This work presents an examination of the main interactions between grid-following (GFL) and grid-forming (GFM) voltage source converters (VSCs) and synchronous generators (SGs), capturing the dynamics of a real power grid and pointing out the limitations of considering an ideal one for stability studies. Eigenvalue trajectories and participation factors are studied to perform in-depth small-signal analyses. Specifically, the GFL and GFM converters are compared in different grid strength scenarios by varying their rating powers and the grid short circuit ratio. Then, time-domain simulations of the non-linear and the developed linear systems are run to validate the mathematical findings from the stability analysis. The results reveal that the stability of VSCs-dominated grids, either in GFL or GFM mode, is strongly affected by both the grid strength and the VSC power, due to the coupling between the VSC control and the SGs.
This paper proposes a novel unified control framework for achieving hybrid grid-forming (GFM) and grid-following (GFL) inverter operation by integrating dispatchable virtual oscillator control with reference-following synchronization. The proposed inverter control method supports…
Reliable fault recovery of grid-forming (GFM) converters under current-limited conditions is increasingly important as inverter-based resources replace synchronous generation. Existing current-limiting strategies primarily focus on current-angle regulation and synchronization tra…
Large-scale power networks are often organized by geography, ownership, or control authority, making stability certificates that require a fully assembled global model challenging. This paper develops a time-domain small-signal stability certification framework for grid-forming i…
This paper analyzes the stability and droop characteristics of Observer-Synchronized grid-forming control. First, a second-order nonlinear autonomous model is derived under the quasi-steady-state assumption. Based on the derived model, the equilibrium points and nonlinear stabili…
As hyperscale and colocation AI data centers continue to expand, the electric grid is increasingly required to support large, concentrated loads, with individual facilities ranging from 500 MW to 2 GW. Current projections estimate that approximately 50 GW of AI data center capaci…
This paper investigates physics-informed neural networks for modeling the full dynamic behavior of droop-controlled grid-forming converters. The approach is trained on synthetic data generated via numerical solvers and benchmarked against both traditional integration methods and…