Integration of renewable energy of solar PV and wind for the optimal charging and discharging of plug-in electric vehicles

In order to maximize the use of renewable energy sources and minimize peak demand on the grid, the study suggests a smart charging/discharging algorithm that regulates when an EV can be charged and discharged. To maximize the community's energy balance, the algorithm makes use of both local and centralized controllers. The simulation's driving and charging patterns were taken from an Australian experiment involving a commercial fleet of BEVs. Three technologies: wind, solar photovoltaics (PV), and a hybrid system that combines PV and wind were simulated and contrasted. According to the simulation results, the load profile was altered by uncontrolled commercial BEV charging, which caused the peak demand to begin at 8 am and end at 5 pm. Although controlled charging produced a lower peak, the commercial use of BEVs did not cause a discernible change in the peak. However, real world considerations like charger interoperability, user compliance, communication latency, and the profitability of bidirectional chargers must be considered when implementing such algorithms in practice. By distributing the load more evenly throughout the day, optimizing EV charging and discharging reduces grid stress. In comparison to uncontrolled charging, controlled charging decreased overall grid consumption by up to 7% and postponed peak demand from 8 AM to 11 AM. However, the lack of high-resolution empirical data on driver behaviors, particularly on weekends, makes it difficult to precisely match EV charging with actual community loads.