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A Study of Central Auction Based Wholesale Electricity Markets S. Ceppi and N. Gatti. Index. 2. Problem Analysis Context: electricity market Problem: finding the market equilibria State of the Art Original Contributions Introduction of the auction mechanism - PowerPoint PPT Presentation
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A Study of Central Auction Based Wholesale Electricity MarketsS. Ceppi and N. Gatti
S. Ceppi and N. Gatti
2Index
• Problem Analysis• Context: electricity market• Problem: finding the market equilibria• State of the Art
• Original Contributions• Introduction of the auction mechanism• Finding the auction optimal solution• Finding the equilibria in the market
• Conclusions and Future Works
S. Ceppi and N. Gatti
Problem Analysis
S. Ceppi and N. Gatti
Italian Electricity Market
S. Ceppi and N. Gatti
Wholesale Market
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S. Ceppi and N. Gatti
State of the Art
• Problem: finding the best prices• Microeconomic problem → Game Theory
• Two approches in literature:1. Multi-agent simulation [Praca et al., 2003]
• Usually there is not any theoretical guarantee that adaptive/learning agents can converge to the optimal strategy
2. Game theoretical: POOLCO model [Hobbs, 2001]• It is based on the Cournot oligopoly: generators choose
only the amount of electricity to sell, while the price is a function of electricity demand and supply
• It admits a unique equilibrium• In the equilibrium all the generators bid the same price• No real-world auction mechanism is considered
S. Ceppi and N. Gatti
Original Contributions
S. Ceppi and N. Gatti
Real-World Auction Mechanism
• Generator:• Action: bid a price per electicity unit for each local region in
which it produces• Goal: maximize its utility
• Electricity Market Manager (EMM):• Actions:
• Choose the generators from which to buy electricity • Choose the amount of electricity to buy from each generator
• Goal: minimize the clearing price• Constraints:
• Satisfy the customers’ demand of electricity• Generators capacities• Network capacity• Market rules
S. Ceppi and N. Gatti
Market Rules
S. Ceppi and N. Gatti
Winner Determination
• Steps:• Bids collection• Bids ordering• Bids acceptance until the customers’ demand is satisfied
S. Ceppi and N. Gatti
Finding Equilibrium Strategies
• Solution Concept: Nash equilibrium in pure strategies• Reduction of the model
• Infinite possible actions → finite possible actions• Search algorithm based on Best Response Dynamics• Use of Tabu List to ensure that the algorithm ends• Implementation
• Static• Dynamic
S. Ceppi and N. Gatti
Conclusions and Future Works
S. Ceppi and N. Gatti
Conclusions
• Context: wholesale electricity market based on a central auction• Original Contributions:
• Enrichment of the model presented in literature with a real-world auction mechanism
• Greedy Algorithm to find the best solution of the Winner Determination Problem for the auction
• Computation of the equilibrium strategy using a solving algorithm based on best response search
• The introduction of the auction mechanism leads to an equilibrium which is different from that obtained in its absence:• There exist multiple equilibria• Generators, in general, bid different prices at the
equilibrium
S. Ceppi and N. Gatti
Future Works
• Efficiency improvement of the algorithms for:• Winner Determination Problem• Equilibrium Computation
• Equilibrium characterization by Evolutionary Game Theory for the selection of one equilibrium when multiple equilibria exist
• Study of the auction mechanism in the presence of uncertain information
• Bayesian Games perspective• Mechanism Design perspective