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Paper detail

GenCos' Behaviors Modeling Based on Q Learning Improved by Dichotomy

Q learning is widely used to simulate the behaviors of generation companies (GenCos) in an electricity market. However, existing Q learning method usually requires numerous iterations to converge, which is time-consuming and inefficient in practice. To enhance the calculation efficiency, a novel Q learning algorithm improved by dichotomy is proposed in this paper. This method modifies the update process of the Q table by dichotomizing the state space and the action space step by step. Simulation results in a repeated Cournot game show the effectiveness of the proposed algorithm.

preprint2020arXivOpen access
Qiangang JiaZhaoyu HuYiyan LiZheng YanSijie Chen
Systems and Controleess.SYMachine Learning
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Qiangang JiaZhaoyu HuYiyan LiZheng YanSijie Chen

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