64 citations · 65 across the 5 of their papers we have counts for
4 papers · 1 filter
Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning
Teodor Åstrand, 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 Åstrand, 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…
Expert Elicitation on Wind Farm Control
J. W. van Wingerden, P. A. Fleming, T. Göçmen +13
Wind farm control is an active and growing field of research in which the control actions of individual turbines in a farm are coordinated, accounting for inter-turbine aerodynamic…