Real-Time Multiobjective Optimization of Operation of Water Supply Systems
Publication: Journal of Water Resources Planning and Management
Volume 141, Issue 9
Abstract
The need for more efficient use of energy in water distribution systems is increasing constantly due to increasing energy prices. A new methodology for optimized real-time operation of a water distribution system is developed and presented here. The methodology is based on the integration of three models: (1) real-time demand forecasting model, (2) hydraulic simulation model of the system, and (3) optimization model. The optimization process is driven by the cost minimization of the energy used for pumping and the maximization of operational reliability. The latter is quantified using alternative measures into the optimization process in order to mimic the conservative attitude to pump scheduling often adopted by control room operators in real-life systems. Optimal pump schedules were generated by using a multialgorithm-genetically-adaptive-method (AMALGAM), hydraulic simulations are performed by using the EPANET2 model, and demand forecasting was performed by using the recently developed DAN2-H model. A number of other methodological developments are used to enable pump scheduling in real time. The new methodology is tested, verified, and demonstrated on the water distribution system of Araraquara, in the state of São Paulo, Brazil. The results obtained demonstrate that it is possible to achieve substantial energy cost savings (up to 13% relative to historical system operation) while simultaneously maintaining the level of supply reliability obtained by manually operating the water system.
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Acknowledgments
The authors acknowledge the support from the São Paulo Research Foundation (FAPESP), from the Coordination for the Improvement of Higher Education (CAPES), and from the Brazilian Scientific and Technological Development Council (CNPq) for providing the PhD’s scholarship and grant to the second author, and also from the Araraquara’s DAAE, SP, Brazil) for providing data and assistance through the agreement between the company and the University of São Paulo.
References
Boulos, P. F., Wu, Z., Orr, C. H., Moore, M., Hsiung, P., and Thomas, D. (2000). Optimal pump operation of water distribution systems using genetic algorithm, H2ONET—Users guide, MW Software Inc., Pasadena, CA.
Broad, D. R., Maier, H. R., and Dandy, G. C. (2010). “Optimal operation of complex water distribution systems using metamodels.” J. Water Resour. Plann. Manage., 433–443.
Coulbeck, B., Orr, C. H., and Brdys, M. (1988). “Real-time optimized control of water distribution systems.” Int. Conf. on Control, 634–640.
Deb, K., and Agrawal, S. (1999). “A niched-penalty approach for constraint handling in genetic algorithms.” Proc., ICANNGA-99, Springer, Heidelberg, Germany, 123–135.
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002). “A fast and elitist multiobjective genetic algorithm: NSGA-II evolutionary computation.” IEEE Trans. Evol. Comput., 6(2), 182–197.
EPA (Environmental Protection Agency). (2008). “Ensuring a sustainable future: An energy management guidebook for wastewater and water utilities.” 〈http://www.epa.gov/waterinfrastructure/pdfs/guidebook_si_energymanagement.pdf〉 (Oct. 24, 2013).
EPRI (Electric Power Research Institute). (2002). “Water and sustainability: U.S. electricity consumption for water supply and treatment—The next half century.”, Vol. 4, Palo Alto, CA.
Giacomello, C., Kapelan, Z., and Nicolini, M. (2012). “Fast hybrid optimization method for effective pump scheduling.” J. Water Resour. Plann. Manage., 175–183.
Goldman, F. E., and Mays, L. W. (2000). “The application of simulated annealing to the optimal operation of water systems.” Proc., 26th Annual Water Resources Planning and Management Conf., ASCE, Washington, DC.
Iman, R. L., and Conover, W. J. (1982). “A distribution-free approach to inducing rank correlation among input variables.” Commun. Stat., 11(3), 311–334.
Jamieson, D. G., Shamir, U., Martinez, F., and Franchini, M. (2007). “Conceptual design of a generic, real-time, near-optimal control system for water distribution networks.” J. Hydroinf., 9(1), 3–14.
Jayaram, N., and Srinivasan, K. (2008). “Performance-based optimal design and rehabilitation of water distribution networks sing life cycle costing.” Water Resour. Res., 44(1), W01417.
Jowitt, P. W., and Germanopoulos, G. (1992). “Optimal pump scheduling in water supply networks.” J. Water Resour. Plann. Manage., 406–422.
Kang, D. (2014). “Real-time optimal control of water distribution systems.” Procedia Eng., 70, 917–923.
Krapivka, A., and Ostfeld, A. (2009). “Coupled genetic algorithm-linear programming for least cost pipe sizing of water-distribution systems.” J. Water Resour. Plann. Manage., 298–302.
Lansey, K. E., and Awumah, K. (1994). “Optimal pump operations considering pump switches.” J. Water Resour. Plann. Manage., 17–35.
Lingireddy, S., and Wood, D. J. (1998). “Improved operation of water distribution systems using variable speed pumps.” J. Energy Eng., 90–103.
Loganathan, G. V., Greene, J. J., and Ahn, T. J. (1995). “Design heuristic for globally minimum cost water-distribution systems.” J. Water Resour. Plann. Manage., 182–192.
López-Ibáñez, M. (2009). “Operational optimization of water distribution networks.” Ph.D. thesis, School of Engineering and the Built Environment, Edinburgh Napier Univ., U.K.
López-Ibáñez, M., Prasad, T. D., and Paechter, B. (2008). “Ant colony optimization for the optimal control of pumps in water distribution networks.” J. Water Resour. Plann. Manage., 337–346.
López-Ibáñez, M., Prasad, T. D., and Paechter, B. (2011). “Representations and evolutionary operators for the scheduling of pump operations in water distribution networks.” Evol. Comput., 19(3), 429–467.
Mackle, G., Savic, D. A., and Walters, G. A. (1995). “Application of genetic algorithms to pumps scheduling for water supply.” Conf. Publ. No. 414, Genetic Algorithms in Engineering Systems: Innovations and Applications, Institute of Engineering and Technology (IET), Stevenage, U.K., 400–405.
Martinez, F., Hernandez, V., Alonso, J. M., Rao, Z., and Alvisi, S. (2007). “Optimizing the operation of the Valencia water-distribution network.” J. Hydroinf., 9(1), 65–78.
McCormick, G., and Powell, R. S. (2003). “Optimal pump scheduling in water supply systems with maximum demand charges.” J. Water Resour. Plann. Manage., 372–379.
Nitivattananon, V., Sadowski, E. C., and Quimpo, R. G. (1996). “Optimization of water supply system operation.” J. Water Resour. Plann. Manage., 374–384.
Odan, F. K., and Reis, L. F. R. (2012). “Hybrid water demand forecasting model associating artificial neural network with Fourier series.” J. Water Resour. Plann. Manage., 245–256.
Pasha, M. F. K., and Lansey, K. (2009). “Optimal pump scheduling by linear programming.” World Environmental and Water Resources Congress 2009, ASCE, Reston VA, 1–10.
Pezeshk, S., and Helweg, O. J. (1996). “Adaptive search optimization in reducing pump operating costs.” J. Water Resour. Plann. Manage., 57–63.
Prasad, T. D., and Park, N. S. (2004). “Multiobjective genetic algorithms for design of water distribution networks.” J. Water Resour. Plann. Manage., 73–82.
Price, E., and Ostfdeld, A. (2013). “An iterative linearization scheme for convex non-linear equations: Application to optimal operation of water distribution systems.” J. Water Resour. Plann. Manage., 299–312.
Rao, Z., and Salomons, E. (2007). “Development of a real-time, near-optimal control process for water-distribution networks.” J. Hydroinf., 9(1), 25–37.
Rossman, L. A. (2000). EPANET 2 user’s manual, EPA, Cincinnati.
Sakarya, A. B. A., and Mays, L. W. (2000). “Optimal operation of water distribution pumps considering water quality.” J. Water Resour. Plann. Manage., 210–220.
Savic, D. A., Walters, G. A., and Schwab, M. (1997). “Multiobjective genetic algorithms for pump scheduling in water supply.” Evol. Comput., 1305, 227–236.
Shamir, U., and Salomons, E. (2008). “Optimal real-time operation of urban water distribution systems using reduced models.” J. Water Resour. Plann. Manage. Div., 181–185.
Tanyimboh, T. T., and Templeman, A. B. (1993). “Optimum design of flexible water distribution networks.” Civ. Eng. Syst., 10(3), 243–258.
Todini, E. (2000). “Looped water distribution networks design using a resilience index based heuristic approach.” Urban Water, 2(2), 115–122.
Todini, E., and Pilati, S. (1987). “A gradient method for the analysis of pipe networks.” Int. Conf. on Computer Applications for Water Supply and Distribution, Research Studies Press, Taunton, U.K.
Ulanicki, B., Kahler, J., and See, H. (2007). “Dynamic optimization approach for solving an optimal scheduling problem in water distribution systems.” J. Water Resour. Plann. Manage., 23–32.
van Zyl, J. E., Savic, D. A., and Walters, G. A. (2004). “Operational optimization of water distribution systems using a hybrid genetic algorithm.” J. Water Resour. Plann. Manage., 160–170.
Vrugt, J. A., and Robinson, B. A. (2007). “Improved evolutionary optimization from genetically adaptive multimethod search.” Proc. Natl. Acad. Sci., 104(3), 708–711.
Yu, G., Powell, R. S., and Sterling, M. J. H. (1994). “Optimized pump scheduling in water distribution systems.” J. Optim. Theory Appl., 83(3), 463–488.
Zessler, U., and Shamir, U. (1989). “Optimal operation of water distribution systems.” J. Water Resour. Plann. Manage., 735–752.
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Published In
Journal of Water Resources Planning and Management
Volume 141 • Issue 9 • September 2015
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Apr 14, 2014
Accepted: Dec 12, 2014
Published online: Feb 9, 2015
Discussion open until: Jul 9, 2015
Published in print: Sep 1, 2015
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