Open AccessFatigue damage estimation and data‐based control for wind turbines
Author(s) -
BarradasBerglind Jose,
Wisniewski Rafael,
Soltani Mohsen
Publication year - 2015
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2014.0730
Subject(s) - turbine , controller (irrigation) , wind power , control theory (sociology) , computer science , process (computing) , model predictive control , control engineering , engineering , control (management) , artificial intelligence , electrical engineering , mechanical engineering , agronomy , biology , operating system
The focus of this work is on fatigue estimation and data‐based controller design for wind turbines. The main purpose is to include a model of the fatigue damage of the wind turbine components in the controller design and synthesis process. This study addresses an online fatigue estimation method based on hysteresis operators, which can be used in control loops. The authors propose a data‐based model predictive control (MPC) strategy that incorporates an online fatigue estimation method through the objective function, where the ultimate goal in mind is to reduce the fatigue damage of the wind turbine components. The outcome is an adaptive or self‐tuning MPC strategy for wind turbine fatigue damage reduction, which relies on parameter identification on previous measurement data. The results of the proposed strategy are compared with a baseline model predictive controller.