Metaheuristic Algorithm Based Energy Management System for Electric Vehicle Charging Station

Electric Vehicles (EVs) are at the forefront of the transition to sustainability. Their almost zero tailpipe emissions and contribution to noise pollution make them suitable for minimizing the current levels of environmental pollution. One aspect that hinders the widespread adoption of EVs is the limited availability of Electric Vehicle Charging Stations (EVCS) in remote areas, making the charging costs extremely high. The goal of reducing EV charging cost can be achieved by integrating renewables into a conventional power system. This study proposes a method for optimizing the charging cost by utilizing renewable energy resources for an EVCS in a modified IEEE 33 bus system. This study involves the incorporation of three renewable energy sources: solar, wind and biogas. Energy management between the various sources and the EVCS was achieved through a metaheuristic algorithm-based Energy Management System (MAEMS). The proposed MAEMS was used to develop a dynamic pricing scheme. A techno-economic analysis of the system was conducted. The analysis was performed on the MATLAB-Simulink platform, considering the standards of the Indian EVCS system.