Optimal Scheduling of Automatic Flushing Devices in Water Distribution System
Publication: Journal of Water Resources Planning and Management
Volume 141, Issue 6
Abstract
Maintaining sufficient chlorine residual in a water distribution system is important for water quality and system integrity. Discharging stagnant water from the pipeline through automatic flushing device (AFD) is a feasible method to maintain water quality. This paper presents a simulation-based optimization method to minimize total AFD discharge volume during a 24-h horizon. EPANET 2.0 is used as a hydraulics and water quality simulator. This is formulated as a single-objective optimization problem. The decision variables are the AFD operation patterns. The methodology has three phases. In the first phase, AFD discharge capacities are calculated to evaluate whether the existing AFDs are able to maintain chlorine residuals in the water network. In the second phase, the decision variables are converted to AFD discharge rates. A reduced gradient algorithm is used to quickly explore and narrow down the solution space. At the end of this phase, decision variables are switched back to the AFD operation patterns. In the third phase, simulated annealing is used to search intensively to exploit the global minimum. The method is demonstrated on the water system located at the south end of Pinellas County, Florida, where AFD optimal operation patterns are achieved.
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Acknowledgments
This paper is funded in part by University of South Florida Graduate School Challenge Grant. The writers would like to acknowledge the anonymous reviewers for their insightful comments that improved the manuscript.
References
Al-Jasser, A. O. (2007). “Chlorine decay in drinking-water transmission and distribution systems: Pipe service age effect.” Water Res., 41(2), 387–396.
Baggett, C. C., et al. (2008). “From start to finish: Calibrating Pinellas County’s 2,000-mile hydraulic water distribution system model.” Florida Water Resour. J., 60(12), 44–54.
Barbeau, B., Gauthier, V., Julienne, K., and Carriere, A. (2005). “Dead-end flushing of a distribution system: Short and long-term effects on water quality.” J. Water Supply Res. Technol.-AQUA, 54(6), 371–383.
Benson, R. E., and Mattausch, P. (2010). “Advanced maintenance flushing for improving water quality within water distribution systems.” Florida Section of AWWA 2010 Fall Conf., FSAWWA, St. Cloud, MN.
Bertsimas, D., and Tsitsiklis, J. (1993). “Simulated annealing.” Stat. Sci., 8(1), 10–15.
Boccelli, D. L., Tryby, M. E., Uber, J. G., Rossman, L. A., Zierolf, M. L., and Polycarpou, M. M. (1998). “Optimal scheduling of booster disinfection in water distribution network.” J. Water Resour. Plann. Manage., 99–111.
Carriere, A., Gauthier, V., Desjardins, R., and Barbeau, B. (2005). “Evaluation of loose deposits in distribution systems through unidirectional flushing.” J. AWWA, 97(9), 82–92.
Cunha, M. C., and Sousa, J. (1999). “Water distribution network design optimization: Simulated annealing approach.” J. Water Resour. Plann. Manage., 215–221.
Friedman, M., Kirmeyer, G. J., and Antoun, E. (2002). “Developing and implementing a distribution system flushing program.” J. AWWA, 94(7), 48–56.
Giacomello, C., Kapelan, Z., and Nicolini, M. (2013). “Fast hybrid optimization method for effective pump scheduling.” J. Water Resour. Plann. Manage., 175–183.
Goldman, F. (1998). “The application of simulated annealing for optimal operation of water distribution systems.” Ph.D. thesis, Arizona State Univ., Tempe, AZ.
Goldman, F. E., and Mays, L. W. (2005). “Water resources systems management tools.” Chapter 5, Water distribution system operation: Application of simulated annealing, McGraw-Hill, New York.
Hanselman, D. C., and Littlefield, B. (2005). Mastering Matlab 7, Pearson/Prentice Hall, Upper Saddle River, NJ.
Hua, G., et al. (2011). “Controlling nitrification in a distribution system receiving blended multiple source waters: The experience of Pinellas County utilities.” Florida Water Resour. J., 63(12), 42–48.
Hua, G., Rosario, R., Baggett, C., Powell, R., and Hall, J. (2012). “Using water quality modeling as a decision making tool to plan distribution system improvements for Pinellas County utilities.” Florida Water Resour. J., 64(12), 52–58.
Husband, S., and Boxall, J. B. (2010). “Field studies of discoloration in water distribution systems: Model verification and practical implication.” J. Environ. Eng., 86–94.
Ingber, L. (1993). “Simulated annealing: Practice versus theory.” Math. Comput. Model., 18(11), 29–57.
Lehtola, M. J., Nissinen, T. K., Miettinen, I. T., Martikainen, P. J., and Vartiainen, T., (2004). “Removal of soft deposits from the distribution system improves the drinking water quality.” Water Res., 38(3), 601–610.
Lopez-Ibanez, M. (2009). “Operation optimization of water distribution networks.” Ph.D. thesis, Edinburgh Napier Univ., Edinburgh, U.K.
Lopez-Ibanez, M., Prasad, T. D., and Paechter, B. (2008). “Ant colony optimization for optimal control of pumps in water distribution networks.” J. Water Resour. Plann. Manage., 337–346.
Monem, M. J., and Namdarian, R. (2005). “Application of simulated annealing (SA) techniques for optimal water distribution in irrigation canals.” Irrig. Drain., 54(4), 365–373.
Mouatasim, A. E. (2012). “Boolean integer nonlinear programming for water multireservoir operation.” J. Water Resour. Plann. Manage., 176–181.
Munavalli, G. R., and Kumar, M. S. M. (2003). “Optimal scheduling of multiple chlorine sources in water distribution systems.” J. Water Resour. Plann. Manage., 493–504.
Reca, J., Martinez, R., Gil, C., and Banos, R. (2008). “Application of several meta-heuristic techniques to the optimization of real looped water distribution networks.” Water Resour. Manage., 22(10), 1367–1379.
Riera, J., Kinard, J., Wilson, M., Haggen, W., Talton, E., and Reiss, C. (2012). “Water quality modeling targets and innovative nitrification strategies for City of St. Petersburg.” Florida Water Resour. J., 64(12), 38–45.
Rossman, L. A. (2002). EPANET 2.0: User’s manual, National Risk Management Research Laboratory, U.S. Environmental Protection Agency, Cincinnati, OH.
Savic, D. A., Kapelan, Z. S., and Jonkergouw, P. M. R. (2009). “Quo vadis water distribution model calibration?” Urban Water J., 6(1), 3–22.
Seidel, C. J., McGuire, M. J., Summers, R. S., and Via, S. (2005). “Have utilities switched to chloramines?” J. AWWA, 97(10), 87–97.
Teegavarapu, R. S. V., and Simonovic, S. P. (2002). “Optimal operation of reservoir systems using simulated annealing.” Water Resour. Manage., 16(5), 401–428.
Tospornsampan, J., Kita, I., Ishii, M., and Kitamura, Y. (2007). “Split-pipe design of water distribution network using simulated annealing.” Int. J. Comput. Inf. Eng., 1(3), 154–164.
U.S. Environmental Protection Agency. (2006). “The effectiveness of disinfectant residuals in the distribution system.”, Office of Ground Water and Drinking Water, Washington, DC.
Wang, X., Sun, Y., Song, L., and Mei, C. (2009). “An eco-environmental water demand based model for optimising water resource using hybrid genetic simulated annealing algorithms. Part I. Model development.” J. Environ. Manage., 90(8), 2628–2635.
Wu, Z. Y., Wang, R. H., Walski, T. M., Yang, S. Y., Bowdler, D., and Baggett, C. C. (2006). “Efficient pressure dependent demand model for large water distribution system analysis.” 8th Annual Int. Symp. on Water Distribution Systems Analysis, U.S. Environment Protection Agency, Washington, DC, 1–15.
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Published In
Journal of Water Resources Planning and Management
Volume 141 • Issue 6 • June 2015
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Feb 24, 2014
Accepted: Jul 21, 2014
Published online: Sep 2, 2014
Discussion open until: Feb 2, 2015
Published in print: Jun 1, 2015
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