Grid-forming (GFM) control strategies are gaining traction in Type-4 wind turbines to support grid stability in low-inertia systems. While the external GFM response is typically evaluated at the point of interconnection, the internal subsystems—such as the DC-link, machine-side inverter, and their associated control loops—are often overlooked, and their impact on the grid-forming behavior remains insufficiently understood. This work aims to reduce this knowledge gap by formulating a system identification framework that captures the influence of these internal dynamics on GFM performance.

The approach is based on analytically deriving signal relationships that enable frequency-domain identification of key GFM metrics—such as inertia-like response, damping behavior, and bandwidth limitations. These metrics are extracted from simulation data using small-signal perturbations applied to detailed wind turbine models.

Results show how internal subsystem interactions can alter the expected GFM behavior, highlighting their influence under weak grid conditions and their role in shaping frequency and voltage response characteristics. This methodology provides a structured way to assess and compare the GFM capabilities of wind turbines, offering practical insights for both manufacturers and system operators.