Equivalent Dynamic Models of Active Distribution Networks with Grid Following and Grid Forming Converters

Thesis from Jakob Günther Ungerland
University of Stuttgart, 2023

The increase in converter based generation, e.g., photovoltaic or battery storage systems, challenges the way of handling power systems. It jeopardizes not only system stability due to the lack of rotating masses stabilizing the grid, an ability inherently provided by synchronous machines. Moreover, due to the evolution of load-dominated to active distribution networks, the importance of accurate modeling of these networks in the context of system stability analysis is increased.

So-called grid forming converters meet the former challenge. This control aims at substituting the stabilizing capabilities of synchronous machines by emulating inertia. The latter challenge calls for ideally detailed models of active distribution networks. However, embedding detailed distribution network models in a dynamic transmission system model is impracticable due to model complexity. Complexity-reduced equivalent dynamic models solve this obstacle.

Putting these two points together, i.e., considering grid forming converters in equivalent dynamic distribution network models, displays a research gap not addressed in previous work. Hence, this work provides a validated methodology to create equivalent dynamic active distribution networks including grid forming converters with the application in comprehensive stability studies of future power systems. The proposed approach for deriving the equivalent dynamic model is a gray-box parameter identification method based on the clustering of the components in the corresponding detailed network. Voltage sensitivities are deployed to represent the grid's strength at the grid forming converter's connection point. The approach utilizes knowledge about the detailed network model and, hence, dynamic simulation or measurement data are not required for parameter identification. This renders a fast equivalent dynamic model derivation possible.

The proposed method is validated in dynamic simulations of four scenarios. The detailed active distribution networks of the scenarios, which are aggregated applying the proposed method, vary in the number of grid forming converters and network topologies. The approach is compared to an existing gray-box approach capable of creating equivalent models for networks dominated by conventional grid following converters for benchmarking purposes. Simulation results for different events of the detailed and equivalent models are compared. The equivalent model aggregated with the proposed approach reproduces the detailed network's dynamic behavior adequately, while the existing approach fails to meet validation criteria. Moreover, the derived equivalent model reduces the detailed network model significantly in terms of nodes and simulation time.

This work also proposes a simplified adaptation of the derived equivalent dynamic model to new operating points. The adapted model is valid for a considerable range of load and generation scenarios. This renders stability studies based on a variety of different operating point scenarios possible since it avoids a new derivation of the equivalent model.

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