<p>A novel approach utilizing Particle Swarm Optimization (PSO) is proposed for optimizing the energy management of distributed generators (DGs) in a networked microgrid system, incorporating electric vehicles (EVs) and battery storage. The Particle Swarm Optimization (PSO) is known for simplicity due to lesser computation requirement and fast figuring rate. The proposed PSO based energy management scheme handles the uncertainty in the networked microgrid due to renewable based DGs, residential and commercial loads, batteries and electric vehicles power requisition in energy management problems and adequately optimize the operating cost. The objective is to minimize the overall cost of operation by assigning priority levels to different generators based on their respective costs. The proposed algorithm effectively leverages the charging and discharging capabilities of EVs during off- peak and peak demand periods respectively, while ensuring their regular operational schedules are not disrupted. Furthermore, the system optimally utilizes renewable-based DGs by employing battery storage units. A mathematical model is formulated to define the cost function, enabling the scheduling of uneconomical generators to operate during peak hours and be shut down during off -peak hours, resulting in a minimized operational cost for the networked microgrid. Simulation scenarios are conducted, comparing the proposed approach with and without the inclusion of EVs, to highlight the significant role of EVs and battery storage in achieving cost minimization and flexible operation of the individual microgrids. Moreover, an economic analysis is performed, comparing the proposed scheme with an existing Modified BAT Algorithm (MBA) and ANT Coloney Optimization (ACO) based energy management program, which further validates the superiority of the proposed approach.</p>