Previous studies on booster disinfection optimization were commonly based on ‘blank networks’, neglecting the impact of existing disinfection facilities, which could result in misleading solutions. To overcome this limitation, a method, which incorporates the existing disinfection facilities, is developed and demonstrated in this study. A particle backtracking algorithm, which traces the upstream pathways of the disinfection insufficiency nodes, is employed to narrow down the potential positions for booster stations. Deterministic optimization results are then efficiently yielded by the introduction of a ‘coverage matrix’. The proposed method is applied to a real life water distribution system in Beijing, China. Results show the methodology effectiveness in optimizing booster disinfection placement and operation for real life water distribution systems. For the explored case study, results suggest that adding a booster disinfection station at 0.1% of the nodes of the system can satisfy chlorine residual at about 97.5% of all nodes.
A deterministic approach for optimization of booster disinfection placement and operation for a water distribution system in Beijing
Fanlin Meng, Shuming Liu, Avi Ostfeld, Chao Chen, Alejandra Burchard-Levine; A deterministic approach for optimization of booster disinfection placement and operation for a water distribution system in Beijing. Journal of Hydroinformatics 1 July 2013; 15 (3): 1042–1058. doi: https://doi.org/10.2166/hydro.2013.149
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