122 citations · 446 across the 9 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…
cs.LG2024★ 15 cited
Extraction of Typical Operating Scenarios of New Power System Based on Deep Time Series Aggregation
Zhaoyang Qu, Zhenming Zhang, Nan Qu +5
Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system. This study proposed a novel deep time series aggregation…
eess.SY2024★ 52 cited
Localization of Dummy Data Injection Attacks in Power Systems Considering Incomplete Topological Information: A Spatio-Temporal Graph Wavelet Convolutional Neural Network Approach
Zhaoyang Qu, Yunchang Dong, Yang Li +8
The emergence of novel the dummy data injection attack (DDIA) poses a severe threat to the secure and stable operation of power systems. These attacks are particularly perilous due…