Efficient BESS Scheduling in AC Microgrids via Multiverse Optimizer: A Grid-Dependent and Self-Powered Strategy to Minimize Power Losses and CO2 Footprint

This paper presents a novel energy management system for AC microgrids that integrates a parallel implementation of the Multi-Verse Optimizer (MVO) with the Successive Approximations method for power flow analysis. The proposed approach optimally schedules battery energy storage systems (BESSs) in both grid-connected and islanded modes, aiming to minimize energy losses and reduce CO2 emissions. Numerical evaluations on a 33-node AC microgrid demonstrate significant improvements: in the grid-dependent mode, energy losses drop from 2484.57 kWh (base case) to 2374.85 kWh, and emissions fall from 9.8874 Ton(CO2) to 9.8693 Ton(CO2). Under the self-powered configuration, energy losses and emissions are curtailed from 2484.57 kWh to 2373.53 kWh and from 16.0659 Ton(CO2) to 16.0364 Ton(CO2), respectively. The results highlight that the proposed method outperforms existing metaheuristics in solution quality and consistency. This work advances microgrid scheduling by ensuring technical feasibility, reducing carbon footprint, and maintaining voltage stability under diverse operational conditions.