Multi-Objective Optimal Allocation of Hybrid Electric Vehicles Charging Stations and Renewable Distributed Generators into the Distribution System

Abstract

Electric vehicle charging stations (EVCS) and renewable distributed generators (RDG) units are very exciting topics that have been implemented and used to enhance the efficiency of the energy of the electrical distribution system (EDS) when it comes to their optimal integration. This paper proposed the use of the marine predators algorithm (MPA) for multi-objective optimal allocation of hybrid EVCS and RDG based on wind and solar power generation in EDS. The novel multi-objective functions proposed for minimizing the active power loss (APL), voltage stability index (VSI), fast voltage stability index (FVSI), line stability factor (LPQ), and power-voltage stability index (PVSI). The capability of the MPA approach is tested for the IEEE 69-bus and compared with other competitive optimization approaches. The simulation results obviously showed the efficiency, feasibility and superiority of the applied MPA algorithm, while respecting the other relevant techniques for optimum solutions for simultaneous hybrid EVCS and RDG unit allocation.