4 citations · 6 across the 2 of their papers we have counts for
5 papers
ZTFed-MAS2S: A Zero-Trust Federated Learning Framework with Verifiable Privacy and Trust-Aware Aggregation for Wind Power Data Imputation
Yang Li, Hanjie Wang, Yuanzheng Li +2
Wind power data often suffers from missing values due to sensor faults and unstable transmission at edge sites. While federated learning enables privacy-preserving collaboration wi…
Large Language Model-aided Edge Learning in Distribution System State Estimation
Renyou Xie, Xin Yin, Chaojie Li +4
Distribution system state estimation (DSSE) plays a crucial role in the real-time monitoring, control, and operation of distribution networks. Besides intensive computational requi…
Joint Trading and Scheduling among Coupled Carbon-Electricity-Heat-Gas Industrial Clusters
Dafeng Zhu, Bo Yang, Yu Wu +4
This paper presents a carbon-energy coupling management framework for an industrial park, where the carbon flow model accompanying multi-energy flows is adopted to track and suppre…
Interpretable Deep Reinforcement Learning for Optimizing Heterogeneous Energy Storage Systems
Luolin Xiong, Yang Tang, Chensheng Liu +4
Energy storage systems (ESS) are pivotal component in the energy market, serving as both energy suppliers and consumers. ESS operators can reap benefits from energy arbitrage by op…
Privacy-Preserved Aggregate Thermal Dynamic Model of Buildings
Zeyin Hou, Shuai Lu, Yijun Xu +4
The thermal inertia of buildings brings considerable flexibility to the heating and cooling load, which is known to be a promising demand response resource. The aggregate model tha…