摘要
为防止分布式电网负荷有功功率出现混乱波动的变化情况,解决电力大数据的不均衡存储问题,提出分布式电力大数据存储系统的参数优化方法。根据Zookkeeper数据协调服务的传输请求,将HBase数据库主机接入至Spark分布式框架的固定单元结构中,完成分布式电力大数据的存储系统构建。在此基础上处理处于传输状态的电力大数据,通过建立关联系数查询标准的方式,得到最终的优化特征提取结果,实现分布式电力大数据存储系统参数优化方法的顺利应用。实例分析结果表明,分布式优化方法可将电网负荷有功功率的波动变化范围限制在既定数值区间之内,更符合均衡存储电力大数据的实际应用需求。
In order to prevent the chaotic fluctuation of load active power in distributed power grid and solve the problem of unbalanced storage of power big data,a parameter optimization method of distributed power big data storage system is proposed.According to the transmission request of Zookkeeper data coordination service,the HBase database host is connected to the fixed unit structure of Spark distributed framework to complete the construction of distributed power big data storage system.On this basis,the power big data in the transmission state is processed,and the final optimization feature extraction results are obtained by establishing the correlation coefficient query standard,so as to realize the smooth application of the parameter optimization method of the distributed power big data storage system.The example analysis results show that the distributed optimization method can limit the fluctuation range of power grid load active power within the established numerical range,which is more in line with the practical application requirements of balanced storage of power big data.
作者
梁雪青
杜舒明
赵小凡
刘超
LIANG Xueqing;DU Shuming;ZHAO Xiaofan;LIU Chao(Guangzhou Power Supply Bureau,Guangdong Power Grid Co.,Ltd.,Guangzhou 510000,China)
出处
《电子设计工程》
2023年第10期101-105,共5页
Electronic Design Engineering
关键词
电力大数据
存储系统
参数优化
分布式框架
数据协调服务
关联系数
electric power big data
storage system
parameter optimization
distributed framework
data coordination service
correlation coefficient
