EM in MGs with EV charging refers to the special mainstream of providing electricity and continuously managing and balancing energy supply, load demand and integrating prosumer elements to maintain proper grid stability and efficiency. There are several disadvantages in the incorporation of EVs in to MGs and smart distribution networks. They are the high initial investment costs which accompany infrastructure improvements like updating charging stations and smart grid technologies may hinder implementation. In this paper, we present a new approach of Beluga Whale Optimization (BWO) incorporating electric vehicle charging stations (EVCS) for EM in MGs. The primary task that the given approach addresses is the optimization of system utilization and LCOE reduction. The BWO is applied for the performance enhancement of load scheduling of MGs with incorporated EV charging in smart distribution grids. The structure of BWO approach is also established on MATLAB platform, and their performance is compared with other algorithms including Artificial Neural Network (ANN), Shell Game Optimization (SGO), Multi-Objective Improved arithmetic Optimization Algorithm (MOIAOA) and Young's double Slit-Experiment Optimizer (YDSEO). The presented BWO method obtains LCOE equal to 22,173/kWh to prove its efficiency over existing methodologies for planning and designing energy systems. © 2025 Elsevier B.V., All rights reserved.