Multi-criteria evaluation of wastewater treatment plant control strategies under uncertainty.

The evaluation of activated sludge control strategies in wastewater treatment plants (WWTP) via mathematical modelling is a complex activity because several objectives; e.g. economic, environmental, technical and legal; must be taken into account at the same time, i.e. the evaluation of the alternatives is a multi-criteria problem. Activated sludge models are not well characterized and some of the parameters can present uncertainty, e.g. the influent fractions arriving to the facility and the effect of either temperature or toxic compounds on the kinetic parameters, having a strong influence in the model predictions used during the evaluation of the alternatives and affecting the resulting rank of preferences. Using a simplified version of the IWA Benchmark Simulation Model No. 2 as a case study, this article shows the variations in the decision making when the uncertainty in activated sludge model (ASM) parameters is either included or not during the evaluation of WWTP control strategies. This paper comprises two main sections. Firstly, there is the evaluation of six WWTP control strategies using multi-criteria decision analysis setting the ASM parameters at their default value. In the following section, the uncertainty is introduced, i.e. input uncertainty, which is characterized by probability distribution functions based on the available process knowledge. Next, Monte Carlo simulations are run to propagate input through the model and affect the different outcomes. Thus (i) the variation in the overall degree of satisfaction of the control objectives for the generated WWTP control strategies is quantified, (ii) the contributions of environmental, legal, technical and economic objectives to the existing variance are identified and finally (iii) the influence of the relative importance of the control objectives during the selection of alternatives is analyzed. The results show that the control strategies with an external carbon source reduce the output uncertainty in the criteria used to quantify the degree of satisfaction of environmental, technical and legal objectives, but increasing the economical costs and their variability as a trade-off. Also, it is shown how a preliminary selected alternative with cascade ammonium controller becomes less desirable when input uncertainty is included, having simpler alternatives more chance of success.

[1]  Marc B Neumann,et al.  Uncertainty in prediction of disinfection performance. , 2007, Water research.

[2]  S Salem,et al.  Model-based evaluation of a new upgrading concept for N-removal. , 2002, Water science and technology : a journal of the International Association on Water Pollution Research.

[3]  Philippe Vincke,et al.  Multicriteria Decision-aid , 1993 .

[4]  P A Vanrolleghem,et al.  Robustness and economic measures as control benchmark performance criteria. , 2002, Water science and technology : a journal of the International Association on Water Pollution Research.

[5]  L Benedetti,et al.  Assessment of WWTP design and upgrade options: balancing costs and risks of standards' exceedance. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[6]  U Jeppsson,et al.  Benchmark simulation Model no 2 in Matlab-simulink: towards plant-wide WWTP control strategy evaluation. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[7]  Ignasi Rodríguez-Roda,et al.  Selection of the Activated Sludge Configuration during the Conceptual Design of Activated Sludge Plants Using Multicriteria Analysis , 2005 .

[8]  Hansruedi Siegrist,et al.  Reduction of biomass decay rate under anoxic and anaerobic conditions , 1999 .

[9]  A. Imai,et al.  Budgets of major ionic species and nutrients on a dam reservoir in forested watershed. , 2007, Water science and technology : a journal of the International Association on Water Pollution Research.

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

[11]  U Jeppsson,et al.  Extension of the IWA/COST simulation benchmark to include expert reasoning for system performance evaluation. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[12]  Ulf Jeppsson,et al.  A practical ASM/ADM model interface for enhanced dynamic plant-wide simulation , 2008 .

[13]  Theodor J. Stewart,et al.  Multiple criteria decision analysis - an integrated approach , 2001 .

[14]  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.

[15]  Ulf Jeppsson,et al.  BSM1 versus BSM1_LT: Is the Control Strategy Performance Ranking Maintained? , 2007 .

[16]  Willy Verstraete,et al.  Reducing the size of a nitrogen removal activated sludge plant by shortening the retention time of inert solids via sludge storage , 2000 .

[17]  P A Vanrolleghem,et al.  Benchmark simulation model no 2: general protocol and exploratory case studies. , 2007, Water science and technology : a journal of the International Association on Water Pollution Research.

[18]  Gürkan Sin,et al.  An efficient approach to automate the manual trial and error calibration of activated sludge models , 2008, Biotechnology and bioengineering.

[19]  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.

[20]  Richard J. Beckman,et al.  A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.

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

[22]  James E. Campbell,et al.  An Approach to Sensitivity Analysis of Computer Models: Part I—Introduction, Input Variable Selection and Preliminary Variable Assessment , 1981 .

[23]  M. B. Beck,et al.  Water quality modeling: A review of the analysis of uncertainty , 1987 .

[24]  Ignasi Rodríguez-Roda,et al.  Systematic Procedure to Handle Critical Decisions during the Conceptual Design of Activated Sludge Plants , 2007 .

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

[26]  P A Vanrolleghem,et al.  Plant-wide (BSM2) evaluation of reject water treatment with a SHARON-Anammox process. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[27]  윤석표.  Activated Sludge Model No.2를 이용한 하수의 생물학적 질소·인 제거 공정의 처리성 평가 , 1999 .

[28]  K V Gernaey,et al.  Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis. , 2007, Water science and technology : a journal of the International Association on Water Pollution Research.