Dynamical Stability Analysis of Grid-Following and Grid-Forming Inverters with Blockchain Integration for Enhanced Performance in Modernized Nested Microgrids

The integration of renewable energy sources and distributed energy resources (DERs) has driven the evolution of modernized nested microgrids, enhancing resilience and flexibility in power distribution systems. Grid-following (GFL) and grid-forming (GFM) inverters are central to these systems, with GFL units emulating current sources challenged by uncertain grid impedance, and GFM units emulating voltage sources required to adapt to dynamic load variations. Mode transitions introduce instability through multi-loop control interactions. This work presents a comprehensive dynamical stability analysis of GFL and GFM inverters in nested microgrids, supported by advanced control strategies addressing dynamic response limitations, sensor dependencies, filter fluctuations, and controller complexities. An eigenvalue-based framework identifies dominant oscillatory modes, while online adaptation mitigates disturbances to preserve closed-loop performance. Time-evolution modeling of observables enables enhanced real-time monitoring. A blockchain-enabled decentralized framework ensures secure, transparent, and automated stability actions. Hardware-in-the-loop (HIL) experiments on a modified IEEE 123-node test feeder demonstrate a total harmonic distortion (THD) of 1.75% under weak-grid conditions compared with 2.73%, 4.76%, 8.40%, and 2.2% for other approaches and 0.3% under grid-impedance variation and <0.3% under nonlinear loading. The proposed controller achieves 0.06% tracking error dynamics and 0.02% steady-state error, outperforming classical methods (0.32–0.87% and 0.17–0.38%, respectively), with a computational time of 29 ms. The blockchain layer, implemented on the Polygon network, achieved a measured throughput of 1,572 transactions/s, an average block time of 2.3 s, and transaction fees below $0.01 USD, enabling rapid, economical, and scalable peer-to-peer stability service execution.