1 citations · 1 across the 4 of their papers we have counts for
4 papers
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,…
Hierarchical RL-MPC Control for Dynamic Wake Steering in Wind Farms
Marcus Binder Nilsen, Teodor Olof Benedict à strand, Tuhfe Göçmen +1
Wind farm wake steering optimization is challenging due to complex flow physics and changing conditions. This paper presents a hierarchical framework that combines reinforcement le…
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…
Adversarial Sensor Errors for Safe and Robust Wind Turbine Fleet Control
Julian Quick, Marcus Binder Nilsen, Andreas Bechmann +2
Plant-level control is an emerging wind energy technology that presents opportunities and challenges. By controlling turbines in a coordinated manner via a central controller, it i…