Enhancing Power System Stability: Integrating High-Fidelity Plant Controller Models for Distributed Energy Resources

High-fidelity models are characterized by their ability to accurately replicate the behaviour of physical devices, such as power system controllers, within simulation environments. This paper demonstrates the successful integration of such a model, specifically for a power management controller, with an existing power system model implemented using one of the industry’s power system simulation software packages. The integration between the simulation tool and the digital twins is crucial, as it provides a realistic representation of how new DER installations would interact with existing grid infrastructure. The fidelity of these models ensures that the simulations closely mirror real-world scenarios, allowing utilities to predict and manage grid responses more effectively. In addition, the paper discusses integration challenges between the power system simulation tools and the high-fidelity plant controller model. One of the primary benefits highlighted in the paper is the reduction in capital expenditure compared to traditional controller hardware-in-the-loop testing. High-fidelity models offer a cost-effective alternative by eliminating the need for expensive physical testing setups and extensive hardware requirements. This financial advantage is particularly beneficial for utilities that are constrained by budget limitations but still need to ensure reliable and efficient power system operations. With no need for a specific hardware testing platform, the models can be shared easily, and simulations can be repeated by different stakeholders.

The study also discusses the correlation between test results obtained using digital twins and those derived from controller hardware-in-the-loop testing. The close alignment between these results validates the effectiveness of virtual models in simulating real-world conditions. This correlation provides confidence in using such models to evaluate the impact of new DERs on existing networks, ensuring that utilities can make informed decisions based on accurate simulations. It is important to note that the precondition for comparison between the response of the high-fidelity model and controller hardware-in-the-loop is the equivalence of power system asset models used in both cases. In the example presented in this paper, the control gains of the inverter and the control architecture are the same between test setups for the high-fidelity model and the controller hardware-in-the-loop.