Water distribution network analysis under fuzzy demands

Spiliotis, Mike; Tsakiris, George

doi:10.1080/10286608.2012.663359

Cited by 38 publications

(15 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…More recently Atkinson et al (2014) maximized flow entropy and resilience index at once in an attempt to generate hybrid solutions with properties derived from the two measures. The above-mentioned extensions and other aspects such as the uncertainties associated with the nodal demands (Spiliotis and Tsakiris 2012) were not considered in this article. Kurec and Ostfeld (2013) addressed tank sizing for a network in the literature.…”

Section: Introductionmentioning

confidence: 99%

Penalty-Free Multi-Objective Evolutionary Approach to Optimization of Anytown Water Distribution Network

Siew

Tanyimboh

Seyoum

2016

Water Resour Manage

View full text Add to dashboard Cite

This paper describes the development and application of a new multiobjective evolutionary optimization approach for the design and upgrading of water distribution systems with multiple pumps and service reservoirs. The optimization model employs a pressure-driven analysis simulator that accounts for the minimum node pressure constraints and conservation of mass and energy. Pump scheduling, tank siting and tank design are integrated seamlessly in the optimization without introducing additional heuristic procedures. The computational solution of the optimization problem is entirely penalty-free, thanks to pressure-driven analysis and the inclusion of explicit criteria for tank depletion and replenishment. The model was applied to the Anytown network that is a benchmark optimization problem. Many new solutions were achieved that are cheaper and offer superior performance compared to previous solutions in the literature. Detailed and extensive simulations of the solutions achieved were carried out. Spatial and temporal variations in water quality were investigated by simulating the chlorine residual and disinfection by-products in addition to water age. The hydraulic requirements were satisfied; efficiency of pumps was consistently high; effective operation of the new and existing tanks was achieved; water quality was improved; and overall computational efficiency was high. The formulation is entirely generic.Keywords Demand-driven analysis . Pressure-driven analysis . Penalty-free constrained multiobjective evolutionary optimization . Water distribution system . Optimal pump scheduling . Service reservoir design and operation Water Resour Manage (2016) 30:3671-3688

show abstract

Section: Introductionmentioning

confidence: 99%

Penalty-Free Multi-Objective Evolutionary Approach to Optimization of Anytown Water Distribution Network

Siew

Tanyimboh

Seyoum

2016

Water Resour Manage

View full text Add to dashboard Cite

show abstract

“…It should be noted that the design optimization approach proposed here follows the convention that demands are known with reasonable certainty. Procedures that address uncertainties in the demands and other relevant parameters (Kumar et al 2010, Spiliotis andTsakiris 2012b) are not considered here.…”

mentioning

confidence: 99%

Penalty-Free Feasibility Boundary Convergent Multi-Objective Evolutionary Algorithm for the Optimization of Water Distribution Systems

Siew

Tanyimboh

2012

Water Resour Manage

View full text Add to dashboard Cite

This version is available at https://strathprints.strath.ac.uk/43222/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. AbstractThis paper presents a new penalty-free multi-objective evolutionary approach (PFMOEA) for the optimization of water distribution systems (WDSs). The proposed approach utilizes pressure dependent analysis (PDA) to develop a multi-objective evolutionary search. PDA is able to simulate both normal and pressure deficient networks and provides the means to accurately and rapidly identify the feasible region of the solution space, effectively locating global or near global optimal solutions along its active constraint boundary. The significant advantage of this method over previous methods is that it eliminates the need for ad-hoc penalty functions, additional "boundary search" parameters, or special constraint handling procedures. Conceptually, the approach is downright straightforward and probably the simplest hitherto. The PFMOEA has been applied to several WDS benchmarks and its performance examined. It is demonstrated that the approach is highly robust and efficient in locating optimal solutions. Superior results in terms of the initial network construction cost and number of hydraulic simulations required were obtained. The improvements are demonstrated through comparisons with previously published solutions from the literature.

show abstract

“…The normal and the minimum and maximum demand values for each node together with the ground elevation of each node are presented in Table 1. The range of the water demand, which is represented by the width of the fuzzy number, is assumed to be 30% of the corresponding central value (Spiliotis and Tsakiris, 2012). The pipes are labelled from 1 to 15 and their diameter and length are given in Table 2.…”

Section: Fig 2 a Looped Water Distribution Network For Illustrativementioning

confidence: 99%

“…Several methodologies have been suggested in the recent past to show how parameter uncertainty is propagated to dependent parameters by considering uncertain parameters as fuzzy (Revelli and Ridolfi 2002, Branisavljevic and Ivetic 2006, Shibu and Reddy 2011, Spiliotis and Tsakiris 2012. All these methods assume that uncertain demands are satisfied at all demand nodes which may not be true.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Analysis of Pressure-Deficient Water Distribution Networks

Gupta

Harkutiya

Dongre

et al. 2014

World Environmental and Water Resources Congress 2014

View full text Add to dashboard Cite

Future water demands and pipe roughness coefficients used in the design of water distribution networks (WDNs) have a high degree of uncertainty. Fuzzy analysis of WDNs provide how the uncertainties in independent or basic parameters (such as nodal demands and pipe roughness coefficients) are propagated to dependent or derived parameters (such as pipe flows, pipe velocities and available pressure heads). Usually demand dependent analysis is used for such analysis. A WDN may be pressure-deficient or may become pressure-deficient because of high pipe roughness or inadequate pump pressure and may not be able to meet desired demands at all nodes. Thus, it is desirable to consider the nodal outflows as unknown and as a function of available pressure heads under pressure-deficient conditions. An approach for fuzzy analysis of a WDN which takes into account pressure-deficient condition using node flow analysis is presented in this paper. The proposed methodology is illustrated with example network taken from literature. The methodology is useful in identifying vulnerable zones in WDNs and can be extended for reliability analysis under uncertainty of nodal demands and pipe roughness coefficients. Comparison of results with usual demand-dependent analysis shows that proposed method is better in identifying vulnerable zones.

show abstract

Water distribution network analysis under fuzzy demands

Cited by 38 publications

References 20 publications

Penalty-Free Multi-Objective Evolutionary Approach to Optimization of Anytown Water Distribution Network

Penalty-Free Multi-Objective Evolutionary Approach to Optimization of Anytown Water Distribution Network

Penalty-Free Feasibility Boundary Convergent Multi-Objective Evolutionary Algorithm for the Optimization of Water Distribution Systems

Fuzzy Analysis of Pressure-Deficient Water Distribution Networks

Contact Info

Product

Resources

About