Modeling and performance improvement of an anaerobic–anoxic/nitrifying-induced crystallization process via the multi-objective optimization method

Abstract

The trade-off between energy savings and emission reductions of an activated sludge process is a multi-objective problem relating to several potentially conflicting objectives. Therefore, the optimal modification of an anaerobic–anoxic/nitrifying/induced crystallization (A2N-IC) process by multi-objective optimization method was studied in this work. The multi-objective optimization model comprised three evaluative indices, (effluent quality (EQ), operation cost (OC), and total volume (TV) of structures), and 14 process parameters (decision variables) solving by non-dominated sorting genetic algorithm II (NSGA-II) in MATLAB. The trade-off relationships among EQ, OC, and TV were investigated under 30 days of dynamic influent with different constraint conditions. A series of Pareto solutions were obtained, and one Pareto solution was selected for further analysis. Results showed improved effluent concentrations of chemical oxygen demand (COD), total nitrogen (TN), ammonia-nitrogen (NH₄⁺-N), and total phosphorous (TP) under the optimized strategy compared to the original strategy, where the average effluent concentrations decreased by 2.22, 0.47, 0.13, and 0.02 mg/L, respectively. The values of EQ and OC decreased from 0.015 kg/day and 0.15 ¥/m³ to 0.0023 kg/day and 0.12 ¥/m³, respectively, while the TV increased from 0.31 to 0.33 m³. These results indicated that the multi-objective optimization method is useful for modifying activated sludge processes.

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