1. Impacts of Reserve and Fixed Costs on Greece’s Day-Ahead Scheduling Problem Panagiotis Andrianesis a, George Liberopoulos a Kostis Sakellaris b,c, Andreas Vlachos b a Department of Mechanical and Industrial Engineering, University of Thessaly, Volos, Greece b Regulatory Authority for Energy, Athens, Greece c Athens University of Economics and Business PROMITHEAS-2 International Black Sea Energy Policy Conference "Energy Investments and Trade Opportunities" 8,9 October 2008, Athens, Greece

2. 1. Introduction European Directive 96/92/EC: liberalization and integration of the national electricity markets GREECE: Regulatory Authority for Energy (RAE) Hellenic Transmission System Operator (HTSO) Grid Control and Power Exchange Code for Electricity (2005):  Day-Ahead Market  Real Time Dispatch  Imbalances Settlement  Capacity Assurance Mechanism

3. 1. Introduction Day-Ahead Scheduling (DAS) Problem: basis for the wholesale electricity market DAS: aims at minimizing overall cost of serving energy load, under conditions of reliable system operation, ensuring adequate reserves, i.e., a security-constrained unit commitment program, co-optimizing energy and reserves

4. 2. Greece’s Electricity System TypeNumber of unitsCapacity (MW) Lignite224808.10 Oil4718.00 Combined Cycle51962.10 Natural Gas3486.80 Small Thermal2116.10 Hydro393016.50 Renewables/Cogeneration>100889.94 Total Capacity:11997.54 Total Capacity (thermal plants):8091.10 Generation mix

5. 2. Greece’s Electricity System Yearly load profile for 2007

6. 2. Greece’s Electricity System Frequency-related ancillary services (“reserves”):  Primary reserve requirement : 80 MW  Secondary reserve requirement : 150-300 MW  Tertiary reserve requirement: 300-600 MW

7. 2. Greece’s Electricity System North: 2/3 of installed capacity South: 2/3 of load Transmission Constraint

8. 2. Greece’s Electricity System 2-zone model : North – South  Producers face different Marginal Generating Prices, when the transmission constraint is activated  Suppliers always face a uniform System Marginal Price (SMP) Incentives: installation of new generation near consumption

9. 3. Day-Ahead Scheduling Problem INPUTS: - Energy offers - Reserve offers - Fixed costs (start-up, shut-down, minimum-load) - System load - Reserve requirements - Transmission constraints - Units’ technical characteristics (technical minimum, technical maximum, maximum reserve availability, minimum up/down times, ramp up/down limits) OUTPUTS: - Unit commitment - Energy and reserve scheduling for each hour of the next day

10. 3. Day-Ahead Scheduling Problem DAS problem formulation (MILP): Variable cost coefficients Continuous variables (energy, reserve) Fixed cost coefficients Integer variables (status, start-up, shut-down) overall variable costs overall fixed costs +minimize

11. 3. Day-Ahead Scheduling Problem subject to: Market clearing constraints: Individual constraints: Initial conditions: and

12. 3. Day-Ahead Scheduling Problem DAS problem formulation : overall reserve cost overall fixed costs + minimize overall energy cost + start- up shut-down minimum-load subject to: energy balance reserve requirements market-clearing constraints technical minimum technical maximum maximum reserve availability minimum up/down times ramp up/down limits individual constraints

13. 3. Day-Ahead Scheduling Problem DAS problem formulation : overall reserve cost overall fixed costs + minimize overall energy cost + start- up shut-down minimum-load subject to: energy balance reserve requirements market-clearing constraints technical minimum technical maximum maximum reserve availability minimum up/down times ramp up/down limits individual constraints

14. 3. Day-Ahead Scheduling Problem 3.1 Impact of Reserve Offers Questions: Pricing reserve as separate commodity ? Priced reserve offers ? Offers included in the objective function ? Pricing scheme? Impact on scheduling ? Rules (price caps…) ?

15. 3. Day-Ahead Scheduling Problem 3.1 Impact of Reserve Offers Pricing schemes for reserve: 1.Scheme based on shadow price: a.Non-priced bids (sorting rule based on energy bids) b.Priced bids included in the objective function 2.Scheme based on highest bid accepted: a.Bids not included in the objective function (sorting rule based on reserve bids) b.Bids included in the objective function 3.Pay-as-bid scheme: a.Bids not included in the objective function (sorting rule based on reserve bids) b.Bids included in the objective function

16. 3. Day-Ahead Scheduling Problem 3.2 Impact of Fixed Costs Fixed costs introduce non-convexities Non existence of equilibrium prices in a Walrasian auction Relevant literature: O’Neill et al. (2002, 2005) Hogan and Ring (2003) Bjørndal and Jörnsten (2004) DAS problem: - Should fixed costs be included in the objective function or not? - Should producers be paid for their fixed costs? - If not paid, they must internalize fixed costs in their energy offers, distorting the SMP.

17. 4. Illustrative Example 8-unit example: TypeUnitCapacity (Technical maximum) Technical minimum Energy bid Ligniteu14000250035 Oilu245025080 Gasu347614472 Gasu4300150110 Gasu555015575 Gasu638924070 Gasu738924085 GTu81410150 Energy offers

18. 4. Illustrative Example 8-unit example: TypeUnitReserve availabilityReserve bid Ligniteu130010 Oilu2505 Gasu31504 Gasu4804.5 Gasu51506 Gasu61493.5 Gasu71493 GTu81412 Reserve offers

19. 4. Illustrative Example 8-unit example: UnitStart-up/ shut-down cost Minimum-load cost Minimum up/down time Initial condition u11 000 000-24ON u240 0008008OFF u316 0005508ON u430 0001 00016OFF u524 0007005ON u614 0005003ON u714 0006003OFF u85 0002000OFF Units’ data

20. 4. Illustrative Example Adjusted demand (load curve) Reserve requirement: 600 MW

21. 4. Illustrative Example DAS problem:  modeled with mathematical programming language AMPL  solved with ILOG CPLEX 9.0 optimization software package

22. 4. Illustrative Example Energy prices (SMP) and Reserve Prices (RP) for different pricing schemes

23. 4. Illustrative Example Energy prices (SMP) and Reserve Prices (RP) for different pricing schemes SMPs RPs

24. 4. Illustrative Example Energy prices (SMP) and Reserve Prices (RP) for different pricing schemes SMPs RPs: shadow price scheme RPs: highest bid accepted scheme

25. 4. Illustrative Example UnitCase 1aCase 1bCase 2aCase 2bCase 3aCase 3b u12 636 0002 662 8202 647 9902 650 6502 636 6602 650 650 u2- 30 150- 26 175- 28 300- 27 125- 28 750- 27 875 u3- 3 00219 935-32145- 12 912-12 135 u4- ----- u5- 21 280905- 19 210- 19 045- 24 244- 24 446 u620 15528 47520 07420 88015 34016 431 u7- 7 812- 5 428- 6 024 - 7 812 u822 70144 13315 91025 3806 768 Units’ net profits in €

26. 4. Illustrative Example UnitCase 1aCase 1bCase 2aCase 2bCase 3aCase 3b u12 636 0002 662 8202 647 9902 650 6502 636 6602 650 650 u2- 30 150- 26 175- 28 300- 27 125- 28 750- 27 875 u3- 3 00219 935-32145- 12 912-12 135 u4- ----- u5- 21 280905- 19 210- 19 045- 24 244- 24 446 u620 15528 47520 07420 88015 34016 431 u7- 7 812- 5 428- 6 024 - 7 812 u822 70144 13315 91025 3806 768 Units’ net profits in €

27. 4. Illustrative Example UnitCase 1aCase 1bCase 2aCase 2bCase 3aCase 3b u128.56228.58328.69228.72128.57028.721 u2- 7.947- 6.899- 7.459- 7.149- 7.578- 7.347 u3- 0.4863.163- 0.0050.023- 2.090- 1.925 u4- ----- u5- 4.3690.186- 3.944- 3.910- 4.977- 5.019 u64.1936.0804.1764.4593.1913.509 u7- 8.138- 5.654- 6.275 - 8.138 u8N/A Units’ net profits in €/MWh

28. 4. Illustrative Example Units may incur losses even if they get paid for their fixed costs WHY? Need for a bid/cost recovery mechanism

29. 4. Illustrative Example Case Overall Energy Payments Overall Reserve Payments Overall Fixed Costs Payments 1a7 281 95096 600158 200 1b7 299 050187 800(as 1a) 2a(as 1a)110 400(as 1a) 2b(as 1b)108 000(as 1a) 3a(as 1a)65 032(as 1a) 3b(as 1b)64 722(as 1a) Overall Payments Reserve Payments: range from 0.9 – 2.6 % of energy payments Fixed Costs Payments: about 2.2 % of energy payments

30. 4. Illustrative Example TypeUnitFixed costs included for all cases Fixed costs excluded for all cases except for 3a Ligniteu11-24 Oilu210-2410-22 Gasu31-24 Gasu4-- Gasu51-24 Gasu69-24 Gasu711-14 GTu81-24 Unit Commitment

31. 5. Summary and Conclusions  Sketch of Greece’s electricity system  Simple model of the Day-Ahead Scheduling problem  Emphasis on: frequency-related ancillary services (“reserves”) fixed costs (start-up, shut-down, minimum-load)  Various reserve pricing schemes: shadow price highest bid accepted pay-as bid  Illustrative 8-unit example

32. 5. Summary and Conclusions  Units may incur losses through DAS participation  Bid/cost recovery mechanism is needed  Reserve payments contribute to the same direction  DAS: very complicated problem due to energy – reserve interaction, and non-convexities introduced by fixed costs  careful and incentive-compatible design is needed

33. Questions ?