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.
作者
王安琪
王强
施恂山
Wang Anqi;Wang Qiang;Shi Xunshan(Electrical and New Energy College of China Three Gorges University,Yi chang 443002,China;Chuzhou Power Supply Company of State Grid Anhui Electric Power Company Limited,Chuzhou 239000,China)
出处
《科技通报》
2018年第7期211-214,222,共5页
Bulletin of Science and Technology
关键词
大数据
错峰
用电管理
负荷
峰谷差
聚类
big data
peak
power management
load
the peak valley is poor
clustering