Optimal Allocation Framework for <scp>EV</scp> Charging Stations in Hybrid Renewable Energy Integrated Distribution Systems

ABSTRACT The global surge in Electric Vehicle (EV) adoption has made the development and deployment of EV Charging Stations (EVCS) crucial for enabling a sustainable transportation infrastructure. However, this increased integration also presents significant challenges for Radial Distribution Systems (RDS). The integration of EVCS presents significant challenges for distribution networks, primarily in the form of increased Energy Loss (EL) and degraded power quality, measured by Total Harmonic Distortion (THD i ). This work introduces a planning framework to strategically install EVCS integrated with multiple renewable and energy storage technologies, including Photovoltaics (PV), Wind Turbines (WT), Battery Energy Storage Systems (BESS), and Compressed Air Energy Storage (CAES). This work has been conducted on a 33‐bus RDS, aiming to minimize EL and THD i while satisfying operational constraints. This work is modeled as a bi‐objective optimization problem and utilize the Symbiotic Organisms Search (SOS) algorithm to identify optimal solutions. The robustness of the SOS‐derived solution is further confirmed through a comparative analysis with two other metaheuristic techniques: the Ant Lion Optimizer (ALO) and the Gray Wolf Optimization (GWO). The findings indicate that the prosumer‐integrated EVCS model not only supports the increased adoption of EVs but also strengthens the power distribution network by improving its efficiency, stability, and sustainability, making it a crucial step toward a greener energy future.