Abstract

Water network protection from accidental and intentional contamination is one of the most critical issues for preserving the citizen health. Recently, some techniques have been proposed in the literature to define the optimal sensor placement. On the other hand, through the definition of permanent DMAs (District Meter Areas), water network partitioning allows significant reduction in the number of exposed users through the full isolation of DMA. In this paper, the optimal sensor placement is coupled with water network partitioning in order to define the best location of isolation valves and control stations, to be closed and installed respectively. The proposed procedure is based on different procedures, and it was tested on a real water network, showing that it is possible both to mitigate the impact of a water contamination and simplify the sensor placement through the water network partitioning.

Highlights

  • The “divide and conquer” concept has recently been gaining attention in the management of water distribution networks (WDNs), since dividing large-scale networks into smaller and manageable subsystems (District Metered Areas, district metered area (DMA)), offers advantages for the monitoring and control of consumption and leakage

  • This paper explores the benefits of network partitioning for the optimal placement of quality sensors for water distribution network (WDN) protection from contaminations

  • The water network partitioning leads to produce 5 DMAs; in Table 1, the number of nodes obtained in each DMA is reported, as well as the number Nec of boundary pipes

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Summary

Introduction

The “divide and conquer” concept has recently been gaining attention in the management of water distribution networks (WDNs), since dividing large-scale networks into smaller and manageable subsystems (District Metered Areas, DMAs), offers advantages for the monitoring and control of consumption and leakage. Numerous works were dedicated to the design of DMAs, based on the application of graph and spectral theory algorithm [1,2,3,4,5], or based on the concept of modularity function [6,7,8,9] In this framework, one of the main research issues lies in determining the optimal location of sensors, able to detect the most common water parameters and, as a result, to monitor the WDN by identifying possible contaminations [10,11,12,13]. The proposed methodology was tested on a real WDN, showing that the partitioning successfully mitigates the impact of contaminations in terms of affected population, thanks to the reduction in the total number of water paths in the WDN

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