Revisiting Small-Signal Modeling for Analyzing Fast Dynamic Interactions in Converter-Dominated Power Systems

Abstract

Detailed Electromagnetic Transient (EMT) programs have become indispensable for studying power system dynamics and stability, particularly in the context of high integration of Inverter-Based Resources (IBRs). However, most commercial software integrating eigenvalue-based modal analysis tools, employ Singular Perturbation Theory hypotheses in deriving corresponding small-signal models used alongside their EMT simulations. Such hypotheses neglect fast dynamics such as the stator flux dynamics of Synchronous Machines (SMs) and network dynamics. This article presents a comprehensive small-signal modeling approach that effectively integrates these dynamics, ensuring accurate representation of the dynamics observed in EMT simulations. By employing this method, the study explores practical scenarios using benchmark networks, demonstrating how the rapid inner current control loops of Grid-Forming (GFM) converters can interact with fast network dynamics, inducing instabilities in SMs' stator flux dynamics manifested by high-frequency sub-synchronous oscillations. The findings highlight the potential of IBRs' output filter sizing and network line parameters to dampen such high-frequency oscillations driven by the fast inner current loop dynamics of GFM-based IBRs.