基于大数据的错峰用电管理系统设计
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摘要
传统用电管理系统存在用户用电量时间协调性差,无法有效降低峰谷差,设计基于大数据的错峰用电管理系统,在大数据环境下设计系统硬件框图,并分别对应用模块、数据模块和外接接口模块进行分析;采用K+means聚类算法对日负荷曲线进行聚类分析,并对分析结果统计,获取相关负荷特性指标判定用户用电模式。设计管理流程,并将错峰管理情况在页面上展示。通过实验验证可知,该系统可调节用户在高峰期用电情况,合理调节用电时间,有效降低峰谷差。
The traditional electricity management system is user power consumption time, poor coordination,unable to effectively reduce the peak valley is poor,the design peak electricity management system based on large data,the system hardware design block diagram,in a big data environment and application module,data module and an external interface module are analyzed; Using K + means clustering algorithm clustering analysis was carried out on the daily load curve,and the analysis results,access to relevant load characteristic index to determine the user power mode. Design management process,and showed the peak management situation on the page.Through experimental verification shows that the system can adjust the user in the peak power usage,reasonable adjusting electricity time,effectively reduce the peak valley is poor.
The traditional electricity management system is user power consumption time, poor coordination,unable to effectively reduce the peak valley is poor,the design peak electricity management system based on large data,the system hardware design block diagram,in a big data environment and application module,data module and an external interface module are analyzed; Using K + means clustering algorithm clustering analysis was carried out on the daily load curve,and the analysis results,access to relevant load characteristic index to determine the user power mode. Design management process,and showed the peak management situation on the page.Through experimental verification shows that the system can adjust the user in the peak power usage,reasonable adjusting electricity time,effectively reduce the peak valley is poor.
引文
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[2]肖建波,郑伟,代作伟,等.基于大数据采集的播出监管系统设计与实现[J].电视技术,2017,41(6):40-44.
[3]张斌,彭其渊.基于大数据的铁路客户关系管理系统设计研究[J].铁道运输与经济,2017,39(6):42-48.
[4]姜明月.云计算平台下的大数据分流系统的设计与优化[J].现代电子技术,2016,39(2):28-32.
[5]吴凯峰,刘万涛,李彦虎,等.基于云计算的电力大数据分析技术与应用[J].中国电力,2015,48(2):111-116.
[6]桂勋,郑永康.基于大数据技术的北美FNET/Grid Eye系统设计与实现[J].电力系统自动化,2017,41(10):112-116.
[7]张向睿,向华.面向云计算大数据中心的制造业项目管理系统设计[J].现代电子技术,2017,40(12):46-48.
[8]徐祥征,王师奇.基于大数据分析的配电网主动检修业务应用研究与实现[J].科技通报,2017,33(6):105-108.
[9]HAO Ran,AI Qian.Rchitecture based on multivariate big data platform for analyzing electricity consumption behavior[J].Electric Power Automation Equipment,2017,37(8):20-27.
[10]GE Leijiao,WANG Shouxiang,QU Haini,et al.Design of storage framework for big data of SPDU[J].Electric Power Automation Equipment,2016,36(6):194-202.
[11]Liang Junrong.Research on Security Analysis and Management of Library Information System Based on Big Data Decision[J].Library Theory and Practice,2017,18(3):93-98.