most citedPhysical Informed-Inspired Deep Reinforcement Learning Based Bi-Level Programming for Microgrid Scheduling

26 citations · 26 across the 2 of their papers we have counts for

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eess.SY2024★ 26 cited

Physical Informed-Inspired Deep Reinforcement Learning Based Bi-Level Programming for Microgrid Scheduling

Yang Li, Jiankai Gao, Yuanzheng Li +4

To coordinate the interests of operator and users in a microgrid under complex and changeable operating conditions, this paper proposes a microgrid scheduling model considering the…

eess.SY2024

Strategic SDN-based Microgrid Formation for Managing Communication Failures in Distribution System Restoration

Jian Zhong, Chen Chen, Zhaohong Bie +1

Grid modernization has increased the reliance of power networks on cyber networks within distribution systems (DSs), heightening their vulnerability to disasters. Communication net…