Why Japan remains skeptical of restructuring Study of Electricity Market Bidding Characteristics for Modeling Generation Capacity Growth

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1 Why Japan remains skeptical of restructuring Study of Electricity Market Bidding Characteristics for Modeling Generation Capacity Growth Satoru Ihara Retired Tetsuo Sasaki, Toshihisa Kadoya Kansai Electric Power Company, Osaka, Japan Presented to: New England Chapter International Association for Energy Economics Cambridge, Massachusetts November 17,

2 Study Objective: Critically evaluate American way of deregulating the electricity market. 2

3 Japan 130 million people, 200 GW system EPC Name Generation Normal GW (Rated GW) 500 KV AC DC Link Hokkaido 5 GW 0 GW (0.6 GW) Kyushu 17 GW 2.2 GW (5.6 GW) 0.8 GW (5.6 GW) Hokuriku 6 GW 0.3 GW (0.3 GW) Tohoku 15 GW 5 GW (6 GW) Chugoku 12 GW 2.6 GW (17 GW) Kansai 33 GW 1.5 GW (5.6 GW) Chubu 28 GW 0 GW (0.9 GW) Tokyo 64 GW 1.4 GW (2.4 GW) Shikoku 6 GW 1.4 GW (1.4 GW) 60 Hz 102 GW 50 Hz 84 GW 3

4 Japan With declining population, GDP and power system will cease to expand. Without natural resources, Japan is totally dependent on imported fuel and raw material. Cooperation and social benefits are valued more than competition and individual gains. Power companies will remain vertically integrated with retail market deregulated. Early retirement of inefficient units is reducing total fuel consumption. Generation mix is optimized. Transmission losses are minimized through selfsufficient generation within each company while maintaining tie-flow capabilities for emergency use. 4

5 Boom-burst cycles in generation capacity growth? PJM Simulation by PA Consulting 5

6 Where is growth? PJM Historic Data and Simulation by PA Consulting 6

7 Limitation of Forecasting Model The model involves many assumptions, thousands of state variables, many feedback loops and delays. It is almost a black box. We need to believe all the assumptions. The past influences the future but cannot be extrapolated into the future: When will new nuclear plants be constructed? Will hydro plants like NYPA s be constructed for the benefit of the people? Will new technologies nobody knows yet change the future? 7

8 Tried to model PJM, NY ISO and ISO NE (Work by GE Power Systems) NY ISO modeling failed. Network congestion needs to be modeled? 8

9 Modeling Generation Capacity Growth (Work by GE Power Systems) Price Signals Bidder characteristics Price formation mechanism New Plant Addition Old Plant Retirement Developer characteristics Plant selection 9

10 Documents on PJM Market Rules as of 2001 (Collected by Andrew P. Hartshorn, LECG, LLC) 10

11 PJM Market Rules 150 page summary by LECG Market Sellers Bid data or Schedule Day-Ahead Market Demand Schedule or Price Demand Data Market Buyers Security- Constrained Unit Commitment Reserve Requirements Network Security Assessment Network Data Hourly Schedule LMP LMP (Locational Marginal Price) Hourly Schedule Bids Real-Time Market Security- Constrained Economic Dispatch Load Forecast Reserve Requirements Network Security Assessment Network Data Dispatch Real-Time LMP LMP Actual Generation Hourly Schedule Payment Settlement Actual Load Payment 11

12 PJM Electricity Market Data Study by GE Power Systems Many price spikes in July Mid-price range widened 12

13 PJM Electricity Market Data Study by GE Power Systems 13

14 Supply Margin Scarcity Resulting in Price Spikes (PJM Electricity Market Data Study by GE Power Systems) 14

15 Large Income during Price Spikes in July (PJM Electricity Market Data Study by GE Power Systems) 15

16 Three companies might have speculated in July, (PJM Electricity Market Data Study by GE Power Systems) 16

17 Minimum Price Curves of 11 Companies Who determined the price? (PJM Electricity Market Data Study by GE Power Systems) Capacity for Speculation 17

18 One company may have determined the price. (PJM Electricity Market Data Study by GE Power Systems) Speculated capacities held constant except for one company. 18

19 Observed Speculator Behavior (PJM Electricity Market Data Study by GE Power Systems) Price spike today? yes Tomorrow s load similar to today s load? Speculate yes no no Do not speculate 19

20 NY and Neighboring Areas Modeled by GE Power Systems 600 GW System with 6,300 generators, 28,000 buses and 42,000 branches Canada 3400 West 5200 East PJM ISO-NE 1100 New York City 100 Long Island 20

21 Hourly Load Data for up to 175 Areas for many years GE MAPS used for NY ISO Study Generation Data heat rates & fuel cost model data emission model data outage & maintenance data energy storage model parameters for up to 7,500 units MAPS Multi-Area Production Simulation Unit Commitment Hourly Dispatch Locational Marginal Price Tie Flows Congestion Cost Transmission Data up to 60,000 lines up to 7,500 constraints for linearized network model Load flow Data Stability Data Transfer Limits PSLF/PSDS Minimize Total Cost of Generation subject to: Total Generation = Total Load + Total Line Loss Min < Transmission Flow < Max where: (Transmission Flow) = A x (Bus Injection) + b Bus Injection = Bus Generation - Bus Load A = Generation Shift Factor Matrix b = Flow Adjustment for Base Condition 21

22 NY ISO Study under Fictitious Assumptions (MAPS Simulation by GE Power Systems) 22

23 NY ISO Study (MAPS Simulation by GE Power Systems) Example with fictitious assumptions on: Loads and generator availability Bidder composition (NYC vs. rest) Capacities subject to speculation Showed: Hard to create initial price spike Modeled speculation sustains price spikes Prices return to normal as supply margin changes 23

24 Price went quickly up with gas price & slowly down (PJM Electricity Market Data Study by GE Power Systems) Nash Equilibrium? 24

25 Simple Example with 2 Players 100 MW capacity each $60/ MWh cost for both Load: 100 MW for 12 hours 200 MW for 12 hours Company A Profit (K$/day) $60 / MWh Company B Bid =$150 / MWh $120 / MWh $90 / MWh X Y High-priced points Zero-profit point Z $30 / MWh Company A Bid ($/MWh) 25

26 Conditions for Nash Equilibrium $ / MWH p Area 2 q p p - p (p, q) (p p, q + q) Area 1 (p - p) q - c Area 2 > Area 1 for all players 0 Cost Curve c q c q + q Hourly MW p p q > q - p q + p q c No more to sell at p Large company q = 0 q >> q 26

27 Logical Strategy for Large Companies Bid high and give market share to small companies - No data available for proof Other reasons for slow normalization of electricity price: - Long-term gas contracts bound some to high cost - Limit on bid prices during capacity deficiency based on past bids 27

28 Evaluations Price spikes might be wrong signals to send in Japan. With price spikes like those in PJM in 1999, Japan would not be able to reduce the total fuel consumption through early retirement of inefficient units. Uncertainty and instability are undesirable in Japan. Without indigenous resources, Japan imports almost everything, and Japanese economy can be easily upset by shortages, market manipulation, unexpected and unplanned-for situations. 28

29 Conclusions Generation capacity growth in deregulated market is very difficult to predict: Market rules constantly change Bidders create innovative new strategies Developers and investors interpret price signals their own ways U.S. type deregulation might not be good everywhere Uncertainty & instability affordable? Search of market rules by trial & error Boom-burst cycles Reasonable reserves & good mix of power plants obtainable? 29

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