Modelling real-time control of WWTP influent flow under data scarcity.

Area of Science:

• Environmental Engineering
• Water Resource Management
• Wastewater Treatment

Background:

• Hydraulic overloading of wastewater treatment plants (WWTPs) can lead to activated sludge washout, violating effluent standards.
• Systematic overloading often results from sewer network expansions without corresponding WWTP capacity increases.
• Minimizing sewer overflow volume is crucial for environmental compliance.

Purpose of the Study:

• To demonstrate the effectiveness of rule-based real-time control (RTC) in reducing WWTP load and sewer overflow volume.
• To assess the value of RTC with limited monitoring data and catchment information.
• To investigate the influence of model and control algorithm parameters through sensitivity analysis.

Main Methods:

• Implementation of rule-based real-time control (RTC) for managing WWTP influent.
• Development of a parsimonious simulation approach using relocated spatial boundaries and reverse modeling for data generation.
• Accurate modeling of pump hydraulics and control systems.
• Application of two global sensitivity analysis methods to assess parameter influence.

Main Results:

• RTC effectively reduces the load to the WWTP while minimizing overall sewer overflow volume.
• The study highlights the added value of RTC even with limited monitoring data.
• Sensitivity analysis confirmed the critical importance of accurate system property knowledge over minor monitoring errors.

Conclusions:

• Rule-based RTC is a viable strategy for managing hydraulic loads in WWTPs and mitigating sewer overflows.
• Parsimonious modeling and reverse engineering can overcome data limitations in control applications.
• Robust understanding of system hydraulics and control parameters is essential for effective wastewater management.