| 1 |
Distributed Economic Dispatch for Energy Internet Based on Multiagent Consensus Control
Chen WS, Li T
IEEE Transactions on Automatic Control, 66(1), 137, 2021 |
| 2 |
Optimal energy management strategies for energy Internet via deep reinforcement learning approach
Hua HC, Qin YC, Hao CT, Cao JW
Applied Energy, 239, 598, 2019 |
| 3 |
Deep learning aided interval state prediction for improving cyber security in energy internet
Wang HZ, Ruan JQ, Ma ZW, Zhou B, Fu XQ, Cao GZ
Energy, 174, 1292, 2019 |
| 4 |
A new generation of AI: A review and perspective on machine learning technologies applied to smart energy and electric power systems
Cheng LF, Yu T
International Journal of Energy Research, 43(6), 1928, 2019 |
| 5 |
Smart dispatching for energy internet with complex cyber-physical-social systems: A parallel dispatch perspective
Cheng LF, Yu T
International Journal of Energy Research, 43(8), 3080, 2019 |
| 6 |
Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch
Wang Y, Zhang N, Zhuo ZY, Kang CQ, Kirschen D
Applied Energy, 210, 1141, 2018 |
| 7 |
Cost-efficient multi-energy management with flexible complementarity strategy for energy internet
Si FY, Wang JK, Han YH, Zhao Q, Han P, Li Y
Applied Energy, 231, 803, 2018 |
| 8 |
How to improve the competiveness of natural gas in China with Energy Internet and "The Belt and Road Initiative"
Hou JC, Wang C, Liu PK
International Journal of Energy Research, 42(15), 4562, 2018 |
| 9 |
Review and prospect of integrated demand response in the multi-energy system
Wang JX, Zhong HW, Ma ZM, Xia Q, Kang CQ
Applied Energy, 202, 772, 2017 |
| 10 |
Energy Internet: The business perspective
Zhou KL, Yang SL, Shao Z
Applied Energy, 178, 212, 2016 |
