YIN Zhao, XU Yujie, ZHANG Hualiang, XU Dehou, WEI Lu, LENG Zhiyi, YE Jia, ZHAO Xinyu, SHI Zhuoqun, CHAI Xingzai, SUN Baozuo, CHEN Haisheng
Journal of Engineering Thermophysics. 2025, 46(12): 4116-4140.
Energy storage technology plays a crucial role in advancing the development of renewable energy, promoting carbon peak and carbon neutrality, and enhancing the quality of power systems. Facing complex and variable electricity supply and demand scenarios, artificial intelligence (AI) powerfully drives energy storage technology towards development in the directions of high efficiency, economy, reliability, and environmental friendliness. This paper first classifies artificial intelligence into categories such as algorithms (intelligent prediction, intelligent optimization, intelligent decision), tasks (predictive AI, generative AI, computer vision, embodied AI, agents), and scale (small models, large models), elaborating on relevant cases. Subsequently, it introduces the application of artificial intelligence across various stages of energy storage technology, encompassing design, experiment, manufacture, operation, fault diagnosis, and decommissioning & recycling. Following this, it proposes future development directions and summarizes the application system of artificial intelligence in energy storage technology. Through the above work, the paper aims to further promote a more comprehensive, orderly, and in-depth cross-integration of ”AI + Energy Storage”.