Techno-Economic and Environmental Analysis of Grid-Connected Electric Vehicle Charging Station Using AI-Based Algorithm

The rapid growth of electric vehicles in India necessitates more power to energize such vehicles. Furthermore, the transport industry emits greenhouse gases, particularly SO2, CO2. national grid has supply an enormous amount on a daily basis due surplus required charge these This paper presents various hybrid energy system configurations meet requirements vehicle charging station (EVCS) situated northwest region Delhi, India. three are: (a) solar photovoltaic/diesel generator/battery-based EVCS, (b) photovoltaic/battery-based and (c) grid-and-solar photovoltaic-based EVCS. meta-heuristic techniques are implemented analyze technological, financial, environmental feasibility possible configurations. optimization algorithm intends reduce total net present cost levelized while keeping value lack probability within limits. To confirm solution quality obtained using modified salp swarm (MSSA), popularly used HOMER software, (SSA), gray wolf applied same problem, their outcomes equated those attained by MSSA. MSSA exhibits superior accuracy robustness based simulation outcomes. performs much better terms computation time followed SSA optimization. results reduced values all configurations, i.e., USD 0.482/kWh, 0.684/kWh, 0.119/kWh 1, 2, 3, respectively. Our findings will be useful for researchers determining best method sizing components.