activity
20242026
most citedPowerGraph-LLM: Novel Power Grid Graph Embedding and Optimization with Large Language Models

20 citations · 20 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Physics-Aware Heterogeneous GNN Architecture for Real-Time BESS Optimization in Unbalanced Distribution Systems

Aoxiang Ma, Salah Ghamizi, Jun Cao +1

Battery energy storage systems (BESS) have become increasingly vital in three-phase unbalanced distribution grids for maintaining voltage stability and enabling optimal dispatch. H…

cs.AI202620 cited

PowerGraph-LLM: Novel Power Grid Graph Embedding and Optimization with Large Language Models

Fabien Bernier, Jun Cao, Maxime Cordy +1

Efficiently solving Optimal Power Flow (OPF) problems in power systems is crucial for operational planning and grid management. There is a growing need for scalable algorithms capa…

cs.LG2025

SafePowerGraph-HIL: Real-Time HIL Validation of Heterogeneous GNNs for Bridging Sim-to-Real Gap in Power Grids

Aoxiang Ma, Salah Ghamizi, Jun Cao +1

As machine learning (ML) techniques gain prominence in power system research, validating these methods' effectiveness under real-world conditions requires real-time hardware-in-the…

eess.SY2024

PowerFlowMultiNet: Multigraph Neural Networks for Unbalanced Three-Phase Distribution Systems

Salah Ghamizi, Jun Cao, Aoxiang Ma +1

Efficiently solving unbalanced three-phase power flow in distribution grids is pivotal for grid analysis and simulation. There is a pressing need for scalable algorithms capable of…

cs.LG2024

SafePowerGraph: Safety-aware Evaluation of Graph Neural Networks for Transmission Power Grids

Salah Ghamizi, Aleksandar Bojchevski, Aoxiang Ma +1

Power grids are critical infrastructures of paramount importance to modern society and their rapid evolution and interconnections has heightened the complexity of power systems (PS…