Learning from Hourly Household Energy Consumption: Extracting, Visualizing and Interpreting Household Smart Meter Data

被引：7
|
作者：
Borgeson, Sam [1 ]
Flora, June A. [1 ]
Kwac, Jungsuk [1 ]
Tan, Chin-Woo [1 ]
Rajagopal, Ram [1 ]
机构：
[1] Stanford Univ, Sustainable Syst Lab, Dept Civil & Environm Engn, Stanford, CA 94305 USA
来源：
DESIGN, USER EXPERIENCE, AND USABILITY: INTERACTIVE EXPERIENCE DESIGN (DUXU 2015), PT III | 2015年 / 9188卷
关键词：
Information design; Data visualization; Energy; Sustainability; Energy efficiency; Customer segmentation; Machine learning;
D O I：
10.1007/978-3-319-20889-3_32
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we present the Energy Visualization and Insight System for Demand Operations and Management platform (VISDOM), a collection of smart meter data analysis algorithms and visualization tools designed to address the challenge of interpreting patterns in energy data in support of research, utility energy efficiency and demand response programs. We provide an overview of how the system works and examples of usage, followed by a discussion of the potential benefits of using VISDOM to identify and target participants whose electricity consumption is best aligned with the goals of efficiency and demand response programs.
引用
收藏
页码：337 / 345
页数：9
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