A GL-CN framework deeply integrates physics-guided and physics-constrained knowledge into a dual-channel GCN-MLP model to deliver fast, accurate, and robust frequency security assessment for power grids with high renewable penetration.
A deep spatial-temporal data-driven approach considering microclimates for power system security assessment[J]
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Knowledge-data fusion framework for frequency security assessment in low-inertia power systems
A GL-CN framework deeply integrates physics-guided and physics-constrained knowledge into a dual-channel GCN-MLP model to deliver fast, accurate, and robust frequency security assessment for power grids with high renewable penetration.