Large wind turbines face design challenges due to increased flexibility of blades. Conventional control strategies fail under large deformations, impacting performance. We present a feedforward–feedback control scheme, addressing flexibility and overcoming the limitations of conventional strategies. By testing it on a large-scale reference turbine with realistic wind conditions, we demonstrated improvements to power by up to 5 % while constraining blade deflections.

This paper presents a methodology for assessing the system design and scaling trends in airborne wind energy (AWE). A multi-disciplinary design, analysis, and optimisation (MDAO) framework was developed, integrating power, energy production, and cost models for the fixed-wing ground-generation (GG) AWE concept. Using the levelized cost of electricity (LCoE) as the design objective, we found that the optimal size of systems lies between the rated power of 100 and 1000 kW.

This work uses simulations to investigate floating offshore wind turbines which have the potential to supply the world's electricity demand many times by 2040. In particular, the effect of the rotor motion on the wake was investigated by forcing the turbine to move under different motions and the results highlight differences between motions. While some motions led to a wake behavior that was close to that of a fixed-bottom turbine, other motions produced a remarkably different wake structure.

The paper investigates the influence of the rain drop diameter on the formation of erosion damage and its implications for erosion-safe mode (ESM). By building an erosion damage model that incorporates several drop-size effects, we found that large droplets are significantly more erosive than small droplets. It is shown that the performance of the ESM is significantly increased when drop-size effects are correctly accounted for. A method to derive optimal ESM strategies is given as well.

Next-generation wind turbines are the largest rotating machines ever built, experiencing local flow Mach where the incompressibility assumption is violated, and even transonic flow can occur. This study assesses the transonic features over the FFA-W3-211 wind turbine tip airfoil for selected industrial test cases, defines the subsonic–supersonic flow threshold and evaluates the Reynolds number effects on transonic flow occurrence. Shock wave occurrence is also depicted.

Rain droplets damage wind turbine blades due to the high impact speed at the tip. In this study, it is found that rain droplets and wind turbine blades interact aerodynamically. The rain droplets slow down and deform close to the blade. A model from another field of study was adapted and validated to study this process in detail. This effect reduced the predicted erosion damage by up to 50 %, primarily affecting smaller drops. It is shown how the slowdown effect can influence erosion mitigation.

In a subsidy-free era, there is a need to optimize wind turbines for maximizing farm revenue instead of minimizing cost of energy. A wind-farm-level modeling framework with a simplified market model is used to optimize the turbine size for maximum profitability. The results show that the optimum size is driven mainly by the choice of the economic metric and the market price scenario, with a design optimized for the cost of energy already performing well w.r.t. most profitability-based metrics

When standing still without a nacelle or blades, the vibrations on a wind turbine tower are of concern to its structural health. This study finds that the air which flows around the tower recirculates behind the tower, forming so-called wakes. These wakes initiate the vibration, and the movement itself causes the vibration to increase or decrease depending on the wind speed. The current study uses a methodology called force partitioning to analyse this in depth.

Turbines are becoming larger. However, it is important to understand the key drivers of turbine design and explore the possibility of a global optimum, beyond which further upscaling might not reduce the cost of energy. This study explores, for a typical farm, the entire turbine design space with respect to rated power and rotor diameter. The results show a global optimum that is subject to various modeling uncertainties, farm design conditions, and policies with respect to wind farm tendering.

As wind turbines produce power, they leave behind wakes of slow-moving air. We analyse three different models to predict the effects of these wakes on downstream wind turbines. The models are validated with experimental data from wind tunnel studies for steady and time-varying conditions. We demonstrate that the models are suitable for optimally controlling wind turbines to improve power production in large wind farms.

Wind turbines placed in farms interact with their wake, lowering the power production of the wind farm. This can be mitigated using so-called wake mixing techniques. This work investigates the coupling between the pulse wake mixing technique and the motion of floating wind turbines using the pulse. Frequency response experiments and time domain simulations show that extra movement is undesired and that the optimal excitation frequency is heavily platform dependent.