Clustering time-series energy data from smart meters

被引：38

作者：

Lavin, Alexander ^{[1
]}

Klabjan, Diego ^{[1
]}

机构：

[1] Northwestern Univ, Dept Ind Engn & Management Sci, Evanston, IL 60208 USA

来源：

ENERGY EFFICIENCY | 2015年 / 8卷 / 04期

关键词：

Energy efficiency program; Smart meter; Time-series clustering; k-means; Electricity load profile;

D O I：

10.1007/s12053-014-9316-0

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Investigations have been performed into using clustering methods in data mining time-series data from smart meters. The problem is to identify patterns and trends in energy usage profiles of commercial and industrial customers over 24-h periods and group similar profiles. We tested our method on energy usage data provided by several U.S. power utilities. The results show accurate grouping of accounts similar in their energy usage patterns, and potential for the method to be utilized in energy efficiency programs.

引用

页码：681 / 689

页数：9

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