Automated sub-zoning of water distribution systems

Lina Sela Perelman, Michael Allen, Ami Preis, Mudasser Iqbal, Andrew J. Whittle

    Research output: Contribution to journalArticlepeer-review

    69 Citations (Scopus)

    Abstract

    Water distribution systems (WDS) are complex pipe networks with looped and branching topologies that often comprise thousands to tens of thousands of links and nodes. This work presents a generic framework for improved analysis and management of WDS by partitioning the system into smaller (almost) independent sub-systems with balanced loads and minimal number of interconnections. This paper compares the performance of three classes of unsupervised learning algorithms from graph theory for practical sub-zoning of WDS: (1) Global clustering – a bottom-up algorithm for clustering n objects with respect to a similarity function, (2) Community structure – a bottom-up algorithm based on the property of network modularity, which is a measure of the quality of network partition to clusters versus randomly generated graph with respect to the same nodal degree, and (3) Graph partitioning – a flat partitioning algorithm for dividing a network with n nodes into k clusters, such that the total weight of edges crossing between clusters is minimized and the loads of all the clusters are balanced. The algorithms are adapted to WDS to provide a practical decision support tool for water utilities. Visual qualitative and quantitative measures are proposed to evaluate models' performance. The three methods are applied for two large-scale water distribution systems serving heavily populated areas in Singapore.
    Original languageEnglish
    Pages (from-to)1-14
    JournalEnvironmental Modelling & Software
    Volume65
    Issue numberMarch 2015
    DOIs
    Publication statusPublished - Mar 2015

    Bibliographical note

    This paper is not yet available on the repository

    Funder

    National Research Council through the Singapore-MIT Alliance for Research and Technology (SMART)

    Keywords

    • Water distribution systems
    • Community structure
    • Graph clustering and partitioning

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