Dynamic State Estimation in Power Electronics-Dominated Grids Using a Digital Twin Approach

This paper proposes a digital twin (DT) based approach to improve dynamic state estimation (DSE) in power electronics-dominated grids (PEDGs), ultimately contributing to a more reliable, efficient, and sustainable power system by enabling better integration of renewable energy sources and reducing grid instability. Traditional DSE methods struggle with the complexities of PEDGs, such as high penetration of distributed generation and energy storage, leading to inaccurate state estimations. Our approach leverages a real-time, high-fidelity virtual model of a microgrid, including detailed models of DG units, power electronics and load dynamics. This enables accurate state estimation even during transient events. The proposed approach is validated using a hardware-in-the-loop test bench which demonstrates the DT’s accuracy in tracking grid dynamics under various operating conditions. Furthermore, a sensitivity analysis highlights the importance of accurate parameter estimation and minimal communication delays for robust DSE. This research provides a framework for developing reliable and accurate DSE solutions for modern PEDGs, enabling advanced grid control, optimization, and predictive maintenance strategies.