摘要
传统电力系统正不断向智能化发展,大规模储能电池管理系统的应用,可以有效及时地分析储能单元和电池的工作情况提高工作效率,面对海量的数据分析压力,需要更先进的技术升级.对此本文分析了大数据技术下的电池管理系统.在明确当前电池储能管理系统的常规框架后,引入大数据技术,提出SOC数据预测办法构建数据集合,通过Hadoop数据管理架构,实现数据高速分析整理.事实证明,大数据技术可以有效应用于储能电池管理系统中,提高其智能化程度,实现数据模块的更快更换扩展.
Abstract
Traditional power systems are constantly developing towards intelligence. The application of large-scale energy storage battery management systems can effectively and timely analyze the working conditions of energy storage units and batteries to improve work efficiency. Faced with the pressure of massive data analysis, more advanced technological upgrades are needed. This article analyzes the battery management system under big data technology. After clarifying the conventional framework of the current battery energy storage management system, big data technology is introduced, and a SOC data prediction method is proposed to construct a data set. Through the Hadoop data management architecture, high-speed data analysis and organization are achieved. It has been proven that big data technology can be effectively applied to energy storage battery management systems, improving their intelligence and achieving faster replacement and expansion of data modules.
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