Operation Policies through Dynamic Programming and Genetic Algorithms, for a Reservoir with Irrigation and Water Supply Uses

In this study, operation policies were obtained for a reservoir in Michoacán, Mexico, used for irrigation and domestic water supplies. The main purpose of these policies is to optimize the uses of the water, an increasingly scarce resource everywhere. Two optimization methodologies were used; stochastic dynamic programming, that provides release decisions for each stage, and genetic algorithms coupled with a reservoir operation simulation program, to achieve annual release curves. The operation of the reservoir was evaluated using historical inflow records. Monthly requirements for crop cycles, as well as the volumes of spills and deficits were examined. Both methodologies gave inverse relationships between deficits and spilled volumes. While both methodologies proved efficient in achieving the objectives, the results of the stochastic dynamic programming showed a better performance for this system.