  The integration of power electronic converters (PECs) and distributed energy
resources (DERs) in modern power systems has introduced dynamism and
complexity. Accurate simulation becomes essential to comprehend the influence
of converter domination on the power grid. This study addresses the
fast-switching and stochastic behaviors exhibited by inverter-based resources
in converter-dominated power systems, highlighting the necessity for precise
analytical models. In the realm of modeling real-world systems, multiple
methodologies exist. Notably, black-box and data-driven system identification
techniques are employed to construct PEC models using experimental data,
without relying on a priori knowledge of the internal system physics. This
approach entails a systematic process of model class selection, parameter
estimation, and model validation. While a range of linear and nonlinear model
structures and estimation algorithms are at our disposal, it remains imperative
to harness creativity and a profound understanding of the physical system to
craft data-driven models that align seamlessly with their intended
applications. These applications may encompass simulation, prediction, control,
or fault detection. This report offers valuable insights into the collection of
datasets from commercial off-the-shelf inverters, along with the presentation
of intricate simulation models.
