Foundation Twins: A New Generation of Power Systems Digital Twins using Foundation AI Models
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arXiv
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866915988989018112 |
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| author | Vergara, Pedro P. |
| author_facet | Vergara, Pedro P. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_05952 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Foundation Twins: A New Generation of Power Systems Digital Twins using Foundation AI Models Vergara, Pedro P. Systems and Control 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. |
| title | Foundation Twins: A New Generation of Power Systems Digital Twins using Foundation AI Models |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2605.05952 |