Robust Booster Disinfection Scheduling Using Incomplete Mixing Water Quality Model (EPANET-IMX)

In the realm of practical water distribution systems (WDS), uncertainties in hydraulic and water quality modeling affect the management of WDS making it a multifaceted challenge. Furthermore, the incorporation of water quality considerations into WDS design and management has become paramount, necessitating the use of precise water quality models. The conventional water quality models employed in drinking WDS have faced inaccuracy due to their underlying assumption of instantaneous and complete mixing at junctions. To address this limitation, recent models such as EPANET-IMX (Incomplete Mixing Extension), EPANET-BAM, and AZRED have emerged, incorporating empirical equations to model the nuances of incomplete mixing. These advancements offer improved accuracy for water quality analysis within WDS. However, the presence of uncertainty in disinfectant reaction rates also presents an obstacle to achieving optimal water quality management. Within such systems, determining the scheduling of booster disinfectant dosages is a challenge. In response, this study seeks to determine the optimal dosage schedule for booster disinfectants while accounting for fluctuations in bulk reaction rate coefficients and acknowledging incomplete mixing at junctions. To tackle this uncertain optimization problem, robust optimization principles are employed. The study applies these principles to a small-scale network as an illustrative example, showcasing robust optimal schedules. Two water quality models, namely EPANET and EPANET-IMX, are utilized for water quality simulations. The resulting optimal schedules are compared and analyzed across all three models. It was observed that considering the incomplete mixing varied the optimal booster dosage by about 10%. The findings emphasized the importance of considering incomplete mixing in both water quality analysis and optimization endeavors.