Verification and Validation of Physics-Informed Surrogate Component Models for Dynamic Power-System Simulation

ArXi:2603.17836v1 Announce Type: cross 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.