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.
@article{arxiv.2406.14361,
title = {Robustness Analysis of AI Models in Critical Energy Systems},
author = {Pantelis Dogoulis and Matthieu Jimenez and Salah Ghamizi and Maxime Cordy and Yves Le Traon},
journal= {arXiv preprint arXiv:2406.14361},
year = {2024}
}