In this thesis, the effect of a surging and pitching motion of a floating wind turbine on its wake as well as the effect of a surging, pitching and yawing motion on a stationary downstream turbine are analysed. Two experiments are conducted in order to address both points. The turbine models used are scale models of the DTU 10 MW turbine, and the upstream turbine is placed onto a kinematic robot which can move in all 6 degrees of freedom. The first objective is studied using Particle Tracking Velocimetry and the second objective using load cell measurements. It is found that pitch has a larger effect on the flow field in the wake than surge and that the effects of low frequency motion are more visible than those of high frequency motion. Moreover, it is found that the tracing particles are concentrated in specific areas, affecting the accuracy of the results. In future research, it should be examined why this is the case and how it can be improved. Additionally, low frequency pitch and surge had the greatest effect on the loads. A clear sinusoidal motion is visible and the mean thrust, torque, and power is increased. The effect of the high frequency motions is not visible in the results. In future studies, the wake behind a downstream turbine can also be examined using Particle Tracking Velocimetry. Moreover, the downstream turbine can also be moving rather than standing still and more movements of the turbine can be examined.

Experimental testing of floating offshore wind turbines (FOWT) is essential for understanding the various engineering challenges posed by their dynamic motion. For example, the pitch and surge motion of the FOWT results in unsteady aerodynamic effects caused by wake interaction. In this project, two FOWT models (DTU10MW with TripleSpar and IEA15MW with VolturnUS) were developed for testing with a hybrid hardware-in-loop (HIL) setup. This setup integrates physical wind loading in a wind tunnel with numerically simulated hydrodynamic loading.

The HIL setup comprises a scaled wind turbine model, a hexapod that can actuate the floating motion, an instrumentation system with sensors to measure forces and accelerations, and a numerical model that simulates FOWT dynamics in real-time based on measured data. This work explores the methodology of developing a numerical model that can simulate the dynamics of the scaled FOWT model in real-time with the applied wind loading and numerically simulated hydrodynamic loading. Furthermore, a methodology for correcting the measured forces to obtain external aerodynamic forces is introduced and validated.

The process of developing the numerical model is thoroughly detailed, including its tuning and validation. The challenges encountered during the validation process are discussed in depth, with an emphasis on their underlying causes. Finally, the HIL numerical model was used to test the scaled DTU10MW wind turbine with a simulated TripleSpar floater at the Open Jet Facility (OJF) wind tunnel at TU Delft. This study also presents intriguing results regarding the HIL model's performance and the impact of wind on FOWT dynamics observed during the test campaign.

The field of floating offshore wind energy is rapidly advancing, offering a promising solution to
harness stronger and more consistent wind resources in deep-water regions, where conventional bottom-fixed turbines are not viable. Floating Offshore Wind Turbines (FOWTs), mounted on floating substructures, enable the deployment of wind turbines in deep offshore locations without the need for extensive foundations. This approach can significantly lower project costs, primarily by reducing substructure procurement expenses for comparable water depths. As a result, the installed capacity of FOWTs is projected to reach approximately 18.9 GW by 2030.

However, the design of cost-efficient FOWTs presents significant challenges due to the complex interactions between aerodynamic and hydrodynamic loads, as well as the coupling of various subsystems. One of the key hurdles is reducing the Levelized Cost of Energy (LCoE) to ensure the economic viability of Floating Offshore Wind Farms (FOWFs). Additionally, the flexibility of the floating substructure, which moves in six degrees of freedom (DOF), introduces complexities in the wake profile, such as enhanced wake meandering, which may affect the wake losses and the overall farm energy production.

Despite the potential impact of floater movements on energy yield, the specific effects on optimal wind farm layout design remain under-explored. Furthermore, the impact of these displacements on the LCoE needs to be examined to determine whether incorporating floater displacements into optimization frameworks leads to more accurate results or merely adds unnecessary complexity and computational cost.

This thesis evaluates the role of static floater displacements, specifically tilt and surge, in the optimization of FOWFs. Two distinct scenarios have been compared to assess how these displacements affect energy yield, the LCoE, and the optimal wind farm layout. The first scenario (Case A) disregards the static equilibrium displacements of the floating turbines, while the second scenario (Case B) incorporates these displacements into the analysis. To conduct the analysis, this thesis develops a wake modeling strategy focusing on wind-induced floater displacements, wherein the tilt and surge displacements of the floater are computed for each turbine using the PyWake framework, based on the effective wind speed experienced by its rotor. This wake modeling approach is then integrated into an OpenMDAO-based optimization framework to minimize the LCoE of the wind farm, which is used for the comparison between the two cases, to achieve the objectives of this study.

A case study of a 42-turbine sample wind farm in the North Sea, arranged in a rectangular gridded layout, was analyzed using the optimization framework. The results showed minimal differences in AEP, LCoE, and layout design between the scenarios that account for floater displacements (Case B) and those that neglect them (Case A). However, the computational time required for the optimization process increased by approximately fourfold for Case B. Case B resulted in a 0.25% reduction in AEP and a 0.162 €/MWh increase in LCoE, primarily due to changes in wake behavior caused by tilt and surge displacements. The optimal layout also shifted in orientation and spacing, with Case B yielding slightly lower power in the final configuration. Despite these effects, the overall impact on the LCoE was modest, suggesting that while incorporating floater displacements could potentially improve the accuracy of results for FOWFs, it might not justify the added computational costs for larger wind farms.

This thesis presents a comprehensive study on Floating Offshore Wind Turbine’s (FOWT’s) modeling and simulation, focusing on the IEA 15MW wind turbine coupled to the VolturnUS-S semi-submersible platform. The primary goal was to develop the building blocks of a high-fidelity Computational Fluid Dynamics (CFD) coupled model using OpenFOAM to simulate large-scale FOWT behavior, verify, and compare each component individually against the mid-fidelity tool OpenFAST. The project builds on the frameworks of previous studies by Pere Frontera Pericàs [81] and Scarlatti [98], expanding them to accommodate the complexities of a larger turbine and more intricate environmental conditions.

The model was implemented using OpenFOAM’s waves2Foam and Moody libraries for wave and mooring modeling, respectively, while aerodynamic simulations employed the turbinesFoam package with an actuator line approach. A spatial convergence study optimized mesh parameters for computational efficiency and accuracy, ensuring reliable and stable simulation results for motions up to 24 meters in surge. Comparisons between OpenFOAM and OpenFAST using a P-Q analysis highlighted significant differences, particularly in modeling damping. OpenFAST was shown to underestimate both linear and quadratic hydrodynamic damping due to its simplified representation of fluid dynamics. Discrepancies in the equilibrium positions were found between the decay tests using CFD; their origin still needs more investigation.

In aerodynamic simulations, steady-state and prescribed motion tests revealed critical differences in thrust and power predictions between OpenFOAM and OpenFAST. OpenFAST overpredicted the reduction in axial wind speed, leading to a reduced power output for steady turbine simulations. The CFD model provided a more accurate representation of rotor wake effects and dynamic responses, particularly in high-frequency surge conditions, where OpenFAST overestimated power fluctuations. These findings underscore the importance of using high-fidelity models like OpenFOAM to improve the accuracy of performance predictions in floating wind turbines.

The study concludes by offering recommendations for future research, including model validation using experimental data and the implementation of overset mesh techniques to improve simulation stability for large motions. The work establishes a reliable CFD framework for simulating this large FOWT, offering insights into enhancing mid-fidelity models and guiding future developments in floating wind turbine design and analysis. It also builds a fully coupled CFD model in OpenFOAM to investigate its behavior.

In recent years, the use of renewable energy sources has increased significantly. As a result, offshore wind energy has expanded due to its advantages compared to onshore, such as steadier winds, reduced visual impact and lower noise emissions. However, 80% of the global offshore wind resource potential is located in areas with water depths greater than 60 meters, making the installation of fixed-bottom wind turbines unfeasible and leading to an increase in floating wind turbines. Floating offshore wind turbines, due to their increased freedom of movement, experience more complex aerodynamic and hydrodynamic phenomena, resulting in different power generation compared to fixed-bottom wind turbines. The effect of six degrees of freedom on power production has not been extensively studied in full-scale operating wind turbines. Additionally, a better prediction of energy production could also reduce the investment risk of floating wind turbines, leading to a reduced levelised cost of energy and better integration of floating wind turbines into a fully renewable energy system.

The aim of this report was to investigate the power generation and response of the TetraSpar demonstrator project, the world’s first fully industrialised floating offshore foundation. To achieve this, a model of the TetraSpar demonstrator was created in OpenFAST. Due to confidentiality, some data, particularly regarding the wind turbine, were unavailable and were instead based on scaling the NREL 5 MW wind turbine. In addition, the ROSCO controller was incorporated into the model and the floating platform was modelled as a six degrees of freedom rigid body.

For the validation of the OpenFAST model, a comparison was performed with the on-site TetraSpar demonstrator. Data for the on-site demonstrator regarding motions, metocean conditions and power generation were provided by RWE. Further filtering and averaging the data in 10-minute periods for an entire year was performed. First, three one-hour simulations were performed for three different operating conditions: cut-in, below rated and above rated. Results from time series and power spectral density analyses showed a good agreement in platform motions. For the generated power, the mean average produced power was closest to the on-site data in the above rated region.

Next, for the power curve and AEP estimation, the probability of occurrence for each wind speed in the operating region was determined based on the on-site measured data. Furthermore, for every wind speed, the most representative significant wave height, wave period, turbulence intensity and other parameters needed as inputs in OpenFAST were found. The results showed that the AEP predicted by OpenFAST was 2.8% lower than the AEP measured at the on-site TetraSpar demonstrator. Moreover, different peak shaving levels of the controller contributed to the AEP percentage difference, ranging from about 4.4% to 2.1% compared to the on-site measurements. As far as platform motions are concerned, the model showed good agreement, capturing the trend of mean values and standard deviations of the two most dominant motions in power production, surge and pitch. In addition, the effect of wave height and wave period showed that the mean generated power is slightly affected. Similar results were also found for different current velocities. However, waves were found to influence the oscillation amplitudes of surge and pitch motions, while currents mainly affected the shift in mean values. Lastly, wind-wave misalignment also proved to have a negative effect on power performance.

In conclusion, the current OpenFAST model can be used to estimate the energy production and platform motion of the TetraSpar demonstrator. However, further improvements and reduction of the assumptions made, mainly due to the unavailability of data because of confidentiality, could enhance its accuracy.

As wind turbines get bigger and bigger, the simulation of wind turbines becomes more complex. The increase in size brings about a multitude of intricate challenges that must be addressed in the simulation process. These challenges lie in the different aspects of the simulations such as aerodynamics, structural dynamics, power electronics, hydrodynamics, turbine control etc.

The central theme of this thesis is to explore the effect of one of the aspects- structural dynamics, on the wind turbine simulations. Moreover, the thesis also emphasises the development of a structural module and it’s integration in an OpenFOAM-based wind turbine simulation library called TurbinesFoam. TurbinesFoam is an actuator line method-based simulation tool, which enables the study of turbine performance as well as wake dynamics using Computational Fluid Dynamics. The key motivation is also to contribute towards the accurate simulation of wind turbines by performing a successful integration as said above.

To fulfil the goals, a structural module was developed in Matlab to simulate the
structural dynamics of wind turbines. The module is developed from the theory
of spinning elements assuming the blade and tower as Euler-Bernoulli beam. The developed module code is called while running the CFD simulations in OpenFOAM to add deflection and rotation of the blades and towers, using a MatLab pipe class.The accuracy of the developed code was measured using BModes and OpenFAST. The results exhibited satisfactory agreement between the outputs.

The NREL 5MW turbine was used to study the effects. The results revealed that,
at slightly above the rated condition, the turbine showed 1% decrease in power
production due to elasticity when compared with a rigid turbine. The thrust and
torque coefficients showed similar trends of reduction in value. Moreover, as the inflow wind velocity increased, the differences in performance got broader, due to increased deflection value. The wake region of the elastic turbine showed a mixed region of both increased and decreased wind velocity when compared with the rigid turbine.

As the urge to decarbonise the energy field becomes increasingly important, a growing interest is shown in wind turbine technologies. In particular, the past few years have seen the development of floating offshore wind turbines for applications in deep waters.

In addition to the harsher environment they are facing, these wind turbines are mounted on floaters and therefore experience motions in the six additional degrees of freedom. As a result, this greatly alters their aerodynamic behaviour. The flow surrounding the rotor gains in complexity, becoming highly unsteady and three-dimensional. Thus, its resolution by numerical means calls for high-fidelity methods such as Large-Eddy Simulations (LES).

The objective of this study is to numerically impose single and coupled motions in the pitch and surge directions on a scale rotor of the DTU 10MW. This scale model was used for an experimental campaign within TU Delft, and particular interest is given to the comparison of the loads obtained.
Additionally, numerical simulations permit access to further information, such as the radial distribution of the loads or the wake development.

For this purpose, the LES code YALES 2 is used, implemented with an actuator line approach capable of dealing with imposed motions. Both 1-DOF and 2-DOF harmonic motions are imposed in the pitch and surge directions. Different reduced velocities and frequencies are considered.

On single-imposed surging motion, the loads are found to be well in accordance with the quasisteady theory (QST), even at high frequency, where much larger fluctuations were encountered during the experiment. Particular phenomena are also captured in the wake, such as the formation of vortex rings when the frequency is sufficiently high. Similar comments are made for 1-DOF pitching. Finally, for combined pitch/surge motions, the loads are also in accordance with the QST predictions made from the 1-DOF results. The influence of each motion on the wake’s development is also discussed.

Keywords: Floating offshore wind turbine (FOWT), Large-eddy simulation (LES), Actuator line method (ALM), Coupled imposed motions, pitch, surge

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.

The purpose of this study has been to develop an aerodynamic load model for the energy harvesting (traction) phase of leading-edge inflatable (LEI) kites operating in an airborne wind energy (AWE) context. The load model stems from multivariate polynomial regression analyses expressing the airfoil lift, drag and moment coefficients as polynomial functions of the angle-of-attack and 2D non-dimensional (relative to the chord length) shape parameters: non-dimensional tube diameter, maximum camber magnitude and chordwise position of maximum camber. The regression analyses relied on numerical data attained from computational fluid dynamics (CFD) simulations of the 2D flow fields around parameterised LEI wing profiles. The RANS equations, closed by the k-ω SST turbulence model, have been used for this purpose. The parameterisation and subsequent geometric construction of LEI wing profiles has been a key aspect of this study. As such, the effects of the shape parameters on the flow field have been assessed.

Considering the goals set by the international community, the implementation of new energy sources has to increase considerably in the next seven years. In this thesis, the focus is on the acceleration and improvement of the application of offshore wind turbines. The power produced using this technology should become 3.6 times more before the end of this decade to comply with the set goals.

To achieve this target, new solutions have to be developed. To this aim, the implementation of model predictive control for wind turbines in the last years has been investigated. This would allow to optimize different parameters at the same time, such as maximization of energy production while minimizing the perceived loads. For this application, it is necessary to have forecasts of different features of the turbine, especially loads, with a higher frequency. As a result, the main research topic is defined as 'Can data-driven surrogate models be used for forecasting load time series on offshore wind turbines?'.

To answer this question, first environmental conditions are sampled within limits deducted from real data through Halton sequencing, and next simulations are run through OpenFAST to determine the resulting loads acting on the turbine. Within all the features resulting from the simulation, only five inputs and five target outputs are selected. This is the result of various considerations. Given the desire to develop a realistic methodology, the input variables are first filtered by assessing their availability from measurement devices. Next, the relationships between the variables are analyzed through cross-correlation to determine the degree of influence of each input on the output.

Using this data, a training database is created. It is used to train two different types of surrogate models, one linear and one non-linear, respectively ARIMAX and LSTM. These are implemented to generate a 30-second forecast of the moments acting at the root of the blade. To do so, the algorithms are trained using different variables as exogenous inputs to assess the models' performance in different cases. Given the wide range of target features, for LSTM two different behaviors are identified and the blade edgewise and flapwise moments are taken as examples. The hyper-parameters are tuned on the blade edgewise moment and lead to overfitting when applied to the blade flapwise and out-of-plane moment.

The obtained results show that the RMSE in ARIMAX is up to seven times larger than the one obtained from the application of LSTM. Within the non-linear models, the one resulting in the lowest percentage error for the blade edgewise, pitching, and in-plane moment considers the wind reference speed, the wind speed time series, and the corresponding tip deflection as exogenous inputs. Very low RMSE errors are obtained for all variables. Furthermore, it is concluded that while it is possible to implement LSTM in real-life, this is not achievable for ARIMAX.

Energy transition is imperative to effectively address the pressing issue of climate change resulting from global warming. In this transition, offshore wind power assumes a pivotal role as a crucial and indispensable source of clean and renewable energy. Offshore benefits become more pronounced as the offshore locations progress far offshore. In deep-water areas, where 80% of the worldwide offshore wind energy can be potentially harnessed, the utilization of floating foundations becomes essential instead of traditional bottom fixed ones. The present study seeks to investigate the disparities in power generation and energy production that arise from the replacement of bottom fixed wind turbines with floating counterparts. The former is represented by the monopile foundation, while the latter by the spar buoy. The power performance difference lies in the ability of floating structures to move, which can lead to suboptimal positioning of the rotor relative to the incoming wind inflow, mainly due to spar’s pitch and surge motions. The investigation is conducted using two distinct aerodynamic model of lower and higher fidelities, BEM and OLAF, respectively, to assess their effects on the outcomes.
In the field of offshore wind turbine design, engineers rely on aero-hydro-servo-elastic software codes to simulate the dynamic behavior of floating offshore wind turbine systems in offshore environments. OpenFAST, an open-source software, has been extensively developed and validated for conducting such investigations. In this study, OpenFAST is employed to develop both floating and bottom fixed wind turbine models. Specifically, a coupled aero-hydro-servo-elastic model of a floating spar wind turbine is created, and the simulated motion of the spar is compared with measurements obtained from an actual floating turbine deployed in the Hywind Scotland floating offshore wind farm. Metocean data, spar measurement data, and spar system descriptions are provided by Equinor to facilitate this benchmarking process. Additionally, an equivalent monopile wind turbine model is developed for energy yield comparison purposes.
The simulated spar motion results of the developed OpenFAST model exhibit reasonable realism when benchmarked with the measured data for all load cases and modal analysis, despite assumptions and uncertainties influencing the model's accuracy. Model discrepancies primarily stem from undisclosed wind turbine parameters and controller strategy as well as some modeling simplifications inherent in OpenFAST. Nevertheless, through statistical, time series and power spectral density comparisons against full-scale Hywind measurements encompassing various wind speeds (below-rated, rated, and above cut-out), the developed floating model is validated, thereby ensuring the reliability of its energy production outcomes.
It is observed that the spar’s pitch and surge mean offset is mostly affected by the current speeds while varying wave conditions (height and period) influence their oscillation amplitudes. Power is slightly affected by the ocean conditions, primarily the wave effects, while it is more strongly influenced by the spar nacelle’s velocity and direction relative to the incoming wind, especially when subjected to lower wind speed fields. Finally, for both BEM and OLAF simulations, monopile bottom fixed structures produce higher amounts of energy annually compared to the floating spar counterparts. The implementation of alternative controllers specifically designed for FOWT, with optimization objectives focused on either maximizing power performance or ensuring structural integrity and longevity, results in estimated AEP reductions when utilizing a spar floater instead of a monopile foundation. For the BEM model, the estimated AEP decrease ranges from 3.46% to 8.62%, depending on the specific controller optimization objective. On the other hand, when employing the VPM-OLAF model, the estimated AEP reduction for a spar floater compared to a monopile substructure ranges from 4.50% to 9.58%, under similar conditions as previously mentioned. By employing OLAF instead of BEM, the computed annual energy yield for both Bottom Fixed and Floating offshore wind turbines increases by approximately 25%.
In conclusion, it is recommended that future research prioritizes resolving identified discrepancies in the model setup, addressing phenomena not adequately captured by the current OpenFAST model, and conducting additional validation of the spar model using a wider range of measured parameters.

Floating Offshore Wind Energy represents an enormous potential for the future of wind energy and will play a pivotal role in the global energy transition. However, important technical challenges still need to be overcome by the industry regarding the standardization of processes like transportation, floating substructure concept, and supply chain optimization. To successfully achieve these milestones, FOWTs must be accurately modeled to minimize uncertainties to ultimately attract investors and capital in the industry. This thesis has the objective of developing and validating a high-fidelity model for the hydrodynamics of FOWTs with the ultimate goal of creating reliable results to be used as a benchmark for faster mid-fidelity software mostly used in the offshore industry.

The model expanded throughout this thesis is developed in OpenFOAM C++ framework. The whole numerical model is built upon three main pillars: Waves2Foam used for the generation of relaxation zones in the numerical wave tank for wave-current generation and absorption; MoorDyn/Moody numerical tools employed for the mooring lines spatial discretization for the station keeping of the floating platform; InterFoam applied as the main OpenFOAM solver for the multi-phase solution which, in combination with a mesh morphing technique and a rigid body solver, is capable of deforming the mesh to accommodate the 6DOF motions of the platform.

A sequential approach has been undertaken. The first step involves the simulation of second-order Stokes wave propagation in an infinite 2D wave tank, followed by a sensitivity study with an associated uncertainty quantification. The next step involves conducting 3D simulations of a floating box, comparing motion and forces under different mooring models: dynamic FEM, dynamic lumped mass, and quasi-static catenary. In the last step, the results and lessons learned from the previous studies are combined for coupled hydrodynamic/aerodynamic simulations of the OC4 DeepCwind semi-submersible floater with the 5MW NREL offshore wind turbine. Forces, displacements, and tensions are extrapolated and compared with experimental and numerical results, validating the model's accuracy.

Simulated across diverse wind and wave conditions, the OpenFOAM model demonstrated remarkable robustness and excellent ability to achieve convergence even under challenging environmental conditions, while maintaining a high level of result accuracy. The framework effectively reproduced the hydrodynamic behavior of a Floating Offshore Wind Turbine (FOWT), establishing itself as a dependable and reliable tool for conducting future high-fidelity FOWT simulations.

Floating offshore wind turbines (FOWTs) unlock the potential to harness energy from wind in deeper waters. Despite their potential, the major obstacle to large-scale commercial deployment remains the floating substructure's high cost. Multidisciplinary design, analysis and optimisation techniques are commonly employed to improve their cost-competitiveness, but existing models often use simplified engineering models. This approach risks neglecting design considerations typical of structures subjected to complex aero-hydro-servo-elastic loads.

To address the need for incorporating higher-fidelity analysis methods, an optimisation framework is developed, integrating OpenFAST to simulate the response of the FOWT system under various environmental and operational conditions. Leveraging the flexibility of the Python framework and the wealth of output data contained within the OpenFAST simulation results, this holistic approach offers opportunities to explore novel and cost-effective platform designs with high reliability.

To demonstrate its effectiveness, the optimisation framework is utilised to achieve a significant reduction of the DeepCWind platform's structural mass. Among the considered constraints, the platform pitch motion was critical, reaching maxima for design load cases characterised by the most extreme wind and waves. Although the inclusion of a structural model for the platform comes at considerable computational expense, it enhances the framework's value, as structural integrity can be verified.

The recommended use of the optimisation framework is for in-depth studies, following preliminary design explorations conducted with cheaper models. Future efforts should focus on extending the structural and hydrodynamic model to improve the framework's versatility, and make it applicable to a wider range of platform concepts and turbine sizes.

Sustainable and renewable energies are essential in achieving climate targets set by the Paris Agreement and Sustainable Development Goals (SDGs). Floating offshore wind turbines (FOWTs) represent an innovative technology with considerable potential to contribute to these goals. However, being a relatively new technology, FOWTs pose challenges that must be addressed to enhance their development. To speed up FOWT installation and optimize their design, accurate numerical simulation tools are essential, particularly mid-fidelity models, which use less computational time but require precise hydrodynamic characteristics to be tuned. These tuning parameters are obtained with experimental tests or with Computational Fluid Dynamics (CFD) simulations.
This thesis aims to analyze the added mass and drag coefficients of the MaRINET2 semi-submersible wind turbine floater when subjected to forced oscillatory motion, utilizing a validated CFD model. To achieve the objective, a nonlinear Navier Stokes numerical model was developed within the open-source CFD software OpenFOAM. The interFoam solver was employed for the simulations. A mesh convergence study identified an optimal mesh configuration, balancing computational efficiency with result accuracy. Two types of simulations were conducted: free decay simulations for model validation against University of Strathclyde (UoS) experimental data and forced oscillatory simulations to compute added mass and drag coefficients under varying oscillation parameters.
It was found that heave added mass is sensitive to both oscillation amplitude and period, while heave drag coefficients displayed minimal influence at shorter periods. For high-amplitude oscillations, surge drag coefficients remained stable across oscillation periods, yet longer periods increased coefficients for
mid and low amplitudes. Pitch added mass coefficients remained unaffected by oscillation amplitude but increased with longer periods. Comparing these hydrodynamic parameters with two reference papers revealed both similarities and discrepancies in trends. It is challenging to attribute these discrepancies
only to floater geometry due to the lack of specific experimental data for this floater.

The advancement of floating wind turbine technology in recent years necessitates accurate predictions of their behaviour using various simulation tools. Utilizing multi-fidelity tools like OpenFAST allows for comprehensive calculations of the entire floating wind turbine structure. However, the precision of these calculations is challenged by the uncertainties associated with different system parameters.

The main goal of this research is to conduct a comprehensive exploration of various parameters, with a particular emphasis on hydrodynamic factors, and their impact on the structural and aerodynamic performance of semi-submersible floating wind turbines. To achieve this, an extensive sensitivity analysis approach is employed, utilizing the multi-fidelity model OpenFAST. The simulations are conducted on a semi-submersible floating wind turbine, specifically the one used in the OC4 experiment, featuring the 5MW NREL wind turbine. The Elementary Effects (EE) method is employed in this study to assess the significance of various factors. These factors include the hydrodynamic drag coefficients, wave height, peak wave period, wind speed, wind direction, current speed, current direction, and turbulence intensity. Their influence on the Damage Equivalent Load (DEL) of different loads acting on the floating offshore wind turbine (FOWT) is thoroughly examined.

The analysis conducted in this study has unveiled several key findings. The most influential parameters identified are the current speed, primarily impacting mooring line tension, and the significant wave height, which exhibits a balanced effect across various outputs, including hydrodynamic loads, tower loads, and rotor dynamics. Additionally, turbulence intensity emerges as a significant factor, particularly concerning rotor thrust and torque.

When employing the Morison equation, the order of parameter significance remains consistent with the hybrid theory (Potential + Drag). However, it is noteworthy that the added mass coefficients carry greater significance compared to the drag coefficient. Furthermore, simulations conducted using probability distributions for different locations confirm that wave height consistently ranks as the most significant parameter. However, the overall significance may vary and decrease in more severe environmental conditions.

The comparison with the OC3 spar platform revealed a similar pattern when examining the influence of current speed and significant wave height. Nonetheless, the simple hydrodynamic drag coefficient used for the whole platform also displayed significance, emphasizing the sensitivity of the spar platform loads to this modelling parameter. This significance is much higher than the corresponding one of the semisubmersible platform.

The research underscores it is imperative to mitigate the uncertainty associated with various parameters. This can be achieved through experimental verification and establishing correlations between modelling parameters and the specific conditions being simulated. Additionally, given that the most influential parameters are related to external conditions, it becomes crucial to simulate conditions that closely resemble the anticipated deployment location for the floating offshore wind turbine (FOWT). By doing so, the accuracy and reliability of the simulations will be enhanced to better inform FOWT design and deployment strategies.

Offshore wind is a rapidly maturing renewable energy technology and is expected to play a central role in future energy systems. It has the potential to generate more than 420,000 TWh per year worldwide, an amount approximately equal to eighteen times the global electricity demand today. While many of the most abundantly resourceful sites are at water depths too extreme for fixed-base solutions, current floating turbine technologies suffer with high-costs and inefficiencies. Seawind Ocean Technology B.V., a Netherlands based company, is a manufacturer of fully integrated floating wind turbine systems. They have designed an innovative set of low-cost, low-weight, upwind two-bladed wind turbines, with teetering hinge and yawed power control. This teetering hinge decouples the shaft from rotor, by adding an extra degree of motion, and protects the turbine from harmful aerodynamic and gyroscopic loads, as well as the rotor from hydrodynamic loads. The innovative active yaw control eliminates the need for complex pitching systems to regulate power output, in turn reducing turbine head weight and turbine costs.

There are a number of aims and objectives for this thesis project. The first, and most fundamental, was to investigate two-bladed and floating offshore turbine technology and share these findings with the hope that they make their way into the hands of change-makers who can promote the technology and consequently accelerate the green transition. The second was to optimise the loading analysis models of the Seawind 6 turbine using DNV GL’s wind turbine design software, Bladed. This is a 6 MW two-bladed floating offshore turbine and is intended for commercialisation by 2024. Seawind have extensive operational data from the Gamma 60’s deployment (the world’s first variable speed, two-bladed, wind turbine with a teetering hinge) in the 1990s. The Gamma 60 was modelled and compared to this operational data, with the calibrations in turn applied to the Seawind 6 models to improve its accuracy. Once achieved, the third goal was to carry out a thorough ultimate and fatigue load analysis of the optimised Seawind 6 model for various design load cases at extreme water depths. This investigation proved that the various investigated turbine components have been adequately sized and that suitable construction materials have been selected considering the loads they are expected to withstand. Following this large body of work, the fourth objective was to verify the theory that teeter motion is aerodynamically damped when the blades of a two-bladed, teetered turbine, are vertically oriented due to differences in angles of attack of the oncoming and retreating blades when yawed out of the wind. The fifth and final goal of this thesis work was to pull everything together and compare the floating offshore two-bladed Seawind 6 to a conventional floating three-bladed state-of-the-art turbine competitor. This was in terms of ultimate and fatigue loads experienced, capital and operational expenses (CAPEX and OPEX), lifetime carbon abatement, levelised cost of energy (LCOE), ease of manufacture and deployment, and operational performance.

Renewable forms of energy, and especially wind energy, have become an integral part of the energy infrastructure around the globe. However, the constant increase of installed wind capacity has put a strain on the selection of potential onshore locations for wind turbine installation. As a result, the wind industry is focusing on offshore applications, mainly with the use of bottom-fixed sub-structures. Nevertheless, research community has started shifting their interest in floating wind turbine designs to harvest the abundant wind potential of far-offshore locations, sited in water depths where monopiles and jacket sub-structures are not economically feasible. Despite the progress on the design of such floating units, there is still no consensus upon their optimum installation and maintenance strategies, activities which comprise one third of the lifetime cost of a floating wind farm.

The aim of this research is to gain understanding on the optimum installation and maintenance strategies for semi-submersible and spar buoy floating units based on their cost and duration. Towards this direction, four different installation strategies are investigated: semi-submersible installation with wind turbine assembly at quayside, semi-submersible installation with wind turbine assembly at wind farm site, spar buoy installation with wind turbine assembly in a single lift with a heavy lift vessel (HLV) and spar buoy installation with wind turbine assembly with multiple lifts with a crane barge. Furthermore, based on the type of the required maintenance activities, the onsite minor and major repairs of wind turbines with the use of a crew transfer vessel (CTV) or a walk-to-work (W2W) vessel are examined, as well as the onsite or offsite replacement of major wind turbine components for wind turbines installed on both semi-submersible and spar buoy floating sub-structures. In the context of this thesis, a deterministic installation and O&M model was developed. This model relies on various input data, including weather time series for near-shore and far-offshore locations, vessels and facilities costs, personnel and components costs and an electricity price for the calculation of the lost revenue due to downtime.

The analysis of the installation and maintenance strategies is based both on a base case scenario and a sensitivity analysis of the main factors influencing the cost and duration of offshore activities: distance from shore/port and weather limits of activities. The results show that semi-submersible installation with wind turbine assembly at quayside is the most cost-effective and fastest of all implemented strategies, followed by the spar buoy installation with HLV. Furthermore, the use of a CTV for onsite repairs is more cost-effective, albeit slower, approach than the W2W one, for all examined distances and weather limits. Finally, the offsite major replacement strategy for semi-submersibles is the most cost-effective of the examined strategies. No definitive conclusion can be drawn on the best major component replacement strategy for spar buoys, as the cost difference between the onsite and offsite approach is small. When the cost difference of different installation and maintenance strategies is low, the final choice depends on the volatile vessel rates and the electricity market prices.

The most effective way to decrease the cost of energy of wind turbines is to increase the rotor diameter. Therefore, this calls for the need of aerodynamic research on large wind turbines. This thesis project will tackle the topics addressed by the IEA Wind Task 47 which is focused on the aerodynamic analysis and comparison of the newly proposed IEA 15-MW reference wind turbine using varying fidelity tools. Therefore, the main goal of this work is to analyze whether a low-fidelity approach is still feasible for aerodynamic analysis in comparison with a high-fidelity approach. It was found that there are quantitative differences between the different fidelity methods but also qualitative similarities. It can be concluded that the low-fidelity methods are relatively less suitable for a large turbine design, especially for high TSR values, which should be confirmed by further research including different fidelity tools and turbines.

The idea of shared mooring systems has been introduced in the offshore wind farm industry as an effort to lower the overall installation costs for floating offshore wind farms. The reason for building such plants is that using floating turbines allows them to move to deeper waters, reducing visual and environmental impact and allowing footprint reduction, with the downside being an increase in the total installation costs.

Because shared mooring lines create couplings between neighbouring turbines, the use of shared mooring lines adds complexity to the design and modelling of offshore floating wind farms. So far, these systems have been investigated and analysed using either quasi-static or fully dynamic models. With the goal of using a method that can be more accurate in terms of dynamic behaviour of the mooring lines than the quasi-static one and less time-consuming than the fully dynamic one by using a system with less degrees of freedom, this project seeks to further explore the idea of shared mooring lines within a quasi-dynamic model.

A quasi dynamic system is not as complex as the dynamic model but more rigorous than the quasi-static one because it includes terms related to the drag and inertia of the mooring lines. Inertial loads on mooring lines can alter the tension of the mooring line at the fairlead, while drag forces on mooring lines will dampen platform motions, especially for slowly varying motions. These are the two reasons why it is critical to include these effects in the model. In this case inertial terms have not been considered, focusing mainly on including drag terms for both the anchor and shared lines together with the geometric and elastic stiffnesses.

To begin with, the quasi-dynamic model has been applied to a two-turbine system, constrained to move only horizontally in surge as a model assumption. The model has been implemented in Matlab as a two-degree-of-freedom system.

The ultimate goal of this research is to see if this approach can be used instead of conducting a thorough dynamic analysis. As a result, in addition to the Matlab model, an equivalent system in SIMA has been built to perform a full dynamic analysis and allow comparison of the two models' findings.

Based on the model results, it appears possible to obtain good accuracy for both motion amplitudes and tension values in a shorter amount of time than a full-dynamic analysis. Indeed, some correlation has been observed between the results obtained with the quasi-dynamic model and the full dynamic one, especially at lower forcing frequencies.