Dynamic optimisation of WWTP inflow to reduce total emission.

Area of Science:

• Environmental Engineering
• Water Resource Management
• Wastewater Treatment Technology

Background:

• Effective wastewater treatment plant (WWTP) operation relies on integrated control systems.
• Capacity-driven inflow control is essential for managing hydraulic, COD, and nutrient loads.
• Existing control strategies often depend on hypothetical models rather than real-world data.

Purpose of the Study:

• To analyze the behavior of three large WWTPs under increased storm water loads using several years of online measurements.
• To identify the main limiting factors affecting WWTP performance during high load conditions.
• To develop and test predictive control strategies for integrated sewer and WWTP management.

Main Methods:

• Analysis of several years of online measurement data from three large WWTPs.
• Identification of limiting factors in secondary clarifier sedimentation and nitrification processes.
• Development of predictive control strategies based on observed operational data and effluent control.

Main Results:

• Sedimentation in secondary clarifiers and nitrification capacity were the primary limitations for increased load handling in all analyzed WWTPs.
• Predictive control strategies, incorporating effluent control, were successfully developed for one case study.
• Integrated sewer and WWTP modeling demonstrated that inflow control effectiveness is highly dependent on rain intensity.

Conclusions:

• Real-world operational data is crucial for understanding WWTP behavior and developing effective control strategies.
• Limiting factors like sedimentation and nitrification must be addressed for robust integrated sewer and WWTP management.
• Inflow control strategies need to account for dynamic factors such as rainfall intensity for optimal performance.