This thesis investigates the concept of turbine repositioning to enhance energy production in floating wind farms. Due to the dense deployment of floating turbines, downstream units could potentially experience reduced wind speeds caused by the wakes of upstream turbines, leading to decreased power output—an effect known as the wake effect. To address this, methods such as power de-rating and yaw-based wake redirection have been extensively studied. Notably, for floating wind farms, the ability of turbine bases to move within a certain range has prompted the proposal of turbine repositioning as a novel wake mitigation strategy.

This study delves into optimal control strategies for turbine repositioning, with a particular emphasis on manipulating rotor yaw angles. It introduces two primary repositioning strategies: static repositioning, suitable for farms with relatively slack mooring lines, and dynamic repositioning, for those with tighter lines. Alongside, the research proposes optimization methods to identify the optimal control sequences for each repositioning strategy. Lastly, by analyzing rotor yaw angle control sequences in the frequency domain, this study distinguishes the frequency component crucial for repositioning turbines from that steering the wakes. The findings provide significant insights into enhancing the cost-effectiveness of power production in floating wind farms through effective wake interaction management.

Accurate wind turbine modelling is essential for reliable aerodynamic performance predictions. The industry primarily uses the Blade Element Momentum (BEM) method with correction models, but BEM’s assumptions become less valid with larger rotors and in Floating Offshore Wind Turbines (FOWTs), where wave interactions and wake dynamics are more complex. The Lifting Line Free Vortex Wake (LLFVW) method offers higher modelling fidelity but is less computationally efficient.

This study compares a BEM and LLFVW model implemented in the software QBlade. The evaluated parameters include power, torque, thrust, root bending moment, tip deflection, and angle of attack using the floating 15 MW UMaine VolturnUS-S reference turbine under various wind and wave conditions taken from several Design Load Cases (DLCs). The aim is to identify any differences between the methods and the met-ocean conditions under which these are most pronounced.

The results show minimal differences in BEM and LLFVW outputs under varying wave conditions. However, wind conditions have a greater impact, particularly around rated speeds where discrepancies were observed, mainly due to different controller dynamics. Above-rated conditions showed similar power, torque, and thrust predictions, but notable differences in angle of attack. The maximum and standard deviation of the root bending moment and tip deflection were found to be consistently lower for LLFVW compared to BEM.