UBC Theses and Dissertations
H∞ position control of a 5-MW offshore wind turbine with a semi-submersible platform Escobar Aquino, Eduardo Eribert
Floating offshore wind farms have a potential in capturing wind energy in a cost-effective manner, with advantages of consistent and strong wind over the ocean, and of little noise and visual impacts on humans. However, a wind farm may lose its efficiency due to the aerodynamic wake, which is the turbulence passed from the upstream turbines to the downstream ones. The wake is undesirable because it can not only reduce the total power of the wind farm but also increase the structural loading of the downwind turbines. This wake effect can be mitigated by optimizing the layout of the wind farm in real time according to the wind speed and direction, as well as power output of each turbine. In this thesis, for a 5 MW floating offshore wind turbine with a semi-submersible platform, an H∞ state-feedback controller design method is proposed to achieve four objectives simultaneously. The objectives are (1) to relocate its position to a specified target location, (2) to regulate its position there by rejecting wind and wave disturbances, (3) to maintain the harvested power to a target level, and (4) to reduce the angular motion of the floating platform. The target location of the floating wind turbine and the target level of the generated power are assumed to be provided by high-level real-time wind farm optimization. For the controller design, a physics-based control-oriented nonlinear model which was previously developed is adopted. The H∞ controller design problem is formulated as minimization of the position deviations from the target, of the generator speed fluctuation, and of platform oscillations. The designed controller is validated using the medium-fidelity software Fatigue-Aerodynamic-Structure-Turbulence (FAST). The simulation results demonstrate that the H∞ state-feedback controller outperforms the linear quadratic regulator with an integrator in various tested scenarios. The research outcome of this thesis will improve the wind farm efficiency, thereby reducing the wind energy cost and increasing the wind energy utilization.
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Attribution-NonCommercial-NoDerivatives 4.0 International