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http://dx.doi.org/10.3741/JKWRA.2021.54.10.759

A study on the practical use of smart meter end-user demand data  

Park, Geunyeong (School of Civil, Environmental and Architectural Engineering, Korea University)
Jung, Donghwi (School of Civil, Environmental and Architectural Engineering, Korea University)
Jun, Sanghoon (Department of Civil and Architectural Engineering and Mechanics, The University of Arizona)
Publication Information
Journal of Korea Water Resources Association / v.54, no.10, 2021 , pp. 759-768 More about this Journal
Abstract
This work introduces a new approach that classifies individual household water usage by examining the characteristics of smart meter end-user demand data. Here, one of the most well-known unsupervised machine learning, K-means algorithm, is applied to classify water consumptions by each household. The intensity and duration of end-user demands are used as main features to determine the households with similar water consumption pattern. The results showed that 21 households are classified into 13 clusters with each cluster having one, two, three, or five houses. The reasoning why multiple households are classified into the same cluster is described in this paper with respect to the collected data and end-user water consumption behavior.
Keywords
End-user demand classification; Smart meter; Unsupervised machine learning; Water distribution system;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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