facilities

Equipment

Site 1

Earth.Eng.

Researchers

Data Repositories &

Computational Resources

Equipment

Site 2

Practitioners

Equipment

Site 3

NEES

Consortium

Emergency

Communities

. . .

Equipment

Site 15

K-14

Education

User

Communities

Other

Site A

NEESgrid

Other

Site B

other nsf ict relevant programs
Other NSF ICT-Relevant Programs
  • CLEANER Small Planning Grants
    • Nick Clesceri, BES,
  • Sensors and Senor Networks
    • Shih-Chi Liu, CMS, sliu@nsf.gov
  • Information Technology Research
  • Cybertrust and Cybersecurity
thank you for your attention
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