Floating offshore wind energy is a technology that has gained significant interest over the past few years due to its potential to unlock vast, high-quality wind resources far from shore and in deeper waters, areas that fixed-bottom turbines cannot reach. However, harnessing this resource presents unique challenges, among them are maximising annual energy production (AEP) while minimising blade fatigue damage. These objectives inherently conflict. Aggressive control settings that boost energy capture tend to increase loads, accelerating material fatigue. Crucially, both AEP and fatigue life depend on the turbine controller. By systematically varying a set of key features of a proportional–integral (PI) controller, this thesis sets up a workflow to investigate how controller parameters shape the trade-off between AEP and blade fatigue. To navigate this multi-objective landscape, Pareto optimisation is employed, generating a front of controller configurations that balance energy yield against blade durability. Economic viability is assessed through levelised cost of energy (LCOE) calculations, linking extended fatigue life to deferred maintenance costs and potential improved lifetime. Within the existing literature, where past studies have treated AEP, fatigue, and control in isolation, this work offers a unified framework, demonstrating how slight adjustments in controller settings can unlock significant performance gains. The core contribution of this thesis lies in the framework itself. An end-to-end roadmap is presented, combining metocean data analysis from Utsira Nord, aero-servo-hydrodynamic simulations using SIMA, AEP analysis and fatigue life estimation, Pareto front construction, and LCOE impact assessment. Key results show that blade life can be extended by over 15% with less than a 1% drop in AEP, translating to a meaningful reduction in LCOE of at least 3% under typical economic assumptions. These findings highlight the opportunity to explore the controller parameter space further with this system, paving the way for more finely tuned strategies that optimise the balance between the two objectives. ... Read more

The projected rise in monopile installations for offshore wind turbines has spurred interest in innovative installation methods to install larger monopiles using floating vessels while simultaneously enhancing workability and efficiency. One such innovation is the motion-compensated gripper frame (MCPG), which stabilizes the monopile by compensating for environment induced motions affecting both the monopile and the floating vessel. The MCPG is capable of compensating for the wave-frequent motions during lowering of the monopile as well as during the hammering phase of the monopile.
This thesis aims to create a frequency domain model to assess the performance of a motion-compensated pile gripper (MCPG) system for offshore monopile installation using a floating installation vessel. Simulating in the frequency domain offers the advantage of minimum computational time, enabling a large number of scenarios to be simulated in a shorter amount of time compared to time-domain simulations. To assess the installation up until the piling phase, two dynamic models have been created, each based on a particular installation. The first steps of the installation process are divided into three phases: upending, lowering, and pre-piling. Two dynamic models were created, focusing on the second and third phases. The phase 2 model accounts for the lowering of the monopile, while the phase 3 model concerns the situation where the pile has reached its self-penetration depth.
The equations of motion were derived for each system and transformed to a state-space model to implement the controller for the motion-compensated gripper. The state-space models were converted into transfer functions in the frequency domain and subjected to first-order wave forces calculated by the diffraction analysis software WAMIT. The method of obtaining the frequency response was validated using data provided by GustoMSC while the motions of the monopile were validated by comparison to an analytical compound double pendulum model.
This research proposes a response-based approach tune the controller proportional and derivative gains. The gains were determined based on the response characteristics of the phase 3 system. These gains were subsequently applied to the phase 2 system across all drafts. The system’s performance and tuning method were assessed using stability analysis, frequency response, spectral analysis and modal analysis. The models and tuning approach were tested using 6, 12 and 15 meter diameter monopiles, which for the phase 2 system were suspended at drafts of 5, 25 and 45 meters. Simulations were conducted for various sea states, comparing open-loop (without controller) and closed-loop (with controller) scenarios. The systems are analyzed based on the following parameters: the monopile roll angle, crane cable offlead angle, gripper force, gripper stroke and gripper stroke rate.
Results indicated that the MCPG effectively eliminated monopile roll motion in both phases. In the closed-loop phase 3 system, gripper stroke and stroke rate were dominated by vessel sway motion, while phase 2 did not show much reduction in gripper stroke and stroke rate. The operability analysis identified the critical operability limits: in the open-loop phase 3 system, the monopile roll angle was the primary limit, followed by gripper stroke. In the closed-loop system, gripper stroke rate and force became the primary limits. For phase 2, gripper stroke was the main limit in both open and closed-loop systems, with stroke rate becoming more significant in the closed-loop system. The MCPG shifted the limiting criteria from monopile roll angle to gripper stroke rate in phase 3. The combined operability of the phase 3 system including the MCPG was found to be 25%.
Finally, the research recommends the addition of time-domain simulations to capture non-linear effects. It is also recommended to extend the models to three dimensions in order to simulate non-beam or bow waves. The phase 3 model can also substantially benefit from the addition of soil loads.
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Floating wind turbines despite the the potential to harness energy from deep offshore areas where higher average wind speeds face challenges in terms of competitiveness. One approach to raising the competitiveness of a wind farm is to mitigate efficiency losses resulting from the wake effect. This report focuses on the combination of three notable wake effect mitigation strategies: layout optimization, yaw-based wake redirection, and turbine repositioning.

A preliminary analysis of the combined effect of wind turbine repositioning and yaw-based wake redirection on power performance for the case of two turbines only is performed. Above rated wind speeds, upstream turbine yawing reduces downstream turbine movement, with reductions of around 1 to 4 rotor diameters longitudinally and 0.2 to 0.5 times the rotor diameter laterally, keeping the same level of power efficiency.

Nextly, an optimization problem that integrate layout optimization with yaw-based wake steering and turbine repositioning for power maximization across an extended wind farm is formulated. The optimization frame followed a sequential approach. The results on a case study confirmed that the effect of adding yaw-based wake redirection to turbine repositioning remains significant for multiple turbines, with several percent-point efficiency improvements for small movable ranges. For larger ranges, the contribution of yaw control diminishes rapidly to one percent-point or less. Yaw control enables movable range reductions of 10% to 50%, preserving wind farm efficiency. Yet, reductions are more pronounced in smaller, less effective movable ranges. Below rated conditions, the effectiveness of yaw control diminishes swiftly.

Furthermore, the study delves into the implications of integrating position mooring for turbine repositioning and yaw-based wake mitigation strategies on mooring system performance. This examination employs a proposed methodology aimed at minimizing the position error across most points within the movable range Both the tension of the mooring lines and the static stiffness of the floater showed to be sensitive to the position of floater, the direction of the wind load and the yaw of the wind turbine, with percentual changes ranging from 0.5% up to 50%. It results that the orientation of the mooring lines with correspondence of the prevailing wind direction, as well as that restrictive constraints on the tension and stiffness may be taken should be taken into account when designing a mooring system for turbine repositioning.

Overall, combining , yaw-based wake redirection, and turbine repositioning allows for greater wind farm AEP, with gains contingent on turbine movable range and upcoming wind speeds. Designing position mooring systems must factor in the influence of yaw-based wake redirection and turbine repositioning on mooring system tension and stiffness. More advanced analyses, including dynamic assessments, are essential for comprehending the mooring lines system's response to position mooring for turbine repositioning, and yaw-based wake redirection.
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Recently, there has been an increase in interest in floating wind turbines that are located offshore. These turbines allow for the harvesting of the power of the wind far offshore, where wind speeds are often higher.

Compared to their fixed counterparts, floating wind turbines allow for a certain mobility after the installation. This allows wind farm developers to consider layouts that change throughout the wind farm’s operational phase. The change in layout can increase the energy yield of the wind farm, which may reduce the cost of floating wind energy.

This Master’s Thesis presents a new method for wind farm layout optimization with movable floating offshore wind turbines. The objective function that is maximized is the annual energy production (AEP). The proposed method first finds the optimal installation locations of the turbines, then searches for the optimal wind farm layout for each wind direction while considering the movable range of the turbines. Different movable range sizes are considered in the analysis. These sizes range from small (there is almost no mobility allowed) to large (the turbine is allowed to move anywhere in the wind farm). The results show that the steepest gains are achieved for a movable range size of up to two rotor diameters (i.e., the turbine is allowed to move two rotor diameters in each direction, evaluated from the installation position). Above this range, a large additional movement is required for a minor increase in AEP. Moreover, for this movable range size, repositioning turbines is so effective that their installation positions almost do not affect the AEP.

In addition to the previous method, this Master’s Thesis also presents a novel method to assess the movable range of floating offshore wind turbines. In this method, it is assumed that the mobility is achieved by adjusting the mooring line lengths through a winch system on board of the floater. The proposed method optimizes the line lengths such that an equilibrium is obtained in the relocated position. Various locations are selected for the analysis that cover most of the mooring system footprint on the seabed. The results show that the assumed movable range shape is not the same as the actual movable range shape.
For a 15MW floating offshore reference turbine, the movable range size with the steepest gains in terms of AEP (two rotor diameters) and the actual movable range are compared. The results show that the actual shape covers large parts of the circular shape.

In conclusion, large gains are expected in terms of AEP for movable floating offshore wind turbines. This brings us one step closer to reducing the cost of floating wind energy, which in turn increases its competitiveness with other energy resources.
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With the highly increased interest in offshore wind turbines and their technologies, the sector has witnessed rapid development in the past decade. For installed offshore wind turbines, there has been a lot of research conducted in the field of aero-, hydro- and structural dynamics, wind turbine-control, operation & maintenance, foundations and moorings. The research field of offshore wind turbine installation is on the other hand relatively new, and the studies regarding this topic are limited. The lifting of heavy objects is one of the most commonly performed offshore installation operations and has become more challenging due to the trend of increasingly larger and heavier payloads. Especially for substantial waves, the pendular motions of the payload may cause operations to be halted.

This thesis performs a study on a positioning control strategy for a complex lifting control scenario, i.e., position-keeping of a complex-shaped 6-DOF payload using a floating vessel equipped with multiple tugger winches. As the system is highly complex and contains non-linear and time-varying dynamic phenomena, it is an impracticable task to formulate a model that meticulously describes the actual system. For this reason, a fully integrated simulation model in Orcaflex has been used to capture the non-linear dynamic behaviour of the system.

The preassembly operation of a Jacket Lifting Tool on a monohull vessel is adopted as a case study to verify the proposed control strategy. Two scenarios are considered -installation and decommissioning- for which an outrigger configuration is used to position the tugger winches. Due to the difference in setpoint (i.e. the desired position) in the two scenarios, the proposed controller is solely implemented in the decommissioning scenario. Damping tuggers, the current state-of-the-art when it comes to motion mitigation, is considered suitable in the installation scenario.

The proposed controller does not consider the state–space equations of the system and only relies on real-time motion and tension measurements of the vessel and suspended payload. In addition, the controller considers the system's velocity tension and power limitations. The controller's impact is evaluated based on the positional error and verified by the peak reduction in the power spectral density spectra of the simulations. Despite its simple form, results show a significant reduction in the positional error, and therefore the possibility to extend the working conditions of the installation vessel. To improve the controller's performance it is recommended to involve derivative control, consider payload motion prediction and to optimise the tugger winch configuration. For further studies, experimental testing is needed to verify the effectiveness of the control scheme as it could appear that the controller does not exhibit similar performance in the real system. However, it is deemed unlikely that the latter would occur as a sensitivity study regarding measurement error indicates a stable response of the controller.
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