Extension of Parametric Rule with the Hedging Rule for Managing Multireservoir System during Droughts
Publication: Journal of Water Resources Planning and Management
Volume 139, Issue 2
Abstract
In contrast to most common methods used in optimal control of reservoir systems requiring a large number of decision variables, parametric rule can make a radical reduction in the number of decision variables without yielding inferior solutions. However, parametric rule employs the standard operating policy to determine releases of reservoirs as much as demand only if there is enough water in the system, which may result in single periods of severe short supply during droughts. The purpose of this paper is to devise an operating rule for multireservoir system by combining parametric rule with the hedging rule to avoid catastrophic water shortage during droughts. In this way, decision variables to be optimized not only make a significant reduction compared with traditional operating rules, but also severe short supply during droughts can be controlled effectively. This paper employs a water supply multireservoir system in northern China to explore the changes of shortage characteristics produced by the proposed rule over a long horizon. In the case study, particle swarm optimization algorithms with a simulation model are used to optimize the decision variables. The results indicate that the extended parametric rule has a significant advantage over the classic parametric rule in dealing with the multireservoir operation problem during droughts.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This research is supported by the Natural Sciences Foundation of China (71171151, 11201039) and the Ph.D. candidate’s self-research (including ) program of Wuhan University in 2008 and 2012. The authors would also like to thank the anonymous reviewers for their review and valuable comments related to this manuscript.
References
Abido, M. A. (2002). “Optimal power flow using particle swarm optimization.” Int. J. Electr. Power Energy Syst., 24(7), 563–571.
Arvanitidis, N. V., and Rosing, J. (1970). “Composite representation of a multi-reservoir hydroelectric power system.” IEEE Trans. Power Appar. Syst., PAS-89(2), 319–325.
Brandão, J. L. B. (2010). “Performance of the equivalent reservoir modeling technique for multi-reservoir hydropower systems.” Water Resour. Manage., 24(12), 3101–3114.
Chang, F.-J., Chen, L., and Chang, L.-C. (2005). “Optimizing the reservoir operating rule curves by genetic algorithms.” Hydrol. Processes, 19(11), 2277–2289.
Chang, L.-C., and Chang, F.-J. (2009). “Multi-objective evolutionary algorithm for operating parallel reservoir system.” J. Hydrol. (Amsterdam, Neth.), 377(1–2), 12–20.
Chen, L. (2003). “Real coded genetic algorithm optimization of long term reservoir operation.” J. Am. Water Resour. Assoc., 39(5), 1157–1165.
Chen, L., and Chang, F.-J. (2007). “Applying real-coded multi-population genetic algorithm to multi-reservoir operation.” Hydrol. Processes, 21(5), 688–698.
Chen, L., McPhee, J., and Yeh, W. W. G. (2007). “A diversified multi-objective GA for optimizing reservoir rule curves.” Adv. Water Resour., 30(5), 1082–1093.
Hsu, S.-K. (1995). “Shortage indices for water-resources planning in Taiwan.” J. Water Resour. Plann. Manage., 121(2), 119–131.
Hydraulic Engineering Center (HEC). (1966). “Reservoir yield, generalized computer program 23-J2-L245.” U.S. Army Corps of Engineers, Davis, CA.
Hydraulic Engineering Center (HEC). (1975). “Reservoir yield.” Vol. 8, Hydrologic engineering methods for water resources development, U.S. Army Corps of Engineers, Davis, CA.
Japan Water Resources Development Public Corp. (1977). “Drought assessment.” Mizu to Tomoni, Vol. 159, Tokyo, Japan (in Japanese).
Jiang, Y., Hu, T. S., Huang, C. C., and Wu, X. N. (2007). “An improved particle swarm optimization algorithm.” Appl. Math. Comput., 193(1), 231–239.
Kennedy, J., and Eberhart, R. (1995). “Particle swarm optimization.” Proc., IEEE Int. Conf. Neural Networks, Vol. 4, The Bureau of Labor Statistics, Washington, DC, 1942–1948.
Koutsoyiannis, D., and Economou, A. (2003). “Evaluation of the parameterization-simulation-optimization approach for the control of reservoir systems.” Water Resour. Res., 39(6), 1170–1186.
Kumar, D. N., and Reddy, M. J. (2007). “Multipurpose reservoir operation using particle swarm optimization.” J. Water Resour. Plann. Manage., 133(3), 192–201.
Labadie, J. (2004). “Optimal operation of multi-reservoir systems: State-of-the-art review.” J. Water Resour. Plann. Manage., 130(2), 93–111.
Nalbantis, I., and Koutsoyiannis, D. (1997). “A parametric rule for planning and management of multiple reservoir systems.” Water Resour. Res., 33(9), 2165–2177.
Neelakantan, T. R., and Pundarikanthan, N. V. (2000). “Neural network based simulation-optimization model for reservoir operation.” J. Water Resour. Plann. Manage., 126(2), 57–64.
Ngo, L. L., Madsen, H., and Rosbjerg, D. (2007). “Simulation and optimization modelling approach for operation of the Hoa Binh reservoir, Vietnam.” J. Hydrol. (Amsterdam, Neth.), 336(3–4), 269–281.
Oliveira, R., and Loucks, D. P. (1997). “Operating rules for multireservoir systems.” Water Resour. Res., 33(4), 839–852.
Reddy, M. J., and Kumar, D. N. (2007a). “Optimal reservoir operation for irrigation of multiple crops using elitist-mutated particle swarm optimization.” Hydrol. Sci. J., 52(4), 686–701.
Reddy, M. J., and Kumar, D. N. (2007b). “Multi-objective particle swarm optimization for generating optimal trade-offs in reservoir operation.” Hydrol. Processes, 21(21), 2897–2909.
ReVelle, C., Joeres, E., and Kirbt, W. (1969). “The linear decision rule in reservoir management and design. I. Development of the stochastic model.” Water Resour. Res., 5(4), 767–777.
Robert, M. H., Jared, L. C., and Charles, S. R. (1977). “Gains from joint operation of multiple reservoir systems.” Water Resour. Res., 13(2), 239–245.
Salman, A., Ahmad, I., and Al-Madani, S. (2002). “Particle swarm optimization for task assignment problem.” Microprocess. Microsyst., 26(8), 363–371.
Shih, J. S., and ReVelle, C. (1994). “Water supply operations during drought: Continuous hedging rule.” J. Water Resour. Plann. Manage., 120(5), 613–629.
Shih, J. S., and ReVelle, C. (1995). “Water supply operations during drought: A discrete hedging rule.” Eur. J. Oper. Res., 82, 163–175.
Shourian, M., Mousavi, S. J., and Tahershamsi, A. (2008). “Basin-wide water resources planning by integrating PSO algorithm and MODSIM.” Water Resour. Manage., 22(10), 1347–1366.
Srinivasan, K., and Philipose, M. C. (1996). “Evaluation and selection of hedging policies using stochastic reservoir simulation.” Water Resour. Manage., 10(3), 163–188.
Stedinger, J. R. (1984). “The performance of LDR models for preliminary design and reservoir operation.” Water Resour. Res., 20(2), 215–224.
Trelea, I. C. (2003). “The particle swarm optimization algorithm: Convergence analysis and parameter selection.” Inf. Process. Lett., 85, 317–325.
Tu, M. Y., Hsu, N. S., Tsai, F. T. C., and Yeh, W. W. G. (2008). “Optimization of hedging rules for reservoir operations.” J. Water Resour. Plann. Manage., 134(1), 3–13.
Tu, M. Y., Hsu, N. S., and Yeh, W. W. G. (2003). “Optimization of reservoir management and operation with hedging rules.” J. Water Resour. Plann. Manage., 129(2), 86–97.
Wilhite, D. A. (1993). “The enigma of drought.” Drought assessment, management and planning: Theory and case studies, D. A. Wilhite, ed., Kluwer Academic Publishers, Norwell, 3–15.
Wurbs, R. A. (1993). “Reservoir system simulation and optimization models.” J. Water Resour. Plann. Manage., 119(4), 455–472.
Yeh, W. W. G. (1985). “Reservoir management and operation models: A state-of-the-art review.” Water Resour. Res., 21(12), 1797–1818.
Zhang, J., Wu, Z., Cheng, C. T., and Zhang, S. Q. (2011). “Improved particle swarm optimization algorithm for multi-reservoir system operation.” Water Sci. Eng., 4(1), 61–73.
Information & Authors
Information
Published In
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Aug 9, 2011
Accepted: Feb 28, 2012
Published online: Mar 3, 2012
Published in print: Mar 1, 2013
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.