Omar A. de la Cruz Courtois’s research while affiliated with Autonomous University of Chiapas and other places

This study aimed to apply the Markovian Model (MM) to obtain optimized operating rules for a hydropower reservoir to maximize its efficiency. In this study, a Markovian Control Model with continuous state space (MCM-CSS) is presented to analyze the climatological effects through stochastic integrals. The MCM-CSS compute the optimal policies of hydropower reservoir system over the Grijalva Hydropower System (GHS). The MCM-CSS can be described as follows: a) Historical data review, b) histograms of variables studied, c) state space analysis, d) action space analysis, e) admissible decision rule, f) expected benefit analysis. As a result, the optimal policy graphs were obtained. The result obtained in this research demonstrated the advantage of having applied a continuous space in reservoir inflow and water demand with the MMC-CSS method to avoid the uncertainness and inaccuracies in simulation results with a discrete space. Modified Svanidze’s Method (MSM) is also employed to investigate their capabilities to predict streamflow over the GHS and mean energy generated. The hydrological monthly simulations were calibrated and validated at GHS station for the period 1952–2018. The main objective of the study is to simulate the optimal policies obtained with the MMC-CSS for continuous states using MSM in GHS.