A gap in the understanding of offshore wind submarine power cables is responsible for 70-80 % of failures in recent times. The failures originate from the phases of design, manufacturing, installation and operations. Joint industry collaborations such as the Cable Lifetime Monitoring project that form the background for this thesis, are aimed at developing knowledge of these failures. The origination of failures from the installation phase of power cables is of particular interest. In order to do so, a model has to be developed first to understand the processes involved in an installation plan, as well as their time and resource costs. Logistics and planning tools such as ECN Install are utilized for this purpose and provide the medium for capturing the installation processes for submarine power cables. This thesis aims to describe the installation of power cables using a discrete event simulation based logistics model such as ECN Install. The first part of the thesis focuses on a literature review to categorize all aspects of power cable installation. Here the stages of a project, the installation processes, assets, methods and influencing weather parameters are identified. From this literature review it is found that the most important stage of a power cable installation project is the Marine Installation Program. The decisions leading to the development of a Marine Installation plan are mapped for modelling. The second part of the thesis deals with applying the knowledge acquired into the logistics model. Here, the model assumptions are set in order to create an accurate depiction of the installation processes. The third part of the thesis investigates the influence of input uncertainties on the model as a means to understand the relationship between the different aspects of a power cable installation project to its Marine Installation Program. A sensitivity study is performed to quantify the impact of different uncertainties on a Marine Installation Program. The final part of the thesis has the analysis of a historical case study. Here the Marine Installation Program of the Gemini export cable is constructed.

In order to reduce the levelised cost of energy, the rotors of wind turbines are increasing in size. To increase the energy yield, wind turbine rotors need to have an innovative tip design; such as winglets. Winglets are used widely in aircraft design; however, they remain mostly absent in state-of-the-art wind turbine design. The low-fidelity wind turbine design models used by industry, such as BEM, are insufficient to capture the full 3D flow physics in such an innovative design. Therefore, high-fidelity methods, such as vortex methods, are becoming more and more important in such a design phase in wind energy research. Single-objective optimisation has been applied in earlier works to maximise power production. Winglets have shown the potential of increasing power production while simultaneously increasing the design-driving loads (DDLs), for example, the thrust or flapwise bending moment. This work focuses on optimisation using machine learning of a winglet that increases power production without increasing DDLs. A parameterised design for a winglet on a wind turbine is created. Different design constraints, such as DDLs or a diameter constraint, are explored to determine under which constraints and conditions a winglet can have an added value to the wind turbine blade design. Multi-objective Bayesian optimisation is used to maximise the rotor's power production and minimise DDLs. Surrogate models, created using machine learning techniques such as Gaussian Processes and Bayesian Neural Networks, are used in combination with an acquisition function, to determine what designs should be evaluated by the lifting line model AWSM. This has the goal to obtain designs that lie on the Pareto front of two or more objectives. The recent Bayesian Neural Networks were able to find the Pareto front most effectively in this work. Furthermore, the results show that different DDL constraints led to different winglet designs, with noticeable differences between upwind and downwind winglet designs obtained by the optimiser. Both a downwind and upwind winglet were found to be able to increase power without increasing the thrust, root flapwise bending moment and flapwise bending moment at 80% of the rotor radius.