Vehicle-to-grid based optimization for managing electric vehicle charging load and reducing grid fluctuations in microgrids

With the growing integration of electric vehicles, the demand for charging increasingly coincides with peak electricity consumption, leading to higher system operating expenses. This issue is expected to intensify as electric mobility continues to expand. To address this challenge, a scheduling strategy is proposed that utilizes bidirectional energy transfer capabilities between electric vehicles and the power network. The approach is evaluated under a scenario where electric vehicles constitute 7 % of the total system load, with the aim of mitigating load variability in microgrid environments. The objective is to manage the significant share of vehicle-related demand in microgrid settings, by coordinating charging and discharging processes. This coordination helps smooth load profiles. To improve computational performance and decrease resource requirements, a loop optimization strategy is adopted, producing outcomes comparable to those of a overall optimization model with reduced processing effort. After optimization via Vehicle-to-Grid, the grid fluctuation was reduced to 35.84 % of that under uncontrolled charging, equivalent to 77.93 % of the original grid fluctuation—a reduction of 22.07 %. A comparison between uncontrolled charging and optimized scheduling demonstrates that the latter decreases the load fluctuation index, shifts peak charging periods, and makes more efficient use of surplus energy stored in electric vehicle batteries, thereby contributing to enhanced grid stability.