Risk Management in Energy Infrastructure Projects
Application to CCS-EOR Projects
Anna Agarwal
Center for Energy and Environmental Policy Research
Massachusetts Institute of Technology
July 30, 2013
Motivation
 Risks in infrastructure projects are combination of exogenous and endogenous
risks
•
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Exogenous risks: e.g. market risks, geological uncertainty
Endogenous risks: inefficient decision-making by involved entities
 Endogenous risks cited as the dominant reason for under-performance in
infrastructure projects (Flyvbjerg, Miller and Lessard, Merrow, World Bank Report on Infrastructure)
 Challenge in designing contracts to address endogenous risks lies in the
multitude of exogenous risks
•
Large number of risk factors make to difficult to foresee all future contingencies and
specify them in contracts (Williamson, 1971)
 Traditionally infrastructure contracts tend to be ‘rule-based’ and not
‘performance-based’, thus contractor has no incentive to reduce risks
 Challenge in infrastructure risk management is to change the current
contracting approach (Flyvbjerg, 2003)
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Objective
Develop a risk management framework that accounts for
both the exogenous and endogenous risks, and
maximizes the aggregate project value.
Application: CCS-EOR Prototype Project
500 MW IGCC Coal-fired Plant
EOR Oil Field
(with 90% CO2 Capture)
(140 million bbl. oil recovery expected)
50-mile Pipeline
(dedicated)
CO2
Source: Bellona Foundation
Source: IPCC Report on CCS
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Risk Management Framework
- Identify risk factors
Stage 1
- Risk Assessment
a) Characterize the uncertainty
Integrated Project Risk Management
b) Evaluate project risk exposure
- Evaluate efficient risk management
decisions
Stage 2: Address Endogenous Risks
Entity 1
Entity 2
Contracts
Entity 3…
Contracts
Evaluate optimal contracts
that incentivize the efficient
decision-making
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Modeling uncertainty in market risk factors
Random Walk Model (Geometric Brownian motion)
 Shocks to log spot price are normally distributed
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Contingent Decision-making
– Adjust CO2 Capture and Injection Rate
• Marginal Benefits of CO2 Capture and Injection
 Revenue from oil production
(depends on oil price)
 Avoided CO2 emission penalty
(depends on CO2 emission penalty)
• Marginal Costs of CO2 Capture and Injection
 Energy penalty of CO2 Capture
(depends on electricity price)
 O&M Costs of CO2 Injection
 Costs involving drilling CO2 injection wells and oil production wells
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Evaluate Optimal CO2 Capture Rate
14% probability of optimal CO2 capture rate being less than 90%
Optimal capture rate
decreases with:
 Decreasing oil price
 Decreasing CO2 price
 Increasing electricity price
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Financial Gains from Contingent Decision-making
Gains from adjusting CO2 capture rate increase with
 Decreasing oil price
 Decreasing CO2 price
 Increasing electricity price
8
Financial Gains from Contingent Decision-making
 14% probability of positive gains from
contingent decision-making
 Financial gains can exceed $300 million
(16% of project NPV)
 Expected value of project value gains is
$11 million
(0.6% of project NPV)
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Criteria for Design of CO2 Delivery Contracts
1) Minimize the risk of insolvency
Oil Field
Power Plant
Pmax
Pmin
2) Incentivize optimal contingent decision-making
Oil Field
Pmin
Power Plant
Pmax
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Evaluating Incentives for Contingent Decisions
Fixed Price CO2 Contracts ( $ / ton CO2)
82% probability of sub-optimal
contingent decision-making
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Evaluating Incentives for Contingent Decisions
Indexed Price CO2 Contracts ( % price of oil / ton CO2)
•
•
•
Sharing oil price risk reduces likelihood of sub-optimal contingent decision-making to 13%
The scenarios with risk of sub-optimal decisions correspond to low electricity price and high
CO2 emission penalty (poor incentive for power plant to lower CO2 capture rate)
In CCS-EOR projects need to index contract to other risk factors – such as electricity price
and CO2 emission penalty
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Conclusions from Market Risk Analysis
• Evaluated optimal contingent decisions, and signified the financial
gains involved.
• Analyzed the implications of contract design and risk-sharing on the
decision-making of the entities.
• Quantitatively illustrated that the final risk exposure of the project
depends on both exogenous risks and endogenous risks.
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Thank you
Anna Agarwal
MIT Center for Energy and Environmental Policy Research
annaag@mit.edu