## 4 Proposed Space Efficient Multi-Level Charging Station Infrastructure Method  
In the past decade, there has been a significant upward trend in the use of electric vehicles or EVs mainly because of the idea, that as this number goes higher we need infrastructure in place that can deliver the necessary power and electricity and also at the same time decreasing the operating costs of the said infrastructure. In metropolitan areas, creating extra infrastructure there is a necessity of space and it has become one of the biggest issues. Therefore, to provide a temporary charging station, especially at the shopping mall, big shops, etc. Hence, this can be achieved with a multi-agent system (MAS) and multi-level charging system, especially in metropolitan cities all over the world. We developed MAS-based multi-level charging system architecture as shown in Figure 1.  
Multi-level charging will help in charging more vehicles in the smaller area. This system involves stacking vehicles layer by layer thus requiring less space and greatly helping in reducing traffic congestion. Making the system automated would require less manual intervention, thus reducing damage and cost. Figure 2 shows that the EV or battery is connected as a load to each of the busses in the 33-bus power grid network. Each bus is also connected with a Multi-Agent System (MAS) and this MAS with the help of IoT Technology transmits the data from the bus and over to the cloud and it is further routed to the main/central MAS moves the data to the edge computing technology involved. When the data are transmitted to the central MAS it is processed through edge computing, this way we can save on computation costs and also use minimal hardware, this can make the whole system much cheaper. In this case, there are a few conditions that must be met to declare the bus stable or unstable, that decision is taken here. Figure 3 shows the different components used while designing the architecture of the proposed system, such as socket, charging kiosk with cable and connector gun, and charging kiosk connected with the socket. Figure 1: Multi-Level EVs Charging Design CAD Model. Figure 2: EV Charging Stations with 33-bus Distribution Network. _Implementation of an EV Charging Station with 33-Bus Distribution Network_  
Figure 2 is designed and implemented in Matlab/Simulink environment by adhering to the following parameters:  
* Each bus is connected to the agent, and this agent, in turn, connects to the charging station. Therefore, the agent analysis its respective bus and shares the information with the charging station. * Every EV/EV battery connected to the station has 40% of the initial state of charge (SoC). * Every EV has the same battery parameters. * Each charging station is equipped with similar chargers in order to linearize the distributed observations. * The simulation assumes a charging station to be operating at 100% capacity in order to make distinct observations. * Residential/Industrial loads are always connected and running at full power. * A single three-phase power source powers the entirety of the grid. Observations and Inferences from IEEE 33-Bus Distribution Network  
The following observations made for the above system simulation and their results obtained are presented are as follows:  
* Utility grid simulation is conducted with only residential/industrial loads and the charging station kept off. For this scenario, we have observed a stable 3-phase voltage of 9.7 kV as shown in Figure 4a in the grid. Figure 4b shows the reactive power of 11 MW in the system. It is absorbed by harmonic filters and some residential/industrial loads. * When all CSs are operated at total capacity and no DC Fast Chargers are operated, there is a voltage drop to 8.88 kV as shown in Figure 4c along with the injection of reactive power as shown in Figure 4d in the system which scaled up to \(-8.5\) MW. Total Harmonic Distortion (THD) has been observed that is 1.8% as shown in Figure 5a using the Powergui FFT analysis tool.