An efficient approach based on bi-sensitivity analysis and genetic algorithm for calibration of activated sludge models

摘要

An efficient approach employing bi-sensitivity analysis and genetic algorithm was proposed for calibration of activated sludge models. The approach mainly contained twice sensitivity analyses and twice caiibrations through minimizing cost function by genetic algorithm, and which was evaluated on Step A~2/O activated sludge process with Commutative Multi-influent (SA~2/OCM) at low temperature, where effluent COD, TN, TP and NH4-N were used. The model was calibrated at HRT 16 h under steady state, while model validation was carried out under HRT 20 h and HRT 24 h using dynamic data, Results showed that, model with default ASM2d parameters had poor predictions of TN and NH4~+-N at low temperature.