Multiobjective Valve Management Optimization Formulations for Water Quality Enhancement in Water Distribution Networks

Journal Article (2019)
Author(s)

Claudia Quintiliani (Università di Pavia, University of Cassino and Southern Lazio, KWR Water Research Institute)

Oscar Marquez-Calvo (IHE Delft Institute for Water Education)

Leonardo Alfonso (IHE Delft Institute for Water Education)

Cristiana Di Cristo (Università degli Studi di Napoli Federico II)

Angelo Leopardi (University of Cassino and Southern Lazio)

Dimitri P. Solomatine (TU Delft - Civil Engineering & Geosciences, Russian Academy of Sciences, IHE Delft Institute for Water Education)

Giovanni De Marinis (University of Cassino and Southern Lazio)

Research Group
Water Resources
DOI related publication
https://doi.org/10.1061/(ASCE)WR.1943-5452.0001133 Final published version
More Info
expand_more
Publication Year
2019
Language
English
Research Group
Water Resources
Journal title
Journal of Water Resources Planning and Management
Issue number
12
Volume number
145
Article number
04019061
Downloads counter
251

Abstract

Water distribution networks (WDNs) need to guarantee that water is delivered with adequate quality. This paper compares the performance of 12 multiobjective procedures to limit water quality deterioration in a WDN through the optimal operation of valves. The first objective (ObF1) is to minimize the water age, chosen as a surrogate parameter of quality deterioration, and the second objective (ObF2) is to minimize the number of valve closures. The 12 procedures are derived from the combination of 4 different optimization algorithms and 3 formulations of ObF1, namely, to minimize the maximum, the arithmetic mean, and the demand-weighted mean water age. The optimization algorithms considered are random search (RS), Loop for Optimal Valve Status Configuration (LOC), and a combination of each of these two with the Archive-based Micro Genetic Algorithm. The procedures are tested on two networks of different complexity. Results show how LOC is able to find near-optimal solutions using a fraction of the computational time required by a brute force search. Furthermore, among the ObF1 formulations, the use of the averages (either arithmetic or demand-weighted) gives better results in terms of impact on the population served by a WDN.