Modern wind turbines are the largest rotating machines ever built, with blade lengths exceeding 100 m. Previous studies demonstrated how the flow around the tip airfoils of such large machines reaches local flow Mach numbers (Ma), at which the incompressibility assumption might be violated, and, even in normal operating conditions, local supersonic flow could appear. In the present study, a numerical analysis of the FFAW3- 211 wind turbine tip airfoil is performed. The results are obtained by means of the application of numerical tools: (1) XFOIL with the Prandtl–Glauert compressible correction and (2) computational fluid dynamic (CFD) simulations, where an unsteady Reynolds-averaged Navier–Stokes (URANS) model is used. A preliminary validation of the latter CFD model is performed to demonstrate that the URANS approach is a viable method for predicting the aerodynamic performances in compressible and transonic flow that provides additional and more reliable information compared to the classical compressibility corrections. From this study, three key findings can be highlighted. Primarily, the main transonic features of the FFA-W3-211 wind turbine tip airfoil have been assessed, selecting specific test cases of particular industrial interest. Then, the threshold between subsonic and supersonic flow is provided, considering also an increase of the Reynolds number (Re) from a characteristic value used in the wind tunnel experiments to the one realistic for large rotors. A strong dependence on this quantity is observed, revealing that, for the same Mach number, also the Reynolds number plays a crucial role in promoting the occurrence of transonic flow. Finally, the possible presence or absence of shock waves was investigated. The results indicate that the appearance of transonic flow is a necessary but not a sufficient condition to lead to shock formation. @en

Leading-edge rain erosion is a severe problem in the wind energy community since it leads to blade damage and a reduction in annual energy production by up to a few percent. The impact speed of rain droplets is a key driver of the erosion rate; therefore, its precise computation is essential. This study investigates the aerodynamic interaction of rain droplets and wind turbine blades. Based on findings from the literature and an analysis of the relevant parameter space, it is found that the aerodynamic interaction leads to a reduction in the impact speed. Additionally, the rain droplets deform and break up as they approach the wind turbine blade. An existing Lagrangian particle model, developed for research in aircraft icing, is adapted, extended, and validated for leading-edge rain erosion to study the process in more detail. Results show that the droplet slowdown reduces predicted damage toward the tip of the blade by over 50 %. The model indicates that the aerodynamic blade interaction affects small droplets significantly more than large droplets. Due to this drop-size dependency, the damage accumulation is shifted toward higher-rain-intensity events. Additionally, the droplet impact speed is sensitive to the aerodynamic nose radius of the airfoil. Due to this sensitivity and its drop-size dependency, the slowdown effect provides interesting levers for erosion mitigation via blade design or operational adjustments. To conclude, the aerodynamic interaction between droplet and blade is non-negligible and needs to be taken into account in erosion lifetime models. @en

This study performed an aerodynamic characterization of the FFA-W3-211 wind turbine tip airfoil in transonic flow using Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations, for both steady and dynamic operational conditions. First, the boundary between subsonic and supersonic flow in static conditions was identified, depending on the angle of attack, the approach flow Mach number, and the Reynolds number. The analysis points out that higher Reynolds numbers promote the occurrence of local supersonic flow. Thereafter, to investigate the dynamic behavior in the transonic flow regime, a sinusoidal pitching motion with representative values was imposed. A hysteresis, similar to but distinct from dynamic stall, was observed for entering and leaving the supersonic and subsonic regions. Elevated reduced frequencies widened the hysteresis loop, resulting in increased normal forces on the airfoil. The study indicated that an increase in reduced frequency leads to an earlier onset of transonic flow. In conclusion, the risk of transonic flow occurring during normal operation of the next generation wind turbines predicted in earlier studies could be corroborated. Moreover, dynamic effects and Reynolds number dependencies can be significant.

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Traditionally, wind turbine and wind farm designs have been optimized to minimize the cost of energy. Such a design would make sense when bidding in price-based auctions. However, in a future with a high share of renewables and zero subsidies, the wind farm developer is exposed to the volatility of market prices, where the price paid per kilowatt-hour of energy would not be constant anymore. The developer might then have to maximize the revenue earned by participating in different energy, capacity, or ancillary services markets. In such a scenario, a turbine designed for maximizing its market value could be more profitable for the developer compared to a turbine designed for minimizing the levelized cost of electricity (LCoE). This study is in line with this paradigm shift in the field of turbine and farm design. It is a continuation of a previous study conducted by the same authors , which explicitly focused on the drivers of turbine sizing with respect to LCoE. The goal of this study is to optimize the design for a new set of objective functions and analyze how various day-Ahead market conditions and objectives drive turbine design. A simplified market model that can generate hourly day-Ahead market prices is developed and coupled with a wind-farm-level multidisciplinary design analysis and optimization (MDAO) framework to evaluate key economic indicators of the wind farm. The results show how the optimum turbine design is driven by both the choice of the economic metric and the market scenario. However, an LCoE-optimized design is found to perform well with respect to profitability-based economic metrics like modified internal rate of return (MIRR) or profitability index (PI), indicating a limited need to redesign turbines for a specific day-Ahead market scenario.

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The flow around wind turbine towers usually reaches very high Reynolds numbers greater than a million. Understanding the flow around the towers under these conditions is crucial, as it may lead to vibrations due to the vortices formed. Investigating aerodynamic characteristics at such high Reynolds numbers, both numerically and experimentally, is challenging. The current study validates such an experimental study, where a rough surface is employed to increase the effective Reynolds numbers and accelerate the laminar-turbulent transition in the boundary layer. Unsteady Reynolds-Averaged Navier-Stokes (RANS) simulations are carried out using OpenFOAM for a Reynolds number range of 1.36·105 to 6.8·105. The constant (a 1) used to calculate the eddy viscosity is varied to simulate the flow separation during adverse pressure gradients. A force partitioning method is implemented in OpenFOAM and various force contributions are analysed for this Reynolds number range. It is seen that the RANS simulations overpredict the aerodynamic characteristics and the extent of flow separation unless the value of a 1 is varied as a function of the Reynolds number. Furthermore, it is observed that the only force contributor is the vorticity-induced force, as the simulations are performed for a fixed cylinder.

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In existing wind farms, the overall power output can be increased through yaw control. However, the cooperative control of start/stop, yaw and turbines positions is often overlooked, leading to wake superposition to downstream wind turbines and suboptimal power output. This paper proposes a synchronized optimized method that considers start/stop, yaw and turbines positions control based on a three-dimensional wake model and yaw flow superposition model. The objective function of the proposed strategy is to maximize the power output of the Chapman Ranch (CR) wind farm. Four cases are considered: start-stop, yaw control, start-stop & yaw control and start-stop & yaw & turbines positions control. The particle swarm algorithm is introduced to optimize the wind farm layout. According to the results, considering start-stop, yaw and turbines positions optimization can not only increase the annual power output of the wind farm by 8.85 %, but also avoid the colliding wake in the CR wind farm. However, the other three cases will cause colliding wake in some fields of the CR wind farm. This study provides important guidance on improving the overall power output of existing wind farms.

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Vortex-induced vibration (VIV) of wind turbine towers during installation is an aero-structural problem of significant practical relevance. Vibrations may happen in the tower structure, especially when the rotor-nacelle assembly is not yet attached to the tower or if the rotor blades are not yet connected to the tower-nacelle assembly. The complexity of aeroelastic phenomena involved in VIV makes modelling and analysis challenging. Therefore, the aim of the current research is to investigate the fundamental mechanisms causing the onset and sustenance of vortex-induced vibrations. To gain more understanding of the nature of vibrations, a methodology is established that distinguishes between different components of the forces at play. This approach allows for identifying how various force components impact the oscillation of a rigid body. The method is executed using the OpenFOAM open-source software. Numerical simulations are conducted on a two-dimensional smooth cylinder at both subcritical and supercritical Reynolds numbers to establish a correlation between wind turbine tower vibrations and the force mechanism. The analysis involves performing unsteady Reynolds-averaged Navier–Stokes (URANS) simulations using the modified pimpleFoam solver with the k–ω shear stress transport (SST) turbulence model. Both fixed and free-vibrating cases are studied for smooth cylinders. For the high-Reynolds-number cases, a setup matching the tower top segment of the IEA 15 MW reference wind turbine was chosen. Studying the flow around a cylinder at a subcritical Reynolds number reveals that the primary force involved is the vortex-induced force. The combined force due to viscosity, added mass, and vorticity contributes most to the overall force. For a freely vibrating cylinder with a single degree of freedom in the crossflow direction, the analysis indicates that the force component associated with the cylinder's motion is crucial and significantly affects the total force. Moreover, analysing the energy transfer between the fluid and the structure, a positive energy contribution by the vortex-induced force is observed on or before the dominant Strouhal velocity. This confirms observations at low Reynolds numbers in the literature that the vortex shedding predominantly contributes to the initiation of oscillations during VIV. The kinematic force contributes to the energy transfer of the system, but the mean energy transfer per cycle is negligible.@en

Large-scale exploitation of offshore wind energy is deemed essential to provide its expected share to electricity needs of the future. To achieve the same, turbine and farm-level optimizations play a significant role. Over the past few years, the growth in the size of turbines has massively contributed to the reduction in costs. However, growing turbine sizes come with challenges in rotor design, turbine installation, supply chain, etc. It is, therefore, important to understand how to size wind turbines when minimizing the levelized cost of electricity (LCoE) of an offshore wind farm. Hence, this study looks at how the rated power and rotor diameter of a turbine affect various turbine and farm-level metrics and uses this information in order to identify the key design drivers and how their impact changes with setup. A multi-disciplinary design optimization and analysis (MDAO) framework is used to perform the analysis. The framework uses low-fidelity models that capture the core dependencies of the outputs on the design variables while also including the trade-offs between various disciplines of the offshore wind farm. The framework is used, not to estimate the LCoE or the optimum turbine size accurately, but to provide insights into various design drivers and trends. A baseline case, for a typical setup in the North Sea, is defined where LCoE is minimized for a given farm power and area constraint with the International Energy Agency 15 MW reference turbine as a starting point. It is found that the global optimum design, for this baseline case, is a turbine with a rated power of 16 MW and a rotor diameter of 236 m. This is already close to the state-of-the-art designs observed in the industry and close enough to the starting design to justify the applied scaling. A sensitivity study is also performed that identifies the design drivers and quantifies the impact of model uncertainties, technology/cost developments, varying farm design conditions, and different farm constraints on the optimum turbine design. To give an example, certain scenarios, like a change in the wind regime or the removal of farm power constraint, result in a significant shift in the scale of the optimum design and/or the specific power of the optimum design. Redesigning the turbine for these scenarios is found to result in an LCoE benefit of the order of 1 %–2 % over the already optimized baseline. The work presented shows how a simplified approach can be applied to a complex turbine sizing problem, which can also be extended to metrics beyond LCoE. It also gives insights into designers, project developers, and policy makers as to how their decision may impact the optimum turbine scale.@en

The ever-growing demand for renewable energy, driven by cost-effectiveness and minimal ecological impacts, has resulted in the deployment of larger wind turbines with rotor diameters surpassing 200 m. This underscores the importance of a thorough understanding of flow dynamics to optimize operational efficiency in diverse atmospheric inflow scenarios. Understanding the intricate impact of atmospheric conditions, including wind shear and turbulence, on wind turbine wakes is crucial for optimizing wind farm layouts and performance, influencing wake evolution, turbine loads, and power output. This research focuses on bridging the gap between idealized inflow scenarios and real-world atmospheric inflow conditions by systematically integrating linear shear, turbulence and the logarithmic wind shear profile into the uniform inflow conditions and analyzing the wake behind the IEA-15 MW wind turbine. To specifically examine inflow effects, a constant hub height wind speed was maintained through a velocity controller. The study focuses on analyzing the wake's flow field and providing insights into its recovery process. It was found that turbulence plays a critical role in a faster wake recovery as well as increasing the power production of the turbine for sheared inflows and the wind speed selected.

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The erosion-safe mode (ESM) is a novel mitigation strategy that reduces rainfall-induced erosion damage by lowering the tip-speed of the turbine during precipitation events. The ESM requires accurate information about future expected rainfall for its control. In current research, it is debated what method or source should be used to this end. This study explores the effectiveness of driving the ESM using a state-of-the-art weather-radar-based probabilistic rainfall nowcast provided by the Royal Netherlands Meteorological Institute (KNMI). The performance of the nowcast is assessed for various lead times with an impingement-based damage model for three sample sites in the Netherlands and for two distinct ESM strategies. The results show that the quality of the nowcast degrades with increasing lead times, where the 5- and 15-minute lead times exhibit sufficiently good accuracy and response time for adjusting turbine speeds. Overall, the results highlight that the probabilistic information in the nowcast can be employed to improve the efficiency and viability of the ESM.

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The future of wind turbines will be characterised by long, slender blades subject to dynamic inflow and aeroelastic deflections. This makes the next generation of blades more prone to encounter dynamic stall effects, in which significant forces and loads fluctuations can be expected. Dynamic stall models can be tailored to suit the aerodynamics of different airfoils. Although different dynamic stall models exist, the impact of the choice of model, its implementation and calibration on the overall wind turbine performance remains to be assessed. In this work, we gathered an experimental dynamic dataset for a representative airfoil, the FFA-W3-211, to define the semi-empirical time constants for the Beddoes-Leishman dynamic stall model. An important differentiation is made between stall regions for positive and negative angles of attack, and the impact of tailored coefficients is assessed at airfoil scale. The difference between the tailored and untailored model is quantified for power performance and loads of the IEA 15 MW reference wind turbine. The results highlight a significant load over-prediction from the untailored Beddoes-Leishman model, whereas changes in power performance are negligible.

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For scenarios of high penetration of renewable energy, it becomes increasingly relevant to improve the dispatchability of supply for wind and solar power plants. Baseload power plants, required to produce a minimum power production at all times, are discussed in this context. The baseload constraint can be satisfied with renewable sources when combined with a storage system but at a high cost. This work studies the design drivers of such a storage system when consisting of short and long-term storage. The capacities of the short-term and long-term storage components are calculated as part of a linear optimization problem with the objective of minimizing the cost of baseload, using a metric based on a net present value formulation. Our analysis, based on 10 locations in Northern Europe, highlights a high sensitivity of optimal storage sizing to storage cost assumptions. In addition, the cost of baseload is found to be correlated to the share of renewable power produced above baseload, but not to the correlation between price and wind power, suggesting arbitrage plays a minor role in the business case.@en

For the largest wind turbines currently designed, when operating at rated power and at high wind speeds, the tip airfoils can experience large negative angles of attack. For these conditions and in combination with turbulence, the airfoils are at risk of reaching locally supersonic flow, even at low free-stream Mach numbers. The possibility of shock wave formation and its consequences endangers the lifetime of these largest rotating machines ever built. So far only numerical analyses of this challenge have been attempted with significant modelling uncertainty. Here, for the first time, a wind turbine airfoil (the FFA-W3-211, used at the blade tip of the IEA 15MW reference wind turbine) is studied under transonic conditions using experimental techniques. Schlieren visualization and Particle Image Velocimetry were employed for free-stream Mach numbers of 0.5 and 0.6 and various angles of attack. It was shown that calculations based on isentropic flow theory and compressibility corrections were able to predict the situations where supersonic flow occurred. However, they could not predict the frequency of occurrence and whether shock waves were formed. In conclusion, an unsteady characterization of such airfoil behavior in transonic flow seems to be warranted.

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Two setups are used to investigate differences between modeling a wind turbine nacelle by means of an actuator-line model (ALM) and a wall-model (WM) using large-eddy simulations. One advantage of the ALM is that it requires a lower mesh refinement, making it less computationally costly. In the first setup, the nacelle is in standalone configuration and the ALM results show a much lower turbulence intensity and a significantly slower wake recovery when compared to the WM cases. In the second setup, the nacelle is in a rotor-nacelle assembly configuration and many variations of the ALM are tested in order to match the results from the experiment addressed in the OC6 task phase III. Contrary to previous findings that the nacelle might affect the turbine loads, this study shows that the improved match with the experiment stems from the increased mesh refinement in the nacelle region rather than the actual presence of the nacelle. Nevertheless, the wake profiles in the near-wake show a very good agreement between the ALM and WM, regardless of the refinement in the nacelle region. These cases also show a higher wake deficit than not using any nacelle at all.

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Modern-day wind turbines are growing continuously in size and reach diameters of more than 200m in an effort to meet the fast growing demand for wind energy. As a consequence, the rotors are exposed to larger velocity variations in the approach flow due to the presence of shear, veer and turbulence. The shear of the ambient flow is an important effect that can impact the wake of a turbine twofold: one way is how the wake evolves in the sheared flow; the other way is by impacting the performance and loading of the turbine and, hence, the wake it produces. Both ways can affect the size, shape, spreading and recovery of the turbine wake and, consequently, impact on loads and power output of turbines located downstream. In this study, we analyzed the influence of different inflow wind shear configurations on the evolution of the wake behind the IEA 15MW reference wind turbine by means of high-resolution Large-Eddy Simulations. In order to isolate the shear effects, the mean and hub height wind speed of the inflow was kept constant by prescribing linear shear profiles without turbulence. The influence of Coriolis forces and thermal stratification are neglected. In addition, the effect of the imposed shear on the turbine's power and thrust, and the effect of including the nacelle in the simulation, were monitored.

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In this research, we explored the potential to reduce the cost of floating wind farms by adopting an integrated approach to optimally size semi-submersible substructures accounting for materials, fabrication and installation-logistics-related costs. A trade-off between manufacturing and installation costs was identified. This trade-off is driven by the growth of shipyard costs when the size of the structure increases, counteracting the reduction of fabrication costs achieved with a larger semi-submersible footprint. For the reference scenario, accounting for this trade-off yields a design that is a few tenths of a percent cheaper than when minimising only fabrication costs. However, the obtained design has a considerably smaller footprint than the fabrication-only case. The sensitivity of this trade-off to different installation strategies affecting the required storage area at the shipyard was assessed. When fabrication costs are dominant, the advantage of accounting for installation costs in the design process is negligible. Instead, larger storage area requirements increase the cost reduction achieved by optimising the semi-submersible while simultaneously accounting for fabrication and installation costs. The coupling effect remained significant for all the cases considered in a further sensitivity analysis of key parameters affecting the cost-optimal design. Furthermore, we identified several different designs that provide enough hydrostatic restoring moment in pitch to counteract the thrust-induced overturning moment within a small cost range from the most cost-effective one. This result suggests that additional criteria than minimising manufacturing and installation costs could drive the final design choice.

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The future generation of wind turbines will be characterised by longer and more flexible blades. These large wind turbines are facing higher Reynolds numbers, as a consequence of longer chord lengths and increased relative wind speeds. Higher tip speeds, however, also result in an increased Mach number. Although the maximum tip speed in steady design conditions may remain (well) below the critical value, the presence of turbulence, wind gusts, blade deflections, etc. in combination with the flow acceleration over the airfoil surface, may cause a significant increase in the velocity perceived over the blade surface. We have evaluated the operational conditions of the IEA 15MW reference turbine using OpenFAST in normal design and off-design conditions to demonstrate that, if unabated, near-future wind turbines will be at risk of suffering from local supersonic flow. The driving factor is identified to be inflow turbulence, however, the tip airfoil is also of major importance. Local supersonic flow conditions may lead to severe lifetime degradation.

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Offshore wind energy (OWE) is a cornerstone of future clean energy development. Yet, research into global OWE material demand has generally been limited to few materials and/or low technological resolution. In this study, we assess the primary raw material demand and secondary material supply of global OWE. It includes a wide assortment of materials, including bulk materials, rare earth elements, key metals, and other materials for manufacturing offshore wind turbines and foundations. Our OWE development scenarios consider important drivers such as growing wind turbine size, introducing new technologies, moving further to deep waters, and wind turbine lifetime extension. We show that the exploitation of OWE will require large quantities of raw materials from 2020 to 2040: 129–235 million tonnes (Mt) of steel, 8.2–14.6 Mt of iron, 3.8–25.9 Mt of concrete, 0.5–1.0 Mt of copper and 0.3–0.5 Mt of aluminium. Substantial amounts of rare earth elements will be required towards 2040, with up to 16, 13, 31 and 20 fold expansions in the current Neodymium (Nd), Dysprosium (Dy), Praseodymium (Pr) and Terbium (Tb) demand, respectively. Closed-loop recycling of end-of-life wind turbines could supply a maximum 3% and 12% of total material demand for OWE from 2020 to 2030, and 2030 to 2040, respectively. Moreover, a potential lifetime extension of wind turbines from 20 to 25 years would help to reduce material requirements by 7–10%. This study provides a basis for better understanding future OWE material requirements and, therefore, for optimizing future OWE developments in the ongoing energy transition.

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