摘要
运维技术是电池储能电站规模化推广应用的关键。针对电池储能电站运维成本高、工作量大且运维数据利用价值小等问题,综述了数据挖掘技术及其在电池储能电站运维中的应用。根据电池管理系统(BMS)的历史数据及在运数据,可对电池的健康状态进行预测;通过对电池柜密闭环境内的气体进行监测与分析,具有提前预警火灾风险的作用。基于电池储能电站特征量分析,通过大数据实现对电站内电气设备故障精准定位,制定科学检修计划,并在此基础上提高电池储能电站的智能化运维水平,为智能运维大数据平台建设提供基础。
Operation and maintenance technology is the key to the large-scale promotion and application of battery energy storage power station.Aiming at the problems of high maintenance and operation cost of battery energy storage power station,large workload and small data value,this paper summarizes data mining technology and its application of operation and maintenance of battery energy storage power station.Through BMS historical data and in-service data,the health status of the battery can be predicted,and by monitoring and analyzing the gas in the closed environment of the battery cabinet,it also has an early warning effect on fires.Based on the analysis of the characteristics of the battery energy storage power station,through big data,it can accurately locate the faults of the electrical equipment in the power station,formulate a scientific maintenance plan,improve the intelligent operation and maintenance level of the battery energy storage power station,and provide the foundation for the construction of the intelligent operation and maintenance big data platform.
作者
田刚领
叶晖
张柳丽
崔美琨
李爱魁
Tian Gangling;Ye Hui;Zhang Liuli;Cui Meikun;Li Aikui(Pinggao Group Energy Storage Technology Co.,Ltd.,Tianjin 300308,China;School of Electrical Engineering,Dalian University of Technology,Dalian 116024,China)
出处
《太阳能》
2022年第5期23-32,共10页
Solar Energy
基金
平高集团科技项目——储能电站智能运维平台开发及应用研究PGKJ2020-077(529100200021)。
关键词
电池储能电站
数据挖掘
运维
新能源波动
调峰调频
battery energy storage power station
data mining
operation and maintenance
new energy fluctuations
peak shaving and frequency modulation
