Battery Energy Storage Sizing and Operational Strategy for Microgrid Considering Electric Vehicle

The integration of electric vehicles (EVs) into microgrids (MGs) presents both opportunities and challenges for energy management. To improve the economic and environment-friendly operation of MGs, integration of battery energy storage (BESS) and EVs with Vehicle-to-Grid (V2G) is necessary. In this paper, a comprehensive study is conducted by comparing the performance of four optimization algorithms, namely Bald Eagle search (BES) Optimization algorithm, Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), and Arithmetic Optimization Algorithm (AOA) in solving the MG scheduling problem. Two scenarios are considered, First without BESS, EVs and the second, with BESS and EVs, to evaluate the impact of storage elements on the MG operation by considering zero renewable power curtailment. The optimization objective is minimizing the total operating cost of MG and the peak is shifted using V2G service of EVs and BESS. The findings demonstrate that the incorporation of BESS and V2G services can improve significantly the economic and environmental performance of the MGs. Moreover, among the four optimization algorithms, BES outperforms the other algorithms regarding solution quality and convergence speed for both scenarios. These results provide valuable insights for designing effective optimization strategies for MGs with renewable energy sources, EVs, and BESS.