TY - JOUR
T1 - Model predictive control of wind turbine fatigue via online rainflow-counting on stress history and prediction
AU - Loew, S.
AU - Obradovic, D.
AU - Bottasso, C. L.
N1 - Publisher Copyright:
© 2020 Published under licence by IOP Publishing Ltd.
PY - 2020/9/22
Y1 - 2020/9/22
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85092357613&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1618/2/022041
DO - 10.1088/1742-6596/1618/2/022041
M3 - Conference article
AN - SCOPUS:85092357613
SN - 1742-6588
VL - 1618
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 2
M1 - 022041
T2 - Science of Making Torque from Wind 2020, TORQUE 2020
Y2 - 28 September 2020 through 2 October 2020
ER -