Data-driven dynamical control for bottom-up energy Internet system H Hua, Z Qin, N Dong, Y Qin, M Ye, Z Wang, X Chen, J Cao IEEE Transactions on Sustainable Energy 13 (1), 315-327, 2021 | 116 | 2021 |
Privacy preserving load control of residential microgrid via deep reinforcement learning Z Qin, D Liu, H Hua, J Cao IEEE Transactions on Smart Grid 12 (5), 4079-4089, 2021 | 81 | 2021 |
Incremental incentive mechanism design for diversified consumers in demand response D Liu, Z Qin, H Hua, Y Ding, J Cao Applied Energy 329, 120240, 2023 | 37 | 2023 |
Demand-side joint electricity and carbon trading mechanism H Hua, X Chen, L Gan, J Sun, N Dong, D Liu, Z Qin, K Li, S Hu IEEE Transactions on Industrial Cyber-Physical Systems, 2023 | 22 | 2023 |
Optimal electricity trading strategy for a household microgrid Z Qin, H Hua, H Liang, R Herzallah, Y Zhou, J Cao 2020 IEEE 16th International Conference on Control & Automation (ICCA), 1308 …, 2020 | 14 | 2020 |
Distributed power dispatching solution for a future economic and environment-friendly energy internet Y Li, Z Qin, F Zhang, Y Qin, H Hua, J Cao Proceedings of the 2020 The 9th International Conference on Informatics …, 2020 | 5 | 2020 |
Does Explicit Prediction Matter in Deep Reinforcement Learning-Based Energy Management? Z Qin, H Zhang, Y Zhao, H Xie, J Cao 2021 IEEE International Conference on Energy Internet (ICEI), 2021 | 3 | 2021 |
Stochastic distributed control for frequency regulation in energy Internet: An ADMM approach G Zhang, Y Qin, Y Li, H Hua, Z Qin, J Cao 2019 9th International Conference on Power and Energy Systems (ICPES), 1-6, 2019 | 3 | 2019 |
Data-Driven Output Feedback Control Based on Behavioral Approach Z Qin, A Karimi 2024 American Control Conference (ACC), 3954-3959, 2024 | 1 | 2024 |
Scalable Multi-Agent Reinforcement Learning for Residential Load Scheduling Under Data Governance Z Qin, N Dong, D Liu, Z Wang, J Cao IEEE Transactions on Industrial Cyber-Physical Systems, 2024 | | 2024 |