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.
Multiobjective Optimization of Bigge Reservoir Operation in Dry Seasons
Coupled Self-Adaptive Multiobjective Differential Evolution and Network Flow Algorithm Approach for Optimal Reservoir Operation
Journal of Hydrologic EngineeringSeptember 2013
Novel Multiobjective Shuffled Frog Leaping Algorithm with Application to Reservoir Flood Control Operation
Journal of Water Resources Planning and ManagementFebruary 2010
Assistant Professor, Dept. of Irrigation and Hydraulics, Faculty of Engineering, Mansoura Univ., Mansoura 35516, Egypt.
Received: March 06, 2013
Accepted: November 26, 2013
Published online: November 28, 2013
© 2014 American Society of Civil Engineers