Optimization of Chlorine Injection Schedule in Water Distribution Networks Using Water Age and Breadth-First Search Algorithm

Chlorine decay over time and distance travelled poses challenges in maintaining consistent chlorine levels from treatment plants to demand nodes in water distribution networks (WDNs). Many studies have focused on optimizing chlorine booster systems and addressing dosage and location. This study proposes a chlorine injection optimization model for maintaining spatial and temporal chlorine residuals within an acceptable range. First, the approach involves identifying potential pathways from the source to demand nodes using a breadth-first search (BFS) algorithm. Subsequently, the required chlorine injection to maintain a 0.2 mg/L residual chlorine level at demand nodes is estimated based on water age. Finally, a single-objective genetic algorithm optimizes the chlorine injection schedule at the source. The results demonstrated that chlorine estimation based on water age exhibited promising results with an average error below 10%. In addition, the four-interval injection scheme performed well in adapting to changing demand patterns, making the method robust to varying demand patterns. Moreover, the model could accommodate fluctuating water temperature conditions according to operating seasons. This study provides valuable insights into effectively managing chlorine levels and operations of WDNs, and paves the way for using water age for chlorine estimation.