Analysis and design of an adaptive turbulence-based controller for wind turbines

Liang Dong, Wai Hou Lio and Georg Raimund Pirrung

Renewable Energy, 2021, vol. 178, issue C, 730-744

Abstract: This work aims to explore methods to retain the robustness and performance of a wind turbine controller under different wind conditions. A method of optimizing the control parameters in response to different turbulence intensity is proposed, which is referred to as adaptive turbulence-based control (ATBC). Specifically, the power spectrum of the rotor effective wind speed has been derived and the analytical expression is explicitly considered in the control optimization. Also, a linear aero-servo-elastic (ASE) model is established, which captures the closed-loop dynamics of the rotor speed, pitch activity and tower fore-aft vibration mode. Subsequently, a computationally-efficient component damage prediction method is proposed that uses rainflow counting and inverse fast Fourier transform. Based on the proposed ASE model and damage prediction method, the controller optimization problem is established using a quadratic cost function to achieve the optimal trade-off between the rotor speed variation and the damage of turbine components. A model validation shows that the proposed scheme is able to predict the component fatigue load and the rotor speed variation in an efficient way. Finally, one design case is given to illustrate the procedure of ATBC and to demonstrate the feasibility of the proposed method in different operating wind conditions.

Keywords: Wind turbine; Adaptive control; Turbulence; Optimization; Fatigue estimation (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:178:y:2021:i:c:p:730-744

DOI: 10.1016/j.renene.2021.06.080

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