Multi-Objective Operation of PV-ESU Powered EV Charging Station

Recently electric vehicles (EV s) have been popular choice in many countries due to low carbon emission and less operation cost. The rapid increase in EV s inevitably increases the number of charging stations used to charge them, and this naturally leads to more power demand at certain times of the day. It is also apparent that the increase in energy demand leads to an increase in electricity prices, as well as an increase in power loss in transmission lines. This may reduce the current aura of EV s, as higher electricity prices mean more expensive charging costs. Therefore, creating more competitive conditions at existing charging stations for lower charging costs is essential for a sustainable future. In this study, the primary objective is to reduce the charging cost by integrating a 20-kWp photovoltaic (PV) array and a 20-kWh energy storage unit (ESU) into an existing charging station fed from the grid and considering the overload of the grid and user charging preference. This multi-objective problem is solved for optimal daily cost using the binari-coded genetic algorithm (BCGA). The results show that proposed optimization model worked well, and the charging cost decreased depending on user preferences.