Optimization of Fuzzified Hedging Rules for Multipurpose and Multireservoir Systems
This article has a reply.
VIEW THE REPLYThis article has a reply.
VIEW THE REPLYPublication: Journal of Hydrologic Engineering
Volume 21, Issue 4
Abstract
In the conventional zone-based hedging rule, as a common approach, the rationing factors are changed from one zone to another at once, which is not proper for actual reservoir operation. Hence a fuzzy-rule-based approach is employed to create a transition zone to assign rationing factors. This remedy causes gradual variation in the rationing factors and mitigates severe water shortages during drought periods. In this paper, a monthly simulation model linked to an evolutionary algorithm is developed. The proposed model was applied to the Zohre multireservoir system in southern Iran. There are two objective functions to supply minimum flow and agriculture demands over a long-term simulation period. Therefore, a multiobjective particle swarm optimization (MOPSO) algorithm was applied. The results showed that annual and long-term modified shortage index (MSI) values have been improved compared to the current conventional hedging rule. Implementation of the proposed hedging rule for the case study results in improving at least 34 and 21% in the maximum MSI, respectively, for the annual minimum flow and agriculture shortages.
Get full access to this article
View all available purchase options and get full access to this article.
References
Afshar, A., Shojaei, N., and Sagharjooghifarahani, M. (2013). “Multi-objective calibration of reservoir water quality modeling using multi-objective particle swarm optimization (MOPSO).” J. Water Resour. Manage., 27(7), 1931–1947.
Ahmadianfar, I., Adib, A., and Salarijazi, M. (2015). “Optimizing multireservoir operation: Hybrid of bat algorithm and differential evolution.” J. Water Resour. Plann. Manage., 05015010.
Akter, T., and Simonovic, S. P. (2004). “Modeling uncertainties in short-term reservoir operation using fuzzy sets and a genetic algorithm.” J. Hydrol. Sci., 49(6), 1081–1097.
Balter, A. M., and Fontane, D. G. (2006). “A generalized multiobjective particle swarm optimization solver for spreadsheet models: Application to water quality.” Proc., 26th Annual American Geophysical Union Hydrology Days, 20–22.
Bárdossy, A., and Duckstein, L. (1995). Fuzzy rule-based modeling with applications to geophysical, biological and engineering systems, CRC, Boca Raton, FL.
Barros, M. T., Zambon, R. C., Delgado, D. M., Barbosa, P. S. F., and Yeh, W. W.-G. (2008). “Planning and operation of large-scale water distribution systems with preemptive priorities.” J. Water Resour. Plann. Manage., 247–256.
Bayazit, M., and Unal, N. E. (1990). “Effects of hedging on reservoir performance.” Water Resour. Res., 26(4), 713–719.
Chen, L., Mcphee, J., and Yeh, G. W. W. (2007). “A diversified multi-objective GA for optimizing reservoir rule curves.” Adv. Water Resour., 30(5), 1082–1093.
Choudhari, S. A., and Raj, P. A. (2010). “Multi-objective multi-reservoir operation in fuzzy environment.” J. Water Resour. Manage., 24(10), 2057–2073.
Coello, C. A., and Lechuga, M. S. (2002). “MOPSO: A proposal for multiple objective particle swarm optimization, evolutionary computation.” Proc., 2002 Congress on CEC'02, IEEE, Piscataway, NJ, 1051–1056.
Coello, C. A. C., Pulido, G. T., and Lechuga, M. S. (2004). “Handling multiple objectives with particle swarm optimization.” IEEE Trans. Evol. Comput., 8(3), 256–279.
Deb, K. (2001). Multi-objective optimization using evolutionary algorithms, Wiley, Chichester, U.K., 81–165.
Deka, C. P., and Chandramouli, V. (2009). “Fuzzy neural network modeling of reservoir operation.” J. Water Resour. Plann. Manage., 5–12.
Dubovin, T., Jolma, A., and Turunen, E. (2002). “Fuzzy model for real-time reservoir operation.” J. Water Resour. Plann. Manage., 66–73.
Fallah-Mehdipour, E., Bozorg Haddad, O., and Marino, M. A. (2011). “MOPSO algorithm and its application in multipurpose multi-reservoir operations.” J. Hydroinf., 13(4), 794–811.
Hsu, N. S., and Cheng, K. W. (2002). “Network flow optimization model for basin scale water supply planning.” J. Watr Resour. Plann. Manage., 102–112.
Huang, W. C., and Yuan, L. C. (2004). “A drought early warning system on real-time multireservoir operations.” Water Resour. Res., 40(6), in press.
Kennedy, J., and Eberhart, R. C. (1995). “Particle swarm optimization.” Proc., IEEE Int. Conf. Neural Networks, Vol. 4, Perth, Australia, 1942–1948.
Kennedy, J., and Eberhart, R. C. (2001). Swarm intelligence, Morgan Kaufmann, San Mateo, CA.
Klir, G. J., and Yuan, B. (1995). Fuzzy sets and fuzzy logic—Theory and applications. Prentice-Hall, Englewood Cliffs, NJ.
Knowles, J., and Corne, D. (1999). “The Pareto archived evolution strategy: A new baseline algorithm for multi-objective optimisation.” Proc., Congress on Evolutionary Computation, IEEE, 98–105.
Moore, J., and Chapman, R. (1999). “Application of particle swarm to multi-objective optimization.” Dept. of Computer Science and Software Engineering, Auburn Univ., Auburn, AL.
Neelakantan, T. R., and Pundarikanthan, N. V. (1999). “Hedging rule optimization for water supply reservoirs system.” Water Resour. Manage., 13(6), 409–426.
Neelakantan, T. R., and Pundarikanthan, N. V. (2000). “Neural network based simulation-optimization model for reservoir operation.” J. Water Resour. Plann. Manage., 57–64.
Price, K., and Storn, R. (1995). “Differential evolution—A simple and efficient adaptive scheme for global optimization over continuous spaces.”, International Computer Science Institute, Berkley, CA.
Price, K. V. (1996). “Differential evolution: A fast and simple numerical optimizer.” Fuzzy Information Processing Society, 1996. NAFIPS., 1996 Biennial Conf. of the North American, IEEE, 524–527.
Reddy, M. J., and Kumar, D. N. (2007). “An efficient multi-objective optimization algorithm based on swarm intelligence for engineering design.” Eng. Optim., 39(1), 49–68.
Russell, S. O., and Campbell, P. F. (1996). “Reservoir operating rules with fuzzy programming.” J. Water Resour. Plann. Manage., 165–170.
Shiau, J. (2003). “Water release policy effects on the shortage characteristics for the Shihmen reservoir system during droughts.” Water Resour. Manage., 17(6), 463–480.
Shiau, J. T. (2009). “Optimization of reservoir hedging rules using multi-objective genetic algorithm.” J. Water Resour. Plann. Manage., 355–363.
Shiau, J. T., and Lee, H. C. (2005). “Derivation of optimal hedging rules for a water-supply reservoir through compromise programming.” Water Resour. Manage., 19(2), 111–132.
Shih, J. S., and ReVelle, C. (1994). “Water-supply operations during drought: Continuous hedging rule.” J. Water Resour. Plann. Manage., 613–629.
Shih, J. S., and ReVelle, C. (1995). “Water supply operations during drought: A discrete hedging rule.” Eur. J. Oper. Res., 82(1), 163–175.
Shrestha, B. P., Duckstein, L., and Stakhiv, E. Z. (1996). “Fuzzy rule based modeling of reservoir operation.” J. Water Resour. Plann. Manage., 262–269.
Srinivasan, K., and Philipose, M. C. (1996). “Evaluation and selection of hedging policies using stochastic reservoir simulation.” Water Resour. Manage., 10(3), 163–188.
Srinivasan, K., and Philipose, M. C. (1998). “Effect of hedging on over year reservoir performance.” Water Resour. Manage., 12(2), 95–120.
Storn, R., and Price, K. (1997). “Differential evolution—A simple and efficient heuristic for global optimization over continuous spaces.” J. Global Optim., 11(4), 341–359.
Taghian, M., Rosbjerg, D., Haghighi, A., and Madsen, H. (2013). “Optimization of conventional rule curves coupled with hedging rules for reservoir operation.” J. Water Resour. Plann. Manage., 693–698.
Teegavarapu, R. S. V., and Simonovic, S. P. (1999). “Modeling uncertainty in reservoir loss functions using fuzzy sets.” Water Resour. Res., 35(9), 2815–2823.
Tu, M. Y., Hsu, N. S., Tsai, F. T. C., and Yeh, W. W. G. (2008). “Optimization of hedging rules for reservoir operations.” Water Resour. Plann. Manage., 3–13.
Tu, M. Y., Hsu, N. S., and Yeh, W. W. G. (2003). “Optimization of reservoir management and operation with hedging rules.” Water Resour. Plann. Manage., 86–97.
Yeh, W. W. G., and Becker, L. (1982). “Multiobjective analysis of multireservoir operations.” Water Resour. Res., 18(5), 1326–1336.
Zadeh, L. A. (1965). “Fuzzy sets.” Information Control., 8(3), 338–353.
Zhang, H., and Li, H. (2010). “Multi-objective particle swarm optimization for construction time-cost tradeoff problems.” Constr. Manage. Econ., 28(1), 75–88.
Zimmermann, H.-J. (1991). Fuzzy set theory and its application, 2nd Ed., Kluwer Academic, Norwell, MA.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 21 • Issue 4 • April 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Mar 7, 2015
Accepted: Oct 7, 2015
Published online: Jan 8, 2016
Published in print: Apr 1, 2016
Discussion open until: Jun 8, 2016
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.