The growing importance of renewable energy to meet the demands of growing population has driven much focus for research in the wind energy sector. Currently most of the power production in the wind energy sector is done using the Horizontal Axis Wind Turbine (HAWT). due to its higher efficiency and reliability as compared to Vertical Axis Wind Turbine (VAWT). However, due to limitations of HAWTs such as the complex yaw mechanism, higher positioning of the center of mass and relatively difficult up-scaling, VAWT are receiving more attention. Attempt to access high range of power from VAWTs at offshore locations may damage the turbine blades due to increased loads. This thesis is dedicated to reduce the periodic disturbances on the turbine blades of VAWTs without affecting the total power production in a rotation, thereby ensuring the reliability and safe operation of VAWT. A control technique called Subspace Predictive Repetitive Controller (SPRC) is used for the recursive identification to estimate the parameters of wind turbine model and further providing an optimal control law accordingly. Basis functions have been used to reduce the dimensionality of the system, following which the system identification has been performed in the lifted domain. Using the identified model, two types of control approaches have been applied. In the first approach, the objective function is to track a specific reference that indicates blade load. This reference ensures a reduction in peak loads of the VAWT by transferring the loads from their upstream to their downstream part, without comprising on the power production in one whole rotation of VAWT. In the second approach, a general control strategy is used in which the controller is given freedom to choose the pitch trajectory so as to reduce the blade loads. The controller is specified with a power reference that ensures the maintenance of total power. This strategy allows the turbine to be operated in different wind conditions, as a higher weighting is assigned to power production when wind speeds are less than rated wind speeds, and a higher weighting is assigned to the reduction of blade load when wind speeds are more than the rated wind speeds. . These results show a real potential of the data-driven SPRC approach in wind turbines, and highlights new mechanisms to reduce the turbine loads on c{VAWT}s. These mechanisms offer valuable insights into enhancing the functions of VAWTs in a more reliable and damage-free manner.

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.

The rapid growth of Floating Offshore Wind (FOW) has spurred intensive research across various aspects of the floating system. A standard practice in mooring system design within the industry is that anchors remain fixed on the seabed. In contrast, plate-type anchors exhibit mobility under loading, a crucial factor considering the thousands of loading cycles experienced by FOW turbines during operation. Understanding the strain accumulation mechanism during cyclic loading has substantial implications for design. This thesis delves into the behavior of Drag Embedded Anchors (DEAs) subjected to static monotonic and cyclic loading, utilizing 3-dimensional Finite Element simulations. The installation trajectory of DEAs is initially defined through established analytical methodologies. Subsequently, the movement of the anchor and soil response under monotonic and cyclic loads is elucidated. Analytical expressions for monotonic force-displacement curves are examined, identifying optimal models and offering relevant parameter values for different anchor trajectory points. Under cyclic loading, the influence of average load and cyclic load amplitude is studied, along with exploring the feasibility of applying an existing 1-dimensional model for predicting anchor response.