Optimizing Booster Chlorination in Water Distribution Networks Under Incomplete Mixing Conditions

<p dir="ltr">Despite considerable progress in optimization strategies over the years to address the optimal booster chlorination problem, the majority of existing approaches rely on water quality models that assume perfect mixing at junctions, potentially leading to inaccurate predictions. This research aims to determine the optimal disinfection schedule by using robust optimization techniques while considering incomplete mixing phenomena at cross junctions and fluctuations in the bulk reaction rate coefficient. The proposed methodology was applied to a simplified real water distribution system, and the resulting dynamic disinfectant schedules were compared across complete and incomplete mixing models. However, the estimation of the optimal booster schedule was not significantly affected by the mixing assumption for the selected network.</p><p dir="ltr">This paper was presented at the 21st Computing and Control in the Water Industry Conference (CCWI 2025) at the University of Sheffield (1st - 3rd September 2025).</p>