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The Benchmark Simulation Modelling Platform – Areas of Recent Development and Extension

  • U. JeppssonEmail author
Conference paper
Part of the Lecture Notes in Civil Engineering book series (LNCE, volume 4)

Abstract

As the formal work of the IWA Task Group on Benchmarking of Control Strategies for Wastewater treatment Plants (WWTPs) has come to an end, it is essential to continue to disseminate the intense research in this field that is still carried out. In 2013 and 2014, all authors of the IWA Scientific and Technical Report on benchmarking came together to provide their insights, highlighting areas where knowledge was still deficient and where new opportunities were emerging, as well as to propose potential avenues for future development and application of the general benchmarking framework and its associated tools. The focus was on the topics of temporal and spatial extensions, process modifications within the WWTP, improved realism of models, control strategy extensions, the potential for new evaluation tools within the existing benchmark system and the need for full-scale validation. Four years later, it is clear that many of these goals have already been accomplished and the toolbox of Benchmark Simulations Models has been greatly extended and enhanced. The focus of this paper is to provide a number of examples of these recent extensions. As always, the different BSM softwares are freely available for the benefit of the global research community.

Keywords

Benchmark BSM Control Modelling Simulation Wastewater treatment 

Notes

Acknowledgements

A large number of excellent researchers and close friends have contributed to the development of the benchmark systems during the last 20 years and the author wishes to express his sincere gratitude to all of them. Special thanks to professor Krist V. Gernaey, Dr Xavier Flores-Alsina and Ms Hannah Feldman at the CAPEC-PROCESS Research Centre, Technical University of Denmark and to Dr Magnus Arnell, Mrs Kimberly Solon and Mr Ramesh Saagi at IEA, Lund University, Sweden, for all their contributions to this paper. The support of the International Water Association (IWA) is gratefully acknowledged.

References

  1. Arnell M (2016) Performance assessment of wastewater treatment plants – multi-objective analysis using plant-wide models. PhD thesis, Division of Industrial Electrical Engineering and Automation, Lund University, SwedenGoogle Scholar
  2. Arnell M, Rahmberg M, Oliveira F, Jeppsson U (2017) Multi-objective performance assessment of wastewater treatment plants combining plant-wide process models and life cycle assessment. J Water Clim (submitted)Google Scholar
  3. Batstone DJ, Keller J, Angelidaki RI, Kalyuzhnyi SV, Pavlostathis SG, Rozzi A, Sanders WTM, Siegrist H, Vavilin VA (2002) Anaerobic digestion model no. 1. IWA scientific and technical report no. 13. IWA Publishing, LondonGoogle Scholar
  4. Bürger R, Diehl S, Farås S, Nopens I (2012) On reliable and unreliable numerical methods for the simulation of secondary settling tanks in wastewater treatment. Comput Chem Eng 41:93–105CrossRefGoogle Scholar
  5. Bürger R, Diehl S, Farås S, Nopens I, Torfs E (2013) A consistent modelling methodology for secondary settling tanks: a reliable numerical method. Water Sci Technol 68(1):192–208CrossRefGoogle Scholar
  6. Bürger R, Diehl S, Nopens I (2011) A consistent modelling methodology for secondary settling tanks in wastewater treatment. Water Res 45(6):2247–2260CrossRefGoogle Scholar
  7. Copp JB (ed.) (2002) The COST simulation benchmark – description and simulator manual. Office for official publications of the European communities, Luxembourg. ISBN 92–894-1658-0Google Scholar
  8. Corominas L, Foley J, Guest JS, Hospido A, Larsen HF, Morera S, Shaw A (2013) Life cycle assessment applied to wastewater treatment: state of the art. Water Res 47(15):5480–5492CrossRefGoogle Scholar
  9. Corominas L, Villez K, Aguado D, Rieger L, Rosen C, Vanrolleghem PA (2011) Performance evaluation of fault detection methods for wastewater treatment processes. Biotechnol Bioeng 108(2):333–334CrossRefGoogle Scholar
  10. Feldman H, Faraghi Parapari N, Bendix Larsen S, Kjellberg K, Flores-Alsina X, Sin G, Jeppsson U, Gernaey KV (2016) Model-based optimization of an industrial wastewater treatment plant combining a full-scale granular sludge reactor and autotrophic nitrogen removal. In: IWA 10th world water congress and exhibition (IWA 2016), Brisbane, Australia, 9–13 October 2016Google Scholar
  11. Feldman H, Flores-Alsina X, Ramin P, Kjellberg K, Jeppsson U, Batstone DJ, Gernaey KV (2017) Optimizing the operational/control conditions of a full-scale industrial granular anaerobic digester. In: 12th IWA conference on instrumentation, control and automation (ICA 2017), Quebec, Canada, 11–14 June 2017Google Scholar
  12. Flores-Alsina X, Arnell M, Amerlinck Y, Corominas Ll, Gernaey KV, Guo L, Lindblom E, Nopens I, Porro J, Shaw A, Snip L, Vanrolleghem PA, Jeppsson U (2014a) Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs. Sci Total Environ 466–467:616–624CrossRefGoogle Scholar
  13. Flores-Alsina X, Corominas L, Snip L, Vanrolleghem PA (2011) Including greenhouse gas emissions during benchmarking of wastewater treatment plant control strategies. Water Res 45(16):4700–4710CrossRefGoogle Scholar
  14. Flores-Alsina X, Kazadi-Mbamba C, Solon K, Vrecko D, Tait S, Batstone D, Jeppsson U, Gernaey KV (2015) A plant-wide aqueous phase chemistry module describing pH variations and ion speciation/pairing in wastewater treatment process models. Water Res 85:255–265CrossRefGoogle Scholar
  15. Flores-Alsina X, Saagi R, Lindblom E, Thirsing C, Thornberg D, Gernaey KV, Jeppsson U (2014b) Calibration and validation of a phenomenological influent pollutant disturbance scenario generator using full-scale data. Water Res 51:172–185CrossRefGoogle Scholar
  16. Flores-Alsina X, Solon K, Kazadi-Mbamba C, Tait S, Gernaey KV, Jeppsson U, Batstone DJ (2016) Modelling phosphorus (P), sulfur (S) and iron (Fe) interactions for dynamic simulations of anaerobic digestion processes. Water Res 95:370–382CrossRefGoogle Scholar
  17. Gernaey KV, Flores-Alsina X, Rosen C, Benedetti L, Jeppsson U (2011) Dynamic influent pollutant disturbance scenario generation using a phenomenological modelling approach. Environ Model Softw 26(11):1255–1267CrossRefGoogle Scholar
  18. Gernaey KV, Jeppsson U, Vanrolleghem PA, Copp JB (eds.) (2014) Benchmarking of control strategies for wastewater treatment plants. IWA scientific and technical report no. 23. IWA Publishing, London. ISBN 9781843391463Google Scholar
  19. Guo LS, Vanrolleghem PA (2014) Calibration and validation of an activated sludge model for greenhouse gases no. 1 (ASMG1): prediction of temperature-dependent N2O emission dynamics. Bioprocess Biosyst Eng 37(2):151–163CrossRefGoogle Scholar
  20. Henze M, Grady Jr, CPL, Gujer W, Marais GVR, Matsuo T (1987) Activated sludge model no. 1. IWA scientific and technical report no. 1. IWA Publishing, LondonGoogle Scholar
  21. Hiatt WC, Grady CPL (2008) An updated process model for carbon oxidation, nitrification, and denitrification. Water Environ Res 80(11):2145–2156CrossRefGoogle Scholar
  22. IPCC (2013) Climate change 2013: the physical science basis. Contribution of working group I to the 5th assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
  23. ISO 14040 (2006) Environmental management – Life cycle assessment – Principles and framework. International Organization for Standardization, Geneva, SwitzerlandGoogle Scholar
  24. Jeppsson U, Alex J, Batstone D, Benedetti L, Comas J, Copp JB, Corominas L, Flores-Alsina X, Gernaey KV, Nopens I, Pons M-N, Rodriguez-Roda I, Rosen C, Steyer J-P, Vanrolleghem PA, Volcke EIP, Vrecko D (2013) Benchmark simulation models, quo vadis? Water Sci Technol 68(1):1–15CrossRefGoogle Scholar
  25. Jeppsson U, Pons M-N, Nopens I, Alex J, Copp JB, Gernaey KV, Rosen C, Steyer J-P, Vanrolleghem PA (2007) Benchmark simulation model no 2 – general protocol and exploratory case studies. Water Sci Technol 56(8):67–78CrossRefGoogle Scholar
  26. Lindblom E (2009) Dynamic modelling of micropollutants in the integrated urban wastewater system. PhD thesis, DTU Environment, Technical University of DenmarkGoogle Scholar
  27. Lingsten A, Lundkvist M, Hellström D (2013) Swedish water and wastewater utilities use of energy in 2011. Technical report SVU 2013–17, The Swedish Water and Wastewater Association, Stockholm, SwedenGoogle Scholar
  28. Mampaey KE, Beuckels B, Kampschreur MJ, Kleerebezem R, van Loosdrecht MCM, Volcke EIP (2013) Modelling nitrous and nitric oxide emissions by autotrophic ammonia-oxidizing bacteria. Environ Technol 34(12):1555–1566CrossRefGoogle Scholar
  29. Nopens I, Benedetti L, Jeppsson U, Pons M-N, Alex J, Copp JB, Gernaey KV, Rosen C, Steyer J-P, Vanrolleghem PA (2010) Benchmark simulation model no 2 – finalisation of plant layout and default control strategy. Water Sci Technol 62(9):1967–1974CrossRefGoogle Scholar
  30. Olsson G (2012) Water and energy – threats and opportunities. IWA Publishing, LondonGoogle Scholar
  31. Reichert P, Borchardt D, Henze M, Rauch W, Shanahan P, Somlyódy L, Vanrolleghem PA (2001) River water quality model no. 1. IWA scientific and technical report no. 12. IWA Publishing, London. ISBN 9781900222822Google Scholar
  32. Rieger L, Koch G, Kühni M, Gujer W, Siegrist H (2001) The EAWAG Bio-P module for activated sludge model no. 3. Water Res 35(16):3887–3903CrossRefGoogle Scholar
  33. Rosen C, Jeppsson U, Vanrolleghem PA (2004) Towards a common benchmark for long-term process control and monitoring performance evaluation. Water Sci Technol 50(11):41–49Google Scholar
  34. Saagi R, Flores-Alsina X, Fu G, Butler D, Gernaey KV, Jeppsson U (2016) Catchment & sewer network simulation model to benchmark control strategies within urban wastewater systems. Environ Model Softw 78:16–30CrossRefGoogle Scholar
  35. Saagi R, Flores-Alsina X, Kroll S, Gernaey KV, Jeppsson U (2017) A model library for simulation and benchmarking of integrated urban wastewater systems. Environ Model Softw 93:282–295CrossRefGoogle Scholar
  36. Snip LJP, Flores-Alsina X, Plósz BG, Jeppsson U, Gernaey KV (2014) Modelling the occurrence, transport and fate of pharmaceuticals in wastewater systems. Environ Model Softw 62:112–127CrossRefGoogle Scholar
  37. Spanjers H, Vanrolleghem PA, Nguyen K, Vanhooren H, Patry GG (1998) Towards a simulation-benchmark for evaluating respirometry-based control strategies. Water Sci Technol 37(12):219–226Google Scholar
  38. Solon K, Flores-Alsina X, Gernaey KV, Jeppsson U (2015a) Effects of influent fractionation, kinetics, stoichiometry and mass transfer on CH4, H2 and CO2 production for (plant-wide) modelling of anaerobic digesters. Water Sci Technol 71(6):870–877CrossRefGoogle Scholar
  39. Solon K, Flores-Alsina X, Kazadi-Mbamba C, Ikumi D, Volcke EIP, Vaneeckhaute C, Ekama G, Vanrolleghem PA, Batstone DJ, Gernaey KV, Jeppsson U (2017) Plant-wide modelling of phosphorus transformations in wastewater treatment systems: impacts of control and operational strategies. Water Res 113:97–110CrossRefGoogle Scholar
  40. Solon K, Flores-Alsina X, Kazadi-Mbamba C, Volcke EIP, Tait S, Batstone D, Gernaey KV, Jeppsson U (2015b) Effects of ion strength and ion pairing on (plant-wide) modelling of anaerobic digestion processes. Water Res 70:235–245CrossRefGoogle Scholar
  41. Takács I, Patry GG, Nolasco D (1991) A dynamic model of the clarification-thickening process. Water Res 25(10):1263–1271CrossRefGoogle Scholar
  42. Vanrolleghem PA, Flores-Alsina X, Guo L, Solon K, Ikumi D, Batstone D, Brouckaert C, Takács I, Grau P, Ekama G, Jeppsson U, Gernaey KV (2014) Towards BSM2-GPS-X: a plant-wide benchmark simulation model not only for carbon and nitrogen, but also for greenhouse gases (G), phosphorus (P), sulphur (S) and micropollutants (X), all within the fence of WWTPs/WRRFs. In: 4th IWA/WEF wastewater treatment modelling seminar (WWTmod 2014), Spa, Belgium, 30 March–2 April 2014Google Scholar
  43. Vesilind PA (1968) Design of prototype thickeners from batch settling tests. Water Sewage Works 115(7):302–307Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Division of Industrial Electrical Engineering ad Automation (IEA), Department of Biomedical EngineeringLund UniversityLundSweden

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