Energy Technology Assessments: Engineering, Economics, and

Institutional Perspectives

GCEP Research Symposium 2006Frances C. Arrillaga Alumni Center

Stanford University September 18, 2006

John P. WeyantDepartment of Management Science & Engineering

Stanford University

Outline

• Engineering, Economics, Institutional Perspectives

• Hoffert, et al.• Pacala & Socolow• Global Technology Strategy Project (GTSP)• GCEP Integrated Assessments• Future Directions

SCIENCE VOL 298 1 NOVEMBER 2002

Stabilizing the carbon dioxide–induced component of climate change is an energy problem. Establishment of a course toward such stabilization will require the development within the coming decades of primary energy sources that do not emit carbon dioxide to the atmosphere, in addition to efforts to reduce end-use energy demand. Mid-century primary power requirements that are free of carbon dioxide emissions could be several times what we now derive from fossil fuels (1013 watts), even with improvements in energy efficiency. Here we survey possible future energy sources, evaluated for their capability to supply massive amounts of carbon emission–freeenergy and for their potential for large-scale commercialization. Possible candidates for primary energy sources include terrestrial solar and wind energy, solar power satellites, biomass, nuclear fission, nuclear fusion, fission-fusion hybrids, and fossil fuels from which carbon has been sequestered. Non–primary power technologies that could contribute to climate stabilization include efficiency improvements, hydrogen production, storage and transport, superconducting global electric grids, and geoengineering. All of these approaches currently have severe deficiencies that limit their ability to stabilize global climate. We conclude that a broad range of intensive research and development is urgently needed to produce technological options thatcan allow both climate stabilization and economic development.

Hoffert, et al. • Good

– Highlighted Magnitude of the Problem– Highlighted A Promising Mega Strategy

• Bad– Called for a Moon Shot Program Without Justification– No Economics or Institutional Considerations

• Ugly– No Discussion of Potential of Existing Technologies– No R&D Prioritization

13 AUGUST 2004 VOL 305 SCIENCE

Humanity already possesses the fundamental scientific, technical, and industrial know-how to solve the carbon and climate problem for the next half-century. A portfolio of technologies now exists to meet the world’s energy needs over the next 50years and limit atmospheric CO2 to a trajectory that avoids a doubling of the pre-industrial concentration. Every element in this portfolio has passed beyond the laboratory bench and demonstration project; many are already implemented somewhere at full industrial scale. Although no element is a credible candidate for doing the entire job (or even half the job) by itself, the portfolio as a whole is large enough that not every element has to be used.

Socolow/Pacala Assessment• Good

– Highlighted Magnitude of the Problem– Highlighted Potential of Existing Technologies

• Bad– Ignored Economics and Institutional Considerations– World Ends in 2050

• Ugly– No Wedge Prioritization– De-emphasize R&D

Battelle Pacific Northwest Laboratories

An Advanced Technology Case

Table 1: Technology Assumptions Year 2100

Technology units 1990 Base

Mini-CAM B2

Mini-CAM B2

AT US Automobiles mpg 18 60 100

Land-based Solar Electricity 1990 c/kWh 61 5.0 5.0 Nuclear Power 1990 c/kWh 5.8 5.7 5.7

Biomass Energy 1990$/gj $7.70 $6.30 $4.00 Hydrogen Production (CH4 feedstock) 1990$/gj $6.00 $6.00 $4.00

Fuel Cell mpg (equiv) 43 60 98 Fossil Fuel Power Plant Efficiency (Coal/Gas) % 33 42/52 60/70

Capture Efficiency % 90 90 90 Carbon Capture Power Penalty (Coal) % 25 15 5 Carbon Capture Power Penalty (Gas) % 13 10 3 Carbon Capture Capital Cost (Coal) % 88 63 5 Carbon Capture Capital Cost (Gas) % 89 72 3

Geologic Disposal (CO2) $/tC 37.0 37.0 23.0

Battelle Pacific Northwest Laboratories

The VALUE OF DEVELOPINGNEW ENERGY TECHNOLOGY

(Present Discounted Costs to Stabilize the Atmosphere)

Minimum Cost Based on Perfect Where & When

Flexibility Assumption. Actual Cost

Could be An Order of

Magnitude Larger.

BAU(1990)BAU(Tech+)

advancedtechnology

550

650

750

$1

$10

$100

$1,000

$10,000

$100,000

Present Discounted C

ost, Billions of 1990 U

S $

Technology Assumption

Steady-State CO2

Concentration (ppmv)

Battelle Pacific Northwest Laboratories

GTSP• Good

– Highlighted Magnitude of the Problem– Highlighted Potential of Existing and New Technologies– Embedded Problem in Economics Framework

• Bad– Only Partially Incorporate Engineering Considerations– Only Partially Incorporate Institutional Considerations

• Ugly– Very Limited Uncertainty Analysis – Very Limited Technology Development Dynamics

Incremental Value of GCEP Renewables Program

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

50 100

150

200

250

300

350

400

450

500

550

600

650

700

750

800

850

900

950

1000

1050

1100

All ProgramsAll Less Renewables

Cumulative Carbon Emission Reductions Through 2100 (GT)

Freq

uenc

y

Insights From GCEP IA Assessment Framework• All Areas Have High Option Values

– Can Identify Plausible Cases Leading to 5-10 Times Expected Values– Nuclear & End-Use Efficiency Wildcards– Choice of Policy Instruments Can Affect Substitutability and

Complementarity of Technologies• Advanced Combustion

– Large Benefits Robust Over Many Uncertainties• Carbon Capture and Sequestration

– Potentially Large Benefits– Public Acceptability & Economic Incentive Issues

• Renewables - Biofuels Look More Promising– Large Potential Benefits Possible, But Timing Uncertain– Economic Incentives And/Or Failures Elsewhere Can Accelerate– Key Potential Roles for Niche Markets

• Hydrogen– Large Benefits Possible, But They Depend on Success in A Number

Complementary Areas – Need Careful Internal Co-ordination and External Monitoring

GCEP Integrated Assessments• Good

– Highlighted Potential of Existing and New Technologies– Embedded Problem in Economics/Uncertainty Framework– Took A Portfolio Approach to R&D

• Bad– Only Partially Incorporate Engineering Considerations– Only Partially Incorporate Institutional Considerations

• Ugly– Weak on Some Prob. Assessments for Uncertainty Analysis – Weak on Technology Development Dynamics

Global CO2 Emissions in IPCC AR4

Ongoing/Future Assessments• Good

– More Systematic Probability Assessments (Baker, Clarke, Weyant, et al. Project)

• Better– Better Integration of Technology, Economics and

Institutions Under Uncertainly (LLNL, LBNL, UCB, SU Consortium Project)

• Best– Add Integrated Technology Dynamics (Several)

Assessments of R&D Projects (Baker)Identify Broad Categories of Technologies and Experts

Joe Eto, LBLTransmission & Grid

Same as aboveNuclear Fusion

Steve Fetter, UMD; Per Petersen, Berkeley

Nuclear Fission

Howard Herzog, MITCarbon Capture and Storage

Chris Edwards, StanfordCombustion

Jim Manwell, UMassWind

Dave O’connor, Evan Hughes, EPRI

Bio-energy

Mike McGehee, StanfordAdvanced Solar

Assessments of R&D Projects (Baker, Cont.)Define Investment Level and Technical success• Example: Advanced Solar; purely organic solar cells• Investment: $15 Million per year, for 10 years.• Technical Success:

– Cost of $50/m2; – efficiency of 15%; – 30 year life time (defined as working at least 75% of

original efficiency after 30 years)• We will define intermediate hurdles:

– Identifying molecules that can achieve efficiency.– Identifying molecules among that group that can achieve

stability.– Hurdles related to the cost of depositing the material and

identifying a low cost substrate.• Then, assess probability of success.

Key uncertainties

and destination

systems identify

candidate actions

Destination systemsHow can system be realistically and economically structured?

• Resources?• Conversion systems?• End-use levels,

patterns, technologies, demand management?

The desirable system depends on technology development and resources available

Key uncertaintiesWhen a “key uncertainty” is resolved, it determines the desired destination systemKey uncertainties resolved through R&D, investigations, and waiting

Today’s actions and policiesDetermine the

• Levels of R&D efforts (and who makes the efforts)

• Investments in infrastructure to hedge against uncertainties

Investigation of

Destination Systems

identifies key uncertainties

Transition modeling tells us how the system might actually evolve, given the uncertainties

Transition modeling• Given policies and actions today, can the system evolve to a desirable

destination system?• What conditions and policies will stimulate appropriate R&D and

infrastructure investment?

There are four basic elements to consortium the analysis

Interplay Between Public R&Dand Private R&D & Investment Decisions

Public R&DDecision

C0

Private R&DDecision

C1C1 C2∞Cost Cost

Time

PrivateInvestmentDecision

C2C3

Cost

Thank You!

The End

GCEP Approach for Assessment Activities

Initial Technical Area

Assessment

Rigorous Energy System Efficiency

Analysis

Integrated Cost and Environmental

Analysis

Selection of Technical Area for Study

Review of current state of energy systems and research directions

• Literature Studies• Workshops

Thermodynamic Framework

Report on issues, barriers and clear opportunities

framed around thermodynamic principles

applied to the area

Second Law Analysis of Selected

Components

System Integration of Components

Exergy Analysis of Systems

Report on potential for significant improvement

over current energy systems based on fundamental

thermodynamics of systems

System Components and Structure

Performance Limits and Expectations

Report on potential market penetration and projected overall impact on global

greenhouse gas emissions

Scenario Probabilities Cost Modeling

Global Impact on GHGs

Projected Range of Impacts of GCEP Programon Global Carbon Emissions

0

5

10

15

20

25

30

35

2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Car

bon

Emis

sion

s (G

T)

High

Reference

Low

High-wGCEP

Ref-wGCEP

Low-wGCEP

Carbon Emission Reductions Resulting From GCEP Renewables R&D

0

0.05

0.1

0.15

0.2

0.25

0.3

25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 525 550

Cumulative Carbon Emission Reductions Through 2100 (GT)

Freq

uenc

y

Carbon Emission Reductions Resulting From GCEP Sequestration R&D

0

0.05

0.1

0.15

0.2

0.25

0.3

25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 525 550

Cumulative Carbon Emission Reductions Through 2100 (GT)

Freq

uenc

y

Contributions of GCEP Technologiesto Carbon Emission Reductions

0

2

4

6

8

10

12

2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Year

Bill

ion

Tonn

es C

arbo

n

Hydrogen

Renewables

Sequestration

Advanced Combustion

Information, Foresight & Uncertainty:Three Alternative Sets of Assumptions

Invest StartOperation

StopOperation

State of Energy System

Time

Plan & Build Operate

t1 t2t0

(1) Static, Myopic, or Recursive Dynamic(2) Perfect Foresight (Rationale Expectations)(3) Decision Making Under Uncertainty

Information, Foresight & Uncertainty:Three Alternative Sets of Assumptions

Invest StartOperation

StopOperation

State of Energy System

Time

Plan & Build Operate

t1 t2t0

(1) Static, Myopic, or Recursive Dynamic(2) Perfect Foresight (Rationale Expectations)(3) Decision Making Under Uncertainty

Interplay BetweenR&D and Investment Decisions

R&DDecision

C0

InvestmentDecision

C1C1 C2

∞Cost Cost

Time

Integrated Assessment ofCarbon Capture, Separation and Sequestration

• Inputs Required (Oscar Mascarenhas Project)– Energy Penalty for Separation– Capital, O&M Costs for Separation– CO2 Transport Costs– Sequestration Costs/Capacities by Region & Category – PRA of Leakage Potentials– Public Acceptability Assessment

• Outputs Produced– Market Share/Carbon Emission Reductions– Impact on Energy System Costs/Energy Markets– Under Broad Range of Energy Market/Technology Futures

Initiating Event

CO2 plume contacts

well

Age

CO2 degrades cement

Cement Seal

Integrity

Cement type/

quality

Leakage through

well

Initial Results

Optimal First Period Investment

RNW FOS SEQ RNW FOS SEQ

$ m

illio

n/yr

$ m

illio

n/yr

U.S. Electric Generation Sector No Budget Constraint

0

50

100

150

200

250

0

50

100

150

200

250

Cost-Benefit CriterionCost-Effectiveness Criterion

5 % Increase

15 % Increase

Blanford Dynamic Programming Model