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Risk Management in Energy Infrastructure Projects Application to CCS-EOR Projects

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.

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Risk Management in Energy Infrastructure Projects Application to CCS-EOR Projects

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  1. Risk Management in Energy Infrastructure ProjectsApplication to CCS-EOR Projects Anna Agarwal Center for Energy and Environmental Policy Research Massachusetts Institute of Technology July 30, 2013

  2. Motivation • Risks in infrastructure projects are combination of exogenous and endogenous risks • 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)

  3. 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 EOR Oil Field (140 million bbl. oil recovery expected) 500 MW IGCC Coal-fired Plant (with 90% CO2 Capture) 50-mile Pipeline (dedicated) CO2 Source: Bellona Foundation Source: IPCC Report on CCS

  4. Risk Management Framework - Identify risk factors - Risk Assessment a) Characterize the uncertainty b) Evaluate project risk exposure - Evaluate efficient risk management decisions Evaluate optimal contracts that incentivize the efficient decision-making Stage 1 Stage 2: Address Endogenous Risks Integrated Project Risk Management Entity 1 Entity 3… Entity 2 Contracts Contracts

  5. Modeling uncertainty in market risk factors Random Walk Model (Geometric Brownian motion) • Shocks to log spot price are normally distributed

  6. Contingent Decision-making – Adjust CO2 Capture and Injection Rate • Marginal Benefits of CO2 Capture and Injection • Revenue from oil production • Avoided CO2 emission penalty • Marginal Costs of CO2 Capture and Injection • Energy penalty of CO2 Capture • O&M Costs of CO2 Injection • Costs involving drilling CO2 injection wells and oil production wells • (depends on oil price) • (depends on CO2 emission penalty) • (depends on electricity price)

  7. 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

  8. Financial Gains from Contingent Decision-making • Gains from adjusting CO2 capture rate increase with • Decreasing oil price • Decreasing CO2 price • Increasing electricity price

  9. 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)

  10. Criteria for Design of CO2 Delivery Contracts 1) Minimize the risk of insolvency Pmax Power Plant Oil Field Power Plant Oil Field Pmin 2) Incentivize optimal contingent decision-making Pmin Pmax

  11. Evaluating Incentives for Contingent Decisions Fixed Price CO2 Contracts ( $ / ton CO2) 82% probability of sub-optimal contingent decision-making

  12. 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

  13. 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.

  14. Thank you Anna Agarwal MIT Center for Energy and Environmental Policy Research annaag@mit.edu

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