4 papers
Multi-agent Reinforcement Learning for Low-Carbon P2P Energy Trading among Self-Interested Microgrids
Junhao Ren, Honglin Gao, Lan Zhao +3
Uncertainties in renewable generation and demand dynamics challenge day-ahead scheduling. To enhance renewable penetration and maintain intra-day balance, we develop a multi-agent…
Multi-agent Reinforcement Learning-based Joint Design of Low-Carbon P2P Market and Bidding Strategy in Microgrids
Junhao Ren, Honglin Gao, Sijie Wang +5
The challenges of the uncertainties in renewable energy generation and the instability of the real-time market limit the effective utilization of clean energy in microgrid communit…
A Unified Framework to Classify Business Activities into International Standard Industrial Classification through Large Language Models for Circular Economy
Xiang Li, Lan Zhao, Junhao Ren +4
Effective information gathering and knowledge codification are pivotal for developing recommendation systems that promote circular economy practices. One promising approach involve…
Top K Enhanced Reinforcement Learning Attacks on Heterogeneous Graph Node Classification
Honglin Gao, Xiang Li, Yajuan Sun +1
Graph Neural Networks (GNNs) have attracted substantial interest due to their exceptional performance on graph-based data. However, their robustness, especially on heterogeneous gr…