Abstract
The optimization of the operation of existing water systems such as dams is very important for water resource planning and management especially in arid and semi-arid lands. Due to budget and operational water resource limitations and environmental problems, the operation optimization is gradually replaced by new systems. The operation optimization of water systems is a complex, nonlinear, multi-constraint, and multidimensional problem that needs robust techniques. In this article, the practical swarm optimization (PSO) was adopted for solving the operation problem of multipurpose Mahabad reservoir dam in the northwest of Iran. The desired result or target function is to minimize the difference between downstream monthly demand and release. The method was applied with considering the reduction probabilities of inflow for the four scenarios of normal and drought conditions. The results showed that in most of the scenarios for normal and drought conditions, released water obtained by the PSO model was equal to downstream demand and also, the reservoir volume was reducing for the probabilities of inflow. The PSO model revealed a good performance to minimize the reservoir water loss, and this operation policy can be an appropriate policy in the drought condition for the reservoir.
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Abraham, A., Guo, H., & Liu, H. (2006). Swarm intelligence: foundations. Perspectives and Applications, 26, 3–25. doi:10.1007/978-3-540-33869-7_1.
Ahmadianfar, I., Adib, A., & Taghian, M. (2016). Optimization of fuzzified hedging rules for multipurpose and multireservoir systems. Journal of Hydrologic Engineering, 21(4), 1–10.
Asfaw, T. D., & Saiedi, S. (2011). Optimal short-term cascade reservoir operation using genetic algorithm. Asian Journal of scientific Research, 4(3), 297–305.
Baltar, A. M., & Fontane, D. G. (2008). Use of multiobjective particle swarm optimization in water resources management. ASCE Journal of Water Resources Planning and Management, 134(3), 257–265.
Becker, L., & Yeh, W. W. G. (1974). Optimization of real time operation of a multiple-reservoir system. Water Resources Research, 10(6), 1107–1112.
Carlisle, A. & Dozier, G. (2001). An off-the-self PSO. Proceeding of the particle swarm optimization workshop, pp. 16.
Chau, K. W. (2004). Rainfall-runoff correlation with particle swarm optimization algorithm. Lecture Notes in Computer Science, 3174, 970–975.
Chau, K. W. (2006). Particle swarm optimization training algorithm for ANNs in stage prediction of Shing Mun River. Journal of Hydrology, 329(3–4), 363–367.
Chu, H., & Chang, L. C. H. (2009). Applying particle swarm optimization to parameter estimation of the nonlinear Muskingum model. Journal of Hydrologic Engineering, 14(9), 1024–1027.
Cyriac, R. & Rastogi, A. K. (2013). An overview of the applications of particle swarm in water resources optimization, Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012), advances in intelligent systems and computing, (202), 41–52.
Dariane, A. B. (1999). Optimization of reservoir operation during droughts by hedging rule, hydrology days, proceedings of the Nineteenth Annual American Geophysical Union, Colorado State University, Fort Collins, 84–96.
Dariane, A. B. (2003). Reservoir operation during drought. International Journal of Engineering Transactions, 16(3), 209–216.
Ebrahinifarsangi, H. (2002). Topological optimization of double layer grids using genetic algorithm. Ph.D Thesis, University of Surry, England.
Felfelani, F., Jalali Movahed, A., & Zarghami, M. (2013). Simulating hedging rules for effective reservoir operation by using system dynamics: a case study of Dez Reservoir, Iran. Lake and Reservoir Management, 29(2), 126–140.
Gholizadeh, S., & Seyedpoor, S. M. (2011). Shape optimization of arch dams by metaheuristics and neural networks for frequency constraints. Scientia Iranica, Transaction A; Civil Engineering, 18(5), 1020–1027.
Hashemi, M. S., Barani, G. A., & Ebrahimi, H. (2008). Optimization of reservoir operation by genetic algorithm considering inflow probabilities (case study: the Jiroft dam reservoir). Journal of Applied Sciences, 8(11), 2173–2177.
He, Q., & Wang, L. (2007). An effective co-evolutionary particle swarm optimization for constrained engineering design problems. Engineering Applications of Artificial Intelligence, 20(1), 89–99.
Hu, T., Zhang, X., Zeng, X., & Wang, J. (2016). A two-step approach for analytical optimal hedging with two triggers. Water journal, 8(52), 1–22.
Izquierdo, J., Montalvo, I., Perez, R., & Fuertes, V. (2008). Design optimization of wastewater collection networks by PSO. Computers and Mathematics with Applications, 56(3), 777–784.
Kennedy, J. (1998). The behavior of particles. In: Porto V. W., Saravanan N., Waagen D. and Eiben A. E. (Eds.), Evolutionary Programming VII, 581–590.
Kennedy, J. & Eberhart, R. C. (1995). Particle swarm optimization. In: Proceedings of the 1995 I.E. International Conference on Neural Networks, IEEE Service Center, Piscataway, NJ, 1942–1948.
Kennedy, J., Eberhart, R. C., & Shi, Y. (Eds.) (2001). Swarm intelligence. San Francisco: Morgan Kaufmann.
Khanjari Sadati, S., Speelman, S., Sabouhi, M., Gitizadeh, M., & Ghahraman, B. (2014). Optimal irrigation water allocation using a genetic algorithm under various weather conditions. Water journal, 6(10), 3068–3084.
Kumar, D. N., & Reddy, M. J. (2007). Multipurpose reservoir operation using particle swarm optimization. Journal of Water Resources Planning and Management, 133(3), 192–201.
Labadie, J. (2004). Optimal operation of multireservoir systems: state of the art review. Journal of Water Resources Planning and Management., 130(2), 93–111.
Mathur, Y. P., & Nikam, S. J. (2009). Optimal reservoir operation policies using genetic algorithm. International Journal of Engineering and Technology, 1(2), 184–187.
Monem, M. J., & Nouri, M. A. (2010). Application of PSO method for optimal water delivery in irrigation networks. Iranian Journal of Irrigation and Drainage, 4(1), 73–82.
Montalvo, I., Izquierdo, J., Perez, R., & Tong, M. M. (2008). Particle swarm optimization applied to the design of water supply system. Computers and Mathematics with Applications, 56(3), 769–776.
Moradi-Jalal, M., Haddad, O. B., Marino, M. A., & Karney, B. W. (2007). Reservoir operation in assigning optimal multi-crop irrigation areas. Journal of Agriculture Water Management, 90(1–2), 149–159.
Parsopoulos, K., & vrahatis, M. N. (2002). Particle swarm optimization method for constrained optimization problem. Frontiers in Artificial Intelligence and Applications, 76, 214–220.
Rani, D., & Moreira, M. M. (2010). Simulation-optimization modeling: a survey potential application in reservoir systems operation. Water Resources Management, 24(6), 1107–1138.
Russell, S., & Campbell, P. (1996). Reservoir operating rules with fuzzy programming. Journal of Water Resources Planning and Management, 3(165), 165–170.
Schardong, A. & Simonovic, S. P. (2011). Multi-Objective Evolutionary Algorithms of Water Resources Management. Water Resources Research Report. Report No. 078, Department of Civil and Environmental Engineering, University of Western Ontario, Canada.
Shi, Y. & Eberhart, R. A. (1998a). Parameter selection in particle swarm optimization. In: Proceedings of the Seventh Annual Conference on Evolutionary Programming. New York, 591–600.
Shi, Y., & Eberhart R.A. (1998b). A modified particle swarm optimizer. In: Proceedings of the IEEE international conference on evolutionary computation. Anchorage, Alaska. 69–73.
Shi, Y. H., & Eberhart, R. A. (1999). Empirical study of particle swarm optimization. IEEE Proc Cong Evol Comput., 3, 1945–1950.
Shih, J. S., & Revelle, C. (1994). Water supply operation during drought: continuous edging rule. Journal of Water Resources Planning and Management, 120(5), 613–629.
Shih, J. S., & Revelle, C. (1995). Water supply operation during drought: a discrete hedging rule. European Journal of Operation Resources., 82, 163–175.
Simonovic, S. P., & Savic, D. A. (1989). Intelligent decision support and reservoir management and operations. Journal computing Civil Engineering, 3(4), 367–385.
Taghian, M., Rosbjerg, D., Haghighi, A., & Madsen, H. (2014). Optimization of conventional rule curves coupled with hedging rules for reservoir operation. Journal of Water Resources Planning and Management, 140(5), 693–698.
Wurbs, R. (1993). Reservoir system simulation and optimization models. Journal of Water Resources Planning and Management, 19(4), 455–472.
Yeh, W. W. G. (1985). Reservoir management and operations models: a state of the-art review. Water Resources Research, 21(12), 1797–1818.
Acknowledgments
The authors would like to acknowledge the financial support of Urmia University for this research under grant number BS/272/2011.
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SaberChenari, K., Abghari, H. & Tabari, H. Application of PSO algorithm in short-term optimization of reservoir operation. Environ Monit Assess 188, 667 (2016). https://doi.org/10.1007/s10661-016-5689-1
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DOI: https://doi.org/10.1007/s10661-016-5689-1