DocumentCode
41135
Title
Household Energy Consumption Segmentation Using Hourly Data
Author
Jungsuk Kwac ; Flora, June ; Rajagopal, Ram
Author_Institution
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
Volume
5
Issue
1
fYear
2014
fDate
Jan. 2014
Firstpage
420
Lastpage
430
Abstract
The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.
Keywords
demand side management; power consumption; smart meters; AMI; CA smart meter data; encoding system; energy lifestyle segmentation strategies; hourly data; household electricity segmentation methodology; household energy consumption segmentation; pre-processed load shape dictionary; residential advanced metering infrastructure; Clustering algorithms; Dictionaries; Electricity; Encoding; Shape; Sociology; Statistics; Clustering; demand response; segmentation; smart meter data; variability;
fLanguage
English
Journal_Title
Smart Grid, IEEE Transactions on
Publisher
ieee
ISSN
1949-3053
Type
jour
DOI
10.1109/TSG.2013.2278477
Filename
6693793
Link To Document