Marine Predator Algorithm for Optimal Placement of EV Charging Station with Optimal Power Factor of DG on Distribution Network

Electric vehicles (EVs) may provide an ecologically sustainable way of transportation. EV charging stations (EVCS) are being developed worldwide to encourage the widespread adoption of EVs. However, the adoption of EVs on a large scale necessitates for the strategic positioning of EVCS across the distribution network. In this paper, the goal of integrating Distributed Generation (DG) with real and reactive power correction capabilities is to mitigate the negative impacts of EVCS load on the distribution network. For optimal siting, sizing and operating power factor of DGs with EVCS, nature inspired Marine Predator Algorithm (MPA) is employed. Multiple objective functions, such as active power losses, voltage deviation, the investment cost of DG units, and the voltage stability index, are taken into account. Several scenarios of different number of DG units with EVCS installations are considered to assess the efficacy of the proposed method on 33 and 69-bus radial power distribution systems. The MPA outcomes are also verified by comparing them with the outcomes of the dragonfly algorithm.