The paper presents an analysis of control strategies for battery energy storage systems (BESS) within power grids, addressing the challenges posed by renewable energy integration and system time delays. The study investigates various control algorithms, including Proportional-Integral-Derivative (PID), PID-Fuzzy, Nelder-Mead Simplex, and Model Predictive Control (MPC), emphasizing their performance in managing energy flows and maintaining system stability. Through simulation experiments using MATLAB/Simulink, the research demonstrates that while traditional PID controllers face limitations in handling time-delay systems, MPC offers superior control by optimizing future actions based on predictive models. The MPC’s adaptability, particularly when utilizing the CARIMA model, allows for effective management of dynamic behaviors and uncertainties in BESS. However, the study highlights the importance of precise tuning and accurate system modeling for optimal performance. The findings underscore the need for advanced adaptive and predictive control strategies to enhance the reliability and efficiency of modern energy systems, particularly in the context of increasing renewable energy deployment.