Powering Future Advancements and Applications of Battery Energy Storage Systems Across Different Scales
Zhao Yang Dong, Yuechuan Tao, Shuying Lai, Tianci Wang, Zhijun Zhang
Abstract
Battery Energy Storage Systems (BESSs) are critical in modernizing energy systems, addressing key challenges associated with the variability in renewable energy sources, and enhancing grid stability and resilience. This review explores the diverse applications of BESSs across different scales, from micro-scale appliance-level uses to large-scale utility and grid services, highlighting their adaptability and transformative potential. This study also includes advanced applications such as mobile energy storage, second-life battery utilization, and innovative models like Energy Storage as a Service (ESaaS) and energy storage sharing. Additionally, it discusses the integration of machine learning (ML) and large language models (LLMs), including advanced reinforcement learning (RL) algorithms, to optimize BESS operations and ensure safety through dynamic and data-driven decision-making. By examining current technologies, modeling methods, and future trends, this review provides a comprehensive overview of BESSs as a cornerstone technology for sustainable and efficient energy management, leading to a resilient energy future.