Deep Reinforcement Learning for Intraday Multireservoir Hydropower Management

Deep Reinforcement Learning for Intraday Multireservoir Hydropower Management

This study investigates the application of Reinforcement Learning (RL) to optimize intraday operations of hydropower reservoirs. Unlike previous approaches that focus on long-term planning with coarse temporal resolutions and discretized state-action spaces, we propose an RL framework tailored to th...

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Bibliographic Details
Main Authors: Rodrigo Castro-Freibott, Álvaro García-Sánchez, Francisco Espiga-Fernández, Guillermo González-Santander de la Cruz
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Mathematics
Subjects:
daily optimization
hydropower generation
multireservoir
reinforcement learning
mixed integer linear programming
Online Access:https://www.mdpi.com/2227-7390/13/1/151
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