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The transportation sector is one of the largest producers of carbon gas emissions. This encouraging electrification to reduce the impact of environmental damage. However, the impact of large-scale electrification causes an increase in peak load demand on the distribution network. This results in an energy crisis, economic losses, and reduces the reliability of the power system if not handled seriously. Important solutions involve optimizing electric vehicle charging stations (EVCS), accelerating the use of renewable energy for transportation and controlling electric vehicle charging. The hybrid microgrid system at EVCS can be an effective solution. This system is able to manage its own electricity needs through an energy management system with a combination of energy sources. This research discusses optimizing photovoltaic capacity and charging electric vehicle batteries at EVCS using particle swarm optimization (PSO). The aim of this research is to increase efficiency in investment and increase profits. The model is determined as an EVCS that is interconnected with photovoltaic (PV). The parameters determined include: charging load data, investment costs, power import tariff provisions and charging rates. PSO is used to size photovoltaic (PV) and battery energy storage systems (BESS). The results show that PSO can be used for optimization. This is proven by obtaining the position of the combination of PV and BESS with the best profit with a combination of PV of 494 kW and BESS of 581 kW, with an NPV of 1, 652, 604. 89, an IRR of 46. 60%, and a payback period of 2. 15 years. The combination with the best PV contribution, namely PV of 3, 146 kW and BESS of 1, 811 kW, produces energy of 75, 504 kWh per month, power import of 35, 946 kWh and battery usage level of 58%. These two combinations of optimization results meet the investment acceptance requirements with an internal rate of return (IRR) of at least 9%.
Arifin et al. (2024) studied this question.