Research on Electric Vehicle Charging Station Planning based on Genetic Algorithm and Particle Swarm Optimization Algorithm (GAIPSO)

Thanks to the advancement of the electric vehicles (EVs) technology, the demand on electric vehicles is on a hideous rise. So follows the demand on corresponding charging stations (CSs) and its facilities. Several countries have witness the rapid growth in the adoption of EVs after they issued incentive policies. However, the current EV charging network cannot shoulder the demand once a considerable number of vehicles in the world migrate to EVs and continuous efforts are still required for the transition. The leading company, Tesla, is setting the benchmark for the industry and on track to help the US to fulfil its switchover to all-electric as the company released its secret patent for superchargers . This strategy not only turns out to be money-saving for Tesla, but also spurs the construction of the charging facilities worldwide. Particularly for city-planners, the architecture of the CS network is in a dire need and that is the focus of this paper. We are supposed to determine the amount and allocation of the CSs and design the charging network for a district or a country. Meanwhile, we shall sort out the construction scheme for the following several years’ time. We would henceforth analyse the construction need for the USA and South Korea using our model and sort out the growth plan and the timeline. We would also talk about the external factors that would influence our decision and bring a classification system.