The placement of wind turbines in wind farms is economically beneficial to the industry. Consequently, the wake generated by the upstream turbines introduces interactions with downstream turbines that significantly affect power generation. However, it is common practice to control the individual turbines to operate at their optimal settings and neglect the wake effect. Turbines in a wake experience lower wind speeds and an increase in turbulence. This results in lower power generation and increased fatigue loads on the downstream turbine. Wind farm control aims to increase overall power generation and reduce fatigue loads by considering all turbines in the wind farm. Recently, numerous studies have been conducted to control the wake itself. The helix approach is one such strategy and seeks to initiate better mixing of the wake. For this, it uses IPC to create sinusoidal blade bending moments acting on the rotor disc. This in turn creates a helical structure in the velocity of the wind, allowing it to better mix with the surrounding energy-rich wind. As a result, the waked downstream turbine experiences an increase in power due to the reduced velocity deficit in the wake. An extensive load analysis of the helix method has shown that the rotational frequency of this helical wake can be measured in the bending moments of the waked downstream turbine. To further develop the field of dynamic wake mixing, this work investigated the initialization of the helix method in a downstream turbine by amplifying these signals through synchronization with the incoming helical wake. This method was tested in simulation environments with increasing levels of fidelity and number of turbines simulated. The results with low fidelity showed that synchronization could be achieved without loss of performance. In addition, less pitch actuation was required to generate large bending moments due to amplification. The final experiment was conducted for a three-turbine setup and was performed in a high-fidelity model using CFD methods. Here it was found that -90 degrees out-of-phase synchronization with the incoming helical wake resulted in a 9.8% increase in power generation in a turbine further downstream. These results demonstrate the clear potential of wake synchronization in a multi-turbine setting. This study, therefore, contributes to the field of dynamic wake mixing by introducing a novel field of wake synchronization.

Floating Offshore Wind Turbines (FOWTs) pave the way to accessing deep water regions with abundant wind resources that are unreachable to bottom-fixed turbines. This technology is not widely deployed due to the increased cost of producing energy. A suitable control strategy can improve the power quality and extend the lifespan of the FOWT, resulting in a reduction of the final cost of energy. However, FOWTs face a specific set of control challenges in the above-rated operational region, such as the negative damping issue, rough environmental conditions, and increased model complexity due to both the floating structure and the increase in wind turbine size. Advanced control strategies are the most suited to resolve the negative damping problem, but obtaining a control model that balances low complexity with good accuracy is an increasingly difficult task. To mitigate the effect of environmental disturbances, feedforward control using wind preview is most commonly employed. Although waves have been shown to increase rotor speed oscillations and turbine loads, wave preview-based methods remain scarce. This thesis implements a model-free, feedforward controller based on wave preview for the above-rated region of a FOWT. The controller uses a preview of wave forces acting on the floating platform and aims for simultaneous rotor speed regulation and platform motion reduction using collective blade pitch control. As a model-free approach, a modified Data-enabled Predictive Control formulation that considers past and future information about measurable disturbances is proposed. The controller is implemented with a linear model of the NREL 5-MW wind turbine installed on the OC3-Hywind spar-buoy platform and tested in several cases. The effectiveness of the wave feedforward data-driven controller is evaluated in a high-fidelity environment using the QBlade simulator. A decrease in rotor speed variance of 67% and platform pitching motions of 71% is obtained, at the cost of a 7-fold increase in blade pitching effort compared to the baseline controller. In turbulent wind conditions, the wind proved to be the dominant disturbance, and including both wind and wave previews in the controller is recommended. This work demonstrated the feasibility of a model-free feedforward control strategy for wave effect mitigation in FOWTs. Further efforts are required to adapt this strategy to closed-loop operation and to validate its effectiveness across the entirety of the above-rated region.