GenCos' Behaviors Modeling Based on Q Learning Improved by Dichotomy
Systems and Control
2020-08-05 v1 Machine Learning
Systems and Control
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.
Keywords
Cite
@article{arxiv.2008.01536,
title = {GenCos' Behaviors Modeling Based on Q Learning Improved by Dichotomy},
author = {Qiangang Jia and Zhaoyu Hu and Yiyan Li and Zheng Yan and Sijie Chen},
journal= {arXiv preprint arXiv:2008.01536},
year = {2020}
}