Verification and Validation of Physics-Informed Surrogate Component Models for Dynamic Power-System Simulation
Physics-informed machine learning surrogates are increasingly explored to accelerate dynamic simulation of generators, converters, and other power grid components. The key question, however, is not only whether a surrogate matches a stand-alone component model on average, but whether it remains accurate after insertion into a differential-algebraic simulator, where the surrogate outputs enter the algebraic equations coupling the component to the rest of the system. This paper formulates that in-simulator use as a verification and validation (V\&V) problem. A finite-horizon bound is derived that links allowable component-output error to algebraic-coupling sensitivity, dynamic error amplifi...
| Authors | Petros Ellinas, Indrajit Chaudhuri, Johanna Vorwerk et al. |
|---|---|
| Primary category | eess.SY |
| Published | 18 March 2026 |
| Last updated at source | 18 March 2026 |
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