EvEMTBench: An Open Benchmark for Machine Learning in Power System Protection
Studies of machine-learning-based power system protection are difficult to compare because task definitions, measurement access, data partitions, metrics, and generalization conditions often differ. EvEMTBench addresses this gap with an open, executable, and versioned benchmark that fixes these evaluation choices while leaving model design open. Across four grids spanning 20-345 kV, it defines 12 protection and event-analysis functions instantiated as 24 scored tasks and supports structured evaluation across observability conditions, predefined distribution shifts, and zero-shot and fine-tuned cross-grid transfer. Committed partitions, leakage controls, and reproducible reporting provide ...
| Authors | Julian Oelhaf, Georg Kordowich, Christian Bergler et al. |
|---|---|
| Primary category | eess.SY |
| Published | 23 September 2026 |
| Last updated at source | 23 September 2026 |
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