Operational Cost Reduction of an Activated Sludge System: Correlation Between Setpoint and Growth Substrate

  • George Simion OstaceEmail author
  • Anca Gal
  • Vasile Mircea Cristea
  • Paul Şerban Agachi
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 170)


This work presents the optimization of two control strategies of the wastewater treatment plant. The control architectures are assessed from an operational costs point of view, and improved by adding an upper, supervisory level of control. The upper control level dictates the optimal set-point for the two control structures by taking into consideration the quantity of ammonia nitrogen that enters the wastewater treatment plant. The relationship between the quantity of ammonia nitrogen that enters the WWTP and the optimal setpoint was established by means of linear and polynomial interpolations. The study is based on the modified Benchmark Simulation Model No. 1 (BSM1). Two modifications were made to the BSM1. The first one is the implementation of an enhanced Activated Sludge Model No. 3. This model includes two additional processes that describe the direct growth of the heterotrophic biomass on readily biodegradable substrate, in both anoxic and oxic conditions. The 2nd modification of the BSM1 regards the secondary settler, which is considered to be reactive. The simulation results show that by using the supervisory level of control the total operational cost can be reduced with almost 15.5 %, while effluent standards are maintained.


BSM1 MPC Operational costs PI Reactive settler Setpoint optimization 



The authors wish to thank for the financial support provided from programs co-financed by the Sectoral Operational Program for Human Resources Development 2007–2013, Contract no.: POSDRU/88/1.5/S/60185–“Innovative doctoral studies in a Knowledge Based Society.


  1. 1.
    Henze M, Gujer W, Mino T, van Loosdrecht MCM (2000) Activated sludge models ASM1, ASM2, ASM2d, and ASM3, IWA scientific and technical report no. 9. IWA Publishing, London, UKGoogle Scholar
  2. 2.
    Henze M, Grady CPL Jr, Gujer W, Marais GVR, Matsuo T (1987) Activated sludge model No. 1, IAWQ scientific and technical report no. 1, London, UKGoogle Scholar
  3. 3.
    Henze M, Gujer W, Mino T, Matsuo T, Wentzel MC, Marais GvR (1995) Activated sludge model No. 2. IAWQ scientific and technical report no. 3. London, IAWQGoogle Scholar
  4. 4.
    Henze M, Gujer W, Mino T, Matsuo T, Wentzel MC, Marais GvR, van Loosdrecht MCM (1999) Activated sludge model no. 2d, ASM2d. Water Sci Technol 39(1):165–182Google Scholar
  5. 5.
    Gujer W, Henze M, Mino T, van Loosdrecht MCM (1999) Activated sludge model no. 3. Water Sci Technol 39(1):183–193CrossRefGoogle Scholar
  6. 6.
    Ostace GS, Cristea VM, Agachi PS (2011a) Cost reduction of the wastewater treatment plant operation by MPC based on modified ASM1 with two-step nitrification/denitrification model. Comput Chem Eng 35:2469–2479CrossRefGoogle Scholar
  7. 7.
    Ostace GS, Gal A, Cristea VM, Agachi PS (2011) Operational costs reduction for the WWTP by means of substrate to dissolved oxygen correlation—a simulation study. Lecture notes in engineering and computer science: proceedings of the world congress on engineering and computer science 2011, WCECS 2011, 19–21 Oct 2011, San Francisco, USA, pp 945–950Google Scholar
  8. 8.
    Giusti E, Marsili-Libelli S, Spagni A (2011) Modelling microbial population dynamics in nitritation processes. Environ Model Softw 26:938–949Google Scholar
  9. 9.
    Iacopozzi I, Innocenti V, Marsili-Libelli S, Giusti E (2007) A modified activated sludge model no. 3 (ASM3) with two-step nitrification/denitrification. Environ Model Softw 22:847–861CrossRefGoogle Scholar
  10. 10.
    Marsili-Libelli S, Ratini P, Spagni A, Bortone G (2001) Implementation, study and calibration of a modified ASM2d for the simulation of SBR processes. Water Sci Technol 43:69–76Google Scholar
  11. 11.
    Sin G, Vanrolleghem PA (2006) Evolution of an ASM2d-like model structure due to operational changes of an SBR process. Water Sci Technol 53:237–245Google Scholar
  12. 12.
    Kaelin D, Manser R, Rieger L, Eugster J, Rottermann K, Siegrist H (2009) Extension of ASM3 for two-step nitrification and denitrification and its calibration and validation with batch tests and pilot scale data. Water Res 43:1680–1692CrossRefGoogle Scholar
  13. 13.
    Ni BJ, Yu HQ (2008) An approach for modeling two-step denitrification in activated sludge systems. Chem Eng Sci 63:1449–1459CrossRefGoogle Scholar
  14. 14.
    Ossenbruggen PJ, Spanjers H, Klapwik A (1996) Assessment of a two-step nitrification model for activated sludge. Water Res 30:939–953CrossRefGoogle Scholar
  15. 15.
    Karahan-Gül Ö, van Loosdrecht MCM, Orhon D (2003) Modification of activated sludge model no. 3 considering direct growth on primary substrate. Water Sci Technol 47(11):219–225Google Scholar
  16. 16.
    Stare A, Vrecko D, Hvala N, Strmcnik S (2007) Comparison of control strategies for nitrogen removal in an activated sludge process in terms of operating costs. Water Res 41:2004–2014CrossRefGoogle Scholar
  17. 17.
    Benedetti L, de Baets B, Nopens I, Vanrolleghem PA (2010) Multi-criteria analysis of wastewater treatment plant design and control scenarios under uncertainty. Environ Model Softw 25:616–621CrossRefGoogle Scholar
  18. 18.
    Cecil D, Kozlowska M (2010) Software sensors are a real alternative to true sensors. Environ Model Softw 25:622–625CrossRefGoogle Scholar
  19. 19.
    Guerrero J, Guisasola A, Vilanova R, Baeza AJ (2011) Improving the performance of a WWTP control system by model-based setpoint Optimisation. Environ Model Softw 26:492–497CrossRefGoogle Scholar
  20. 20.
    Copp JB (2002) The COST simulation benchmark: description and simulator manual. Office for Official Publications of the European Communities, LuxembourgGoogle Scholar
  21. 21.
    Takács I, Patry GC, Nolasco D (1991) A dynamic model of the clarification-thickening process. Water Res 25:1263–1271CrossRefGoogle Scholar
  22. 22.
    Ostace GS, Cristea VM, Agachi PS (2010) Investigation of different control strategies for the BSM1 waste water treatment plant with reactive secondary settler model. In: 20th European symposium on computer aided process engineering, Ischia, pp 1841–1846Google Scholar
  23. 23.
    Gernaey KV, Jeppsson U, Batstone DJ, Ingildsen P (2006) Impact of reactive settler models on simulated WWTP performance. Water Sci Technol 53:159–167Google Scholar
  24. 24.
    Alex JL, Benedetti L, Copp JB, Gernaey KV, Jeppsson U, Nopens I, Pons MN, Rosen C, Steyer JP, Vanrolleghem P, Winkler S (2008) Benchmark simulation model no. 1 (BSM1), Technical report no. LUTEDX/(TEIE- 7229)/1-62/2008Google Scholar
  25. 25.
    Carstensen J (1994) Identification of wastewater processes. Ph.D. Thesis, Institute of Mathematical Modelling, Technical University of DenmarkGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • George Simion Ostace
    • 1
    Email author
  • Anca Gal
    • 1
  • Vasile Mircea Cristea
    • 1
  • Paul Şerban Agachi
    • 1
  1. 1.Faculty of Chemistry and Chemical EngineeringBabes-Bolyai UniversityCluj-NapocaRomania

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