Robustness Analysis of AI Models in Critical Energy Systems
<|reference_start|>Robustness Analysis of AI Models in Critical Energy Systems: This paper analyzes the robustness of state-of-the-art AI-based models for power grid operations under the $N-1$ security criterion. While these models perform well in regular grid settings, our results highlight a significant loss in accuracy following the disconnection of a line.%under this security criterion. Using graph theory-based analysis, we demonstrate the impact of node connectivity on this loss. Our findings emphasize the need for practical scenario considerations in developing AI methodologies for critical infrastructure.<|reference_end|>
@article{dogoulis2024robustness,
    title={Robustness Analysis of AI Models in Critical Energy Systems},
    author={Pantelis Dogoulis, Matthieu Jimenez, Salah Ghamizi, Maxime Cordy, Yves
  Le Traon},
    journal={arXiv preprint arXiv:2406.14361},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.14361},
    primaryClass={cs.AI cs.SY eess.SY}
}