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Theoretical foundations for optimal control of floating offshore wind farms

University of British Columbia

Due to a phenomenon termed the wake effect, wind turbines that are placed in close proximity within wind farms interact aerodynamically. In short, each turbine generates a wake within which wind speeds are reduced, and these wakes overlap with the rotors of machines located downstream. This interaction diminishes power production in wind farms by up to 60%. Using a process referred to as wind farm control, individual wind turbines may be operated in a manner that increases power production from the collective. This thesis investigates the potential of a wind farm control strategy named yaw and induction-based turbine repositioning (YITuR) that is specifically compatible with floating offshore wind farms. Since floating platforms are anchored to the seabed using slack mooring line cables, each turbine may be repositioned in real-time using the aerodynamic forces exerted on its rotor. By relocating floating platforms accordingly, the overlap area between the wakes generated by upstream turbines and the rotors of downstream machines may be reduced; leading to an increase in wind farm efficiency. The potential of YITuR is assessed through several steps. First, a steady-state model of floating offshore wind farms is constructed and stationary optimization studies are carried out to determine the potential of YITuR under idealized steady wind conditions. Major findings from this study are that wind farm efficiency may increase by more than 40% using YITuR over traditional wind farm operation; however, these benefits are strongly influenced by mooring system designs. Second, a dynamic floating wind farm model is developed to evaluate the performance of real-time control systems. Third, due to the non-convexity of the YITuR control problem, novel distributed economic model predictive control (DEMPC) theory is developed to guarantee power maximization. Existing DEMPC algorithms do not offer such a guarantee in the presence of non-convex objective functions. Finally, the DEMPC algorithm is evaluated using the dynamic simulation tool. Neural networks are used to estimate the dynamics of floating platforms in order to expedite decision-making in DEMPC. Simulation results indicate gains of 20% in energy production when YITuR replaces traditional wind farm operation.

Text

2021-05-17

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/76830

Mechanical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/