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arXiv · 2406.14361

Robustness Analysis of AI Models in Critical Energy Systems

Pantelis Dogoulis·Matthieu Jimenez·Salah Ghamizi·Maxime Cordy·Yves Le Traon
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Abstract

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.

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Pantelis Dogoulis, Matthieu Jimenez, Salah Ghamizi, Maxime Cordy, Yves Le Traon. 2024-06-20. Robustness Analysis of AI Models in Critical Energy Systems. https://arxiv.org/abs/2406.14361

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