Print Email Facebook Twitter Dynamic Time Warping Clustering to Discover Socioeconomic Characteristics in Smart Water Meter Data Title Dynamic Time Warping Clustering to Discover Socioeconomic Characteristics in Smart Water Meter Data Author Steffelbauer, D.B. (TU Delft Water Resources; Norwegian University of Science and Technology (NTNU)) Blokker, E.J.M. (TU Delft Sanitary Engineering; KWR Water Research Institute) Buchberger, S. G. (University of Cincinnati) Knobbe, Arno (Universiteit Leiden) Abraham, E. (TU Delft Water Resources) Date 2021 Abstract Socioeconomic characteristics are influencing the temporal and spatial variability of water demand, which are the biggest source of uncertainties within water distribution system modeling. Improving current knowledge of these influences can be utilized to decrease demand uncertainties. This paper aims to link smart water meter data to socioeconomic user characteristics by applying a novel clustering algorithm that uses a dynamic time warping metric on daily demand patterns. The approach is tested on simulated and measured single-family home data sets. It is shown that the novel algorithm performs better compared with commonly used clustering methods, both in finding the right number of clusters as well as assigning patterns correctly. Additionally, the methodology can be used to identify outliers within clusters of demand patterns. Furthermore, this study investigates which socioeconomic characteristics (e.g., employment status and number of residents) are prevalent within single clusters and, consequently, can be linked to the shape of the cluster’s barycenters. In future, the proposed methods in combination with stochastic demand models can be used to fill data gaps in hydraulic models. Subject Smart metersclusteringmachine learning (ML)Demand modelingDynamic time warpingSocioeconomic characteristics To reference this document use: http://resolver.tudelft.nl/uuid:dea04b79-74eb-44a8-b3b5-d347986ea7ce DOI https://doi.org/10.1061/(ASCE)WR.1943-5452.0001360 Embargo date 2021-10-01 ISSN 0733-9496 Source Journal of Water Resources Planning and Management, 147 (6) Bibliographical note Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2021 D.B. Steffelbauer, E.J.M. Blokker, S. G. Buchberger, Arno Knobbe, E. Abraham Files PDF _28ASCE_29WR.1943_5452.0001360.pdf 16.17 MB Close viewer /islandora/object/uuid:dea04b79-74eb-44a8-b3b5-d347986ea7ce/datastream/OBJ/view