| Probabilistic charging power forecast of EVCS: Reinforcement learning assisted deep learning approach Y Li, S He, Y Li, L Ge, S Lou, Z Zeng IEEE Transactions on Intelligent Vehicles 8 (1), 344-357, 2022 | 85 | 2022 |
| Federated multiagent deep reinforcement learning approach via physics-informed reward for multimicrogrid energy management Y Li, S He, Y Li, Y Shi, Z Zeng IEEE Transactions on Neural Networks and Learning Systems, 2023 | 61 | 2023 |
| Artificial intelligence-based methods for renewable power system operation Y Li, Y Ding, S He, F Hu, J Duan, G Wen, H Geng, Z Wu, HB Gooi, Y Zhao, ... Nature Reviews Electrical Engineering 1 (3), 163-179, 2024 | 35 | 2024 |
| TransformGraph: A novel short-term electricity net load forecasting model Q Zhang, J Chen, G Xiao, S He, K Deng Energy Reports 9, 2705-2717, 2023 | 34 | 2023 |
| Renewable energy absorption oriented many-objective probabilistic optimal power flow Y Li, S He, Y Li, Q Ding, Z Zeng IEEE Transactions on Network Science and Engineering, 2023 | 14 | 2023 |
| Generation maintenance scheduling based on multi-objective particle swarm optimization considering carbon emissions H Guo, S He, C Huang, Q Zhou, Y Zhao 2021 IEEE 2nd China International Youth Conference on Electrical Engineering …, 2021 | 2 | 2021 |
| Boosting communication efficiency in federated learning for multiagent-based multimicrogrid energy management S He, Y Li, Y Li, Y Shi, CY Chung, Z Zeng IEEE Transactions on Neural Networks and Learning Systems, 2024 | 1 | 2024 |
| Graph Learning for Power Flow Analysis: A Global-Receptive Graph Iteration Network Method J Huang, Y Li, S He, G Hao, C Zhou, Z Zeng IEEE Transactions on Network Science and Engineering, 2024 | | 2024 |
| Unveiling Optimization Potential: Using Large Language Models to Estimate Initial Solutions for Unit Commitment S He, W Zhang, C Chung Available at SSRN 4807712, 0 | | |
