Abstract

In this paper, a simplified methodology to increase the water distribution equity in existing intermittent water distribution systems (WDSs) is presented. The methodology assumes to install valves in the water distribution network with the objective to re-arrange the flow circulation, thus allowing an improved water distribution among the network users. Valve installation in the WDS is based on the use of algorithms of sequential addition (SA). Two optimization schemes based on SA were developed and tested. The first one allows identifying locations of gate valves in order to maximize the global distribution equity of the network, irrespectively of the local impact of the valves on the supply level of the single nodes. Conversely, the second scheme aims to maximize the global equity of the network by optimizing both location and setting (opening degree) of control valves, to include the impact of the new flow circulation on the supply level of each node. The two optimization schemes were applied to a case study network subject to water shortage conditions. The software EPA Storm Water Management Model (SWMM) was used for the simulations in the wake of previous successful applications for the analysis of intermittent water distribution systems. Results of the application of the SA algorithms were also compared with those from the literature and obtained by the use of the multi-objective Non-Dominated Sorted Genetic Algorithm II (NSGA II). The results show the high performance of SA algorithms in identifying optimal position and settings of the valves in the WDS. The comparison pointed out that SA algorithms are able to perform similarly to NSGA II and, at the same time, to reduce significantly the computational effort associated to the optimization process.

Highlights

  • Intermittency in water supply is increasingly adopted both in developing and developed countries around the world (McIntosh and Yñiguez 1997; Hardory et al 2001; Vairavamoorthy et al 2007; Andey and Kelkar 2009; Mohapatra et al 2014; Agathoklis and Christodoulou 2016; Galaitsi et al 2016; Simukonda et al 2018).Extended author information available on the last page of the articleIntermittent Water Distribution Systems (WDSs) are never a design choice

  • The paper presents the results of a novel methodology aimed at increasing the water distribution equity among users of intermittent water distribution systems characterized by water shortage conditions

  • The methodology is based on the use of algorithms of sequential addition (SA) for the optimal location and setting of control valves in the network with the aim of modify the circulation of flows and improve the water distribution among the network users

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Summary

Introduction

Intermittency in water supply is increasingly adopted both in developing and developed countries around the world (McIntosh and Yñiguez 1997; Hardory et al 2001; Vairavamoorthy et al 2007; Andey and Kelkar 2009; Mohapatra et al 2014; Agathoklis and Christodoulou 2016; Galaitsi et al 2016; Simukonda et al 2018). They can supply water for the whole 24 h but making only a fraction of the water daily demand available In both cases, the WDS behaves as an intermittent system, with cyclical phases of network filling/emptying and users that may have access to water in a discontinuous way (Ameyaw et al 2013; Gullotta et al 2021). Several authors (e.g. Arregui et al 2006; Cobacho et al 2008; Criminisi et al 2009) have shown that the water supply performance of intermittent WDSs may be worsened by the presence of private tanks at the household level (i.e. roof or basement tanks) Such tanks are progressively installed by the end users with the objective to store water volumes as back-up source for non-supply hours. All the simulations presented in this work were run up to the achievement of the condition of regime, that was considered to be achieved when the daily values of SR and UC do not change anymore during the simulation

SA Algorithms
SA of Gate Valves
SA of Control Valves
Simulation of the No‐Valve Scenario
Application of the SA Algorithms
Comparison with NSGA II
Conclusions
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