Scalable Heterogeneous Graph Foundation Models for Data-Driven Optimal Power Flow in Smart Grids

arXiv:2605.23194 · cs.LG, cs.AI · Submitted 2026-05-22 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-05-22

Updated: 2026-09-28

Code: https://github.com/ORNL/HydraGNN

Terminology

• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Heterogeneous Graph — 3× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Foundation Models — 1× in this paper · explained in 7 episodes
• Graph Neural Network (GNN) — 1× in this paper · explained in 3 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Optimal Power Flow Using Graph Neural Networks
• LUMINA: Foundation Models for Topology Transferable ACOPF
• LUMINA: A Grid Foundation Model for Benchmarking AC Optimal Power Flow Surrogate Learning
• Towards Systematic Generalization for Power Grid Optimization Problems
• OPFData: Large-scale datasets for AC optimal power flow with topological perturbations
• The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms
• Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction

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