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cs.LG2026
Scaling Laws for Physics-Aware ACOPF Surrogate Learning
Yijiang Li, Emon Dey, Stefano Fenu +3
Learning-based surrogates for AC optimal power flow (ACOPF) promise large speedups over classical solvers, but their operational value depends on physical feasibility as much as pr…
cs.LG2026
Scalable Heterogeneous Graph Foundation Models for Data-Driven Optimal Power Flow in Smart Grids
Massimiliano Lupo Pasini, Yijiang Li, Kibaek Kim +1
Fast and reliable optimal power flow (OPF) approximation is important for power system operation, yet heterogeneous OPF graph models are often evaluated either with architecture-sp…