Optimal Planning of Electric Vehicle Charging Station and Distributed Generation in a Multi-microgrid System Using Puma Optimization

Electric vehicle charging station (EVCS) networks are essential in the process of the sustainable development of the electric mobility sector. Nonetheless, the random nature of EVCS installations may result in a number of technical and economical drawbacks in the distribution network, such as an increase in the losses of energy. Thus, the unfavorable impact of EV charging demand is to be mitigated by strategically choosing locations of both the EVCSs and distributed generators (DGs). To resolve these issues, the present paper presents a Puma Optimization (PO) that would help to select the position and capacity of EVCSs and DGs in the most optimal way. The proposed multi-objective algorithm is used to assign EVCSs, DGs, and capacitors at the same time to optimize the voltage stability, decrease the active and reactive power losses, and decrease the computation time in the Multi-Microgrid (MMG) setup. The method has been tested on a modified 33-bus radial distribution system, which is broken into zones that are referred to as microgrids. The results prove the higher efficiency of the PO, which enables obtaining a substantial decrease in the active power losses by 81.33 percent and 80 percent, and in the reactive power losses by 78.46 and 80.26% regarding the modified 33-bus system.