Singular Perturbation-based Large-Signal Order Reduction of Microgrids for Stability and Accuracy Synthesis with Control

TL;DR

This paper introduces a singular perturbation-based large-signal order reduction method for microgrids, enabling stable and accurate reduced models that simplify complex control systems for better analysis and design.

Contribution

It develops a novel LSOR approach with a proven stability and accuracy assessment theorem, applicable to arbitrary dynamic systems, enhancing microgrid stability analysis.

Findings

The method guarantees stability and accuracy of reduced models.

Case studies demonstrate effective simplification of microgrid dynamics.

The approach is generic and applicable to various nonlinear systems.

Abstract

With the increasing penetration of distributed energy resources (DERs), it is of vital importance to study the dynamic stability of microgrids (MGs) with external control inputs in the electromagnetic transient (EMT) time scale. This requires detailed models of the underlying control structure of MGs and results in a high-order nonlinear MG control system. Higher-level controller design and stability analysis of such high-order systems are usually intractable and computation-costly. To overcome these challenges, this paper proposes a large-signal order reduction (LSOR) method for MGs with considerations of external control inputs and the detailed dynamics of underlying control levels based on singular perturbation theory (SPT). Specially, we innovatively proposed and strictly proved a general stability and accuracy assessment theorem that allows us to analyze the dynamic stability of a full-order nonlinear system by only leveraging its corresponding reduced-order model (ROM) and boundary layer model (BLM). Moreover, this theorem also theoretically provides a set of conditions under which the developed ROM is accurate. Finally, by embedding such a theorem into the SPT, we propose a novel LSOR approach with guaranteed accuracy and stability analysis equivalence. The proposed LSOR method is generic and can be applied to arbitrary dynamic systems. Multiple case studies are conducted on MG systems to show the effectiveness of the proposed approach.