Real‐Time Optimal Operation of Water Systems Under Demand Uncertainty and Maximum Water Age Constraints

Abstract The inherent uncertainty in water demand poses significant challenges to water distribution systems' (WDSs) efficiency and quality. This study introduces a model predictive control framework tailored for real‐time optimal operation of WDSs under uncertain demand and maximum water age constraints to ensure water quality requirements. The methodology presented utilizes a scenario‐based energy‐cost optimization approach to account for demand uncertainties. As water age is unmeasurable, a model linearly related to some measured/observed network variables (e.g., flows, water levels, etc.) is proposed to infer water age values. Then, a scenario‐based mixed‐integer linear programming problem is formulated and solved repeatedly online to adjust operational strategies for minimizing energy operation costs while satisfying water age constraints. The outcome of this model is a feasible operation scheme for all demand scenarios, providing a cost‐effective decision that meets water age limits. The proposed model is tested on a real‐world‐based test case and validated through a series of sensitivity analyses.