A multi-agent RL system using Independent Soft Actor-Critic and a local-inflow surrogate for damage-equivalent loads learns policies that raise wind-farm power while respecting explicit load-increase limits.
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Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning
A multi-agent RL system using Independent Soft Actor-Critic and a local-inflow surrogate for damage-equivalent loads learns policies that raise wind-farm power while respecting explicit load-increase limits.