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A Reinforcement Learning Method For Power Suppliers' Strategic Bidding with Insufficient Information (2008.01552v1)
Published 4 Aug 2020 in eess.SY and cs.SY
Abstract: Power suppliers can exercise market power to gain higher profit. However, this becomes difficult when external information is extremely rare. To get a promising performance in an extremely incomplete information market environment, a novel model-free reinforcement learning algorithm based on the Learning Automata (LA) is proposed in this paper. Besides, this paper analyses the rationality and convergence of the algorithm in case studies based on the Cournot market model.
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