Deep Reinforcement Learning for Multi-Stage Hydropower Scheduling with Dynamic Grid Stability Constraints
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资源简介：
Hourly two-year (2021–2022, 17,520 steps) multi-stage scheduling dataset for a four-plant Lancang River cascade hydropower system (8,355 MW), covering hydrology, meteorology, grid frequency/price, dynamic stability constraints, cascade operating states, and deep-reinforcement-learning state–action–reward tuples, with reproducibility code.
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Zenodo创建时间：
2026-07-01
