1. ONS SDDP Workshop, August 17, 2011 Slide 1 of 31 Andy Philpott EPOC (www.epoc.org.nz) joint work with Ziming Guan (now at UBC/BC Hydro) Electricity Market Benchmarking Exploring Risk

2. ONS SDDP Workshop, August 17, 2011 Slide 2 of 31 Before 1996, the New Zealand wholesale electricity system was operated as a state monopoly. Since October 1996 this has been run as an electricity pool market. Generation ownership last changed in 1999 when ECNZ was broken up. The system is dominated by generation from hydro-electric reservoirs. This leads to unique and interesting problems when trying to understand how pool markets should operate. Electricity Supply in New Zealand

3. ONS SDDP Workshop, August 17, 2011 Slide 3 of 31 http://www.electricityinfo.co.nz/ New Zealand national reservoir storage

4. ONS SDDP Workshop, August 17, 2011 Slide 4 of 31 NZ wholesale electricity market Generators specify supply curves defining prices at which they will generate. Curves fixed for each half hour Linear programming model runs every five minutes to determine –electricity generated –electricity flows in network –spot price (shadow price) of electricity at 244 out of 470 network nodes Waikato River Waitaki system

5. ONS SDDP Workshop, August 17, 2011 Slide 5 of 31 SPXII, Halifax, August 20, 2010 Slide 5 of 50

6. ONS SDDP Workshop, August 17, 2011 Slide 6 of 31 6/42 The economic dispatch problem New Zealand electricity market

7. ONS SDDP Workshop, August 17, 2011 Slide 7 of 31 New Zealand electricity market Lake storage (blue) and price (pink)

8. ONS SDDP Workshop, August 17, 2011 Slide 8 of 31 Questions How should this system be operated to provide security of supply at low cost? As a pool market or some alternative? Do generators manage hydro-reservoir storage to minimize overall national thermal fuel cost or are they behaving strategically? (as discussed in Bushnell, 2003). If market power gives higher prices, is this accompanied by a deadweight loss from inefficient dispatch? The NZ Electricity Commission maintains a Centralized Data Set that can be used to address some of these questions.

9. ONS SDDP Workshop, August 17, 2011 Slide 9 of 31 (New Zealand Herald May 21, 2009, downloaded from site: http://www.nzherald.co.nz) New Zealand Commerce Commission on Market Power There is something fundamentally wrong in the way in which were marketing electricity in New Zealand, Mr Brownlee said. Power generators overcharged customers $4.3 billion over six years by using market dominance, according to a Commerce Commission report. This has already been done

10. ONS SDDP Workshop, August 17, 2011 Slide 10 of 31 Source: CC Report, p 177 The view from economics New Zealand electricity market

11. ONS SDDP Workshop, August 17, 2011 Slide 11 of 31 Deadweight loss = empirical price of anarchy Offered cost curve True cost curve New Zealand electricity market

12. ONS SDDP Workshop, August 17, 2011 Slide 12 of 31 Deadweight loss = empirical price of anarchy New Zealand electricity market

13. ONS SDDP Workshop, August 17, 2011 Slide 13 of 31 Deadweight loss = empirical price of anarchy New Zealand electricity market

14. ONS SDDP Workshop, August 17, 2011 Slide 14 of 31 Deadweight loss = empirical price of anarchy New Zealand electricity market

15. ONS SDDP Workshop, August 17, 2011 Slide 15 of 31 Source: CC Report, p 200 The view from economics again New Zealand electricity market

16. ONS SDDP Workshop, August 17, 2011 Slide 16 of 31 What is counterfactual 1? –Fix hydro generation (at historical dispatch level). –Simulate market operation over a year with thermal plant offered at short-run marginal (fuel) cost. –The Appendix of Borenstein, Bushnell, Wolak (2002)* rigorously demonstrates that the simplifying assumption that hydro-electric suppliers do not re-allocate water will yield a higher system-load weighted average competitive price than would be the case if this benchmark price was computed from the solution to the optimal hydroelectric generation scheduling problem described above [Commerce Commission Report, page 190]. (* Borenstein, Bushnell, Wolak, American Economic Review, 92, 2002) New Zealand electricity market

17. ONS SDDP Workshop, August 17, 2011 Slide 17 of 31 Counterfactual 1 Now set y=y 0 not equal to y* (fix hydro generation) (x*, y*, *) (x 0, y 0, 0 ) Linear programming interpretation

18. ONS SDDP Workshop, August 17, 2011 Slide 18 of 31 Counterfactual 1 What about uncertain inflows? wet dry Stochastic program counterfactual The optimal generation plan burns thermal fuel in stage 1 in case there is a drought in winter. The competitive price is high (marginal thermal fuel cost) in the first stage, but zero in the second (if wet). Counterfactual 1 In the year under investigation, suppose all generators optimistically predicted high inflows and used all their water in summer. They were right, and no thermal fuel was needed at all. Counterfactual prices are zero. summerwinter

19. ONS SDDP Workshop, August 17, 2011 Slide 19 of 31 What is a better counterfactual? –Solve a multistage stochastic linear program (MSLP) to compute a centrally-planned generation policy, and simulate this policy. –Previous work does this with a dynamic program for Nordpool (Kauppi & Liski, 2008). –In our model, we re-solve the MSLP every 13 weeks and simulate the policy between solves using a detailed model of the system. includes transmission system with constraints and losses river chains are modeled in detail historical station/line outages included in each week unit commitment and reserve are not modeled New Zealand electricity market

20. ONS SDDP Workshop, August 17, 2011 Slide 20 of 31 Yearly problem represented by this system S N demand WKOHAWMAN H demand Stochastic Counterfactual

21. ONS SDDP Workshop, August 17, 2011 Slide 21 of 31 Rolling horizon counterfactual –Set s=0 –At t=s+1, solve a DOASA model to compute a weekly centrally-planned generation policy for t=s+1,…,s+52. –In the detailed 18-node transmission system and river-valley networks successively optimize weeks t=s+1,…,s+13, using cost-to-go functions from cuts at the end of each week t, and updating reservoir storage levels for each t. –Set s=s+13. Application to NZEM

22. ONS SDDP Workshop, August 17, 2011 Slide 22 of 31 We simulate an optimal policy in this detailed system MANHAW WKO Application to NZEM

23. ONS SDDP Workshop, August 17, 2011 Slide 23 of 31 Thermal marginal costs Application to NZEM Gas and diesel prices ex MED estimates Coal priced at $4/GJ

24. ONS SDDP Workshop, August 17, 2011 Slide 24 of 31 Gas and diesel industrial price data ($/GJ, MED) Application to NZEM

25. ONS SDDP Workshop, August 17, 2011 Slide 25 of 31 Load curtailment costs Application to NZEM

26. ONS SDDP Workshop, August 17, 2011 Slide 26 of 31 Market storage and centrally planned storage New Zealand electricity market 20052006200720082009

27. ONS SDDP Workshop, August 17, 2011 Slide 27 of 31 Risk aversion and competitive equilibrium New Zealand electricity market Is the central plan the competitive equilibrium? yes, if all agents are risk neutral, and share the same probability distribution as the central planner no, if agents are risk averse so the behaviour we are seeing could be risk aversion in a perfectly competitive market

28. ONS SDDP Workshop, August 17, 2011 Slide 28 of 31 New Zealand electricity market Estimated daily savings from central plan $481,000 extra is saved from anticipating inflows during this week

29. ONS SDDP Workshop, August 17, 2011 Slide 29 of 31 Savings in annual fuel cost Total fuel cost = (NZ)$400-$500 million per annum (est) Total wholesale electricity sales = (NZ)$3 billion per annum (est) New Zealand electricity market

30. ONS SDDP Workshop, August 17, 2011 Slide 30 of 31 Benmore half-hourly prices over 2008 New Zealand electricity market

31. ONS SDDP Workshop, August 17, 2011 Slide 31 of 31 FIM