Neural Controlled Differential Equations for EMT-Level Surrogate Modeling of Grid-Forming Inverters

• URL: http://arxiv.org/abs/2607.16258v1
• Date: Sun, 28 Jun 2026 10:47:26 GMT
• Title: Neural Controlled Differential Equations for EMT-Level Surrogate Modeling of Grid-Forming Inverters
• Abstract summary: This paper proposes a Neural Controlled Differential Equation framework for learning continuous-time surrogate models of grid-forming inverters for electromagnetic transient (EMT) simulation.<n>A physics-inspired regularization method is utilized to enhance stability and coherence.<n>The results show that Neural CDE-based component modeling offers a physically consistent surrogate modeling approach for EMT-level simulation studies.
• Score: 13.252561724661085
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The application of artificial intelligence methods in power electronic converter modeling is becoming increasingly widespread, but existing applications still face many challenges, such as difficulties in multi-time-scale hybrid analysis and the lack of physics-aware evaluation criteria and constraints, resulting in poor performance. This paper proposes a Neural Controlled Differential Equation (Neural CDE) framework for learning continuous-time surrogate models of grid-forming inverters for electromagnetic transient (EMT) simulation, which relaxes the constraint of fixed sampling rates and enables multi-time-scale control analysis. Then, an affine-control formulation with dual slow/fast pathways is proposed to capture the hierarchical and multiscale behavior of converter dynamics, and a physics-inspired regularization method is utilized to enhance stability and coherence. Evaluated on EMT-generated trajectories, the model accurately reproduces transient responses, preserves effective damping and the dominant oscillatory characteristics, and maintains bounded long-horizon rollouts. The results show that Neural CDE-based component modeling offers a physically consistent surrogate modeling approach for EMT-level simulation studies.

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