Small-Signal Stability Analysis in an Uncertain Microgrid with Distributed Energy Resources: A Data-Driven Monitoring

In low-inertia microgrids (MGs) with intermittent distributed energy resources (DERs), the requirement to pre-determine MG parameters results in a challenge as these parameters evolve over time. Consequently, conducting small-signal stability analysis becomes impractical due to the dynamic nature of the MG's parameter variations. In this paper, we propose an adaptive data-driven approach designed for grid-forming converters of DERs. The goal is to improve small-signal stability within a dynamically shifting window range. Additionally, we propose a data-driven approach to identify the MG model within a moving window. Subsequently, small-signal stability can be assessed. Comprehensive simulation results are systematically generated for an MG with DERs under various crucial conditions, including (i) intermittent power outputs of DERs, (ii) generator outages, (iii) diverse levels of total MG inertia, and (iv) different MG operation modes.