Optimal Operation of Water Resources Systems by Using MOPSO Multi-Objective Algorithm

Document Type : Research Paper


1 University of Ahvaz

2 Razi University of Kermanshah


In this study, a method is proposed by using a multi-objective structure and employing new formulations, in which instead of increasing reliability based on meeting a demand of 100 percent in some months regardless of the dry months, part of the water of wet months or seasons is stored in reservoirs so that it can be used in dry months in order to amend failure intensity. To this end, Multi-Objective Particle Swarm Optimization (MOPSO) algorithm was connected to the WEAP simulation model. The main purpose of this type of structures is to offer a resolution to increase the percentage of demand coverage in dry months in addition to reaching to an acceptable demand meeting reliability over the entire period considering the operation capacity of the reservoir. Ultimately, the results of three scenarios, including a current situation, land development management scenario and an optimization one, were evaluated. According to the results of the current situation scenario, in all of the operation period the situation was reported acceptable, except for a few months. In land development scenario, for most consumptions in most of the dry years and in the last six years of planning, the demand coverage was equal to zero in three to eight consecutive dry months, and it was lower than 5% in these months in the rest of the low-water years. On the other hand, the demand coverage increased from 28% to 60% in these months by implementing the optimization model. Also, in the optimal scenario of reliability, supplying downstream environmental demand and Maroon hydroelectric dam need was improved. This study depicts that using the strategies of this research will lead to a better reservoir management and will reduce failure intensity in supplying different consumptions during low-water months.


Main Subjects

Aboutalebi, M., Bozorg Haddad, O. and Loáiciga H.A. (2015). Optimal Monthly Reservoir Operation Rules for Hydropower Generation Derived with SVR-NSGAII. Journal of Water Resources Planning and Management, 141(11), 04015029-9.
Ashofteh, P. S, Bozorg Haddad, O. and Loáiciga H.A. (2015). Evaluation of Climatic-Change Impacts on Multiobjective Reservoir Operation with Multiobjective Genetic Programming. Journal of Water Resources Planning and Management, 141(11), 04015030-9.
Azarafza, H., Rezaei, H., Behmanesh, J. and Besharat, S. (2012). Results Comparison of Employing PSO, GA and SA Algorithms in Optimizing Reservoir Operation (Case Study: Shaharchai Dam, Urmia, Iran). Journal of Water and Soil, 26(5), 1101-1108. (In Farsi)
Azari, A., Akhoond-Ali, A.M., Radmanesh, F. and Haghighi, A. (2015). Groundwater–Surface Water Interaction Simulation in Terms of Integrated Water Resource Management (Case Study: Dez Plain). Journal of Irrigation Science and Engineering, 38(2), 33-47. (In Farsi)
Borhani Dariane, A. and Mortazavi Naeini, S.A. (2008). Comparison of Heuristic Methods Applied for Optimal Operation of Water Resources. Water and Waste Water, 19(4), 57-66. (In Farsi)
Coello C. A., Pulido G. T. and Lechuga M. S. (2004). Handling Multiple Objectives with Particle Swarm Optimization. IEEE Transactions on Evolutionary Computation Journal, 8(3)
Dariane, A.B. and Moradi, A.M. (2008). Reservoir Operating by Ant Colony Optimization for Continuous Domains (ACOR) Case Study: Dez Reservoir. World Academy of Science, Engineering and Technology, International Journal of Civil, Environmental, Structural, Construction and Architectural Engineering, 2(7), 136-140
Esat, V. and Hall, M.J. (1994). Water resources system optimization using genetic algorithms. Hydroinformatics '94, In: Proceedings 1st International Conference on Hydroinformatics, Balkema, Rotterdam, the Netherlands, pp. 225-231.
Fahmy, H.S., King, J.P., Wentzel, M.W. and Seton, J.A. (1994). Economic optimization of river management using genetic algorithms. Paper No. 943034, ASAE 1994 International Summer Meeting, American Society Of Agricultural Engineers. St. Joseph, Mich
Garousi-Nejad, I., Bozorg-Haddad, O., Loáiciga, H.A. and Mari˜no, M.A. (2016). Application of the Firefly Algorithm to Optimal Operation of Reservoirs with the Purpose of Irrigation Supply and Hydropower Production, Journal of Irrigation and Drainage Engineering, 142(10)
Hojati, A., Farid-Hoseini, A., Ghahreman, B. and Alizadeh, A. (2013) Comparison of heuristic techniques in multi-objective optimization of water resources systems. Iran Water and Environmental Engineering, 1(2): 9-14.
Jalali, M.R., Afshar,A. and Marino,M.A. (2006). Reservoir Operation by Ant Colony Optimization Algorithms. Iranian Journal of Science & Technology, 30(B1), 107-117
Kennedy, J. and Eberhart, R. (1995). Particle Swarm Optimization. In: Proceedings of the IEEE International Conference on Neural Networks, Perth, Australia, 1942-1945.
Moeini,R., Afshar,M.H. (2009). Application of an Ant Colony Optimization Algorithm for Optimal Operation of Reservoirs: A Comparativ Study of Three Proposed Formulations. Scientia Iranica, Transaction A: Civil Engineering, 16(4), 273-285
Nabi Nejad, Sh. and Mousavi, S.J. (2013). Simulation-optimization for Basin-wide Optimum Water AllocationConsidering System’s Performance and Equity Measures. Water and Waste Water, Vol. 24, Number 2 (86), 70-79 (In Farsi)
Oliveira, R. and Loucks, D. (1997). Operating rules for multireservoir systems. Water Resource Research, 33(4), 839–852.
Rafiee Anzab,N., Mousavi,S.J., Rousta,B.A. and Kim,J.H. (2016). Simulation Optimization for Optimal Sizing of Water Transfer Systems. In: Proceedings of the 2nd International Conference on Harmony Search Algorithm (ICHSA2015) 382, 365-375.
Rezaei, F., Safavi, H. R., Mirchi, A. and Madani K. (2016). f-MOPSO: An alternative multi-objective PSO algorithm for conjunctive water use management. Journal of Hydro-environment Research, 14 (2016), 1–18.
Saber Chenari, K., Abghari, H., Erfanian, M. and Gholizadeh, S. (2013).Short-term model of optimization operation of water resources using particle swarm optimization and comparedwith genetic algorithm. Watershed Management Research (Pajouhesh & Sazandegi), No. 97, 63-72 (In Farsi)
SaberChenari, K., Abghari, H. and Tabari, H. (2016). Application of PSO algorithm in short-term optimization of reservoir operation. Environmental Monitoring and Assessment, (2016) 188-667.
Shourian,m., Mousavi,S.J. and Tahershamsi,A., (2008). Basin-wide Water Resources Planning by Integrating PSO Algorithm and MODSIM. Water Resources Management 22,1347–1366
Zhang,J., Wu, Z., Cheng,C. and Zhang,S. (2011) Improved particle swarm optimization algorithm for multi-reservoir system operation. Water Science and Engineering, 4(1), 61-73