The management of power generation systems requires the optimized coordination of resources and investments across timeframes ranging from days to decades. This paper introduces a mixed-integer optimization model (MIP) for the short-term operation of the Río Negro Hydroelectric Complex, a crucial asset in Uruguay’s efforts to achieve energy sovereignty by primarily relying on wind, solar, and hydroelectric power sources. The model addresses the challenge of balancing fluctuating renewable energy supply with hydroelectric resources while ensuring cost-effective dispatch and system reliability. The experimental results demonstrate the accuracy with which a MIP approximation can model an extremely nonlinear problem.