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arXiv · 2605.05952

Foundation Twins: A New Generation of Power Systems Digital Twins using Foundation AI Models

Pedro P. Vergara
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Abstract

Power systems are inherently multi-timescale systems, with different physical phenomena and decision-making processes spanning multiple timescales, time horizons, and geographic scopes. I envision power systems digital twins (DTs) as powerful modeling and simulation tools that can accelerate and improve decision-making across different time scales and geographic scopes. However, until now, research has not delivered such a vision, and power systems DTs remain a concept distant from implementation. This is not a regular research paper. This is a position paper that outlines my vision for developing a new generation of power systems DTs that leverage recent advances in artificial intelligence (AI) and machine learning (ML). I call these Foundation Twins. Foundation Twins combines the generalization features of foundation models with the decision-making capabilities of reinforcement learning (RL) architectures to deliver the envisioned power systems DTs.

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Pedro P. Vergara. 2026-05-07. Foundation Twins: A New Generation of Power Systems Digital Twins using Foundation AI Models. https://arxiv.org/abs/2605.05952

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