Stochastic dynamic programming (SDP) is an optimization technique used in the operation of reservoirs for many years. However, being an iterative method requiring considerable computational time, it is important to establish adequate convergence criterion for its most effective use. Based on two previous studies for the optimization of operations in one of the most important multi-reservoir systems in Mexico, this work uses SDP, centred on the interest in the convergence criterion used in the optimization process. In the first trial, following the recommendations in the literature consulted, the difference in the absolute value of two consecutive iterations was taken and compared against a set tolerance value and a discount factor. In the second trial, it was decided to take the squared difference of the two consecutive iterations. In each of the trials, the computational time taken to obtain the optimal operating policy was quantified, along with whether the optimal operating policy was obtained by meeting the convergence criterion or by reaching the maximum number of iterations. With each optimization policy, the operation of the system under study was simulated and four variables were taken as evaluators of the system behaviour. The results showed few differences in the two operation policies but notable differences in the computation time used in the optimization process, as well as in the fulfilment of the convergence criterion.

The guide curves are tools that specify rules for dam operation that allow reducing the chances of unwanted spill or deficit events. In this research, we analyzed the importance of using guide curves and penalizing the deviation of such curves by the occurrence of surplus volume, or deficit, using optimization tools on an objective function that apply stochastic dynamic programming (SDP), guide curves and reservoir operation simulation all together, to obtain and evaluate biweekly operation policies for hydropower generation purposes. The main dams of the Grijalva River were taken as a case study. The optimization tool is based on sequential decision stages (time intervals) to operate a dam system that considers the restrictions on storage volumes, defined by high and low guide curves. An objective function was considered which maximizes energy generation, it uses coefficients to penalize unwanted events of spills, deficits, and operation conditions outside the limits of the guide curves. In conjunction with the agencies that manage the system, three tests with different guide curves were defined. To analyze their sensitivity in the results (mainly events of spillage) one more test was defined for an operation rule without considering guide curves. The system behavior was simulated with the historical record, where five variables were analyzed: total spills and deficit, minimum and maximum storage, as well as the average energy generated. By using the guide curves, the occurrence of spills and deficits was avoided.