A Data Driven Stability Assessment Approach for Multiple Microgrids Interconnection

This paper proposes a novel stability assessment approach and control strategy for stable interconnection of multiple microgrids (MMG). The dynamic characteristics of low inertia islanded microgrids significantly mandate accurate and computationally efficient evaluation of their stability status in response to small and large disturbances. The reported studies in the literature heavily rely on offline small-signal models which are obtained through linearization around one operating point. Therefore, offline small signal stability studies can't track the damping ratios as the microgrid largely deviates from the initial operating point when interconnection and/or severe disturbances are experienced. To address this issue, the dynamic mode decomposition (DMD) is deployed in this paper to provide online assessment for both small signal and transient stability. The proposed method allows real-time tracking of the stability status of individual/interconnected microgrid(s) prior, during and post interconnection through estimating the damping ratio and frequency of the dominant oscillatory mode. Then, a supervisory controller is proposed for ensuring stable microgrids interconnection taking advantage of the DMD accurate estimation. The proposed controller can also provide adaptive droop gain modification for stability enhancement based on the microgrid configuration. A comprehensive stability analysis is carried out for various configurations of microgrids and interconnection scenarios. The simulation results and experimental validation demonstrate the superior performance of the proposed DMD method and the supervisory controller for assessing and enhancing the stability while interconnecting MMG.