Open AccessModel predictive control of wind turbine fatigue via online rainflow-counting on stress history and prediction
Author(s) -
Stefan Loew,
Dragan Obradović,
Carlo L. Bottasso
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1618/2/022041
Subject(s) - model predictive control , turbine , cycle count , control theory (sociology) , stress (linguistics) , computer science , engineering , control (management) , operations research , artificial intelligence , mechanical engineering , linguistics , philosophy
The standard fatigue estimation procedure is implemented in Model Predictive Control via externalization of the Rainflow algorithm from the optimization problem. Additionally, stress history is considered in a consistent manner by employing a so-called stress residue. The formulation is implemented in the state-of-the-art MPC framework acados and tested in closed-loop with the 5MW onshore turbine in OpenFAST. Simulation results indicate that the new formulation outperforms conventional PID- and MPC-controllers over the entire wind regime, and that the consideration of stress history is highly beneficial.