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Title: Model-based aeroservoelastic design and load alleviation of large wind turbines
Author: Ng, Bing Feng
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2015
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With the increase in size of wind turbine for larger energy capture, aeroelastic effects previously not seen in smaller rotors are beginning to surface as a result of increased blade flexibility. This has brought about new needs in terms of modelling requirements and methods of load control to improve the fatigue life of turbine blades. This dissertation presents an aeroservoelastic modelling approach for dynamic load alleviation in large wind turbines with trailing-edge aerodynamic surfaces. Time-domain aerodynamics are given by a linearised three-dimensional unsteady vortex-lattice method that allows better characterisation of aeroelastic responses under attached flow conditions and the direct modelling of lifting surfaces. The resulting unsteady aerodynamics is written in a state-space formulation suitable for model reductions and controller design. This approach does not rely on empirical corrections commonly found in Blade Element Momentum methods. Structural modules of the tower, potentially on a moving base, and the rotating blades are modelled using geometrically non-linear composite beams, which are linearised around reference conditions that have undergone arbitrarily-large structural displacements. The land-based NREL 5MW reference wind turbine is chosen to demonstrate the unified aeroelastic framework, in which the coupled rotor and tower description is modelled to examine both the aeroelastic effects and potential of load alleviation. In the presence of realistic wind fields, turbine blade root-bending moments and tower deflections can be reduced by 13% using active control methods. When combined with passive mechanisms through bend-twist coupling, performance can be improved to more than 40%. The baseline configuration is further extended to cover offshore floating wind turbine concepts. The focus of this dissertation is to provide higher-fidelity efficient numerical models for linear robust controller design (LQG and Hinf), to achieve load alleviation in larger and more flexible wind turbines.
Supervisor: Palacios, Rafael; Graham, Michael; Kerrigan, Eric Sponsor: Energy Innovation Programme Office ; Singapore
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral