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人工智能在磷酸铁锂电池储能电站中的应用研究 被引量:2

Research on the application of artificial intelligence in lithium iron phosphate battery energy storage power station
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摘要 磷酸铁锂电池储能电站是现代能源体系的关键构成要素之一。作为新型电力系统构建的关键技术,人工智能可以有效提升磷酸铁锂电池储能电站运行效率与安全管理水平,对于增强电网灵活性及优化可再生能源消纳能力具有关键性作用。首先介绍了磷酸铁锂电池储能电站的工作原理,分析了磷酸铁锂电池储能电站在实际应用中面临的多重挑战,解释了人工智能技术在磷酸铁锂电池储能电站中应用的必要性,阐述了人工智能技术在磷酸铁锂电池储能电站中的应用优势,重点聚焦于辅助电池管理系统实现更精确的状态监测和故障诊断,通过赋能提升磷酸铁锂电池储能电站调度和分配效率,以及人工智能在储能电站安全防护体系中的强化作用,旨在为磷酸铁锂电池储能电站的智能化发展提供有益参考。 Lithium iron phosphate battery energy storage power station is one of the key components of modern energy system.As a key technology for the construction of new power system,artificial intelligence can effectively improve the operation efficiency and safety management level of lithium iron phosphate battery energy storage power station,which plays a key role in enhancing the flexibility of power grid and optimizing the consumption capacity of renewable energy.Firstly,the working principle of lithium iron phosphate battery energy storage power station is introduced.The multiple challenges faced by lithium iron phosphate battery energy storage power station in practical application are analyzed.The necessity of the application of artificial intelligence technology in lithium iron phosphate battery energy storage power station is explained.The application advantages of artificial intelligence technology in lithium iron phosphate battery energy storage power station are expounded.The focus is on the auxiliary battery management system to achieve more accurate condition monitoring and fault diagnosis.By enabling,the scheduling and distribution efficiency of lithium iron phosphate battery energy storage power station is improved,and the strengthening effect of artificial intelligence in the safety protection system of energy storage power station is enhanced.The aim is to provide a useful reference for the intelligent development of lithium iron phosphate battery energy storage power station.
作者 李陈 LI Chen(College of Science and Technology,China Three Gorges University,Yichang 443002,Hubei China)
出处 《粘接》 2025年第8期103-106,共4页 Adhesion
基金 三峡大学科技学院2025年重点教学研究项目(项目编号:JY20250003)。
关键词 磷酸铁锂电池 人工智能 储能电站 电池管理系统 微电网 热失控 lithium iron phosphate battery artificial intelligence energy storage power station battery management system microgrid thermal runaway
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