To aid in the reduction of the dependency on fossil fuels and greenhouse gas emissions that cause poor air quality, migration from internal combustion engine (ICE) vehicles to electric vehicles (EV) is advised. It will also be essential to integrate renewable energy sources (RES) like photovoltaics (PVs), wind, biogas etc. However, there is little progress in Singapore due to the limited EV electric range in affordable EVs and low EV charging availability. Hence, there is a need for EV charging stations (EV CS) implementation to ease anxiety range, without causing adverse effects on existing electric distribution networks. In this paper, siting and sizing of EV CS is done using K-means clustering algorithm on a test feeder with various predicted EV penetration levels applicable to Singapore. Linear approximation on complex plane power flow analysis and cost analysis were implemented to check the practicality of the proposed methodology. The results showed feasibility in the three EV penetration levels of low 10%, medium 30%, and high 50% with AC slow charging. Optimal charging device rating is AC slow 3.3 kW to better meet the potential charging demands of private vehicles in Singapore, which are to be implemented in residential car parking areas.