Dynamic state estimation of hybrid systems: Inverters that switch between grid-following and grid-forming control schemes

TL;DR

This paper introduces a hybrid system modeling framework for inverters that switch between grid-following and grid-forming modes, enhancing state estimation accuracy and stability during mode transitions.

Contribution

It develops a hybrid automata-based model for inverters with guard conditions and reset maps, integrated into an extended Kalman filter for improved estimation performance.

Findings

Ensures stable and well-behaved inverter dynamics.

Improves state estimation accuracy near switching events.

Demonstrates robustness of the hybrid model in simulations.

Abstract

This paper develops a hybrid system modeling framework for inverters that switch between grid-following and grid-forming control schemes. In particular, such inverters are modeled as hybrid automata with guard conditions on voltage and frequency, and reset maps that maintain consistent phase, frequency, and droop references during mode transitions. The hybrid model is embedded within an extended Kalman filter to assess estimation performance under explicit mode switching. Results show that the proposed framework ensures stable, well-behaved dynamics and improves state estimation, especially near switching instants, compared with smooth continuous models.