Optimization of aeration profiles in the activated sludge process

Abstract We show that the aeration rate in the activated sludge process, which is responsible for the greatest energy burden (up to 50%) in wastewater treatment, can be reduced by more than 60%, while preserving an effluent quality of less than 0.10 mg/L of ammonia and more than 8.5 mg/L of dissolved oxygen. An in-depth survey of the performances of different aeration profiles is given through utilization of an activated sludge tank model that was calibrated and validated with data from a real plant. First, the total rate of aeration is manipulated while employing equal rates of local aeration across the activated sludge tank. Then, scenarios with a nonuniform distribution of local aeration rates are investigated. For this purpose, a mixed-integer nonlinear programming (MINLP) problem was devised to minimize computational burden, which was solved using a genetic algorithm. Also, a similar MINLP problem was set to obtain aeration profiles with segments of equally aerated zones in the tank, which can facilitate execution in real plants. Finally, all aeration profiles were challenged with a 2-day storm through dynamic simulations.