Real-time model predictive and rule-based control with green infrastructures to reduce combined sewer overflows

Area of Science:

• Environmental Engineering
• Urban Water Management
• Wastewater Systems

Background:

• Combined sewer systems (CSS) are susceptible to overflows (CSOs) during rainfall events, leading to environmental pollution.
• Green infrastructures (GIs) are increasingly implemented to mitigate CSOs, but their effectiveness depends on control strategies.
• Real-time control (RTC) offers dynamic management of sewer systems and GIs.

Purpose of the Study:

• To assess the impact of large-scale GI integration with different control strategies on combined sewer overflows (CSOs).
• To compare the performance of static control, rule-based control (RBC), and model predictive control (MPC) for GIs in managing CSOs.
• To evaluate GI efficiency in runoff capture and CSO volume reduction under various distribution and implementation scenarios.

Main Methods:

• Development of an iterative process using synthetic rainfall and MPC for cost-efficient GI distribution.
• Simulation of sewer system performance with GIs integrated with static, RBC, and MPC strategies over a two-month period.
• Comparative analysis of CSO volume and frequency reduction, environmental priority fulfillment, and runoff capture transferability.

Main Results:

• Static control, RBC, and MPC achieved average CSO volume reductions of 65%, 82%, and 92%, respectively, compared to no GIs.
• The MPC strategy, integrating GIs, was the only approach to nearly eliminate CSO events and meet environmental priorities.
• MPC demonstrated the highest GI efficiency in transferring runoff capture to CSO volume reduction across different scenarios.

Conclusions:

• Model predictive control (MPC) is highly effective for managing green infrastructures (GIs) to significantly reduce combined sewer overflows (CSOs).
• Integrating GIs with MPC optimizes performance, ensuring CSO mitigation and achievement of environmental objectives.
• The spatial distribution and implementation level of GIs further enhance the benefits when managed by advanced RTC strategies like MPC.