Journal of Water and Wastewater; Ab va Fazilab (in persian)

Journal of Water and Wastewater; Ab va Fazilab (in persian)

Multi-Objective Optimization of Pressure-Reducing Valves Operation in Extreme Water Consumption Scenarios (Case Study: Najaf Abad Urban Water Distribution Network)

Document Type : Research Paper

Authors
1 PhD. in Civil Engineering-Water Resources Management, Civil Engineering and Transportation Faculty, University of Isfahan, Isfahan, Iran
2 Assoc. Prof. of Civil Engineering-Water Resources Management, Civil Engineering and Transportation Faculty, University of Isfahan, Isfahan, Iran
Abstract
Pressure and residual chlorine concentration are among the key parameters in urban water distribution networks that require continuous monitoring and control. These networks must ensure that consumer water demands are met with adequate pressure while optimizing water quality parameters, such as residual chlorine concentration, to maximize service satisfaction. In this study, the Najaf Abad urban water distribution network was selected as a real large-scale case study. A simultaneous optimization model was developed to determine nodal average pressure, residual chlorine concentration, and network combined reliability. The multi-objective optimization problem was solved using the NSGA-II algorithm under two extreme water consumption scenarios-maximum and minimum water withdrawal during warm and cold seasons. A Pressure-Driven Analysis approach was employed to calculate network parameters. Additionally, three objective functions were optimized using the NSGA-II multi-objective optimization algorithm. The optimal solution was selected from the Pareto front using the TOPSIS method. The network under study includes four operational pressure-reducing valves; after determining their optimal set pressure values, the average network pressure was reduced by 2.9% during ward days and 13.5% during cold days. The average residual chlorine concentration did not undergo significant changes however, its further reduction was prevented through optimization, effectively achieving this objective as well. Lastly, the combined reliability increased by 1.7% and 1.3% for warm and cold days, respectively.
Keywords

AbdelMeguid, H. and Ulanicki, B., 2010. Pressure and leakage management in water distribution systems via flow modulation PRVs. Water Distribution Systems Analysis, 1124-1139. https://doi.org/10.1061/41203(425)102.
Ardeshir, A., Behzadian, K., Alimohamadnejad, M., Jalilsani, F. and F‌o‌r‌u‌t‌a‌n A‌l‌i‌z‌a‌d‌e‌g‌a‌n, H., 2017. O‌p‌t‌i‌m‌a‌l chlo‌r‌i‌n‌a‌t‌i‌o‌n o‌f w‌a‌t‌e‌r d‌i‌s‌t‌r‌i‌b‌u‌t‌i‌o‌n s‌y‌s‌t‌e‌m‌s w‌i‌t‌h r‌e‌s‌p‌e‌c‌t r‌e‌s‌i‌d‌u‌a‌l c‌h‌l‌o‌r‌i‌n‌e a‌n‌d f‌o‌r‌m‌a‌t‌i‌o‌n o‌f T‌H‌M. Sharif Journal of Civil Engineering, 33(3.1), 21-29. (In Persian). https://doi.org/10.24200/j30.2017.20073.
Bazovski, I., 1961. Reliability Theory and Practice, Prentic Hall, Englewood. New Jersey.
Coello, C. A. C., Lamont, G. B. and Veldhuizen, D. A. V., 2007. Evolutionary Algorithms for Solving Multi-Objective Problems. Springer, New York, NY. https://doi.org/10.1007/978-0-387-36797-2.
De Paola, F., Giugni, M. and Portolano, D., 2017. Pressure management through optimal location and setting of valves in water distribution networks using a music-inspired approach. Water Resources Management, 31(5), 1517-1533. https://doi.org/10.1007/s11269-017-1592-y.
Deb, K., Pratap, A., Agarwal, S. and Meyarivan, T., 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197. https://doi.org/10.1109/4235.996017.
Dini, M. and Asadi, A., 2020. Optimal operational scheduling of available partially closed valves for pressure management in water distribution networks. Water Resources Management, 34, 2571-2583. https://doi.org/10.1007/s11269-020-02579-4.
Dini, M. and Tabesh, M., 2019. Optimal renovation planning of water distribution networks considering hydraulic and quality reliability indices. Urban Water Journal, 16(4), 249-258. https://doi.org/10.1080/1573062X.2019.1669185.
Dini, M., Mohammadikaleibar, A., Hashemi, S. and Nourani, V., 2022. Stochastic long-term reliability of water distribution networks using Monte Carlo simulation. Urban Water Journal, 19(2), 151-160. https://doi.org/10.1080/1573062X.2021.1971264.
Fernández García, I., Ferras, D. and Mc Nabola, A., 2019. Potential of energy recovery and water saving using micro-hydropower in rural water distribution networks. Journal of Water Resources Planning and Management, 145(3), 05019001. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001045.
Ferrarese, G., Fontana, N., Gioffreda, S., Malavasi, S. and Marini, G., 2022. Pressure reducing valve setting performance in a variable demand water distribution network. Environmental Sciences Proceedings, 21(1), 61. https://doi.org/10.3390/environsciproc2022021061.
Hwang, C. L., Yoon, K., 1981. Methods for multiple attribute decision making. In: Hwang, C. L. and Yoon, K., Ed. Multiple Attribute Decision Making: Methods and Applications a State-of-the-Art Survey, Springer, Berlin, Heidelberg. pp. 58-191. https://doi.org/10.1007/978-3-642-48318-9_3.
Jazayeri, P., Safavi, H., Nazemizadeh, M., Ebrahimi, M. S. and Rahmatpanah, A., 2024. Daily urban water consumption prediction and optimization of pumping station operation hours: a case study of Najaf Abad. Journal of Water and Wastewater Science and Engineering, 9(3), 17-28. https://doi.org/10.22112/jwwse.2024.411391.1373
Khashei, M., Tabesh, M., Shahangian, S. A. and Abbasi, M., 2022. The effect of demand management using optimal pressure regulation in WDNs during normal and water scarcity conditions. Journal of Water and Wastewater, 33(5), 1-18. (In Persian). https://doi.org/10.22093/wwj.2022.318859.3206.
Koşucu, M. M. and Demirel, M. C., 2024. Cost efficiency assessment of four pressure management methods in water distribution systems. Journal of Water Resources Planning and Management, 150(3), 05023022. https://doi.org/10.1061/JWRMD5.WRENG-5984.
Kyriakou, M. S., Demetriades, M., Vrachimis, S. G., Eliades, D. G. and Polycarpou, M. M., 2023. EPyT: an EPANET-Python Toolkit for smart water network simulations. Journal of OpenSource Software, 8(92), 5947. https://doi.org/10.21105/joss.05947.
Lambora, A., Gupta, K. and Chopra, K., 2019. Genetic algorithm-a literature review. In 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon), 380-384. https://doi.org/10.1109/COMITCon.2019.8862255.
Moslehi, I., Ghazizadeh, M. J. and Yousefi-Khoshqalb, E., 2020. An economic valuation model for alternative pressure management schemes in water distribution networks. Utilities Policy, 67, 101129. https://doi.org/10.1016/j.jup.2020.101129.
Patelis, M., Kanakoudis, V. and Kravvari, A., 2020. Pressure regulation vs. water aging in water distribution networks. Water, 12(5), 1323. https://doi.org/10.3390/w12051323.
Vazifehdoest Saleh, P., Yazdi, J. and Moridi, A., 2024. Pressure management in water distribution networks with optimal placement of pressure relief valve and pump as turbine. Journal of Water and Wastewater Science and Engineering, 9(2), 31-42. (In Persian). https://doi.org/10.22112/jwwse.2023.389161.1355.
Wagner, J. M., Shamir, U. and Marks, D. H., 1988. Water distribution reliability: simulation methods. Journal of Water Resources Planning and Management, 114(3), b276-294. https://doi.org/10.1061/(ASCE)0733-9496(1988)114:3(276).