Supplier's optimal bidding strategy in electricity pay-as-bid auction: Comparison of the Q-learning and a model-based approach |
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Authors: | Morteza Rahimiyan Habib Rajabi Mashhadi |
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Affiliation: | Electrical Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran |
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Abstract: | In this paper, the bidding decision making problem in electricity pay-as-bid auction is studied from a supplier's point of view. The bidding problem is a complicated task, because of suppliers’ uncertain behaviors and demand fluctuation. In a specific case, in which, the market clearing price (MCP) is considered as a continuous random variable with a known probability distribution function (PDF), an analytic solution is proposed. The suggested solution is generalized to consider the effect of supplier market power due to transmission congestion. As a result, an algebraic equation is developed to compute optimal offering price. The basic assumption in this approach is to take the known probabilistic model for the MCP. |
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Keywords: | Bidding strategy Q-learning Pay-as-bid auction Transmission congestion Market power Multi-agent system |
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