EVALUATION OF DIFFERENT CONTROL STRATEGIES OF THE WASTE WATER TREATMENT PLANT BASED ON A MODIFIED ACTIVATED SLUDGE MODEL NO. 3

The first part of this work presents the development and implementation in the Benchmark Simulation Model No 1 (BSM1) of a modified Activated Sludge Model No 3 (ASM3). The enhanced ASM3 presented in this study has three modifications compared to the original ASM3. The first modification is the representation of the simultaneous heterotrophic biomass growth on the primary substrate and on the internal storage products. Second, nitrification is modeled as a two-step process with nitrite as an intermediate product, bringing an increased degree of complexity to the mathematical model. Third, the denitrification process is modeled as a three step process with nitrite and nitric oxide as intermediates. The nitric oxide is introduced in the model to account for the inhibition of some enzymes that are responsible for the growth of the heterotrophic bacteria under aerobic conditions. For a better representation of the real plant behavior, the secondary settler is modeled to be reactive. The built reactive settler model is the combination of the settler model described by Takacs in 1991 and the enhanced ASM3. The second part of this research consists of the investigation of five control strategies applied to the waste water treatment plant (WWTP). The control architectures studied in this research are multi-input-multi-output (MIMO) Model Predictive Controllers (MPC). The assessment of these strategies is made from three points of view: control performance, cost evaluation and quality of the effluent. The simulation results show that operational costs can be reduced using automatic control.

[1]  Mircea Vasile Cristea,et al.  Cost reduction of the wastewater treatment plant operation by MPC based on modified ASM1 with two-step nitrification/denitrification model , 2011, Comput. Chem. Eng..

[2]  N. Carstensen.  Identification of wastewater processes , 1994 .

[3]  Sylvie Gillot,et al.  The COST Simulation Benchmark: Description and Simulator Manual , 2001 .

[4]  P A Vanrolleghem,et al.  Limitations of ASM1 and ASM3: a comparison based on batch oxygen uptake rate profiles from different full-scale wastewater treatment plants. , 2005, Water science and technology : a journal of the International Association on Water Pollution Research.

[5]  I. Takács.  A dynamic model of the clarification-thickening process , 1991 .

[6]  Wenhao Shen,et al.  Application of model predictive control to the BSM1 benchmark of wastewater treatment process , 2008, Comput. Chem. Eng..

[7]  G. A. Ekama,et al.  A GENERAL MODEL FOR THE ACTIVATED SLUDGE PROCESS , 1981 .

[8]  JayHyung Lee,et al.  Nonlinear model predictive control of the Tennessee Eastman challenge process , 1995 .

[9]  Gustaf Olsson,et al.  Integration of wastewater treatment plant design and operation - A systematic approach using cost functions , 1996 .

[10]  W. Gujer,et al.  Activated sludge model No. 3 , 1995 .

[11]  Stefano Marsili-Libelli,et al.  A modified Activated Sludge Model No. 3 ASM3) with two-step nitrification-denitrification , 2007, Environ. Model. Softw..

[12]  J. Richalet,et al.  Model predictive heuristic control: Applications to industrial processes , 1978, Autom..

[13]  Mogens Henze,et al.  Activated sludge models ASM1, ASM2, ASM2d and ASM3 , 2015 .

[14]  C. Grady,et al.  An Updated Process Model for Carbon Oxidation, Nitrification, and Denitrification , 2008, Water environment research : a research publication of the Water Environment Federation.

[15]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[16]  P Ratini,et al.  Implementation, study and calibration of a modified ASM2d for the simulation of SBR processes. , 2001, Water science and technology : a journal of the International Association on Water Pollution Research.

[17]  P. Vanrolleghem,et al.  Influence of microbial growth kinetics on steady state multiplicity and stability of a two‐step nitrification (SHARON) model , 2007, Biotechnology and bioengineering.

[18]  D Orhon,et al.  Modification of Activated Sludge Model no. 3 considering direct growth on primary substrate. , 2003, Water science and technology : a journal of the International Association on Water Pollution Research.

[19]  Han-Qing Yu,et al.  An approach for modeling two-step denitrification in activated sludge systems , 2008 .

[20]  Manfred Morari,et al.  Model predictive control: Theory and practice - A survey , 1989, Autom..

[21]  M. V. van Loosdrecht,et al.  Kinetic model of a granular sludge SBR: Influences on nutrient removal , 2007, Biotechnology and bioengineering.

[22]  B. Holenda,et al.  Dissolved oxygen control of the activated sludge wastewater treatment process using model predictive control , 2008, Comput. Chem. Eng..

[23]  J J Heijnen,et al.  Kinetic modeling of poly(beta-hydroxybutyrate) production and consumption by Paracoccus pantotrophus under dynamic substrate supply. , 1997, Biotechnology and bioengineering.

[24]  P A Vanrolleghem,et al.  Evolution of an ASM2d-like model structure due to operational changes of an SBR process. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[25]  Javier Lafuente,et al.  Cost and effluent quality controllers design based on the relative gain array for a nutrient removal WWTP. , 2009, Water research.

[26]  M. Loosdrecht,et al.  Substrate flux into storage and growth in relation to activated sludge modeling , 1999 .

[27]  J J Heijnen,et al.  Glycogen metabolism in aerobic mixed cultures. , 2001, Biotechnology and bioengineering.

[28]  Cristian Picioreanu,et al.  Multi-scale individual-based model of microbial and bioconversion dynamics in aerobic granular sludge. , 2007, Environmental science & technology.

[29]  Leiv Rieger,et al.  Extension of ASM3 for two-step nitrification and denitrification and its calibration and validation with batch tests and pilot scale data. , 2009, Water research.

[30]  Ramón Vilanova,et al.  Improving the performance of a WWTP control system by model-based setpoint optimisation , 2011, Environ. Model. Softw..

[31]  M. V. van Loosdrecht,et al.  Modelling of activated sludge processes with structured biomass. , 2002, Water science and technology : a journal of the International Association on Water Pollution Research.

[32]  Stefano Marsili-Libelli,et al.  Modelling microbial population dynamics in nitritation processes , 2011, Environ. Model. Softw..

[33]  G. S. Ostace,et al.  EXTENSION OF ACTIVATED SLUDGE MODEL NO 1 WITH TWO-STEP NITRIFICATION AND DENITRIFICATION PROCESSES FOR OPERATION IMPROVEMENT , 2011 .

[34]  Henri Spanjers,et al.  Assessment of a two-step nitrification model for activated sludge. , 1996 .

[35]  U Jeppsson,et al.  Impact of reactive settler models on simulated WWTP performance. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[36]  R Ramadori,et al.  Effect of different carbon sources on aerobic storage by activated sludge. , 2002, Water science and technology : a journal of the International Association on Water Pollution Research.

[37]  N Hvala,et al.  Comparison of control strategies for nitrogen removal in an activated sludge process in terms of operating costs: a simulation study. , 2007, Water research.

[38]  Karl Svardal,et al.  The dynamic behaviour of nitrifying activated sludge systems influenced by inhibiting wastewater compounds , 1995 .