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1、计算机系统应用 ISSN 1003-3254, CODEN CSAOBNE-mail: csa@iscas.ac.cnComputer Systems & Applications,2018,27(12):62−68 [doi: 10.15888/j.cnki.csa.006667]http://www.c-s-a.org.cn©中国科学院软件研究所版权所有.Tel: +86-10-62661041面向电力大数据的异构数据混合采集系统①孙 超, 王永贵, 常夏勤, 陆 鑫, 顾 全(南京南瑞继保电气有限公司, 南京 21
2、1102)通讯作者: 孙 超, E-mail: sunc@nrec.com摘 要: 随着智能电网的快速发展, 电力系统数据量的增长也非常迅速, 电力大数据急待开展深入研究. 电力数据产生的速率跨度大, 数据源众多且交互方式繁杂, 数据种类繁多等特点, 已有大数据采集方式难以适应多源异构数据的混合采集应用场景. 本文针对电力大数据提出了新的解决方案, 通过混合数据采集模型和采集集群实现了对异构数据源采集任务的混合调度和管理; 通过数据置信度标签技术, 在保留原始数据的同时, 标示数据的质量, 为后续大数据分析应用提供了便利; 通过
3、Sqoop、Kafka、文件传输等方式将采集与处理后的数据提交给大数据平台存储.系统已经在用户现场部署并投入使用, 运行稳定, 效果良好.关键词: 电力大数据; 异构数据源; 混合采集; 置信度; 数据监视引用格式: 孙超,王永贵,常夏勤,陆鑫,顾全.面向电力大数据的异构数据混合采集系统.计算机系统应用,2018,27(12):62–68. http://www.c-s-a.org.cn/1003-3254/6667.htmlMixedHeterogeneousDataAcquisitionSystemforPowerBigD
4、ataSUN Chao, WANG Yong-Gui, CHANG Xia-Qin, LU Xin, GU Quan(Nanjing NR Electric Co., Ltd., Nanjing 211102, China)Abstract: With the rapid development of smart grid, the growth of power system data is also very fast. There is an urgentneed of in-depth research for powe
5、r big data. Because of the large span of the data acquistion speed, numerous datasources, complicated interaction interfaces, and various kinds of data type, the existing big data technologies are unable toadapt to power big data aquisition. In this study, a new solu
6、tion for power big data acquisition is proposed. The systemschedules and manages the heterogeneous data source acquisition tasks through mixed data acquisition model andcollection cluster. With the technology of data confidential degree label, the system preserves th
7、e original data, indicatesthe quality of the data and provides convenience for big data analysis applications. The system submittes collected data tothe big data platform for storage by Sqoop, Kafka, file transfer, or other methods. The system has been deployed and p
8、utsinto use in the user site. It runs stably and has a sound effect.Keywords: big data for power system; heterogeneous data sources
