Stochastic Optimization of Reservoir Operation by Applying Hedging Rules

Abstract

The high percentage of reliability of water resources systems has always been considered as a positive advantage by users. However, in arid and semiarid areas in which the flow rate of the reservoir is highly variable, it makes sense to reduce the system reliability and allocate less water to demand sites in order to avoid critical conditions such as reservoir depletion and to reduce severity of failure in low water months. In this study, a parameterization-simulation-optimization (PSO) based operation model was used whereby the efficiency of two different hedging rules was studied based on one-dimensional and two-dimensional relationships between release, storage, and input flow considering the stochastic conditions of the input flow. The optimal hedging parameters were determined through linking the reservoir simulation model to the multiobjective imperialist competitive algorithm. The model combines stochastic and historical monthly flow data of the Marun River (10,800 months in total) to optimize the system and extract hedging rules for the Marun Dam reservoir in Iran. In order to validate the developed model, the combination of stochastic data and residual historical data (612 months in total) was used. The model results from two different hedging policies were then compared with those from standard operating policies (SOPs). The results indicated that PSO model based on one-dimensional reservoir hedging policy compared to two-dimensional hedging methods and SOP was able to manage needs allocation in dry months and prevent reservoir depletion.