1 / 26

Deregulated Power, Pollution, and Game Theory

Explore the impact of deregulation on pollutant emissions distribution and how game theory can provide insights in a cap-and-trade pollution scenario. Learn about power grid challenges, pricing strategies, and the application of game theory in optimizing energy generation. Discover market timelines, congestion management, and mechanisms to address grid congestion effectively.

tova
Download Presentation

Deregulated Power, Pollution, and Game Theory

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Deregulated Power, Pollution, and Game Theory Frank Deviney 11/16/05

  2. My Questions • How does deregulation affect the distribution of pollutant emissions? • Can game theory help answer this question?

  3. Pollution – Cap and Trade • SO2 allowances are allocated or auctioned • After-market exists for trading allowances • ~9 million allowances per year • An allowance permits emission of a fixed amount of SO2 • Local power plants • Possum Point 0.001 lbs SO2/mmBtu 550+ MW • Mt Storm 0.10 lbs SO2/mmBtu 1600 MW • Bremo Bluff 1.45 lbs SO2/mmBtu 250 MW • Fear – hot spots

  4. Power Grid Situation • Problems under environment of deregulation • Energy (Generation) pricing • Congestion management and pricing • Others • Capacity expansion • Reserve capacity • Environmental/other constraints

  5. - 2004 - 2005

  6. Generation • Old Paradigm – minimize costs subject to “Keep the Lights On” constraint. A regulated monopolies environment. • New Paradigm – Competition leads to efficiency. Maximize benefits for all. • Game theory has been used to: • Justify the switch • Establish bidding procedures for participants

  7. Generation I • Ferrero, Rivera, and Shahidehpour, 1998 • Objective: maximize each participant’s benefit • Assumptions (PoolCo model) • Coordinator schedules (dispatches) generation beginning with lowest bid price until demand is met • Generators receive the “spot price”, the max bid of all dispatched generators • Assumption: spot price equal throughout the grid • “sealed bids” – submit bids at same time • Knows own cost but not others’ costs • Knows others’ bid history, but not their benefit • Gen costs are 2nd order fn of power output

  8. Generation I, cont. • Aspects of the Game • Formulated as non-cooperative, two-player • Correlated costs allowed (used in the example) • Strategy is to bid with respect to initial marginal cost (as if not in the market) • Probability distribution of the game derived from available information, they use fuel prices in the example. • Demonstrate analytical solution for Nash equilibria  so presumably participant could use game theory to establish bidding positions

  9. Generation II • Park, Kim, Kim, Jung, and Park 2001 • Assumptions (PoolCo model) • Total generation bids  demand • Individual generation bid < demand • Demand is constant • Transmission losses and congestion ignored • Complete information available to all (apparently holds in some countries) • Again the 2nd order cost function • Generation allocation • < last-dispatched unit, all generation offered • = last-dispatched unit, split with others with equal bids

  10. Generation II, cont. • Aspects of the Game • Formulated as non-cooperative, two-player • Strategy = (bid price, bid generation) in continuous space • Suggest a hybrid approach combining analytical and graphical methods • Inelastic demand  Bidding price cap

  11. A question • I have tended to think of the allowances as being a constraint on production. Generator’s goal is to maximize production or profit subject to the emission allowance constraint. • Companies tend to re-distribute their allowances in-house rather than through the market. • How does the existence of such global constraints affect the assumptions inherent in a non-cooperative game?

  12. How does PJM do it? • As complicated as the game theory models may be, the actual market is more complicated

  13. Market Timelines • Day-ahead • Until noon – PJM receives bids and offers for energy for next day • Noon until 4 p.m. Market is closed. PJM computes next-day LMPs. • 4 p.m. PJM posts initial day-ahead LMPs. • 4-6 p.m. Market re-opens for re-bidding. • 6 p.m. – Day-ahead LMPs locked in. • Remainder of day – PJM continually updates the dispatch list • Real-time ? • 5-minute intervals?

  14. What is congestion? • When the economic dispatch solution cannot be implemented due to transmission line constraints.

  15. Congestion • Silva, Wollenberg, and Zheng, 2001 • Assumptions • Constant marginal cost for generation • Constant demand • An “economic dispatch” solution exists • Competitors will not provide cost information, but can estimate others’ costs • Marginal cost domains are bounded • The pdf is otherwise continuous

  16. Congestion, cont. • Mechanism Design • A mechanism is a game. Proposed game is that: • Generators submit bids to agent • Agent allocates production and reward • Goal is to get generators to provide true cost bids • Claim is that the proposed payment scheme achieves this

  17. What does PJM do? • LMPs • Implicit congestion – payments/receipts based on bus LMP • explicit congestion – transactions pay differential between source and sink LMPs • FTRs – Financial Transmission Rights • Monthly, annual auctions • Serve as a hedge against day-ahead uncertainty as to when and where congestion will occur.

More Related