Resolving Charging Station Placement Issues for Electric Vehicles: Hybrid Optimization-Assisted Multi-Objective Framework

As new energy technology has advanced to a respectable level, Electric Vehicles (EV) have gained recognition from people all over the world and have become increasingly popular in a number of nations. Effective charging station placement is critical for the rapid growth of electric vehicles, as it is vital to provide convenience for electric vehicles while also ensuring the effectiveness of traffic networks. The location of an EV charging station is simply an application situation for the facility location problem. Traditional works often pay attention to the mileage concerns of electric vehicle customers while ignoring their competitive and strategic charging tactics. This research aims to frame the allocation of charging stations issue as a multi-faceted venture by assessing the aspects economically along with the characteristics of the power grid like "cost, Voltage stability, Reliability, and Power loss (VRP) index, waiting time, and accessibility index". Further, we proposed a hybrid artificial intelligence to resolve the allocation issue. The proposed new Artificial Intelligence (AI) based algorithm is termed as Hybridized Salp and Harris Algorithm (HS-HA). The effectiveness and scalability of the presented algorithm for the charging station placement issue are also assessed through different plans in the IEEE 33-bus distribution systems. Finally, the efficiency of the presented approach is proved over the existing approaches with respect to various measures.