基于向量误差修正模型的电池簇不一致检测方法及智能运维方案
Battery Cluster Inconsistency Detection Method and Intelligent O&M Scheme Based on Vector Error Correction Model
郭源 1夏向阳 1岳家辉 1李辉 2吴晋波2
作者信息
- 1. 长沙理工大学电气与信息工程学院,湖南长沙 410114
- 2. 国网湖南省电力科学研究院,湖南长沙 410000
- 折叠
摘要
针对储能电站实际运行数据中存在电池数据不完整、数据片段化导致检测不准确的问题,提出基于向量误差修正模型的电池簇不一致检测方法.该方法根据随机电压片段数据构建电池簇与电池单体的向量误差修正模型,计算脉冲响应函数,分析电池单体对电池簇的动态作用机制,判断电池簇不一致程度,再通过方差分解分析确定异常电池单体及后续运维.最后,根据储能电站实际运行数据进行分析,验证了电池簇不一致检测方法及运维方案的可行性和有效性,并在100 kW/200 kW·h储能平台进行实际工程测试.
Abstract
To solve the problems of incomplete battery data and fragmented data segments leading to inaccurate detection in the actual operation data of energy storage power stations,this paper proposes a battery cluster inconsistency detection method based on the vector error correction model.In this method,the vector error correction model of battery clusters and battery cells is constructed using random voltage fragment data,the impulse response function is calculated,the dynamic mechanism of battery cells on battery clusters is analyzed,and the inconsistency degree of battery clusters is assessed.Subsequently,the abnormal battery cells and subsequent operation and maintenance are identified by variance decomposition analysis.Finally,through the actual operation data of the energy storage power station,the feasibility and effectiveness of the battery cluster inconsistency detection method and operation and maintenance scheme are verified in an actual engineering test on a 100 kW/200 kW·h energy storage platform.
关键词
电池簇不一致/随机片段数据/向量误差修正模型/智能运维方案Key words
battery inconsistency/random fragment data/vector error correction model/intelligent O&M scheme引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据