The widespread adoption of Electric vehicles (EVs) is largely attributed to their eco-friendly and cost-effective attributes. As the number of EVs charging on electrical distribution systems is expected to rise, it is essential to consider the potential effects on the infrastructure, including generation capacity, transformer overloading levels, line congestion, and load profiles, with the impact of EV charging on load profiles being the most pressing concern, Consequently, developing accurate models and predicts of EV charging demand is crucial. This paper presents a methodology for analyzing the load demand of load profiles due to EV battery charging. A comparative study is carried out by simulating three EV charging scenarios, uncontrolled charging, controlled off-peak charging, and smart charging. The proposed method considers the initial state of charge and start time of EV battery charging. Results show that a 10% market penetration of EVs in the studied system would result in increase in peak demand by up to 17.3% for an uncontrolled charging scenario is a worst-case to the system and may cause congestion issues to the local network. A controlled off-peak charging scenario can shift the EV charging load to an off-peak time; therefore, the EV can be introduced to a new peak or near-peak in early off-peak time. Smart charging method which optimizes the start time of EV charging is the most beneficial charging method to distribution network operators and EV users