335835 Optimal Aeration Strategy for Sequencing Batch Reactors With Bypass Nitrification

Thursday, November 7, 2013: 10:24 AM
Continental 8 (Hilton)
Mariano Nicolas Cruz Bournazou1, Juan Delgado San Martin2, Tilman Barz3, Guenter Wozny3 and Harvey Arellano-Garcia4, (1)Technische Universitaet Berlin, (2)AstraZeneca UK Limited, (3)Chair of Process Dynamics and Operation, Berlin Institute of Technology, Berlin, Germany, (4)Environmental Sciences and Process Engineering, Brandenburg University of Technology Cottbus, Cottbus, Germany

In this work, an approach is proposed for the implementation of an optimal aeration control strategy for Waste Water Treatment in a SBR (Sequencing Batch Reactor) for dual nitrification-denitrification [1]. The optimal numbers of aeration-anoxic intervals as well as the duration of each interval are to be determined. Thus, two different objectives are considered: operating time and the energy required by aeration. Moreover, output concentrations of ready biodegradable substrate, ammonia, and nitrogen oxides have to comply with environmental regulations, which constraint the feasible region. Consequently, a highly nonlinear problem with very tight constraints is obtained. The proposed solution strategy is based on [2] addressing: optimal time control, hard constraints, computational load, and single shooting. Moreover, different rounding strategies are tested showing that penalty homotopy can be applied for those strictly constrained problems. The efficiency of SBR processes can drastically be increased as well as the flexibility of the process so as to deal with constantly changing load quality. Finally, the results are discussed proposing new control concepts for SBR processes and showing its advantages over conventional two phase nitrification-denitrification. 

[1] Cruz Bournazou, M.N., Arellano-Garcia, H., Wozny, G., Lyberatos, G., Kravaris, C., ASM3 extended for two-step nitrification-denitrification: a model reduction for sequencing batch reactors. Journal of Chemical Technology and Biotechnology. Vol. 87, Issue 7, pp. 887–896, 2012

[2] Sager, S., Numerical methods for mixed{integer optimal control problems, Der Andere Verlag, Tonning, Lubeck, Marburg, ISBN 3-89959-416-9


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