most citedLoad constrained wind farm flow control through multi-objective multi-agent reinforcement learning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

eess.SY2026★ 1 cited

Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning

Teodor à strand, Marcus Binder Nilsen, Iasonas Tsaklis +3

This study presents a multi-agent reinforcement learning (MARL) framework for load-constrained wind farm flow control (WFFC). While wake steering can enhance total wind farm power,…

eess.SY2026

Accelerating Reinforcement Learning for Wind Farm Control via Expert Demonstrations

Marcus Binder Nilsen, Julian Quick, Tuhfe Göçmen +2

Reinforcement learning (RL) offers a promising approach for adaptive wind farm flow control, yet its practical deployment is hindered by slow training convergence and poor initial…