Multi-Time Scale Model Order Reduction and Stability Consistency Certification of Inverter-Interfaced DG System in AC Microgrid

Abstract

AC microgrid mainly comprise inverter-interfaced distributed generators (IIDGs), which are nonlinear complex systems with multiple time scales, including frequency control, time delay measurements, and electromagnetic transients. The droop control-based IIDG in an AC microgrid is selected as the research object in this study, which comprises power droop controller, voltage-and current-loop controllers, and filter and line. The multi-time scale characteristics of the detailed IIDG model are divided based on singular perturbation theory. In addition, the IIDG model order is reduced by neglecting the system fast dynamics. The static and transient stability consistency of the IIDG model order reduction are demonstrated by extracting features of the IIDG small signal model and using the quadratic approximation method of the stability region boundary, respectively. The dynamic response consistencies of the IIDG model order reduction are evaluated using the frequency, damping and amplitude features extracted by the Prony transformation. Results are applicable to provide a simplified model for the dynamic characteristic analysis of IIDG systems in AC microgrid. The accuracy of the proposed method is verified by using the eigenvalue comparison, the transient stability index comparison and the dynamic time-domain simulation.

Dynamic Analysis and Model Order Reduction of Virtual Synchronous Machine Based Microgrid

“…The small-signal model is obtained by linearizing the nonlinear DAEs around a set of steadystate operating points. However, for microgrids, their smallsignal models exhibit multi-time scale characteristics, which requires small time steps for fast dynamics and a long simulation time to capture slow dynamics [14]. With the growing scale of microgrids, their time-domain simulations are becoming time-consuming and computational burdens.…”

Nonlinear model reduction of dynamical power grid models using quadratization and balanced truncation

“…Therefore, most research on model reduction of power grid models involves reduction of a linearized system or subsystem. Researchers have used, e.g., balanced truncation [1,2,8,22,35,37,[40][41][42][43][44]54], balanced residualization [32], Krylov methods [6,38,46,47], SVD-Krylov methods [17], proper orthogonal decomposition (POD) [48], singular perturbation theory [10,25,31], variants of clustering [7,14,49], and sparse approximations [23] to reduce such linearized models.…”

PSO Based reduced order modelling of autonomous AC microgrid considering state perturbation

“…Several methods have been explored to reduce the dimensionality of large power systems in the literature [1][2][3][4][5][6][7][8]. Aggregation, balanced realization, truncation, and certain mixed methods have been discussed to reduce the order of these power systems in [3].…”

“…In [7], a simplified sixth order islanded microgrid model has been reduced to fourth order by retaining the very fast dynamics in the response through singular perturbation and direct truncation methods. A three-time scale model was developed for an AC microgrid in [8] based on the relative eigenvalue loci. This droop based inverter interfaced DGs evaluated model parameter for order reduction of a linearized system based on singular perturbation theory which depends upon the system time constant derived from values of circuit parameters.…”