GenCos' Behaviors Modeling Based on Q Learning Improved by Dichotomy

• URL: http://arxiv.org/abs/2008.01536v1
• Date: Tue, 4 Aug 2020 13:48:09 GMT
• Title: GenCos' Behaviors Modeling Based on Q Learning Improved by Dichotomy
• Authors: Qiangang Jia, Zhaoyu Hu, Yiyan Li, Zheng Yan, Sijie Chen
• Abstract summary: A novel Q learning algorithm is proposed in this paper. It 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.
• Score: 3.14969586104215
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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