Parameter optimization and smooth adaptive control of VSG-based grid-connected converters via MO-POACS
To address the difficulty of fixed-parameter virtual synchronous generator (VSG) control in balancing frequency support, dynamic recovery, and steady-state power quality under varying operating conditions, this paper proposes a coordinated parameter optimization and smooth adaptive control strategy for VSG-based grid-connected converters. First, a small-signal active power–frequency model is established to analyze the effects of virtual inertia and damping on dynamic performance. Then, a six-dimensional dual-objective optimization model is formulated using the integral of time-weighted absolute frequency error and the total harmonic distortion (THD) of PCC voltage as optimization objectives. The model is solved using an improved multi-objective Pelican optimization algorithm, and the optimized parameter set is incorporated into an online adaptive law. By combining sigmoid-based smooth triggering with first-order tracking, continuous adjustment of virtual inertia and damping is achieved. Simulation results demonstrate that the proposed method effectively reduces power overshoot and maximum frequency deviation while maintaining a low three-phase average PCC voltage THD. In addition, additional non-optimized validation cases under low-SCR weak-grid operation and grid phase-jump disturbance verify the adaptability and operational stability of the optimized parameter set.