储能
可再生能源
可靠性工程
系统工程
工程类
电网储能
间歇式能源
汽车工程
工艺工程
计算机科学
电气工程
分布式发电
功率(物理)
物理
量子力学
作者
Chen Chen,Jun Lai,Minyuan Guan
标识
DOI:10.3389/fenrg.2022.846741
摘要
With the motivation of electricity marketization, the demand for large-capacity electrochemical energy storage technology represented by prefabricated cabin energy storage systems is rapidly developing in power grids. However, the designs of prefabricated cabins do not initially fit for the requirement of grid energy storage in terms of manufacturing and implementation, resulting in difficulties in condition monitoring and having high risks of fire failures. It is necessary to develop a modularized and intelligent integration technology for cabin-type energy storge in MW ∼ GW for the deep embeddedness in power grid. With the core objective of improving the long-term performance of cabin-type energy storages, this paper proposes a collaborative design and modularized assembly technology of cabin-type energy storages with capabilities of thermal runaway detection and elimination in early stage, classified alarm of system operation status based on big data analysis, and risk-informed safety evaluation of cabin-type energy storage. Research in this paper can be guideline for breakthrough in the key technologies of enhancing the intrinsic safety of lithium-ion battery energy storage system based on big data analysis, proposing a prototype of novel energy storage system suitable for applications in power grid with high proportion of renewable energy.
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