Model-based optimization of a sequencing batch reactor for biological nitrogen removal.

Area of Science:

• Environmental Engineering
• Chemical Engineering
• Wastewater Treatment Technologies

Background:

• Sequencing Batch Reactors (SBRs) are versatile for wastewater treatment.
• Optimizing SBR operation is crucial for efficient pollutant removal and reduced cycle times.
• Denitrification in SBRs often requires an external carbon source, which this study aimed to avoid.

Purpose of the Study:

• To determine an optimal operating mode for an SBR using model-based optimization.
• To minimize the batch cycle time for treating synthetic wastewater containing organic matter and nitrogen.
• To achieve denitrification without the addition of an external carbon source.

Main Methods:

• Development of a simplified process model with six ordinary differential equations and an oxygen consumption rate correlation.
• Utilizing batch cycle time as the objective function for minimization.
• Employing a successive quadratic programming algorithm with constraints on final pollutant concentrations (COD, nitrate, ammonium) and feed pump flow rate.

Main Results:

• Optimization indicated a one-step feed strategy as the most effective.
• The optimal strategy resulted in a minimized batch cycle time of 5 hours.
• Effective removal of organic matter and nitrogen was achieved without external carbon addition.

Conclusions:

• A single feed step strategy is optimal for SBR operation under the studied conditions.
• Model-based optimization can effectively determine efficient SBR operating modes.
• The developed approach facilitates efficient wastewater treatment, specifically denitrification, with reduced cycle times.