3 papers
eess.SY2024
Deep Reinforcement Learning for Multi-Objective Optimization: Enhancing Wind Turbine Energy Generation while Mitigating Noise Emissions
Martín de Frutos, Oscar A. Marino, David Huergo +1
We develop a torque-pitch control framework using deep reinforcement learning for wind turbines to optimize the generation of wind turbine energy while minimizing operational noise…
physics.flu-dyn2024
Reinforcement learning for anisotropic p-adaptation and error estimation in high-order solvers
David Huergo, Martín de Frutos, Eduardo Jané +3
We present a novel approach to automate and optimize anisotropic p-adaptation in high-order h/p solvers using Reinforcement Learning (RL). The dynamic RL adaptation uses the evolvi…
cs.LG2024
Reinforcement learning to maximise wind turbine energy generation
Daniel Soler, Oscar Mariño, David Huergo +2
We propose a reinforcement learning strategy to control wind turbine energy generation by actively changing the rotor speed, the rotor yaw angle and the blade pitch angle. A double…