Open Access

ARTICLE

Partitioning of Water Distribution Network into District Metered Areas Using Existing Valves

Aniket N. Sharma¹, Shilpa R. Dongre¹, Rajesh Gupta¹, Prerna Pandey¹, Neeraj Dhanraj Bokde^2,*

1 Department of Civil Engineering, Visvesvaraya National Institute of Technology, Nagpur, 440010, India
2 Department of Civil and Architectural Engineering, Aarhus University, Aarhus, 8000, Denmark

* Corresponding Author: Neeraj Dhanraj Bokde. Email:

(This article belongs to the Special Issue: Computer Modeling for Smart Cities Applications)

Computer Modeling in Engineering & Sciences 2022, 131(3), 1515-1537. https://doi.org/10.32604/cmes.2022.018867

Received 21 August 2021; Accepted 11 November 2021; Issue published 19 April 2022

Abstract

Water distribution network (WDN) leakage management has received increased attention in recent years. One of the most successful leakage-control strategies is to divide the network into District Metered Areas (DMAs). As a multi-staged technique, the generation of DMAs is a difficult task in design and implementation (i.e., clustering, sectorization, and performance evaluation). Previous studies on DMAs implementation did not consider the potential use of existing valves in achieving the objective. In this work, a methodology is proposed for detecting clusters and reducing the cost of additional valves and DMA sectorization by considering existing valves as much as possible. The procedure of DMAs identification has been divided into three stages, i.e., a) clusters identification; b) sectorization or boundaries optimization and c) performance evaluation of the partitioned network. The proposed methodology is evaluated on a simple network and a real-world water network with the findings provided and compared to the DMAs, established for a raw water network with no existing valves. It is found that there is an adequate difference in cost of strategy implementation in both the cases for the network under consideration and the existing valve system achieved better network performance in terms of resilience index.

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Keywords

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