Impact of Optimized Pump Scheduling on Water Quality in Distribution Systems
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 11, Issue 4
Abstract
Pump scheduling can improve performance of water supply systems, but it may have a different effect on water quality. The target of this article is to examine optimized pump schedules’ impact on water quality. EPANET’s quality simulator is applied for modeling water age and chlorine residuals through extended period simulations within two distribution networks: optimized and nonoptimized pumps. Results indicate that optimized pumps, in our case study, can improve water quality in and around the storage tank because they produce shorter tank filling and emptying, but they increase water retention time and reduce disinfectant residuals within most network pipes. Leakage can cause some pipes in the optimized network to have chlorine concentrations under the standard level (). In addition, the average rate of chlorine decay for the optimized system (36%) is faster than that of the nonoptimized one (33%) when a reactive contaminant is considered. Overall, these results indicate that hydraulic benefits and water quality must be considered together for pump scheduling problems.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Anytown network data and EPANET files.
References
Abdelaziz, A., and E. Mourad. 2017. “Optimization of technical computing chlorine in a network of drinking water distribution.” ARPN J. Eng. Appl. Sci. 12 (3): 919–930.
AwwaRF (Awwa Research Foundation). 2005. Impact of distribution system water quality on disinfection efficacy. Denver: AwwaRF.
Biscos, C., M. Mulholland, M. V. Le Lann, C. A. Buckley, and C. J. Brouckaet. 2003. “Optimal operation of water distribution networks by predictive control using MINLP.” Water SA 29 (4): 393–404. https://doi.org/10.4314/wsa.v29i4.5044.
Boryczko, K., and B. Tchórzewska-Cieślak. 2014. “Analysis of risk of failure in water main pipe network and of delivering poor quality water.” J. Environ. Prot. Eng. 40 (4): 77–92. https://doi.org/10.37190/epe140407.
Branz, A., M. Levine, L. Lehmann, A. Bastable, S. A. Imran, K. Kadir, T. Yates, D. Bloom, and D. Lantagne. 2017. “Chlorination of drinking water in emergencies: A review of knowledge to develop recommendations for implementation and research needed” J. Waterlines 36 (1): 4–39. https://doi.org/10.3362/1756-3488.2017.002.
Cuesta Cordoba, G. A., L. Tuhovčáka, and M. Tauš. 2014. “Using artificial neural network models to assess water quality in water distribution networks.” Procedia Eng. 70: 399–408. https://doi.org/10.1016/j.proeng.2014.02.039.
Darweesh, M. S. 2018a. “Assessment of variable speed pumps in water distribution systems considering water leakage and transient operations.” J. Water Supply Res. Technol. AQUA 67 (1): 99–108. https://doi.org/10.2166/aqua.2017.086.
Darweesh, M. S. 2018b. “Impact of variable speed pumps on water quality in distribution systems.” Water SA 44 (3): 419–427. https://doi.org/10.4314/wsa.v44i3.09.
Duzinkiewicz, K., M. A. Brdys, and T. Chang. 2005. “Hierarchical model predictive control of integrated quality and quantity in drinking water distribution systems.” Urban Water J. 2 (2): 125–137. https://doi.org/10.1080/15730620500144043.
Gibbs, M. S., G. C. Dandy, and H. R. Maier. 2010. “Calibration and optimization of the pumping and disinfection of a real water supply system.” J. Water Resour. Plann. Manage. 136 (4): 493–501. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000060.
Kim, H., and S. Kim. 2017. “Evaluation of chlorine decay models under transient conditions in a water distribution system.” J. Hydroinf. 19 (4): 522–537. https://doi.org/10.2166/hydro.2017.082.
Kurek, W., and A. Ostfeld. 2014. “Multi-objective water distribution systems control of pumping cost, water quality, and storage-reliability constraints.” J. Water Resour. Plann. Manage. 140 (2): 184–193. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000309.
Monteiro, L., D. Figueiredo, S. Dias, R. Freitas, D. Covas, R. Menaia, and S. T. Coelho. 2014. “Modeling of chlorine decay in drinking water supply systems using EPANET-MSX.” Procedia Eng. 70: 1192–1200. https://doi.org/10.1016/j.proeng.2014.02.132.
Ozdemir, O. N., and M. E. Ucaner. 2005. “Success of booster chlorination for water supply networks with genetic algorithms.” J. Hydraul. Res. 43 (3): 267–275. https://doi.org/10.1080/00221680509500121.
Quintiliani, C., and E. Creaco. 2019. “Using additional time slots for improving pump control optimization based on trigger levels.” J. Water Resour. Manage. 33 (9): 3175–3186. https://doi.org/10.1007/s11269-019-02297-6.
Raei, E., M. E. Shafiee, M. R. Nikoo, and E. Berglund. 2019. “Placing an ensemble of pressure sensors for leak detection in water distribution networks under measurement uncertainty.” J. Hydroinf. 21 (2): 223–239. https://doi.org/10.2166/hydro.2018.032.
Rossman, L. A. 2000. EPANET 2 user’s manual. Cincinnati: USEPA.
Sakarya, A., and L. Mays. 2000. “Optimal operation of water distribution pumps considering water quality.” J. Water Resour. Plann. Manage. 126 (4): 210–220. https://doi.org/10.1061/(ASCE)0733-9496(2000)126:4(210).
Savić, D. A., J. Bicik, and M. S. Morley. 2011. “A DSS generator for multiobjective optimization of spreadsheet-based models.” J. Environ. Modell. Software 26 (5): 551–561. https://doi.org/10.1016/j.envsoft.2010.11.004.
Solgi, M., O. Bozorg-Haddad, S. Seifollahi-Aghmiuni, P. Ghasemi-Abiazani, and A. H. Loaiciga. 2016. “Optimal operation of water distribution networks under water shortage considering water quality.” J. Pipeline Syst. Eng. Pract. 7 (3): 04016005. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000233.
Tabesh, M., B. Azadi, and A. Roozbahani. 2011. “Quality management of water distribution networks by optimizing dosage and location of chlorine injection.” Int. J. Environ. Res. (IJER) 5 (2): 321–332. https://doi.orgl10.22059/IJER.2011.317.
Uber, J., M. Polycarpou, F. Shang, and Z. Wang. 2002. Autonomous feedback control of booster chlorination systems for distribution system residual maintenance. Denver: American Water Works Association and AWWA Research Foundation.
USEPA. 2002. Effects of water age on distribution system water quality. Washington, DC: Office of Ground Water and Drinking Water, USEPA.
van Zyl, J. E., and R. Malde. 2017. “Evaluating the pressure-leakage behaviour of leaks in water pipes.” J. Water Supply Res. Technol. AQUA 66 (5): 287–299. https://doi.org/10.2166/aqua.2017.136.
Walski, T. M., et al. 1987. “Battle of the network models: Epilogue.” J. Water Resour. Plann. Manage. 113 (2): 191–203. https://doi.org/10.1061/(ASCE)0733-9496(1987)113:2(191).
Walski, T. M. 1995. “Optimization and pipe-sizing decisions.” J. Water Resour. Plann. Manage. 121 (4): 340–343. https://doi.org/10.1061/(ASCE)0733-9496(1995)121:4(340).
WHO (World Health Organization). 2011. Guidelines for drinking-water quality. 4th ed. Geneva: WHO.
Xie, X., B. Zeng, and M. Nachabe. 2015. “Sampling design for water distribution network chlorine decay calibration.” Urban Water J. 12 (3): 190–199. https://doi.org/10.1080/1573062X.2013.831911.
Yu, G., R. S. Powell, and M. G. Sterling. 1994. “Optimized pump scheduling in water distribution systems.” J. Optim. Theory Appl. 83 (3): 463–488. https://doi.org/10.1007/BF02207638.
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©2020 American Society of Civil Engineers.
History
Received: Oct 31, 2019
Accepted: Apr 24, 2020
Published online: Jun 19, 2020
Published in print: Nov 1, 2020
Discussion open until: Nov 19, 2020
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