Inexact left-hand side two-stage chance-constrained programming for booster optimization in water distribution system

Area of Science:

• Environmental Engineering
• Water Quality Management
• Operations Research

Background:

• Chlorine is essential for disinfecting water distribution systems (WDS) but can form harmful byproducts.
• Maintaining chlorine concentration within acceptable limits is vital for public health.
• Uncertainty in chlorine decay and concentration limits poses challenges for effective management.

Purpose of the Study:

• To develop a robust method for determining optimal chlorine injection mass in WDS.
• To address uncertainties in chlorine decay processes and concentration limits.
• To provide a framework for managing chlorine levels under variable conditions.

Main Methods:

• An inexact left-hand-side chance-constrained programming (ILCCP) model was formulated.
• Response coefficients were treated as random variables with normal distributions, linked with EPANET simulations.
• A two-step algorithm was employed to solve the ILCCP model and determine injection mass intervals.

Main Results:

• The ILCCP model successfully determined optimal injection mass intervals for two WDS.
• Analysis showed that higher probability levels for lower chlorine limits increased optimal injection mass.
• Conversely, higher probability levels for upper chlorine limits decreased optimal injection mass.

Conclusions:

• The proposed ILCCP model effectively manages chlorine injection under uncertain conditions.
• Findings assist water managers in optimizing disinfectant dosage for public health protection.
• The methodology is adaptable for application in more complex water distribution networks.