Model-Based Optimization of Downstream Impact during Filling of a New Reservoir: Case Study of Mandaya/Roseires Reservoirs on the Blue Nile River

Abstract

The aim of this paper is to develop a methodology based on coupled simulation-optimization approach for determining filling rules for the proposed Mandaya Reservoir in Ethiopia with minimum impact on hydropower generation downstream at Roseires Reservoir in Sudan, and ensuring power generation at Mandaya Reservoir in Ethiopia. The Multi-Objective Optimization (MOO) approach for reservoir optimization presented in this paper is a combination of simulation and optimization models, which can assist decision making in water resource planning and management (WRPM). The combined system of reservoirs is set in MIKE BASIN Simulation model, which is then used for simulation of a limited set of feasible filling rules of the Mandaya reservoir according to the current storage level, the inflow, and the time of the year. The same simulation model is then coupled with Multi-Objective optimization Non-dominated Sorting Genetic Algorithm (NSGA-II), which is adopted for determining optimial filling rules of the Mandaya Reservoir. The optimization puts focus on maximization of hydropower generation in both the Mandaya and the Roseires Reservoirs. The results demonstrate that optimal release- (and correspondingly filling-) rules for Mandaya Reservoir which maximize the hydropower generation in both Mandaya and Roseires reservoirs can be found. These rules are determined along the Pareto frontier obtained by the optimization algorithm, which can serve as a decision support tool for choosing the actual filling rule. The results also showed that the NSGA- II is an efficient and powerful tool that could assist decision makers for solving optimization problems in complex water resource systems.