储能科学与技术 ›› 2025, Vol. 14 ›› Issue (10): 3872-3874.doi: 10.19799/j.cnki.2095-4239.2025.0809

• 储能系统与工程 • 上一篇    下一篇

大数据支持下化学储能网络安全问题分析

刘嘉瑞()   

  1. 濮阳职业技术学院数学与信息工程学院,河南 濮阳 457000
  • 收稿日期:2025-09-09 修回日期:2025-10-11 出版日期:2025-10-28 发布日期:2025-10-20
  • 作者简介:刘嘉瑞(1985—),男,本科,讲师,研究方向为计算机应用,E-mail:liujiarui00007@163.com

Security analysis of chemical energy storage network supported by big data

Jiarui LIU()   

  1. School of Mathematics and Information Engineering, Puyang Vocational and Technical College, Puyang 457000, Henan, China
  • Received:2025-09-09 Revised:2025-10-11 Online:2025-10-28 Published:2025-10-20

摘要:

化学储能系统的广泛应用带来了重要的电力资源,为国家电网升级提供了保证,但是其自身的网络安全问题也需要妥善解决。本研究针对大数据下的化学储能系统网络安全问题进行分析综述,首先重点归纳了现阶段化学储能系统的研究进展,包括主流化学储能系统的种类和化学储能系统在电力系统中的应用情况;然后整理分析了当前常规化学储能系统的内部结构,即储能电池管理系统、升压变流系统以及能量管理系统(EMS)三部分内容,最后结合大数据技术探讨了化学储能系统网络安全问题的解决策略和发展方向,希望对未来化学储能系统的研究提供借鉴。

关键词: 化学储能, 电力资源, 大数据, 电池管理

Abstract:

The wide application of chemical energy storage system has brought important grid power resources and provided an important guarantee for the upgrading of the national grid, but its own network security problems also need to be properly solved. This research analyzes and summarizes the security issues of chemical energy storage network under big data. Firstly, it mainly summarizes the research progress of chemical energy storage system at this stage, including the types of mainstream chemical energy storage systems and the application of chemical energy storage in power system; Then the internal structure of the current conventional chemical energy storage system is analyzed, including the energy storage battery management system, the boost converter system and the energy management system (EMS). Finally, combined with the big data technology, the solution strategy and development direction of the network security problem of the chemical energy storage system are discussed, hoping to provide some ideas for the future research of the chemical energy storage system.

Key words: chemical energy storage, power resources, big data, battery management

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