The electric vehicles (EVs) efficiently interface with the AC microgrid through bidirectional operations, enabling both grid to vehicle and vehicle to grid power exchange. Virtual synchronous generators (VSG) control mechanism regulates the two-way power exchange between the microgrid and the charging or/and discharging of EVs. Additionally, it has been shown that PEVs respond more rapidly to load variations or system fluctuations compared to diesel generators. Power imbalance between power generation and demand during charging and discharging help to support frequency stability. This article presents the integration of a buck-boost converter in a non-isolated bi-directional system, along with adaptive control based on reference values, as an effective method for managing EV battery charging and discharging. This research study introduces an entirely novel adaptive genetic algorithm-based proportional-integral control. A comparison analysis for adaptive genetic algorithm-based PI and convectional PI controllers was done in MATLAB/Simulink. The control scheme is multi-objective, with both active and reactive power being precisely regulated to the desired levels by the adaptive GA-based PI controller, leading to minimal deviation and reduced restoration time. The comparison study unequivocally shows that adaptive genetic algorithm-based PI controller is more effective than conventional PI controllers.