Electric Vehicle Charging Load Management System

The rapid electric vehicle (EV) penetration might strain grid stability due to uncontrolled charging demands; hence, we propose the Electric Vehicle Charging Load Management System (EV-CLMS) as an alternative solution that enables the real-time intelligent coordination of charging activities and associated loads. EV-CLMS integrates dynamic load conditions, adaptive load balancing, and priority-based scheduling to synchronize EV charging requests with grid capacity constraints. The proposed techniques could be used to optimize resource dispatches according to their utility during peak demand periods while simultaneously maximizing the utilization of renewable energy. Load balancing is achieved using the proposed techniques. In the case of grid to vehicle (G2V), the grid is feeding the loads connected to the grid side and the inverter side. This also represents the charging of the EV batteries stations draw large amounts of power from the grid which leads to instability of the grid so, in the case of vehicle to grid (V2G) condition the grid is eliminated with some loads connected to the grid side as EV batteries are not capable to feed every load connected in the power system. So now, the EV batteries will be supplying electricity only to the load connected to the inverter side, and the utility grid will be feeding other loads; hence, load balancing is achieved. The results observed in this paper are satisfactory and are also represented effectively. In the future, advanced optimization algorithms developed by AI and machine learning can help our system to work properly to manage the load. Also, focusing on renewable energy, expanding charging infrastructure, cost optimization, and smart charging features can improve the user experience.