Programme  Poster session 1  abstract 175

Reservoir Operation at Drought Condition under the Uncertainty

Author(s): H. Seyyedi, A. Ganji
Arman Ganji, Assistant Professor, Water Engineering Department, College of Agriculture, Shiraz University, Shiraz, Iran


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Session: Poster session 1
AbstractIgnoring the uncertainty as the main

source of variability in reservoir operation leads to failure in water supply, especially at drought conditions. Several

deterministic models have been developed for reservoir operation in such as conditions, i.e. Hedjing rule models. In

this study, an explicit stochastic optimization model is developed to incorporate the uncertainty for optimal hedjing

rules determination. The proposed methodology is based on the constraint state formulation which uses the first and

second order moments of storage state variable as the constraint to incorporate the uncertainty in optimization. The

proposed optimization model is solved using the Genetic Algorithms (GAs). As a result of using this model, an

optimal reservoir operation rule at drought condition, and its long-term average net benefit as well as reservoir mean

and standard deviation can be determined

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