Probabilistic modeling and optimization of leakages in water distribution networks

We develop an integrated framework for resilient reduction of leakages in water distribution networks (WDNs), which combines: a) a set of probabilistic approaches for minimum night flow (MNF) estimation and parametric modeling of water losses in WDNs, and b) a combination of statistical clustering a...

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Κύριος συγγραφέας: Σεραφείμ, Αθανάσιος
Άλλοι συγγραφείς: Serafeim, Athanasios V.
Γλώσσα:English
Έκδοση: 2022
Θέματα:
Διαθέσιμο Online:https://hdl.handle.net/10889/24051
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spelling nemertes-10889-240512022-11-19T04:42:46Z Probabilistic modeling and optimization of leakages in water distribution networks Πιθανοτική μοντελοποίηση και βελτιστοποίηση διαρροών σε δίκτυα διανομής νερού Σεραφείμ, Αθανάσιος Serafeim, Athanasios V. Water distribution networks Minimum night flow Confidence interval estimation Water losses Water balance Leakage Parametric modeling Pressure effect Statistical clustering Water networks partitioning Leakage management Hydraulic resilience Pressure management areas Δίκτυα ύδρευσης Απώλειες νερού Ζωνοποίηση δικτύων ύδρευσης Ζώνες διαχείρισης πίεσης Παραμετρική μοντελοποίηση Ελάχιστη νυχτερινή ροή Εκτίμηση διαστημάτων εμπιστοσύνης Υδατικό ισοζύγιο Διαρροές We develop an integrated framework for resilient reduction of leakages in water distribution networks (WDNs), which combines: a) a set of probabilistic approaches for minimum night flow (MNF) estimation and parametric modeling of water losses in WDNs, and b) a combination of statistical clustering and hydraulic modeling techniques for WDN partitioning into pressure management areas (PMAs; or districted metered areas, DMAs). The strong point of the proposed probabilistic methods is that they allow for confidence interval estimation of both observed and parametrized MNFs, while taking into account the effect of operational pressures on leakages. The statistically rigorous and user unbiased clustering approach produces realistic PMA (or DMA) configurations, allowing water experts and engineers to develop effective strategies for management and reduction of leakages, based on a fast and easy to implement algorithmic procedure. The efficiency of the developed framework is tested in the water distribution network of the City of Patras in western Greece, which serves approximately 213 000 consumers, consists of more than 700 km of pipeline grid (mainly HDPE and PVC pipes), and includes 86 pressure management areas (PMAs) equipped with automated local stations for water flow rates monitoring and pressure regulation. The research project was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “1st Call for H.F.R.I. Research Projects to support Faculty Members & Researchers and the procurement of high-cost research equipment grant” (Project Number: 1162). We develop an integrated framework for resilient reduction of leakages in water distribution networks (WDNs), which combines: a) a set of probabilistic approaches for minimum night flow (MNF) estimation and parametric modeling of water losses in WDNs, and b) a combination of statistical clustering and hydraulic modeling techniques for WDN partitioning into pressure management areas (PMAs; or districted metered areas, DMAs). The strong point of the proposed probabilistic methods is that they allow for confidence interval estimation of both observed and parametrized MNFs, while taking into account the effect of operational pressures on leakages. The statistically rigorous and user unbiased clustering approach produces realistic PMA (or DMA) configurations, allowing water experts and engineers to develop effective strategies for management and reduction of leakages, based on a fast and easy to implement algorithmic procedure. The efficiency of the developed framework is tested in the water distribution network of the City of Patras in western Greece, which serves approximately 213 000 consumers, consists of more than 700 km of pipeline grid (mainly HDPE and PVC pipes), and includes 86 pressure management areas (PMAs) equipped with automated local stations for water flow rates monitoring and pressure regulation. 2022-11-18T08:48:43Z 2022-11-18T08:48:43Z 2022-11-04 https://hdl.handle.net/10889/24051 en Attribution-NonCommercial-NoDerivs 3.0 United States http://creativecommons.org/licenses/by-nc-nd/3.0/us/ application/pdf
institution UPatras
collection Nemertes
language English
topic Water distribution networks
Minimum night flow
Confidence interval estimation
Water losses
Water balance
Leakage
Parametric modeling
Pressure effect
Statistical clustering
Water networks partitioning
Leakage management
Hydraulic resilience
Pressure management areas
Δίκτυα ύδρευσης
Απώλειες νερού
Ζωνοποίηση δικτύων ύδρευσης
Ζώνες διαχείρισης πίεσης
Παραμετρική μοντελοποίηση
Ελάχιστη νυχτερινή ροή
Εκτίμηση διαστημάτων εμπιστοσύνης
Υδατικό ισοζύγιο
Διαρροές
spellingShingle Water distribution networks
Minimum night flow
Confidence interval estimation
Water losses
Water balance
Leakage
Parametric modeling
Pressure effect
Statistical clustering
Water networks partitioning
Leakage management
Hydraulic resilience
Pressure management areas
Δίκτυα ύδρευσης
Απώλειες νερού
Ζωνοποίηση δικτύων ύδρευσης
Ζώνες διαχείρισης πίεσης
Παραμετρική μοντελοποίηση
Ελάχιστη νυχτερινή ροή
Εκτίμηση διαστημάτων εμπιστοσύνης
Υδατικό ισοζύγιο
Διαρροές
Σεραφείμ, Αθανάσιος
Probabilistic modeling and optimization of leakages in water distribution networks
description We develop an integrated framework for resilient reduction of leakages in water distribution networks (WDNs), which combines: a) a set of probabilistic approaches for minimum night flow (MNF) estimation and parametric modeling of water losses in WDNs, and b) a combination of statistical clustering and hydraulic modeling techniques for WDN partitioning into pressure management areas (PMAs; or districted metered areas, DMAs). The strong point of the proposed probabilistic methods is that they allow for confidence interval estimation of both observed and parametrized MNFs, while taking into account the effect of operational pressures on leakages. The statistically rigorous and user unbiased clustering approach produces realistic PMA (or DMA) configurations, allowing water experts and engineers to develop effective strategies for management and reduction of leakages, based on a fast and easy to implement algorithmic procedure. The efficiency of the developed framework is tested in the water distribution network of the City of Patras in western Greece, which serves approximately 213 000 consumers, consists of more than 700 km of pipeline grid (mainly HDPE and PVC pipes), and includes 86 pressure management areas (PMAs) equipped with automated local stations for water flow rates monitoring and pressure regulation.
author2 Serafeim, Athanasios V.
author_facet Serafeim, Athanasios V.
Σεραφείμ, Αθανάσιος
author Σεραφείμ, Αθανάσιος
author_sort Σεραφείμ, Αθανάσιος
title Probabilistic modeling and optimization of leakages in water distribution networks
title_short Probabilistic modeling and optimization of leakages in water distribution networks
title_full Probabilistic modeling and optimization of leakages in water distribution networks
title_fullStr Probabilistic modeling and optimization of leakages in water distribution networks
title_full_unstemmed Probabilistic modeling and optimization of leakages in water distribution networks
title_sort probabilistic modeling and optimization of leakages in water distribution networks
publishDate 2022
url https://hdl.handle.net/10889/24051
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