L. Schena
This article presents two model-free controllers for wind-turbine torque and pitch control. These controllers are based on reinforcement learning (RL) and Bayesian optimization (BO) and do not rely on any mathematical model of the wind-turbine dynamics, in contrast to classical approaches designed on linearized models. The model-free controllers were benchmarked against a proportional-integral-derivative (PID) regulator in a numerical environment using Blade Element Momentum theory for computing the aerodynamic torque and the blade loads. The results showed that the model-free approaches could increase power harvesting while reducing wind turbine loads.
Keywords:
Published on 24/11/22Accepted on 24/11/22Submitted on 24/11/22
Volume Industrial Applications, 2022DOI: 10.23967/eccomas.2022.297Licence: CC BY-NC-SA license
Views 5Recommendations 0
Are you one of the authors of this document?