储能科学与技术2024，Vol.13Issue(10)：3653-3655,3.DOI:10.19799/j.cnki.2095-4239.2024.0902
基于大数据和人工智能的储能系统故障预测与诊断方法研究
Research on fault prediction and diagnosis methods of energy storage system based on big data and artificial intelligence
摘要
Abstract
With the rapid development of energy storage grid technology and new energy electric vehicle technology,the global demand for energy storage systems is increasing.However,the complexity of the application environment and the large-scale battery composition increase the probability of failure of the energy storage system.This paper describes the research on big data technology and artificial intelligence technology in energy storage system fault prediction and diagnosis from two perspectives.Big data technology can analyze a large amount of energy data,thereby improving the production and utilization efficiency of energy storage systems and reducing energy waste and loss.Artificial intelligence technology can mine the valuable information hidden behind big data,train energy data,and predict and diagnose energy storage systems.The integration of big data technology and artificial intelligence technology can process and analyze a large amount of energy data,thereby improving the efficiency of energy storage systems,predicting and diagnosing whether energy storage systems have failed,and promoting the monitoring and management of energy storage systems.关键词
储能系统/故障预测和诊断/大数据技术/人工智能Key words
energy storage system/fault prediction and diagnosis/big data technology/artificial intelligence分类
信息技术与安全科学引用本文复制引用
李根,刘珊珊..基于大数据和人工智能的储能系统故障预测与诊断方法研究[J].储能科学与技术,2024,13(10):3653-3655,3.基金项目
2023年广东省教育厅青年创新人才项目(自然科学)(2023KQNCX143). （自然科学）
