Case Studies
Nov 28, 2013

Multiobjective Optimization of Bigge Reservoir Operation in Dry Seasons

Publication: Journal of Hydrologic Engineering
Volume 19, Issue 9

Abstract

The optimal reservoir operation in dry seasons is an important topic in water resources management due to conflict of interest. This paper tends to address this issue by providing possible reservoir operation for individual months, together with multiobjective optimization and other constraints. A multiobjectives genetic algorithm optimization model is presented to determine the optimum releases of the Bigge reservoir, Germany, by assuming two inflow scenarios for dry seasons. The first one represents the minimum recorded monthly inflow during the period between 1995 and 1996; whereas the second scenario was the minimum monthly inflow during a five consecutive years generated using Monte Carlo model. The objectives of this study are to maximize energy production, the benefits of recreation, as well as the benefits of the energy produced, and to minimize the total penalty due to deviation from the targets. Several trade-off Pareto optimal solutions were obtained. A compromise solution is presented from a set of Pareto optimal solutions to help the decision maker. Details of the model formulations and implementation are described. The results demonstrate the efficiency of the developed model to determine the optimum releases effectively in the two inflow scenarios of dry seasons achieving all constrains.

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References

Abdel-Gawad, H. A. (2004). “Reliability in multi-objective management of saltwater intrusion under uncertainty of hydraulic conductivities.” Mansoura Eng. J., 29(4), C.15–C.28.
Chang, F. J., Chen, L., and Chang, L. C. (2005). “Optimizing the reservoir operating rule curves by genetic algorithms.” Hydrol. Process., 19(11), 2277–2289.
Chen, L. (2003). “Real time genetic algorithm optimization of long term reservoir operation.” J. Am. Water Resour. Assoc., 39(5), 1157–1165.
Chen, L., McPhee, J., and Yeh, W. W.-G. (2007). “A diversified multiobjective GA for optimizing reservoir rule curves.” Adv. Water Resour., 30(5), 1082–1093.
Diaz, G. E., Brown, T. C., and Sveinsson, O. (2005). “Aquarius: A modeling system for river basin water allocation.”, U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO.
Dittmann, R., Froehlich, F., Pohl, R., and Ostrowski, M. (2009). “Optimum multi-objective reservoir operation with emphasis on flood control and ecology.” Nat. Hazards Earth Syst. Sci., 9(6), 1973–1980.
Elabd, S. (2010). “Data-driven modeling for water resources management (case study: The Ruhr river basin).” Ph.D. thesis, Water Resources and Hydraulic Engineering Dept., Univ. of Wuppertal, Wuppertal, Germany.
Elbeltagi, E., Hegazy, T., and Grierson, D. (2010). “A new evolutionary strategy for pareto multi–objective optimization.” Proc., Seventh Int. Conf. on Engineering Computational Technology, Civil-Comp Press, Stirlingshire, U.K.
Field, R. C. (2007). “Multi–objective optimization of Folsom reservoir operation.” M.S. thesis, Civil and Environmental Engineering Dept., Univ. of California, Davis, CA.
Goel, T., Vaidyanathan, R., Haftka, R. T., Shyy, W., Queipo, N. V., and Tucker, K. (2007). “Response surface approximation of Pareto optimal front in multi–objective optimization.” Comput. Meth. Appl. Mech. Eng., 196(4–6), 879–893.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning, Addison Wesley, Reading, MA.
Grierson, D. E. (2008). “Pareto multi-criteria decision making.” J. Adv. Eng. Inf., 22(3), 371–384.
Liu, C., and Hammad, A. (1997). “Multiobjective optimization of bridge deck rehabilitation using a genetic algorithm.” Microcomput. Civ. Eng., 12(6), 431–443.
Lohr, H. (2001). “Simulation, bewertung und optimierung von betriebsregeln für wasserwirtschaftliche speichersysteme.” Ph.D. thesis, Technische Universität Darmstadt, Institut f¨ur Wasserbau und Wasserwirtschaft, Darmstadt, Germany.
Mitchell, M. (1996). An introduction to genetic algorithms, MIT Press, Cambridge, MA.
Ngatchou, P., Zarei, A., and El-Sharkawi, M. A. (2005). “Pareto multi objective optimization.” Univ. of Washington, Scattle, WA, 84–91.
Ngo, L. L. (2006). “Optimising reservoir operation A case study of the Hoa Binh reservoir, Vietnam.” Ph.D. thesis, Technical Univ. of Denmark, Institute of Environment and Resources, Kongens Lyngby, Denmark, 39.
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. (2006). “Optimal reservoir operation using multi–objective evolutionary algorithm.” Water Resour. Manage., 20(6), 861–878.
Wardlaw, R. B., and Sharif, M. (1999). “Evaluation of genetic algorithms for optimal reservoir system operation.” J. Water Resour. Plann. Manage., 25–33.
Yeh, W. W.-G. (1985). “Reservoir management and operations models: A state-of-the-art review.” Water Resour. Res., 21(12), 1797–1818.

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Information

Published In

Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 19Issue 9September 2014

History

Received: Mar 6, 2013
Accepted: Nov 26, 2013
Published online: Nov 28, 2013
Published in print: Sep 1, 2014
Discussion open until: Nov 3, 2014

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Authors

Affiliations

Samer Elabd
Assistant Professor, Dept. of Irrigation and Hydraulics, Faculty of Engineering, Mansoura Univ., Mansoura 35516, Egypt.
Hamdy A. El-Ghandour [email protected]
Assistant Professor, Dept. of Irrigation and Hydraulics, Faculty of Engineering, Mansoura Univ., Mansoura 35516, Egypt (corresponding author). E-mail: [email protected]; [email protected]

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