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.
Review on deep learning applications in frequency analysis and control of modern power system[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.