Hedging strategy and operational flexibility in the electricity market

1. Hedging strategy and operational flexibility in the electricity market Characteristics of the electricity market • Non-storability • Transmission constraints • Very complex contracts • Physical production

2. European Energy Exchange Profit in 2002(for FPD): 5'127 €/MWh Profit in 2003(for FPD): -15'434 €/MWh

3. Introduction Focus of the Study Risk management in the electricity market Interaction between physical production and contracts Operational flexibility as hedging tool

4. Hydro plant and Options Is Ls In each period we have the option to produce Es Payoff K Electricity price xs K = marginal cost of production

5. If we produce today the possibility to produce tomorrow will be affected In each period we have the option to produce ifEs > 0 Max capacity, 500MW Time (hourly buckets) Min capacity, -50MW A series of interdependent options High spot prices Storage almost empty Low spot prices

6. Inflow (I) Demand (D) Portfolio optimization Production portfolio Contract portfolio Strike Availability Exercise flexibility Marginal costs Volume uncertainty Fixed costs Interaction Flexibility Interruptability Contract engineering & Portfolio optimization Portfolio optimization Optimal dispatch strategy Optimal contract portfolio Engineering thinking Financial thinking Spot price (S) Fuel prices

7. Maximize expected profit Given risk constraint (measured as CVaR) Large problems can be handled if X is a polyhedral set “static model” Besides production decisions (pump or produce) we model the amount of futures positions to be hold given the written bilateral contracts Optimal (static) portfolio

8. Case study portfolio Long positions Short positions Hydro plants Swing options Future contract Spot contracts

9. Modeling the Stochastics • Yearly seasonality • Daily variations • Modeling the Stochastics? • Jumps • Mean reversion • Risk measure?

11. Portfolio optimization Scenarios j Spot price Demand Inflow

12. Notations in Period s Is Ls xs Production / Pumping Is Inflow Es Waterlevel Ls Spill-over Es xs

13. Modeling of hydro plant Don’t produce when storage empty Don’t pump when storage full Leave water for future production Technical constraint Note: E, I, and L are stochastic variables !!!

15. Dynamic Dispatch • Dispatch responds to observations of uncertainties • Spot-price S • Aggregated Inflow up to time t: I • Demand • Corresponds to an exercise-frontier in American options

16. Let the decision variable determine exercise conditions instead of the actual dispatch in each period The dispatch is allowed to react to new information Modeling exercise conditions Exercise condition Decision variables

17. Pure profit maximization  dispatch is a step function Risk averse case  convex combination of step functions The step functions and are given exogenously and the weighting factors and are decision variables Can optimize the complex hydro storage plant with LP Hydro dispatch strategy

18. Portfolio optimization & hedging strategy Dispatch strategy Tight risk constraint (low C) No risk constraint (high C)

19. Uncertain demand is risky Cannot hedge with standardized contracts Operational flexibility to hedge against volume risk Hedging strategy What is the operational flexibility worth?

21. Additional Flexibility Slide 1

22. Additional Flexibility Slide 2 Risk Expected Profit: Constant 24, 2 Mio 24,0 Mio Volume

23. Guidance on how to dispatch hydro storage plants under risk / return considerations. Not just identify but actually quantify operational flexibility with regard to handle uncertainty. Perceive uncertainty as a challenge to flexibility instead of a threat. Identified an important value driver in hydro storage plants (and flexible plants in general). Achievements