<p>Microgrids are localized energy systems that increase the dependability and resilience of power supply, especially in distant or underserved regions, by functioning independently or in combination with the main electrical grid. In this paper, a unique adaptive leaky least mean fourth (ALLMF) control algorithm is designed to control a single-phase voltage source converter, and it is utilised as a compensator to improve the quality of power. Furthermore, the on-board electric vehicle (EV) charger with photovoltaic (PV) is applied to smooth the operation of the EV charging system. These systems incorporate a single-phase grid, non-linear load, and renewable energy sources such as PV systems and a battery bank (BB) to guarantee a consistent power supply. PV systems give the benefit of exploiting plentiful solar energy, while BB offers efficient energy management by balancing supply and demand and storing surplus energy. Advanced control systems, including self-adaptive control and fuzzy logic-based maximum power point tracking, increase system performance by assuring efficient power sharing, reducing disruptions, and protecting batteries from overcharging. The performance of PV- and EV-based microgrid is also analysed in Matrix Laboratory/Simulink. The designed microgrid system is developed to charge and discharge the EV BB to support the grid. The hardware prototype model is designed for experimental validation, and various results are analysed under steady-state and dynamic-state conditions. The comparative analysis of the ALLMF controller, least mean fourth algorithm, and least mean square algorithm is also presented in this paper.</p>