Modelling and optimization of energy consumption in the activated sludge biological aeration unit

Abstract The biological aeration unit consumes the highest energy (67.3%) in wastewater treatment compared with physical (18.8%) and chemical (13.9%) processes. high consumption is caused by supply of oxygen using air pumps/blowers temperature that controls microorganisms' growth. purpose this study was to model optimize unit. multilayer perceptron (MLP) artificial neural network (ANN) algorithm used consumption. particle swarm optimization (PSO) model. Sensitivity analysis performed determine percentage contribution input variables towards MLP ANN modelled successfully produced R², RMSE, MSE 0.89, 0.0265, 0.00070, respectively, during testing phase. PSO optimized a global solution 0.993 kWh/m³. reduction between lowest measured 38.4%. Aeration period (81%) (10.7%) contributed In conclusion, played significant role airflow rate (4.2%). When conducive allowing growth microorganisms, removal COD ammonia will be rapid resulting low