Water Network Partitioning (WNP) improves water network management, simplifying the computation of water budgets and, consequently, allowing the identification and reduction of water loss. It is achieved by inserting flow meters and gate valves in the network, previously clustered in subsystems. The clustering and partitioning phases are carried out with different procedures. The first one requires clustering algorithms that assign network nodes to each district (or cluster). The second one chooses the boundary pipes where flow meters or gate valves are to be inserted. In this paper, SWANP software is employed to achieve a network clustering through two different algorithms based on a multilevel-recursive bisection and community-structure procedures. After that, a novel multi-objective function is introduced and applied to a large Mexican network integrating both cost and energy performance, thus providing a smart Decision Support System (DSS) based on qualitative and quantitative measures, and diagrams for evaluating the optimal layout in terms of the number of districts, cost, and hydraulic performance.

Water Supply Network Partitioning Based on Simultaneous Cost and Energy Optimization

Armando Di Nardo
;
Michele Di Natale;Giovanni Francesco Santonastaso;
2016

Abstract

Water Network Partitioning (WNP) improves water network management, simplifying the computation of water budgets and, consequently, allowing the identification and reduction of water loss. It is achieved by inserting flow meters and gate valves in the network, previously clustered in subsystems. The clustering and partitioning phases are carried out with different procedures. The first one requires clustering algorithms that assign network nodes to each district (or cluster). The second one chooses the boundary pipes where flow meters or gate valves are to be inserted. In this paper, SWANP software is employed to achieve a network clustering through two different algorithms based on a multilevel-recursive bisection and community-structure procedures. After that, a novel multi-objective function is introduced and applied to a large Mexican network integrating both cost and energy performance, thus providing a smart Decision Support System (DSS) based on qualitative and quantitative measures, and diagrams for evaluating the optimal layout in terms of the number of districts, cost, and hydraulic performance.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/384050
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