Journal of Hydroinformatics (May 2022)

Topological and hydraulic metrics-based search space reduction for optimal re-sizing of water distribution networks

  • Kegong Diao,
  • Luigi Berardi,
  • Daniele B. Laucelli,
  • Bogumil Ulanicki,
  • Orazio Giustolisi

DOI
https://doi.org/10.2166/hydro.2022.158
Journal volume & issue
Vol. 24, no. 3
pp. 610 – 621

Abstract

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Pipe re-sizing of water distribution networks (WDNs) aims at improving the service performance to the required level, while minimizing the cost of replacing pipes in the network. The main challenge comes from the identification of the most effective pipes to re-size from a large number of interacting components. Performing a global search over all pipes in large WDNs does not guarantee a feasible and efficient solution due to the enormous search space, even by employing advanced algorithms, e.g., evolutionary algorithms. This paper proposes a novel method to reduce the search space for optimal re-sizing based on topological metrics from Complex Network Theory and hydraulic metrics, while providing suboptimal solutions comparable to the full search solutions, i.e., considering all pipes as candidates. The topological metrics are based on the edge-betweenness tailored for WDN analysis. Hydraulic metrics are unit head loss and flow rates of pipes computed based on simulation of the WDN in the current configuration. The optimal re-sizing plans obtained, particularly those using edge betweenness, were tested on a real WDN. The results are comparable with the full search solutions but they are much more efficient to obtain and require replacing mostly contiguous pipes, i.e., easier for practical fieldwork. HIGHLIGHTS Developed a novel method for search space reduction for optimal re-sizing of water distribution networks.; The method selects a subset of pipes for re-sizing based on topological and hydraulic metrics.; Using indirect topological metrics produces better optimization solutions than using direct metrics.; The solution based on indirect edge betweenness selection is comparable with the solution from full search.;

Keywords