India promised at the Paris "climate change" summit to reduce carbon emissions by 33–35% up to 2030. Transport and energy are the largest CO2 emitters. Electric vehicles for public transportation and large-scale renewable energy production are viable solutions. In this paper, a newly developed SWEG model is designed for the EV charging station to address the issue of grid power dependency and carbon emissions. The proposed system is developed for a public EV charging station located on highways and powered by solar, wind, energy storage units, and the grid. The city of Bhuj in Gujarat State, India, is being considered for the evaluation of renewable energy sources. According to the energy forecast throughout the day from the renewable sources, various modes of energy flow among sources and EV load are designed. The system is designed to charge a total of 137 electric vehicles at a charging station. The goals are to achieve continuous charging of EVs, to reduce grid dependency, to maximise profit for the charging station owner, and to make the charging station environmentally friendly. The energy sources' cost-priority based energy management strategy (CEMS) for the SWEG model has been developed to charge the EVs. The proposed methodology is compared with that of the PSO and GA algorithms. The outcome shows that PSO optimization gives the best cost compared to GA. The amount of grid power used dropped by 37%, resulting in a 27.86 kg carbon dioxide reduction throughout the day.