2. Outline of Talk
• Background on Deregulated Power Markets
Regulated vs. Deregulated Power markets
Market Structure and Participants
Risk Exposures
• Decision Making Under Uncertainty
Deterministic Analysis
Sensitivity Analysis
Monte Carlo Simulation
Optimizing the Decision Making Process
• Monte Carlo Simulation
Model Specification
Model Estimation
Model Simulation
Calibration
Benchmarking
3. Analytics for Deregulated Power Markets
• Business questions:
What is my portfolio worth? (valuation)
How much of my expected dispatch output should I sell into
the forward market? (hedging)
How much money can I lose? (risk management)
What trades should I enter into so I can maximize my profits
and minimize my risk? (portfolio optimization)
10. Decision Making Under Uncertainty
• Risk Drivers
Deterministic scenario planning models
Sensitivity analysis
Monte Carlo simulation
• Optimizing the Decision Making Process
Unconstrained Optimization
Constrained Optimization
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12. Deterministic Planning Models
• Deterministic planning models
Pro:
o Simple
Con:
o How to come up with assumptions?
o Are these assumptions realistic?
o Doesn’t acknowledge uncertainty
o Can lead to biased decisions
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16. Sensitivity Analysis
• Sensitivity analysis
Pro:
o Simple
Con:
o How to create sensitivity scenarios?
o Are these scenarios realistic?
• In general the following does not hold, especially for nonlinear functions
E[𝑓 𝑋 ] ≠ 𝑓(𝐸 𝑋 )
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17. Monte Carlo Simulation
• Monte Carlo simulation
Pro:
o Realistic representations of possible states of the world (this could actually happen)
o Correlations are maintained
o Can benchmark against actual price distributions
Cons:
o Complex, slow
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18. Optimizing the Decision Process
• Given the prices, we want to optimize a decision process
• Example:
European Call Option
o Value a call option, value=max(P-K,0) simple decision rule, if P>K then exercise,
otherwise don’t
o Decisions today don’t impact decisions tomorrow
Power Plant
o Operational constraints can’t turn on and off instantly
o How to optimize the decision process, given that decisions today impact possible
decisions tomorrow?
o Answer is provided through dynamic programming
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21. Monte Carlo Framework
- Model Specification
- Specify a model of the fundamental risk drivers
- Model Estimation
- Estimate the unknown parameters of the model
- Simulation
- Simulate the risk drivers
- Calibration
- Use any known information to calibrate the simulations, to match observed real world
quantities
- Decision Making
- Optimize the decision process
- Summarize
- Summarize the outcomes (e.g. using probability distributions)
36. Analytics for Deregulated Power Markets
• Business questions:
What is my portfolio worth? (valuation)
How much of my expected output should I sell into the
forward market? (hedging)
How much money can I lose? (risk management)
What trades should I enter into so I can maximize my profits
and minimize my risk? (portfolio optimization)
37. What is My Portfolio Worth?
Gross Margin At Expected
Risk Value of
Portfolio
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38. How Sensitive is My Portfolio To Prices?
Sensitivity of gross
margin = $19 million
per $/MWh
Optimal forward sale = ~1500 MW
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39. Questions?
Scotty Nelson
snelson@ascendanalytics.com
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