Gorilla Troops Optimization Algorithm for Optimal Placement of EV Charging Station with DG on Power Network

This paper employs a novel optimization approach for addressing the problem of optimal allocation of Distributed Generators (DGs) with Electric Vehicle Charging Stations (EVCSs) on Radial Power Distribution Networks (RPDNs). In this paper, the goal of integrating Distributed Generation (DG) is to mitigate the negative impacts of EVCS load on the RPDN. In this study, a nature-inspired Gorilla Troops Optimization Algorithm (GTOA) is utilized to determine the optimal placement, sizing, and power factor of Distributed Generation (DG) units in conjunction with Electric Vehicle Charging Stations (EVCS) installation on the RPDN. The primary optimization objectives of this coordination approach are the minimization of power loss, reduction of voltage deviation, and enhancement of the voltage stability of the system. The effectiveness of the proposed approach is evaluated by considering various cases of DG placement with EVCSs on the RPDNs. Also, a comparative analysis is conducted to assess the effectiveness of the proposed method in comparison with Moth-flame optimization and ant lion optimizer algorithms. The results demonstrate that the GTOA provides superior solution quality compared to competing algorithms.