An improved hybrid community detection algorithm for partitioning of water distribution networks

District metered areas (DMAs) are widely used by water utilities to manage water distribution networks (WDNs). This study presents a novel methodology that couples the improved hybrid community detection algorithm and combinatorial optimization process for partitioning WDNs into DMAs. In the node clustering phase, the hybrid algorithm based on the improved modularity index enables the fast formation of sufficient partition solutions with a more balanced water demand distribution and reduced diameters of boundary pipes. Then, in the partition dividing phase, a three-step optimization method, comprising preliminary hydraulic analysis, search for a suboptimal solution and multi-objective optimization, is presented to find a fast and optimal solution for the location of flow meters and isolation valves in WDNs. The overall methodology is applied to a large-scale WDN, proving its applicability and superiority in generating engineering partition configurations.

Automated summary

This study presents a novel methodology that combines an improved hybrid community detection algorithm and combinatorial optimization process for partitioning water distribution networks into district metered areas (DMAs). The methodology utilizes different optimization techniques in the node clustering and partition dividing phases, resulting in more balanced water demand distribution and faster optimal solutions.