Energy Management and Metaheuristic Methods for Cost-Effective and Reliable Vehicle-to-Grid Sizing

The integration of Vehicle-to-Grid (V2G) systems into modern power grids has emerged as a promising solution to enhance grid stability, reduce energy costs, and promote renewable energy utilization. However, the optimal sizing of V2G systems remains a critical challenge due to the conflicting objectives of minimizing costs and maximizing reliability. This paper proposes a novel approach that combines the Grasshopper Optimization Algorithm (GOA) with a rule-based energy management scheme to address the sizing problem of V2G systems. The GOA is employed to optimize the system configuration, while the rule-based energy management scheme ensures efficient energy distribution and utilization. The proposed methodology is evaluated through a case study, demonstrating its effectiveness in achieving a balance between cost and reliability. The results indicate that the proposed approach outperforms traditional methods in terms of both economic and operational performance.