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Received November 11, 2013
Accepted February 12, 2014
- This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Mathematical modeling and modification of an activated sludge benchmark process evaluated by multiple performance criteria
1School of Resources and Environment Engineering, East China University of Science and Technology, Meilong Road, Shanghai 200237, China 2School of Energy and Environment, Southeast University, ERC Taihu Lake Water Environment (Wuxi),, Sipailou Road, Nanjing 210096, China, Linghu Avenue, Wuxi 214135, China 3School of Energy and Environment, Southeast University, Sipailou Road, Nanjing 210096, China 4ERC Taihu Lake Water Environment (Wuxi), Linghu Avenue, Wuxi 214135, China
Korean Journal of Chemical Engineering, August 2014, 31(8), 1330-1338(9), 10.1007/s11814-014-0056-9
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Abstract
Optimal modification of an activated sludge process (ASP) evaluated by multiple performance criteria was studied. A benchmark process in BSM1 was taken as a target process. Four indexes of percentage of effluent violation (PEV), energy consumption (OCI), total volume of tanks (TV) and total suspended solid in tank5 (TSSa5), were criteria and eleven process parameters were decision variables, making up the multiple criteria optimization model, which was solved by non-dominated sorting genetic algorithm II (NSGA-II) in MATLAB. Pareto solutions were obtained;_x000D_
one solution (opt1) was selected based on the authors’ decision for a further analysis. Results show that the process with opt1 strategy exhibits much better performance of PEV and OCI than with the default, being improved by 74.17% and 9.97% specifically under dry influent and without control. These results indicated that the multiple criterion optimization method is very useful for modification of an ASP.
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References
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Jeppsson U, Pons M, Control Eng. Practice, 12, 299 (2004)
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Beraud B, Steyer J, Lemoine C, Latrille E, Comput. Aided Chem. Eng., 25, 539 (2008)
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Guerrero J, Guisasola A, Comas J, Rodriguez-Roda I, Baeza JA, Chem. Eng. J., 188, 23 (2012)
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Benedetti L, De Baets B, Nopens I, Vanrolleghem PA, Environ. Modell. Softw., 25, 616 (2010)
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Fonseca CM, Fleming PJ, Evolutionary Computation, 3, 1 (1995)
Deb K, Pratap A, Agarwal S, Meyarivan T, Evolutionary Computation, IEEE Transactions on, 6, 182 (2002)
Henze M, Grady CPL, Gujer W, Marais GVR, Matsuo T, Activated sludge model no. 1. Technical Report 1, International Water Assn, London (1987).
Takacs I, Patry GG, Nolasco D, Water Res., 25, 1263 (1991)