A Neural Lyapunov Approach to Transient Stability Assessment of Power Electronics-Interfaced Networked Microgrids

This paper proposes a novel Neural Lyapunov method-based transient stability assessment framework for power electronics-interfaced networked microgrids. The assessment framework aims to determine the large-signal stability of the networked microgrids and to characterize the disturbances that can be tolerated by the networked microgrids. The challenge of such assessment is how to construct a behavior-summary function for the nonlinear networked microgrids. By leveraging strong representation power of neural network, the behavior-summary function, i.e., a Neural Lyapunov function, is learned in the state space. A stability region is estimated based on the learned Neural Lyapunov function, and it is used for characterizing disturbances that the networked microgrids can tolerate. The proposed method is tested and validated in a grid-connected microgrid, three networked microgrids with mixed interface dynamics, and the IEEE 123-node feeder. Case studies suggest that the proposed method can address networked microgrids with heterogeneous interface dynamics, and in comparison with conventional methods that are based on quadratic Lyapunov functions, it can characterize the stability regions with much less conservativeness.

I. Introduction

The past decade has witnessed increasing deployment of distributed energy resources (DERs) in the electric distribution grid. DERs play a crucial role of decarbonizing the energy sector and enhancing the resilience of the grid [1]. However, deepening penetration of DERs leads to unprecedented complexity for distribution system operation in monitoring, control, and protection. One promising architecture to manage the massive integration of DERs is to reconfigure the distribution system as power electronics-interfaced networked microgrids shown in Figure 1. A microgrid packages interconnected distributed generation units (DGUs) and loads which are regulated locally by the microgrid central controller (MGCC) [2]. The microgrid has a power-electronic (PE) interface [2] that physically connects to its host distribution system via a point of common coupling (PCC). Microgrids are networked with each other through PCCs and distribution lines. With such a configuration, instead of managing massive DGUs at grid edges, a distribution system operator (DSO) only needs to coordinate a few PE interfaces of microgrids [2], by which the system management complexity at the DSO level is significantly reduced.¹

In the sequel, “power electronics-interfaced networked microgrids” and “networked microgrids” are used interchangeably for the sake of brevity.