Advanced predicting technique for optimal operation of wastewater treatment process: A ProActive scheduling approach

Abstract

Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives.