Electricity Market Benchmarking Exploring Risk Andy Philpott EPOC

Electricity Market Benchmarking Exploring Risk Andy Philpott EPOC (www. epoc. org. nz) joint work with Ziming Guan (now at UBC/BC Hydro) 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 1 of 31

Electricity Supply in New Zealand • 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. 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 2 of 31

New Zealand national reservoir storage 12/5/2020 ONS SDDP Workshop, August 17, 2011 http: //www. electricityinfo. co. nz/Slide 3 of 31

NZ wholesale electricity market • Generators specify supply Waitaki system curves defining prices at which they will generate. Waikato River • 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 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 4 of 31

12/5/2020 ONS SDDP Workshop, August 17, 2011 SPXII, Halifax, August 20, 2010 Slide 5 of 50 31

New Zealand electricity market The economic dispatch problem 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 6 of 31 6/42

New Zealand electricity market Lake storage (blue) and price (pink) 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 7 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. 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 8 of 31

This has already been done New Zealand Commerce Commission on Market Power “There is something fundamentally wrong in the way in which we’re 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. (New Zealand Herald May 21, 2009, downloaded from site: http: //www. nzherald. co. nz) 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 9 of 31

New Zealand electricity market The view from economics 12/5/2020 ONS SDDP Workshop, August 17, 2011 CC Report, p 177 Source: Slide 10 of 31

New Zealand electricity market Deadweight loss = empirical price of anarchy Offered cost curve True cost curve 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 11 of 31

New Zealand electricity market Deadweight loss = empirical price of anarchy 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 12 of 31

New Zealand electricity market Deadweight loss = empirical price of anarchy 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 13 of 31

New Zealand electricity market Deadweight loss = empirical price of anarchy 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 14 of 31

New Zealand electricity market The view from economics again Source: CC Report, p 200 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 15 of 31

New Zealand electricity market 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) 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 16 of 31

Counterfactual 1 Linear programming interpretation (x*, y*, p*) Now set y=y 0 not equal to y* (“fix hydro generation”) (x 0, y 0, p 0) 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 17 of 31

Counterfactual 1 What about uncertain inflows? wet dry summer winter 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. 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). 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 18 of 31

New Zealand electricity market 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 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 19 of 31

Stochastic Counterfactual Yearly problem represented by this system demand WKO N MAN H S HAW demand 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 20 of 31

Application to NZEM 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. 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 21 of 31

Application to NZEM We simulate an optimal policy in this detailed system WKO MAN HAW 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 22 of 31

Application to NZEM Thermal marginal costs Gas and diesel prices ex MED estimates Coal priced at $4/GJ 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 23 of 31

Application to NZEM Gas and diesel industrial price data ($/GJ, MED) 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 24 of 31

Application to NZEM Load curtailment costs 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 25 of 31

New Zealand electricity market Market storage and centrally planned storage 2005 2006 2007 12/5/2020 ONS SDDP Workshop, August 17, 2011 2008 2009 Slide 26 of 31

New Zealand electricity market Risk aversion and competitive equilibrium 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 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 27 of 31

New Zealand electricity market Estimated daily savings from central plan $481, 000 extra is saved from anticipating inflows during this week 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 28 of 31

New Zealand electricity market 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) 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 29 of 31

New Zealand electricity market Benmore half-hourly prices over 2008 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 30 of 31

FIM 12/5/2020 ONS SDDP Workshop, August 17, 2011 Slide 31 of 31