most citedLearning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration

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cs.LG2025

RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations

Enrico Marchesini, Benjamin Donnot, Constance Crozier +7

Reinforcement learning (RL) can provide adaptive and scalable controllers essential for power grid decarbonization. However, RL methods struggle with power grids' complex dynamics,…

cs.LG2024★ 1 cited

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration

Caleb Ju, Constance Crozier

Variable renewable generation increases the challenge of balancing power supply and demand. Grid-scale batteries co-located with generation can help mitigate this misalignment. Thi…