Water Resources Management

, Volume 31, Issue 4, pp 1283–1304 | Cite as

Optimization of Pump Scheduling Program in Water Supply Systems Using a Self-Adaptive NSGA-II; a Review of Theory to Real Application

  • Yasaman Makaremi
  • Ali Haghighi
  • Hamid Reza Ghafouri
Article

Abstract

The operation of pumps imposes significant costs on a water distribution system for energy supply and pumps maintenance. To derive an optimum pumps scheduling program, this study presents a multiobjective optimization problem with the objective functions of 1- energy cost and 2- the number of pump switches. The optimization of both objective functions together leads to a multiobjective constrained optimization problem. To solve the problem, the Non-Dominated Sorting Genetic Algorithm, version II, (NSGA-II) is coupled to the EPANET hydraulic simulation model. For constraint handling, some modifications are introduced to the standard NSGA-II to make it self-adaptive through which all constraints of the problem are automatically satisfied. Application of the model to a test example and a real pipe network verifies that the proposed scheme is computationally efficient and reliable. Also, optimization of the real pipe network reveals that by a careful pump scheduling program the total number of pump switches even in optimum operations could be decreased by 69% while the energy cost increases at most by 10%.

Keywords

Pump scheduling program Self-adaptive NSGA-Ii Multiobjective optimization Energy costs 

References

  1. Andersen JH, Powell RS (1999) The use of continuous decision variables in an optimising fixed speed pump scheduling algorithm. Paper presented at the 3rd Computing and control for the water industry International conference, Baldock, United KingdomGoogle Scholar
  2. Atkinson R, Van Zyl JE, Walters GA, Savic DA (2000) Genetic algorithm optimisation of level-controlled pumping station operation. Water Network Modelling for Optimal Design and Management, Centre for Water Systems, Exeter, U.K., 79–90Google Scholar
  3. Bagirov AM, Barton AF, Mala-Jetmarova H, Al Nuaimata A, Ahmeda ST, Sultanova N, Yearwooda J (2013) An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling. Math Comput Model 57(3–4):873–886CrossRefGoogle Scholar
  4. Boulos PF, Orr CH, de Schaetzen W, Chatila JG, Moore M, Hsiung P & Thomas D (2001) Optimal pump operation of water distribution systems using genetic algorithms. In: AWWA Distribution System Symp. Denver, USA: American Water Works AssociationGoogle Scholar
  5. Bunn S (2006) Water distribution systems analysis symposium, proceedings of the 2006 EWRI. Conference, ASCE. Pump Scheduling Optimization in Four US Cities: Case StudiesGoogle Scholar
  6. Bunn S, Hillebrand C (2006) Energy management in a deregulated market. Proceedings of the AWWA, Annual Conference and Exposition, San Antonio, TX, USAGoogle Scholar
  7. Costa LHM, de Athayde PB, Ramos HM, de Castro MAH (2015) A branch-and-bound algorithm for optimal pump scheduling in water distribution networks. Water Resour Manag 30:1037–1052. doi: 10.1007/s11269-015-1209-2 CrossRefGoogle Scholar
  8. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA–II. IEEE Trans Evol Comput 6(2):182–197CrossRefGoogle Scholar
  9. Ertin E, Dean AN, Moore ML, Priddy KL (2001) Dynamic optimization for optimal control of water distribution systems. Paper presented at the 4th, Applications and science of computational intelligenceGoogle Scholar
  10. Eshelman LJ, Schaffer JD (1993) Real-coded genetic algorithms and interval-schemata. Foundations of Genetic Algorithms 2:187–202CrossRefGoogle Scholar
  11. Eusuff M, Lansey K, Pasha MFK (2006) Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization. J Eng Optim 38(2):129–154CrossRefGoogle Scholar
  12. Ghimire SR, Barkdoll BD (2007) Issues in energy consumption by municipal drinking water distribution systems. Proc ASCE World Environ Water Resour Congr 2007Google Scholar
  13. Goldman FE, Mays LW (2000) The application of simulated annealing to the optimal operation of water systems. Paper presented at the 26th Annual Water Resources Planning and Management Conference, Tempe, USAGoogle Scholar
  14. Kazantzis MD, Simpson AR, Kwong D & Tan SM (2002) A new methodology for optimizing the daily operations of a pumping plant. In: Proceedings of 2002 Conference on Water Resources Planning. Roanoke, USA: ASCEGoogle Scholar
  15. Kurek W, Ostfeld A (2012) Multi-objective water distribution systems control of pumping cost, water quality, and storage-reliability constraints. J Water Resour Plan Manag 140(2):184–193CrossRefGoogle Scholar
  16. Lansey KE, Awumah K (1994) Optimal pump operations considering pump switches. J Water Resour Plan Manag 129(1):17–35CrossRefGoogle Scholar
  17. López-Ibáñez M (2009) Operational optimisation of water distribution networks. (Doctoral dissertation), Edinburgh Napier UniversityGoogle Scholar
  18. López-Ibáñez M, Prasad TD, Paechter B (2005) Multi-Objective Optimisation of the Pump Scheduling Problem using SPEA2. Paper presented at the 2005 I.E. congress. Edinburgh, ScotlandGoogle Scholar
  19. López-Ibáñez M, Prasad TD, Paechter B (2008) Ant colony optimisation for the optimal control of pumps in water distribution networks. J Water Resour Plan Manag 134(4):337–346CrossRefGoogle Scholar
  20. López-Ibáñez M, Prasad TD, Paechter B (2011) Representations and evolutionary operators for the scheduling of pump operations in water distribution networks. Evol Comput 19(3):429–467CrossRefGoogle Scholar
  21. Mackle G, Savic DA, Walters GA (1995) Application of genetic algorithms to pump scheduling for water supply. Paper presented at the genetic algorithms in engineering. Systems, Innovations and Applications, Sheffield, UKGoogle Scholar
  22. Mala-Jetmarova H, Barton A, Bagirov A (2014) Optimal operation of a multi-quality water distribution system with changing turbidity and salinity levels in source reservoirs. Paper presented at the 16th Water Distribution System Analysis Conference, Barli, Italy, 197–205Google Scholar
  23. Nitivattananon V, Sadowski EC, Quimpo RG (1996) Optimization of water supply system operation. Journal of Water Resources Planning and Management, ASCE 125(5):374–384CrossRefGoogle Scholar
  24. Ormsbee LE, Reddy SL (1995) Nonlinear heuristic for pump operations. J Water Resour Plan Manag 121(4):302–309CrossRefGoogle Scholar
  25. Pasha MFK, Lansey KE (2009) Optimal pump scheduling by linear programming. Proceedings of the ASCE World Water and Environmental Resources Congress, May 17–21, 2009, Kansas City, Missouri, USAGoogle Scholar
  26. Pasha MFK, Lansey K (2010) Strategies for real time pump operation for water distribution systems. Water Distribution Systems Analysis Conference (WDSA 2010). In: September 12–15, 2010. Tucson, AZGoogle Scholar
  27. Pasha MFK, Lansey K (2014) Strategies to develop warm solutions for real-time pump scheduling for water distribution systems. Water Resour Manag 28(12):3975–3987CrossRefGoogle Scholar
  28. Rossman LA (1999) The EPANET Programmer’s Toolkit for analysis of water distribution systems. Paper presented at the 29th Annual Water Resources Planning and Management Conference. Reston, USA: ASCEGoogle Scholar
  29. Savic DA, Walters GA, Schwab M (1997) Multiobjective genetic algorithms for pump scheduling in water supply. Lect Notes Comput Sci 1305:227–236CrossRefGoogle Scholar
  30. Srinivas N, Deb K (1994) Multi-objective optimization using nondominated sorting in genetic algorithm. Journal of Evolutionary Computation 2(3):221–248CrossRefGoogle Scholar
  31. Van Zyl JE, Savic DA, Walters GA (2004) Operational optimization of water distribution systems using a hybrid genetic algorithm. J Water Resour Plan Manag 130(2):160–170CrossRefGoogle Scholar
  32. Walski TM, Chase DV, Savic DA, Grayman W, Beckwith S, Koelle E (2003) Advanced Water Distribution Modeling and ManagementGoogle Scholar
  33. Wang JY, Chang TP, Chen JS (2009) An enhanced genetic algorithm for bi-objective pump scheduling in water supply. Expert Syst Appl 36(7):10249–10258CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.Civil Engineering Department, Faculty of EngineeringShahid Chamran University of AhvazAhvazIran

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