一、个人基本信息及简要介绍

张国洲，男，工学博士。

2019.09-2022.12 电子科技大学机械与电气工程学院 博士

2016.09-2019.06 电子科技大学机械与电气工程学院 硕士  

2012.09-2016.06 重庆理工大学电子与电气工程学院 本科

二、主要研究领域及方向

1）双高电力系统的稳定分析与控制

2）综合能源系统的运行优化研究

3）机器学习在电力系统稳定控制中的应用

三、社会工作

IEEE会员；担任IEEE Transactions on Industrial Informatics, IEEE Transactions on Power System, International journal of Electrical Power and Energy System, IET Renewable Power Generation等中科院一区、二区期刊以及国际会议审稿人。

四、近年科研项目及获奖情况

1.中央高校基本科研业务费博士启动基金，高水电占比系统振荡抑制关键技术研究，2024/01-2026/12，在研，主持；

2.国家重点研发计划, 弱互联混合可再生能源系统规划与稳定控制关键技术研究，2020/07-2022/06，结题，参与；

3.四川省重点研发计划，智慧电厂电气控制系统关键技术及应用示范，2019/1-2020/12，结题，参与；

五、近年科研代表论文

已发表中科院SCI一区/二区论文20余篇，其中，1篇获得2021川渝科技学术大会优秀论文二等奖，1篇论文获 2020年《Journal of Modern Power Systems and Clean Energy》年度最佳论文奖, 1篇论文入选《IET Renewable Power Generation》封面文章，部分代表性论文如下：

[1] Guozhou Zhang, Junbo Zhao, Weihao Hu, et al. "A novel data-driven self-tuning SVC additional fractional-order sliding mode controller for transient voltage stability with wind generations" IEEE Transactions on Power Systems, early access, 2022.

[2] Guozhou Zhang, Weihao Hu, Junbao Zhao, et al, "A novel deep reinforcement learning enabled multi-band PSS for multi-mode oscillation control," IEEE Transactions on Power Systems, vol. 36, no. 4, pp. 3794-3797, Jul. 2021.

[3] Guozhou Zhang, Weihao Hu, Di Cao, et al, "Deep reinforcement learning-based approach for proportional resonance power system stabilizer to prevent ultra-low-frequency oscillations," IEEE Transactions on Smart Grid, vol. 11, no. 6, pp. 5260-5272, Nov. 2020.

[4] Guozhou Zhang, Junbo Zhao, Weihao Hu, et al, "A multiagent deep reinforcement learning-enabled dual-branch damping controller for multimode scillation," IEEE Transactions on Control Systems Technology, early access.

[5] Guozhou Zhang, Weihao Hu, Di Cao, et al, A multi-agent deep reinforcement learning approach enabled distributed energy management schedule for the coordinate control of multi-energy hub with gas, electricity, and freshwater, Energy Conversion and Management, vol. 255, 2022, pp. 115340.

[6] Guozhou Zhang, Weihao Hu, Di Cao, et al, Data-driven optimal energy management for a wind-solar-diesel-battery-reverse osmosis hybrid energy system using a deep reinforcement learning approach, Energy Conversion and Management, vol. 227, 2021, pp. 113608.

[7] Guozhou Zhang, Weihao Hu, Di Cao, Dao Zhou, Qi Huang, Zhe Chen, Frede Blaabjerg, "Coordinated active and reactive power dynamic dispatch strategy for wind farms to minimize levelized production cost considering system uncertainty: A soft actor-critic approach, " Renewable Energy, vol. 218, 2023, pp. 119335.

[8] Guozhou Zhang, Weihao Hu, Di Cao, et al, "A novel deep reinforcement learning enabled sparsity promoting adaptive control method to improve the stability of power systems with wind energy penetration," Renewable Energy, vol. 178, 2021, pp. 363-376.

 [9] Guozhou Zhang, Weihao Hu, Di Cao, et al, A data-driven approach for designing STATCOM additional damping controller for wind farms, International Journal of Electrical Power & Energy Systems, vol. 117, 2020, pp. 105620.

[10] Guozhou Zhang, Junbao Zhao, Weihao Hu, et al, " Deep reinforcement learning enabled bi-level optimization of hydro-governor parameters for ultra-low frequency oscillation control," Journal of Modern Power Systems and Clean Energy, accept.

[11] 张国洲，易建波，滕予非，王鹏，黄琦，多运行方式下机 PSS 的协调优化方法[J]. 电网技术，2018, 42(9): 2797-2805.

[12] 易建波, 张国洲, 张鹏, 刘敏, 张星. 抑制超低频振荡的稳定器控制机理及策略验证. 电工技术学报: 2022, :37(05): 1219-1228.

[13] 易建波, 张国洲, 张鹏, 刘敏, 张星. 超低频振荡阻尼控制中的水轮机调速系统参数双层优化策略. 电工技术学报: 2022, :37(05): 1219-1228.

六、获批（授权）的发明专利

1. 易建波，黄琦，井实，张国洲，董彬彬。一种计及超低频振荡的调速器PID参数鲁棒优化方法。专利号：CN10861622B

2. 胡维昊, 任曼曼, 井实, 张国洲, 曹迪, 李坚, 张真源, 唐远鸿, 邓惠文, 王浩。一种计及风速变化的控制器自适应鲁棒优化方法。专利号：CN112510700B

七、联系地址、电话/传真、邮箱

联系地址：bat365在线平台新工科大楼

邮箱：gzzhang@swu.edu.cn