Abstract

Water Network Partitioning (WNP) improves water network management, simplifying the computation of water budgets and, consequently, allowing the identification and reduction of water losses. It is achieved by inserting flow meters and gate valves into a network which has been previously clustered into subsystems. Generally, the procedures are subdivided into two main steps: the clustering and partitioning phases. At first, network nodes are assigned to each cluster and then the appropriate pipes are selected, in which flow meters or gate valves are to be inserted. In this paper, an improved multilevel-recursive bisection algorithm was used to achieve network clustering. To better allocate the hydraulic devices, the partitioning phase was carried out through the minimization of a novel, multi-objective function, taking simultaneous account of energy and economic aspects. The aim is to define a solution that occupies a minimum possible number of flow meters, simplifying the water budget computation, preserving the hydraulic performances, and minimizing the capital and the operational costs. The procedure was tested on an extensive and real Mexican network, providing different optimal solutions and a smart Decision Support System (DSS) (based on visual diagrams and innovative energy, robustness, and balancing metrics).

Highlights

  • Nowadays, most systems have a networked structure, making their dynamic behaviour and development difficult to understand

  • San Luis Rio Colorado is a Mexican city located in the northern part of the state of Sonora, which is near the Mexico-United States (US) border

  • The mean and minimum pressures of all Water Network Partitioning (WNP) layouts are close to their original values, showing that the partitioning provides only a slight hydraulic deterioration

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Summary

Introduction

Most systems have a networked structure (from the Internet to transportation, to food webs, as well as social and biochemical structures), making their dynamic behaviour and development difficult to understand. If—on the one hand—it makes network structures more robust against unplanned and unforeseen operational conditions [1], on the other hand it obligates the development of new analysis approaches to better understand their complex functioning. The paradigm of “divide and conquer” has been adopted in order to simplify the management of water distribution systems, reducing the complexity of networks by subdividing them into more manageable sub-regions. The ability to find and analyse such groups can provide invaluable help in understanding and visualising the structure and behaviour of the networks, making the identification of common and distinctive features simpler.

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