This study aims to enhance wind turbine modeling by incorporating industry-standard control functionalities. A control design framework was developed and applied to a 1 : 100 scale model of a large floating wind turbine. Wind tunnel tests confirmed the scaled turbine accurately reproduced the steady-state rotor speed, blade pitch, and thrust torque characteristics of the full-size turbine. However, challenges arose in simulating the turbine's aerodynamic response during above-rated operation.

Vortex generators are evaluated on a 2 MW wind turbine rotor blade by computational fluid dynamic methods. Those devices delay flow separation on the airfoils and thus increase their efficiency. On the wind turbine blade, rotational phenomena (e.g. rotational augmentation) appear and interact with the vortices from the vortex generators. The understanding of those interactions is crucial in order to optimise the placement of the vortex generators and evaluate their real efficiency on the blade.

We present recent research on dynamically modelling wind farm wakes and integrating these enhancements into the wind farm simulator, HAWC2Farm. The simulation methodology is showcased by recreating dynamic scenarios observed in the Lillgrund offshore wind farm. We successfully recreate scenarios with turning winds, turbine shutdown events, and wake deflection events. The research provides opportunities to better identify wake interactions in wind farms, allowing for more reliable designs.

Vertical axis wind turbines experience a variation of torque and power throughout their rotation. Traditional non-morphing blades are intrinsically not able to respond to this variation, resulting in a turbine which has suboptimal performance. In principle, it is possible to have a morphing blade that adapts to the blade's rotation and changes its geometry in such a way as to optimise the performance of the turbine. This paper addresses the question of how such blade should morph as it rotates.

Wake steering is a promising strategy to increase the power output of modern wind farms by mitigating the negative effects of aerodynamic interaction among turbines. As farm layouts grow in size to meet renewable targets, the complexity of wake steering optimisation increases too. With the objective of enabling robust and predictable wake steering solutions, this study investigates the sensitivity of wake steering optimisation for three different farm layouts with increasing complexity levels.

With the challenges of ensuring secure energy supplies and meeting climate targets, wind energy is on course to become the cornerstone of decarbonized energy systems. This work proposes a new method to optimize wind farms by means of smartly placing wind turbines within a given project area, leading to more green-energy generation. This method performs satisfactorily compared to state-of-the-art approaches in terms of the resultant annual energy production and other high-level metrics.

Wind turbines are designed to withstand any wind conditions they might encounter. This includes high-turbulence flow fields found within wind farms due to the presence of the wind turbines themselves. The international standard allows for two ways to account for wind farm turbulence in the design process. We compared both ways and found large differences between them. To avoid overdesign and enable a site-specific design, we suggest moving towards validated, higher-fidelity simulation tools.