Robustness Analysis of AI Models in Critical Energy Systems

Pantelis Dogoulis, Matthieu Jimenez, Salah Ghamizi, Maxime Cordy, Yves Le Traon
6/20/2024
cs.AIeess.SY

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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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@article{dogoulis2024robustness,
  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},
  year   = {2024},
  eprint = {2406.14361},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.14361v1}
}

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