Developing an Optimal Chlorination Pattern in Water Distribution System Utilizing Meta-Heuristic Algorithms

Document Type : Case study


1 PhD. Student in Water Structures, Dept. of Water Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 Assoc. Prof., in Water Structures, Dept. of Water Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

3 Lecturer, Dept. of Civil Engineering and Surveying, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran


Control of residual chlorine concentration within a desirable range throughout water distribution systems can cause the destruction of potentially harmful pathogens without chlorine adverse health effects & its toxic by-products. Hence, optimal scheduling of booster chlorination stations in the WDSs to ensure healthy water supply with the lowest dose of chlorine consumption is vital. The aim of the present study is to develop a multi-objective optimization model in order to minimize the mass injection rate as well as the probability of chlorine violation in the WDSs, which has been implemented in the MATLAB-EPANET platform. Multi-objective krill herd and multi-objective particle swarm optimization algorithms have been utilized as optimizers to obtain the desired Pareto front in the real-scale Brushy Plains network. The resulted Pareto fronts showed that in most of their solutions, as long as the mass injection rate increased, the probability of chlorine violation decreased. In this study, the solution with the less PCV in each Pareto was selected as the optimal solution to assure the healthy water supply. Though the MOPSO resulted Pareto showed more solution diversity, MKH optimal solution has a better MIR function than MOPSO optimal solution with the same amount of PCV. Analyzing the residual chlorine concentration profiles of the monitoring period corresponding to the MKH optimal solution showed that the chlorine concentration of the most nodes of Brushy Plains network exist in the desirable range of 0.2 to 0.8 mg/L and the residual chlorine of 100% of nodes exist in the range of 0.2 to 1.6 mg/L. Also, the MKH results are superior to those of the previous studies in terms of the total mass injection rate. Generally, in addition to economic advantages, minimizing chlorine injection rate and the probability of chlorine violation simultaneously in the water distribution systems reduces the adverse health effects of the disinfectant by-products.


Main Subjects

Ayala, H. V., Segundo, E. H., Mariani, V. C. & Coelho, L. D. S. 2015. Multiobjective krill herd algorithm for electromagnetic optimization. IEEE Transactions on Magnetics, 52, 1-4.
Behzadian, K., Alimohammadnejad, M., Ardeshir, A., Jalilsani, F. & Vasheghani, H. 2012. A novel approach for water quality management in water distribution systems by multi-objective booster chlorination. International Journal of Civil Engineering, 10(1), 51-60.
Boccelli, D. L., Tryby, M. E., Uber, J. G., Rossman, L. A., Zierolf, M. L. & Polycarpou, M. M. 1998. Optimal scheduling of booster disinfection in water distribution systems. Journal of Water Resources Planning and Management, 124, 99-111.
Coello, C. A. C. & Lamont, G. B. 2004. Applications of Multi-Objective Evolutionary Algorithms, World Scientific Pub., Toh Tuck Link, Singapore.
Coello, C. A. C., Pulido, G. T. & Lechuga, M. S. 2004. Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8, 256-279.
Cotruvo, J. A. 2017. 2017 WHO guidelines for drinking water quality: first addendum to the fourth edition. Journal-American Water Works Association, 109, 44-51.
Dini, M. & Tabesh, M. 2018. A new reliability index for evaluating the performance of water distribution network. Journal of Water and Wastewater, 29(3), 1-16. (In Persian). 51035.2154.
Hasanpour, Z., Shahinejad, B., Torabi Podeh, H. & Jabbary, A. 2022. Optimum design of water distribution networks utilizing optimization krill herd algorithm. Journal of Civil and Environmental Engineering, 51, 31-43. (In Persian).
Kurek, W. & Ostfeld, A. 2013. Multi-objective optimization of water quality, pumps operation, and storage sizing of water distribution systems. Journal of Environmental Management, 115, 189-197.
Maheshwari, A., Abokifa, A., Gudi, R. D. & Biswas, P. 2020. Optimization of disinfectant dosage for simultaneous control of lead and disinfection-byproducts in water distribution networks. Journal of Environmental Management, 276, 111186.
Munavalli, G. & Kumar, M. M. 2003. Optimal scheduling of multiple chlorine sources in water distribution systems. Journal of  Water Resources Planning and Management, 129, 493-504.
Nono, D. & Basupi, I. 2019. Robust booster chlorination in water distribution systems: design and operational perspectives under uncertainty. Journal of Water Supply: Research and Technology-AQUA, 68, 399-410.
Nouiri, I. 2017. Optimal design and management of chlorination in drinking water networks: a multi-objective approach using genetic algorithms and the Pareto optimality concept. Applied Water Science, 7, 3527-3538.
Pineda Sandoval, J. D., Brentan, B. M., Lima, G. M., Cervantes, D. H., García Cervantes, D. A., Ramos, H. M., et al. 2021. Optimal placement and operation of chlorine booster stations: a multi-level optimization approach. Energies, 14, 5806.
Rossman, L. 2000. EPANET 2 Users Manual, Water Supply and Water Resources Division, National Risk Management Research Laboratory: EPA/600/R-00/057. Cincinnatti, OH, USA.
Tabesh, M., Azadi, B. & Roozbahani, A. 2011a. Quality management of water distribution networks by optimizing dosage and location of chlorine injection. International Journal of Environmental Research, 5, 321-332.
Tabesh, M., Azadi, B. & Rouzbahani, A. 2011b. Optimization of chlorine injection dosage in water distribution networks using a genetic algorithm. Journal of Water and Wastewater, 22(1), 2-11. (In Persian).
Tryby, M. E., Boccelli, D. L., Koechling, M. T., Uber, J. G., Summers, R. S. & Rossman, L. A. 1999. Booster chlorination for managing disinfectant residuals. Journal-American Water Works Association, 91, 95-108.
Wang, Y. & Zhu, G. 2022. Fuzzy credibility-constrained quadratic optimization for booster chlorination of the water distribution system under uncertainty. AQUA-Water Infrastructure, Ecosystems and Society, 71, 608-627.
Xin, K., Zhou, X., Qian, H., Yan, H. & Tao, T. 2019. Chlorine-age based booster chlorination optimization in water distribution network considering the uncertainty of residuals. Water Supply, 19, 796-807.
Yoo, D. G., Lee, S. M., Lee, H. M., Choi, Y. H. & Kim, J. H. 2018. Optimizing re-chlorination injection points for water supply networks using harmony search algorithm. Water, 10, 547.