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

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

Optimization of Intermittent Water Supply Systems Using Particle Swarm Optimization Algorithm and Pressure Driven Hydraulic Analysis

Document Type : Research Paper

Authors
Massoud Tabesh 1
Reza Safaiee Broujeni 2
Akbar Shirzad 3
Meisam Shokoohi 2
1 Prof., Center of Excellence for Engineering and Management of Civil Infrastructures, School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran
2 MSc Student, School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran
3 Assist. Prof., Faculty of Civil Engineering, Urmia University of Technology, Urmia, Iran
10.22093/wwj.2019.108365.2553
Abstract
In this research, intermittent water supply is optimized using pressure driven hydraulic analysis and particle swarm optimization algorithm with the aim of maximizing the uniformity of water distribution in the network and reliability. In the following, by calculating the resiliency as an efficiency criterion, system performance is evaluated. Obtain­ed results from pressure driven hydraulic analysis and demand driven hydraulic analysis are compared. In this regard, the particle swarm optimization algorithm and the EPANET hydraulic analysis model are linked. Pressure driven hydraulic analysis is performed by applying some modifications on the hydraulic calculation process. The proposed model is evaluated on a sample network in several water shortage scenarios. According to the obtained results, the objective function (uniformity of water distribution) has higher values for the scenarios with lower water shortage, so that the maximum value is relevant to the scenario without water shortage. The values of the objective function for scenarios with pressure driven hydraulic analysis are 20% more than its values for scenarios with demand driven hydraulic analysis. By comparing the values obtained for system efficiency criteria it can be observed that the network resiliency and nodal resiliency for most of the scenarios with demand driven hydraulic analysis are more than their values for scenarios with pressure driven hydraulic analysis. This is because of the independency of nodal discharge from nodal pressure in demand driven hydraulic analysis that leads to unreal values for nodal discharges and therefore, hydraulic failure accrues rarely. The maximum value achieved for resiliency is around 99% which is relevant to efficiency threshold of 70% in nodal form. Uniformity and equity of water distribution between demand nodes and as a result satisfaction of stakeholders can be maximized by using optimization models. Employing pressure driven hydraulic analysis models makes it possible to simulate the behavior of water distribution networks realistically.
Keywords
Water Shortage
Intermittent Supply
Pressure Driven Hydraulic Analysis
Particle Swarm Optimization Algorithm
Resiliency
Alperovits, E., & Shamir, U. 1977. Design of optimal water distribution systems. Water Resource Research, 13(6), 885-900.
Ameyaw E. E., Memon F. A., & Bicik J. 2013. Improving equity in intermittent water supply systems. Journal of Water Supply: Research and Technology-AQUA, 62(8), 552-562.
Andey, S. P., & Kelkar, P. S. 2009. Influence of intermittent and continuous modes of water supply on domestic water consumption. Water Resources Management, 23(12), 2555-2566.
Bozorg-Haddad, O., Hoseini-Ghafari, S., Solgi, M., & Loaiciga, H. A. 2016. Intermittent urban water supply with protection of consumers’ welfare. Journal of Pipeline Systems Engineering and Practice, 7(3), 04016002.
Coelho, S. T., James, S., Sunna, N., Jaish, A. A., & Chatila, J. 2003. Controlling water quality in intermittent supply systems. Water Supply, 3(1-2), 119-125.
De Marchis, M., Fontanazza, C. M., Freni, G., La Loggia, G., Napoli, E.,& Notaro V. 2010. Modelling analysis of distribution network filling process during intermittent supply. In Proceedings of Computing and Control in the Water Industry, Boxal and Maksimovic, Taylor and Francis Group, London, 189-194.
Eberhart, R. C., & Kennedy, J. 1995. A new optimizer using particle swarm theory. In Proceedings of the 6th International Symposium on Micro Machine and Human Science, Nagoya, Japan, 1, 39-43.
Hashimoto, T., Stedinger, J. R., & Loucks, D. P. 1982. Reliability, resiliency and vulnerability criteria for water resources system performance evaluation. Water Resources Research, 18(1), 14-20.
Ingeduld, P., Pradhan, A., Svitak, Z., & Terrai, A. 2006. Modelling intermittent water supply systems with EPANET. 8th Annual Water Distribution Systems Analysis Symposium, Cincinnati, USA, 1-8.
Islamic Republic of Iran Vice Presidency for Strategic Planning and Supervision (IRIVPSPS). 2011. Guidelines for design of urban and rural water supply and distribution systems, Report No. 117-3 (First Revision), Islamic Republic of Iran Vice Presidency for Strategic Planning and Supervision Press. (In Persian)
Karimi, M., Ahrar Yazdi, B., & Ahrar Yazdi, B. 2017. Comparison of particle swarm optimization and genetic algorithm for optimization of CGAM problem. Sharif Journal of Mechanical Engineering, 33.3(1), 129-136. (In Persian)
Samsami, R. 2013. Comparison between genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO) techniques for NOx emission forecasting in Iran. World Applied Sciences Journal, 28(12), 1996-2002.
Sashikumar, N., Mohankumar, M. S., & Sridharan, K. 2003. Modeling an intermittent water supply. In Proceedings of World Water and Environmental Resources Congress, USA, June, 23-26.
Shirzad, A., Tabesh, M., Farmani, R., & Mohammadi, M. 2013. Pressure-discharge relations with application in head driven simulation of water distribution networks. Journal of Water Resources Planning and Management, 139(6), 660-670.
Shokoohi, M., Tabesh, M., & Nazif, S. 2017. Water quality based multi-objective optimal design of water distribution systems. Water Resources Management, 31(1), 93-108.
Soltanjalili, M., Bozorg Haddad, O., & Marino, M. A. 2013. Operating water distribution networks during water shortage conditions using hedging and intermittent water supply concepts. Journal of Water Resources Planning and Management, 139(6), 644-659.
Tabesh, M., & Zia, A. 2003. Dynamic management of water distribution networks based on hydraulic performance analysis of the system. Journal of Water Science and Technology: Water Supply, 3(1-2), 95-102.
Vairavamoorthy, K. 1994. Water distribution networks: design and control for intermittent supply. PhD Thesis, Imperial College of Science, Technology and Medicine, London UK.
Vairavamoorthy, K., Gorantiwar, S. D., & Mohan, S. 2007. Intermittent water supply under water scarcity situations. Water International, 32(1), 121-132.
Wagner, J., Shamir, U., & Marks, D. 1988. Water distribution reliability: simulation methods. Journal of Water Resources Planning and Management, 114(3), 276-294.
Journal of Water and Wastewater; Ab va Fazilab (in persian)
Volume 31, Issue 3 - Serial Number 127
July and August 2020
Pages 12-25