Evolutionary Multi-Objective Optimal Control of Combined Sewer Overflows

Abstract

This paper presents a novel multi-objective evolutionary optimization approach for the active control of intermittent unsatisfactory discharges from combined sewer systems. The procedure proposed considers the unsteady flows and water quality in the sewers together with the wastewater treatment costs. The distinction between the portion of wastewater that receives full secondary treatment and the overall capacity of the wastewater treatment works (including storm overflow tanks) is addressed. Temporal and spatial variations in the concentrations of the primary contaminants are incorporated also. The formulation is different from previous approaches in the literature in that in addition to the wastewater treatment cost we consider at once the relative polluting effects of the various primary contaminants in wastewater. This is achieved by incorporating a measure of the overall pollution called the effluent quality index. The differences between two diametrically opposed control objectives are illustrated, i.e. the minimization of the pollution of the receiving water or, alternatively, the minimization of the wastewater treatment cost. Results are included for a realistic interceptor sewer system that show that the combination of a multi-objective genetic algorithm and a stormwater management model is effective. The genetic algorithm achieved consistently the frontier optimal control settings that, in turn, revealed the trade-offs between the wastewater treatment cost and pollution of the receiving water.

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References

  1. Barlow E, Tanyimboh T (2014) Multiobjective memetic algorithm applied to the optimisation of water distribution systems. Water Resour Manag 28(8):2229–2242

    Article  Google Scholar 

  2. Beraud B, Mourad M, Soyeux E, Lemoine C, Lovera M (2010) Optimisation of sewer networks hydraulic behaviour during storm weather: coupling genetic algorithms with two sewer networks modelling tools. NOVATECH 2010, Lyon, France

  3. Cembrano G, Quevedo J, Salamero M, Puig V, Figueras J, Marti J (2004) Optimal control of urban drainage systems. Control Eng Pract 12:1–9

    Article  Google Scholar 

  4. Chen Z, Han S, Zhou F-Y, Wang K (2013) A CFD modeling approach for municipal sewer system design optimization to minimize emissions into receiving water body. Water Resour Manag 27:2053–2069

    Article  Google Scholar 

  5. Copp H, Spanjers H, Vanrolleghem P (2002) Respirometry in control of the activated sludge process. IWA Publishing Scientific and Technical Report No. 11

  6. Darsono S, Labade J (2007) Neural-optimal control algorithm for real-time regulation of in-line storage in combined sewer systems. Environ Model Softw 22:1349–1361

    Article  Google Scholar 

  7. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA II. IEEE Trans Evol Comput 6(2):182–197

    Article  Google Scholar 

  8. Duncan P (1999) Urban stormwater quality: a statistical overview. Cooperative Research Centre for Catchment Hydrology 99/3, ISBN 1876006455

  9. Metcalf and Eddy (2004) Wastewater engineering. Treatment and reuse. McGraw-Hill

  10. Friedler E, Pisanty E (2006) Effects of design flow and treatment level on construction and operation costs of municipal wastewater treatment plants and their implications on policy making. Water Res 40:3751–3758

    Article  Google Scholar 

  11. Fu G, Butler D, Khu S (2008) Multiple objective optimal control of integrated urban wastewater systems. Environ Model Softw 23(2):225–234

    Article  Google Scholar 

  12. Fu G, Khu S, Butler D (2010) Optimal distribution and control of storage tank to mitigate the impact of new developments on receiving water quality. J Environ Eng 136(3):335–342

    Article  Google Scholar 

  13. Hernandez-Sancho, Sala-Garrido (2008) Cost modelling in wastewater treatment processes: an empirical analysis for Spain. Danger Pollutants Urban Water Cycle 4:219–226

    Article  Google Scholar 

  14. Institution of Water and Environmental Management (IWEM) (1993) Handbook of UK wastewater practice: glossary

  15. Joseph-Duran B, Jung M, Ocampo-Martinez C, Sager S, Cembrano G (2014) Minimization of sewage network overflow. Water Resour Manag 28:41–63

    Article  Google Scholar 

  16. Kaini P, Artita K et al (2012) Optimizing structural best management practices using SWAT and genetic algorithm to improve water quality goals. Water Resour Manag 26:1827–1845

    Article  Google Scholar 

  17. Karovic O, Mays L (2014) Sewer system design using simulated annealing in Excel. Water Resour Manag 28:4551–4565

    Article  Google Scholar 

  18. Kim J, Ko J, Lee J et al (2006) Parameter sensitivity analysis for activated sludge models No. 1 and 3 combined with one-dimensional settling model. Water Sci Technol 53:129–138

    Article  Google Scholar 

  19. Lacour C, Schütze M (2010) Real time control of sewer systems using turbidity measurements. Int. Conf. Sustainable Technics and Strategies for Urban Water Mngt, Lyon

  20. Lau J, Butler D, Schutze M (2002) Is combined sewer overflow spill frequency/volume a good indicator of receiving water quality impact? Urban Water J 4:181–189

    Article  Google Scholar 

  21. Lee S, Ko J, Poo K et al (2006) Practical approach to parameter estimation for ASM3+bio-P module applied to five-stage step-feed EBPR process. Water Sci Technol 53:139–148

    Article  Google Scholar 

  22. Li L, Yin C, He Q, Kong L (2007) First flush of storm runoff pollution from an urban catchment in China. J Environ Sci 19:295–299

    Article  Google Scholar 

  23. Meirlaen J, Van Assel J, Vanrolleghem P (2002) Real time control of integrated urban wastewater system using surrogate models. Water Sci Technol 45(3):109–116

    Google Scholar 

  24. Mussati M, Gernaey K, Gani R, Jorgesen S (2002) Performance analysis of a denitrifying wastewater treatment plant. Clean Techn Environ Policy 4:171–182

    Article  Google Scholar 

  25. Petruck A, Cassar A, Dettmar J (1998) Advanced real time control of a combined sewer system. Water Sci Technol 37(1):319–326

    Article  Google Scholar 

  26. Rathnayake U (2013) Optimal management and operational control of urban sewer systems. PhD Thesis, University of Strathclyde, UK

  27. Rathnayake U, Tanyimboh T (2012a) Integrated optimal control of urban wastewater systems. IWA-WCE conference. Dublin, Republic of Ireland, 13–18 May 2012

  28. Rathnayake U, Tanyimboh T (2012b) Multi-objective optimization of urban wastewater systems. 10th International Conf. on Hydroinfomatics. Hamburg, Germany, 14–18 July 2012

  29. Rauch W, Harremoes P (1998) Correlation of combined sewer overflow reduction due to real-time control and resulting effect on oxygen concentration in the river. Water Sci Technol 37(12):69–76

    Article  Google Scholar 

  30. Rauch W, Harremoes P (1999) Genetic algorithms in real time control applied to minimize transient pollution from urban wastewater systems. Water Research 33(5):1265–1277

  31. Rodrıguez R, Gundy P, Rijal G, Gerba C (2012) The impact of combined sewage overflows on the viral contamination of receiving waters. Food Environ Virol 4:34–40

    Article  Google Scholar 

  32. Rossman LA (2006) Storm water management model quality assurance report: dynamic wave flow routing. EPA National Risk Management Research Laboratory, Cincinnati

    Google Scholar 

  33. Rossman LA (2009) SWMM 5.0 user’s manual EPA/600/R-05/040. Water Supply and Water Resources Division, National Risk Management Research Laboratory, Cincinnati

    Google Scholar 

  34. Saleh S, Tanyimboh T (2013) Coupled topology and pipe size optimization of water distribution systems. Water Resour Manag 27(14):4795–4814

    Article  Google Scholar 

  35. Saleh S, Tanyimboh T (2014) Optimal design of water distribution systems based on entropy and topology. Water Resour Manag 28(11):3555–3575

    Article  Google Scholar 

  36. Saxena K, Duro J, Tiwari A, Deb K (2013) Objective reduction in many-objective optimization: linear and non-linear algorithms. IEEE Trans Evol Comput 17(1):77–99

    Article  Google Scholar 

  37. Siew C, Tanyimboh T (2012) Penalty-free feasibility boundary-convergent multi-objective evolutionary algorithm for the optimization of water distribution systems. Water Resour Manag 26(15):4485–4507

    Article  Google Scholar 

  38. Siew C, Tanyimboh T, Seyoum A (2014) Assessment of penalty-free multi-objective evolutionary optimization approach for the design and rehabilitation of water distribution systems. Water Resour Manag 28(2):373–389

    Article  Google Scholar 

  39. Sinha A, Saxena D, Deb K, Tiwari A (2013) Using objective reduction and interactive procedure to handle many-objective optimization problems. Appl Soft Comput 13(1):415–427

    Article  Google Scholar 

  40. Susnik J, Clemens S, et al. (2014) Assessing financial loss due to pluvial flooding and the efficacy of risk-reduction measures in the residential property sector. Water Resour Manag

  41. Tabari M, Soltani J (2013) Multi-objective optimal model for conjunctive use management using SGAs and NSGA-II models. Water Resour Manag 27(1):37–53

    Article  Google Scholar 

  42. Takbiri Z, Afshar A (2012) Multi-Objective optimization of fusegates system under hydrologic uncertainties. Water Resour Manag 26(8):2323–2345

    Article  Google Scholar 

  43. Thomas N (2000) Optimal pollution control models for interceptor sewer systems. PhD Thesis, University of Liverpool, UK

  44. Thomas N, Templeman A, Burrows R (1999) Optimal pollution control models for interceptor sewers and overflow chambers. International Conference on Computing and Control for the Water Industry. Exeter, UK, 265–278

  45. Thomas N, Templeman A, Burrows R (2000) Pollutant load overspill minimization of interceptor sewer systems. Eng Optim 32:393–416

    Article  Google Scholar 

  46. United Nations (2003) Wastewater treatment technologies: a general review

  47. Vanrolleghen P, Meirlaen J (2002) Model reduction through boundary relocation to facilitate real-time control optimization in integrated urban wastewater system. Water Sci Technol 45:373–381

    Google Scholar 

  48. Vanrolleghen P, Benedetti L, Meirlaen J (2005) Modelling and real-time control of integrated urban wastewater system. Environ Model Softw 20(4):427–442

    Article  Google Scholar 

  49. Weinreich G, Schilling W, Birkely A, Moland T (1997) Pollution based real time control strategies for combined sewer systems. Water Sci Technol 36(8–9):331–336

    Article  Google Scholar 

  50. Yusop Z, Tan L, Ujang Z, Mohamed M, Nasir K (2005) Runoff quality and pollution loading from a tropical urban catchment. Water Sci Technol 52(9):125–132

    Google Scholar 

Download references

Acknowledgments

Upaka Rathnayake’s PhD was funded by the UK Government’s Overseas Research Students Award Scheme and the University of Strathclyde. The authors are grateful for the above mentioned funding and the support of Prof. Richard Burrows (University of Liverpool, UK) who provided the data for the sewer system.

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Correspondence to Tiku T. Tanyimboh.

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Rathnayake, U.S., Tanyimboh, T.T. Evolutionary Multi-Objective Optimal Control of Combined Sewer Overflows. Water Resour Manage 29, 2715–2731 (2015). https://doi.org/10.1007/s11269-015-0965-3

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Keywords

  • Optimal control
  • Combined sewer system
  • Effluent quality index
  • Integrated wastewater management
  • Water pollution control
  • Wastewater treatment cost