Big Data Analysis Research of Power Saving in Consumer Side

被引：0

作者：

Chen H. ^{[1
]}

Wang S. ^{[1
]}

Liang D. ^{[2
]}

Su Y. ^{[3
]}

机构：

[1] Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Nankai District, Tianjin

[2] State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Beichen District, Tianjin

[3] Shanghai Municipal Electric Power Company of State Grid, PudongNew District, Shanghai

来源：

Dianwang Jishu/Power System Technology | 2019年 / 43卷 / 04期

关键词：

Big data; Data visualization; Distributed storage; Electric power saving analysis; Parallel computation;

D O I：

10.13335/j.1000-3673.pst.2018.1207

中图分类号：

学科分类号：

摘要：

To solve the problems existing in user-side power saving, such as data opacity and lack of guidance, a general power-saving analysis method is put forward based on data mining under the background of big data. Then it is implemented on a big data platform in a distributed manner and a direct visualization form is designed. Firstly, electricity groupsaresubdivided with high-dimensional clustering method according to the characteristics of power consuming. Then power, weather, economy and other multi-dimensional data are combined to carry out power saving analysis. The benchmark power consumer is acquired based on comprehensive evaluation of energy efficiency within a certain group, so the power-saving potential can be calculated. A power-saving strategy is obtained through multi-source data correlation analysis. Finally, the power-saving algorithm and business are implemented on a big data platform. Based on JavaWeb MVC framework, the analysis results are visualized directly. Practical application results show that the proposed method can effectively correlate multi-source data and realize efficient analysis of huge amount of user data. © 2019, Power System Technology Press. All right reserved.

引用

页码：1345 / 1353

页数：8

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