Adaptive parameter tuning strategy of VSG-based islanded microgrid under uncertainties

This paper proposes adaptive parameter tuning strategy for a virtual-synchronous generator (VSG) during islanding conditions to improve frequency oscillations occurring due to uncertainties in load and solar photovoltaic (PV) output. Accordingly, an adaptive two-level optimization model has been developed for optimal tuning of VSG parameters. It provides dynamic virtual inertia value to VSG by maintaining rate-of-change-of-frequency (RoCoF) within prescribed limits under disturbance. The first level calculates the initial value of VSG parameters using robust control considering day-ahead operation schedules and uncertainty information. During intra-day operation stage on the following day, as soon as islanding is detected, the VSG is operated with robust values of the parameters computed day ahead at the first level. Furthermore, during islanded operation, second level utilizes initial values from first level and determines expectation values of short-leading-time predictions of PV output and load, and performs an adaptive stochastic optimization of VSG parameters in intervals of 5 min. Extensive simulations have been performed to evaluate the performance of proposed adaptive parameters tuning strategy on modified Cigre European LV network. Furthermore, effectiveness of proposed control approach has been validated on laboratory-scale hardware experimental setup under uncertain environments and cyber-attack. Results reveal improved performance of adaptive VSG in regulating network frequency in presence of system uncertainties.