The rapid increase in the number of electric vehicles has a massive contribution to the environmental aspect. However, the associated power demand may result in an overload on the power system grid. The additional load of the electric vehicle charging station (EVCS) can force a critical voltage drop. The energy storage system is a solution to the voltage problem resulted from the EVCS load. The energy storage system can be more efficient if used with a PV system. The energy storage systems need to be optimally sized properly to overcome EVCS demand while optimally dimensioned photovoltaic systems (PV) charge the storage sustainably. Generally, the energy storage and photovoltaic systems have been optimally sized for EVCS considering the grid efficiency in terms of voltage stability. However, these methods require optimal power flow calculation. Due to the lack of grid data in practical implementations, optimal sizing problem considering voltage deviation is challenging. In this paper, a new methodology for optimal sizing for the energy storage and PV systems for EVCS is analysed for a low voltage grid, where the required grid data are unknown parameters. However, the voltage profile at the connection point is known. Based on the voltages, a new factor is introduced defined as the change in voltage per load. It is used in optimization to determine the optimal capacity of the energy storage and PV system. In this way, the grid data can be omitted. The energy storage charging and discharging is optimized for the EVCS load for one year. The resulted mixed-integer linear programming intending to decrease the power from the grid is solved using the gurobi solver. The EVCS load profile has been modelled using Monte-Carlo simulation. The EVCS load profile consists of the electric vehicle traveling and charging behaviour considering the real traffic model. The results show that the methodology has the potential to be used under these circumstances and the critical voltage deviation can be minimized.