Fatigue load mitigation in wind turbine using a novel anticipatory predictive control strategy

Abstract

Wind energy has become a recent evolving source of renewable energy which needs an extensive exploration. The increased configuration of wind turbine instantaneously increases the structural loading of wind turbine components. The prolonged loading on structural components imposes a great impact on the lifetime of the wind turbine and reduces the feasibility of thinner rotor blade. These economical detriments due to the structural damage of turbine are dealt effectively by proposing an anticipatory preview-based control strategy for individual pitching of blades. The proposed multiple point model predictive controller with fuzzy logic switching, exploits the preview wind measurement from the light detection and ranging system which predicts the wind speed in advance. The utmost objective of the proposed controller is its optimized individual blade pitching to reduce the fatigue loads on the wind turbine components using the preview wind data. The blade root bending moment of individual blades and the tower fore-aft deflection which are chosen as the parameters of fatigue stress to be analyzed and controlled. The National Renewable Energy Laboratory’s Fatigue, Aerodynamics, Structures and Turbulence 5 MW baseline onshore wind turbine is used for validating the proposed controller in MATLAB simulation. The non-linear wind field is simulated using the TurbSim software, and the short-term and lifetime damage equivalent loads of the wind turbine for the simulated wind field is analyzed using the MLife software of the National Renewable Energy Laboratory. The proposed controller is compared with the typical model predictive controller and linear quadratic-based controller.