Abstract
The growing use of photovoltaic (PV) systems and electric vehicles (EVs) require the smart coordination mechanisms to achieve the efficient use of renewables and the stable charging process. The current paper gives MATLAB/Simulink modeling and simulation of a PV-powered EV charging station with an Adaptive Supervisory Energy Management Strategy (ASEMS). The proposed DC-coupled microgrid system comprises of PV array with Incremental Conductance maximum power point tracking, battery energy storage system (BESS), DC to DC converters (bidirectional), EV battery model, and grid interface. An urgency-based charging index is proposed as a dynamically controlled prioritized index to charge EV according to the state-of-charge deficit and the remaining departure time. According to this index, the supervisory controller will choose between four operating modes, i.e., PV Priority, Hybrid PVBESS, Grid Assistance, and Smart Delay. The Smart Delay is a system that delays charging temporarily when there is low urgency to use energy to maximize the use of solar energy and minimize dependence on the grids. The simulation findings in a 24-hour operating horizon prove that the recommended ASEMS would maximize the PV penetration, ensure that batteries work within the safety range, and ensure the completion of EV charging in a timely manner. The proposed solution is better than traditional fixed-priority strategies as it enhances the use of renewable energy, and it maintains the reliability of charging without using computationally-intensive optimization techniques. The framework provides a viable and expandable real-time energy management solution to PV-integrated EV charging stations