Optimal Chlorine Dosage Scheduling in Drinking Water Distribution Systems Considering Fairness Objectives

Abstract Submission: Regulating water quality in drinking water distribution networks (DWDNs) is a challenging task that requires careful consideration of both technical and ethical dimensions. Traditional approaches to optimal disinfectant dosing typically focus on minimizing average deviations in residual chlorine levels from prescribed limits at specific locations. As a result, this can lead to an uneven distribution of good-quality water in other locations. For instance, certain urban areas, e.g., at the network's extremities, may be receiving lower-quality water. This article introduces a novel approach to optimizing chlorine dosage scheduling within DWDNs to ensure safe and equitable access to drinking water at all consumer nodes. The study employs the Water Quality Index (WQI), which considers residual chlorine concentrations to evaluate fairness in water quality distribution. This method aligns with social welfare principles and Rawls's theory of social justice, promoting a more fair distribution of water quality across the network. To address the complexities of this challenge, the article proposes an optimization framework that integrates fairness alongside efficiency objectives. The framework uses the impulse response method, a linear superposition approximate surrogate model, to estimate residual chlorine levels, allowing for more accurate dosage scheduling. Linear programming techniques are employed to determine the optimal chlorine dosage schedules, while balancing the dual goals of efficiency and fairness. Impulse response matrices are calculated using the EPyT toolkit, an EPANET-python interface, with the optimization process conducted through the Gurobi python package. The proposed approach provides a fresh perspective on water quality regulation within DWDNs, emphasizing the importance of equitable distribution and advancing the management of fair and safe drinking water systems.

Learning Objectives/Expected Outcome (Optional) : 1. Understand different fairness objectives and their relationship to water quality in DWDNs.
2. Explore the integration of fairness and efficiency in an optimization framework for water quality management in DWDNs.