张 斌

发布者:宋阳发布时间:2025-03-28浏览次数:45

张 斌

职称:  讲师

研究方向: 人工智能在电力系统中的应用、新能源电力系统优化

Email: 101013887@seu.edu.cn

办公电话: 19502203089




个人简介:

张斌,博士,本科毕业于河海大学,硕士毕业于电子科技大学,博士毕业于丹麦奥尔堡大学。 2025年加入东南大学电气工程学院。



论著:       

  1. Bin Zhang, Weihao Hu, Di Cao, Amer M.Y. M. Ghias, and Zhe Chen*, Novel data-driven decentralized coordination model for electric vehicle aggregator and energy hub entities in multi-energy system using an improved multi-agent DRL approach, Applied Energy, vol. 339, pp. 120902, 2023.

  2. Bin Zhang, Xiao Xu, Weihao Hu, Zhe Chen, Two-timescale autonomous energy management model based on multi-agent deep reinforcement learning approach for residential multicarrier energy system, Applied Energy, vol. 351, no. 121777, 2023.

  3. Bin Zhang, Di Cao, Weihao Hu, and Zhe Chen. Physics-informed multi-agent deep reinforcement learning enabled distributed voltage control for active distribution network, International Journal of Electrical & Power System, vol. 155, no. 109641, 2024.

  4. Bin Zhang, Weihao Hu, Xiao Xu, Zhenyuan Zhang, Zhe Chen, Hybrid data-driven method for low-carbon economic energy management strategy in electricity-gas coupled energy systems based on transformer network and deep reinforcement learning, Energy, vol. 273, no. 127183, 2023.

  5. Bin Zhang, Weihao Hu, Amer M.Y.M. Ghias, Xiao Xu, Zhe Chen, Multi-agent deep reinforcement learning based distributed control architecture for interconnected multi-energy microgrid energy management and optimization, Energy Conversion and Management, vol. 277, no. 116647, 2023.

  6. Xuewei Wu, Bin Zhang, Mads Nielsen, Zhe Chen. Multi-stage planning of integrated electricity-gas-heating system in the context of carbon emission reduction, Applied Energy, vol. 358, no. 122584, 2024.

  7. 胡维昊, 曹迪, 黄琦, 张斌, 李思辰, 陈哲. 深度强化学习在配电网优化运行中的应用[J]. 电力系统自动化, 2023, 47 (14): 174-191.

  8. Tao Li, Weihao Hu, Bin Zhang, Guozhou Zhang, Jian Li, Zhe Chen, Frede Blaabjerg, Mechanism analysis and real-time control of energy storage based grid power oscillation damping: A soft actor-critic approach, IEEE Transactions on Sustainable Energy, vol. 12, no. 4, pp. 1915-1926, 2021.