Optimal design activated sludge process by means of multi-objective optimization: case study in Benchmark Simulation Model 1 (BSM1)

Optimal design of activated sludge process (ASP) using multi-objective optimization was studied, and a benchmark process in Benchmark Simulation Model 1 (BSM1) was taken as a target process. The objectives of the study were to achieve four indexes of percentage of effluent violation (PEV), overall cost index (OCI), total volume and total suspended solids, making up four cases for comparative analysis. Models were solved by the non-dominated sorting genetic algorithm in MATLAB. Results show that: ineffective solutions can be rejected by adding constraints, and newly added objectives can affect the relationship between the existing objectives; taking Pareto solutions as process parameters, the performance indexes of PEV and OCI can be improved more than with the default process parameters of BSM1, especially for N removal and resistance against dynamic NH₄⁺-N in influent. The results indicate that multi-objective optimization is a useful method for optimal design ASP.