Open access
Oct 2026
Hierarchical Graph Neural Network for Probabilistic Power Flow With Grid Topology Contingencies
Data-driven surrogates reduce the nonlinear solves required for probabilistic power flow (PPF), but models tied to a fixed bus--branch graph often generalize poorly when outages change electrical coupling. This paper proposes a topology-decomposition-driven hierarchical bidirectional graph neural network (TDD--HBGNN) f...
Jin-Bao Wang, Jun Liu, Shi-Liang Zhang et al.
· IEEE Transactions on Industr... · 0 citations