Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
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A Gaussian Process surrogate for the stability exponent of generator dynamics is integrated into AC Optimal Power Flow to produce both cost-optimal and dynamically stable operating points.
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Learning Dynamic Stability Landscapes in Synchronization Networks
Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
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Stability-Constrained AC Optimal Power Flow--A Gaussian Process-Based Approach
A Gaussian Process surrogate for the stability exponent of generator dynamics is integrated into AC Optimal Power Flow to produce both cost-optimal and dynamically stable operating points.