目前主要从事新能源发电、主动配电网的研究和教学工作。

主持国家自然科学基金青年基金、安徽省重点实验室开放基金、中央高校基本科研业务费项目、校学术新人提升计划以及电网公司科研项目多项。

近年来在国内外学术期刊发表论文近20篇，其中以第一作者/通信作者发表SCI/EI期刊论文12篇。

申请发明专利6项，其中获授权专利2项。

部分科研项目（主持）：

     1）国家自然科学基金青年基金项目（52407092）：面向低碳需求的用户侧共享储能电碳耦合交易及优化运行研究，2025-2027

      2）安徽省重点实验室开放基金项目：多时间尺度用户侧储能协调优化调度策略研究，2024-2025

      3）中央高校基本科研业务费项目：青年教师科研创新启动专项（JZ2024HGQA0081）、学术新人提升计划项目（JZ2024HGTA0181）

      4）国网安徽省电力公司科技项目：考虑车-路-网耦合的电动汽车充电负荷特性分析及调度运行优化研究，2024-2025

      5）企业委托横向科技项目：特高压换流变励磁涌流分析与评估技术服务合同，2023-2024

代表性学术论文：

1) Ye He, Hongyun Fu, Andrew Y. Wu, et al. Enhancing resilience of distribution system under extreme weather: Two-stage energy storage system configuration strategy based on robust optimization[J]. International Journal of Electrical Power & Energy Systems, 2025,167:110624.

2) Ye He, Hongbin Wu, Ming Ding, et al. Optimized shared energy storage in a peer-to-peer energy trading market: two-stage strategic model regards bargaining and evolutionary game theory[J]. Renewable Energy, 2024, 224: 120190. 

3) Ye He, Wenyuan Bai, Lulu Wang, et al. SOH estimation for lithium-ion batteries: An improved GPR optimization method based on the developed feature extraction[J]. Journal of Energy Storage, 2024,83:110678.  （ESI高被引）

4)  Ye He, Hongbin Wu, Rui Bi, et al. Coordinated planning of distributed generation and soft open points in active distribution network based on complete information dynamic game[J], International Journal of Electrical Power and Energy Systems, 2022, 138: 107953. 

5) Ye He, Hongbin Wu, Ming Ding, et al. Reduction Method for Multi-Period Time Series Scenarios of Wind Power[J], Electric Power Systems Research,2023, 214: 108813.

6）何叶，杨晓东，吴红斌, 等. 面向新型配电系统灵活性提升的智能软开关-储能协调规划[J]. 电力系统自动化, 2023,47(18):142-150.

7）Lei Zhang, Ye He*, Nikos D. Hatziargyriou, et al. An Optimization Scheduling Strategy for Hydrogen-based Integrated Energy Systems Using Multi-Agent Deep Reinforcement Learning[J]. Energy Conversion and Management, 2025,326: 119483.

8）Hongbin Wu, Xinjie Lan, Ye He*，et al.  Orderly charging of electric vehicles: A two-stage spatial-temporal scheduling method based on user-personalized navigation[J]. Applied Energy, 2025, 378: 124800.

9）Hongbin Wu, Zhe Liu, Ye He*, et al. Two-layer optimal scheduling method for regional integrated energy system considering flexibility characteristics of CHP system. Energy,  2024, 308: 132970.

10）Hansheng Tang, Ye He*, Xiaoming Wang, et al. Two-stage multi-mode voltage control for distribution networks: A deep reinforcement learning approach based on multiple intelligences[J]. IEEE Transactions on Industry Applications, 2024,60(4): 5681-5691