Enhancing Microgrid Small-Signal Stability and Reactive Power Sharing Using ANFIS-Tuned Virtual Inductances

Microgrid as the main building block for future smart grids is prone to instability originated from converter-based distributed generations (DG). Herein, we first analyze small-signal stability of an inverter-interfaced microgrid. Afterwards, a novel adaptive network fuzzy inference system (ANFIS)-based optimization method introduced which aims at online tuning virtual inductances (VI) in islanded microgrids. The data ANFIS training drawn by particle swarm (PSO) algorithm and proposed objective function. A total 140 load scenarios are considered provide optimal VI each condition generate training. This process minimizes reactive power mismatches improves microgrid different levels. simultaneous application PSO facilitates objectives pursued current study. Finally, trained networks installed converter control. performance controllers makes converters responses independent change location value. effectiveness control methodology verified using simulations studies.