Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.

The present investigation used numerical simulations to study the vortex induced vibrations (VIVs) of a 96 m long wind turbine blade. The results of this baseline shape were compared with four additional geometry variants featuring different tip extensions. The geometry of the tip extensions was generated through the variation of two design parameters: the dihedral angle bending the blade out of the rotor plane and the sweep angle bending the blade in the rotor plane. The applied numerical methods relied on a fluid structure interaction (FSI) approach, coupling a computational fluid dynamics solver with a multi-body structural solver. The methodology followed for locating VIV regions was based on the variation of the inclination angle. This variable was defined as the angle between the freestream velocity and the blade axis, being 0° when these vectors were normal and positive when a velocity component from tip to root was introduced. For the baseline geometry, the FSI simulations predicted significant blade vibrations for inclination angles between 47.5° and 60° with a maximum peak-to-peak amplitude of 2.3 m. The installation of the different tip extensions on the blade geometry was found to significantly modify the inclination angles where VIV was observed. In particular, the simulations of three of the tip designs showed a shifting of several degrees for the point where the maximum vibrations were recorded. For the specific tip geometry where only the sweep angle was taken into account, a total mitigation of the VIV was observed.

The present investigation used numerical simulations to study the vibrations of a wind turbine blade in standstill. Such vibrations are presumed to affect horizontal axis wind turbine designs and can jeopardize the structural integrity of the machine. The applied numerical methods relied on a fluid–structure interaction (FSI) approach, coupling a computational fluid dynamics (CFD) solver with a multibody finite-element structural solver. A 96-m-long wind turbine blade was studied for a large parametric space, accounting for the variation of both pitch and inclination. The inclination was defined as the angle between the freestream velocity and the cross-sectional plane at the root, allowing for the introduction of a flow component in the spanwise direction. The pitch variation corresponded to the rotation of the inflow around the spanwise axis, steering the angles of attack seen by the airfoils. Two regimes of vibrations were characterized, depending on the considered range of the inclination angle. For high inclinations, the pitch angles leading to vibrations clustered around a particular region of the parametric space, and the appearance of large oscillations was accompanied by the synchronization of the loading with the frequency of motion. At low inclination angles, the mechanism triggering vibrations was relatively similar, even if the excitation spectrum was richer, and the critical pitch angles seemed to be more scattered. Regardless of the inflow, the problem was highly three-dimensional, and several complex flow phenomena such as oblique shedding and phase dislocations were identified.

This work presents a high-fidelity shape optimization framework based on computational fluid dynamics (CFD). The presented work is the first comprehensive curved tip shape study of a wind turbine rotor to date using a direct CFD-based approach. Preceding the study is a thorough literature survey particularly focused on wind turbine blade tips in order to place the present work in its context. Then follows a comprehensive analysis to quantify mesh dependency and to present needed mesh modifications ensuring a deep convergence of the flow field at each design iteration. The presented modifications allow the framework to produce up to six-digit-accurate finite difference gradients which are verified using the machine-accurate Complex-Step method. The accurate gradients result in a tightly converged design optimization problem in which the studied problem is to maximize power using 12 design variables while satisfying constraints on geometry, as well as on the bending moment at 90 % blade length. The optimized shape has about 1 % $r/R$ blade extension, 2 % $r/R$ flapwise displacement, and slightly below 2 % $r/R$ edgewise displacement resulting in a 1.12 % increase in power. Importantly, the inboard part of the tip is de-loaded using twist and chord design variables as the blade is extended, ensuring that the baseline steady-state loads are not exceeded. For both analysis and optimization an industrial-scale mesh resolution of above 14×10⁶ cells is used, which underlines the maturity of the framework.

In this work, a computationally efficient engineering model for the aerodynamics of swept wind turbine blades is proposed for the extended blade element momentum (BEM) formulation. The model is modified based on a coupled near- and far-wake model, in which the near wake is assumed to be the first quarter revolution of the non-expanding helical wake of the own blade. For the special case of in-plane trailed vorticity, the original empirical equations determining the steady-state value of the near-wake induction are replaced by the analytical results, which are in the form of incomplete elliptic integrals. For the general condition of helical trailed vorticities, the steady-state near-wake induction is approximated based on the results of the special conditions and a correction factor. The factor is calculated using empirical equations with influence coefficient tensors, to minimize the computational effort. These influence coefficient tensors are pre-calculated and are fitted to the results from the numerical integration of the Biot–Savart law. With the indicial function approach, it is not necessary to explicitly save the information of the vorticities that were trailed in the previous time steps. This engineering approach is a combination of analytical results and numerical approximations, with low and constant computational effort for each time step. The proposed model is practically applicable to time-marching aero-servo-elastic simulations. The results of the swept blades with uniform inflow perpendicular to the rotor calculated from the proposed model are compared with the results from a BEM code, a lifting-line solver and a Navier–Stokes solver. The significantly improved agreement with the higher-fidelity models compared to the BEM method highlights the performance of the proposed method.