A Comprehensive Review and Analysis of the Allocation of Electric Vehicle Charging Stations in Distribution Networks

In recent times, the limited availability of fossil fuels and growing concerns regarding the emission of greenhouse gases (GHGs) have directly impacted the shift from conventional automobiles to electric vehicles (EVs). Additionally, there have been notable advancements in new energy research, which have significantly improved the viability of EVs. Consequently, EVs have gained widespread recognition and have been rapidly adopted in many countries worldwide. However, the rapid growth of EVs has given rise to several challenges, such as insufficient charging infrastructure, unequal distribution, high costs, and a lack of charging stations, which have become increasingly significant. The limited availability of charging facilities is hindering the widespread adoption of EVs. However, as more people embrace EVs, there has been a growth in the installation of electric vehicle charging stations (EVCSs) in public locations. Recent research has focused on identifying the ideal locations for EVCSs in order to assist the electrification of transport systems and meet the growing demand for EVs. A well-developed EVCS infrastructure can help address some key issues facing EVs, such as pricing and range limitations. Researchers have used various methodologies, objective functions, and constraints to formulate the problem of identifying the best sites for EVCSs. Current research is focused on determining the best locations for EVCSs. This endeavor intends to ease the transition to electrified transport networks while also addressing the growing demand for EVs. This review article explores various optimization techniques to achieve optimal solutions while considering the impact of EV charging load on the distribution system (DS), environmental implications, and economic impact. The research used a standard IEEE 33-bus radial distribution system (RDS) with a full variety of potential energy sources to improve understanding of the subject. The use of the bald eagle search algorithm (BESA) and cuckoo search algorithm (CSA) aided in the best identification of energy source locations and their relative capacities. In addition, the examination of EV charging techniques, including both the traditional charging technique (TCT) and the innovative charging technique (ICT), is being undertaken to assess the effectiveness of these approaches. The study included ten separate scenarios, each of which was thoroughly evaluated to demonstrate the individual and synergistic usefulness of various energy sources in mitigating the effects of EV charging on the DS. The collected data from the empirical inquiry was aggregated and thoroughly analyzed.