Optimization of reservoir release operation using genetic algorithm method
Sri Wahyuni, Dian Sisinggih, Ikhwan Elhuda, Kazuyoshi Souma, Iqbal Zaenal Dasylva
Abstract
Genetic Algorithms (GA) are highly effective in optimizing hydropower release parameters, identifying global optima in complex systems, and adapting to varying circumstances, making them ideal for managing hydropower conditions. This study employs GA to optimize hydropower release at Wonorejo Reservoir, Indonesia, aiming to balance power generation with flood control, irrigation, and environmental sustainability. The application of GA improved operational efficiency, resulting in a 10.24 % increase in electricity production. Notably, during the rainy season, the improvement was 27.3 % higher than in the dry season, highlighting GA responsiveness to seasonal variations. These findings demonstrate GA potential as a valuable tool for reservoir management.