Accurate Modeling of Material Nonlinearities in a Wind Turbine Spar Cap.
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Various wind turbine blade components, such as shear webs and skins, commonly use fiber-reinforced composite sandwich structures with a core material like balsa or foam. During manufacturing, core gap defects may result from the misalignment of adjacent foam or balsa core sheets in the blade mold. It is important to understand the influence that core gaps have on the structural integrity of wind turbine blades and how to mitigate their influence. This research characterized the effects of core gap defects at the manufacturing and mechanical levels for both epoxy and next-generation thermoplastic composites. Common repair methods were assessed and compared. Multiple defect sizes were compared using temperature data gathered with thermocouples embedded during manufacturing to core gap defect characteristics obtained using image-mapping techniques, optical microscopy, and mechanical characterization by long beam flexure. Results showed that peak exothermic temperatures during curing were closely related to core gap size. The long beam flexure tests determined that transverse core gaps under pure bending loads can have a substantial effect on the ultimate facesheet strength of both epoxy and thermoplastic composite sandwich structures (up to 25% strength reduction), although the size of the defect itself had less of an influence on the magnitude of the strength reduction. The supporting image-mapping techniques indicated that the distortion of the composite facesheets by the core gaps contributed to the premature failures. The repair methods used in this study did very little to improve the ultimate strength of the sandwich panels that previously had core gap defects. The repair of the thermoplastic panel resulted in a further loss in ultimate facesheet strength. This research demonstrated that there is a vital need for the development of a compatible thermoplastic polymer repair resin system and appropriate resin specific repair procedures for the next generation of recyclable thermoplastic wind blades.
Presentation at the 7th Wind Energy Systems Engineering workshop from NREL principal engineer Jason Jonkman, Ph.D., on NREL's numerical tools Wind Energy with Integrated Servo-control (WEIS), which focuses on the integrated design of floating wind turbines, and FAST.Farm, a simulation tool for multi-turbine wind farms based on popular aero-servo-hydro-elastic solver OpenFAST. The presentation discusses recent advancements beyond wind turbine aero-elasticity.
Offshore floating wind foundations supporting a large wind turbine require a large yard facility or significant facility upgrades for their fabrication. To overcome the cost increase associated with facility upgrades, an innovative lightweight modular floating foundation is developed. The foundation comprises multiple modules to enable their assembly on water, offering many benefits and expanding fabrication options for a reduction in the overall cost of the platform. In this paper, the foundation modules and their assembly are briefly described, and an analysis of the platform’s dynamic responses is presented. The modular foundation includes a modular and lightweight tension leg platform (TLP) called “MarsVAWT” which supports a Darrieus 10 MW vertical axis wind turbine (VAWT). The platform is moored with highly pretensioned wire rope tendons. The responses of the platform are analyzed in the time domain in a semi-coupled manner under the turbine operating and parked conditions for an offshore site in the US Northeast. The tower base shear forces and bending moments increase considerably with the combination of wind and waves, compared to those with wind only. The tendon tensions on the weatherside in the operating condition at high wind speeds are comparable to the values of the 50-year extreme (parked). The tendon tension increases are highly correlated to the platform pitch, as well as the horizontal and vertical velocities and vertical acceleration at the tendon porch. The modular platform performances and tendon designs are confirmed to comply with industry standards and practices.
Abstract Offshore wind energy deployment in the U.S. is expected to increase in the years to come, with proposed wind farm sites located in regions with high risk for tropical cyclones. Yet, the wind turbine design criteria outlined by the International Electrotechnical Commission for extreme events may not account for wind field characteristics unique to tropical cyclones. To evaluate if current design standards capture the extreme conditions of these storms, we perform idealized large‐eddy simulations of three tropical cyclones (one Category 1, one Category 2, and one Category 3 storms) using the Weather Research and Forecasting model. Wind conditions near the eyewall of Cat‐1, Cat‐2, and Cat‐3 storms can exceed current design standards for offshore wind turbines. Winds at 90 m can be faster than outlined in the design criteria for Class I and Class T turbines for 50‐year recurrence periods. Wind speed shear across the turbine rotor layer is also larger than assumed in design specifications. Moreover, vertical variations in wind direction across the turbine rotor layer are large for tropical cyclones of all intensity levels, suggesting design standards should include veer, which can amplify loads in wind turbines. The existence of hurricane wind field characteristics that are not represented in design standards does not imply that damage or failure will certainly occur. Engineering safety factors incorporated in the design of the turbine's blades and structural components may prevent damage from occurring.
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Modern wind turbines push the predictive capabilities of state-of-the-art aero-servo-elastic tools. The existing limitations hide across the numerical tool chain and can result in serious issues, such as missing aeroelastic instabilities during the design phase. Structural damping is an input that is usually hard to estimate, but also has a major impact on the turbine behavior. In this paper, we discuss an experiment that aims to accurately quantify the structural damping characterizing the edgewise modes of modern wind turbine blades. The experiment is carried out on a 2.8-MW land-based wind turbine and features a fast yaw actuation that induces an edgewise motion on one of the three blades. The Covariant-subspace system identification (Cov-SSI) method is then used to post-process the blade root moment to estimate the short-term edgewise structural damping. Despite limitations of the Cov-SSI method, which consistently under-predicts the absolute values of damping, we observe that structural damping decreases across the first three blade edgewise modes, which is different from the stiffness-proportional damping model that assumes that structural damping increases with the modes. This paper argues that a stiffness-proportional damping model, which is implemented in most aeroelastic tools, is therefore not conservative and might hide aeroelastic instabilities that can instead appear in the field.
While modern wind turbines have become by far the largest rotating machines on Earth with further upscaling planned for the future, a renewed interest in small wind turbines (SWTs) is fostering energy transition and smart grid development. Small machines have traditionally not received the same level of aerodynamic refinement as their larger counterparts, resulting in lower efficiency, lower capacity factors, and therefore a higher cost of energy. In an effort to reduce this gap, research programs are developing worldwide. With this background, the scope of the present study is 2-fold. In the first part of this paper, an overview of the current status of the technology is presented in terms of technical maturity, diffusion, and cost. The second part of the study proposes five grand challenges that are thought to be key to fostering the development of small wind turbine technology in the near future, i.e. (1) improving energy conversion of modern SWTs through better design and control, especially in the case of turbulent wind; (2) better predicting long-term turbine performance with limited resource measurements and proving reliability; (3) improving the economic viability of small wind energy; (4) facilitating the contribution of SWTs to the energy demand and electrical system integration; (5) fostering engagement, social acceptance, and deployment for global distributed wind markets. To tackle these challenges, a series of unknowns and gaps are first identified and discussed. Based on them, improvement areas are suggested, for which 10 key enabling actions are finally proposed.
Gearbox and wind turbine design and application standards have contributed significantly to improvements in reliability over the past two decades. The International Electrotechnical Commission (IEC) 61400-4 standard of wind turbine gearbox design is currently being revised by a joint working group (JWG) of experts in IEC TC 88 (wind energy) and International Organization for Standardization (ISO) TC60 (gears) to further that effort. Experts from ISO TC4 (rolling bearings) and ISO TC28 (lubricants) have actively participated. This revision has implemented lessons learned from industry use of edition 1 since its publication in 2012. The main document, IEC 61400-4, was pared down to essential design requirements and application-specific recommendations along with a design verification framework. The JWG leveraged concurrent development of other standards, such as IEC 61400-8 on wind turbine structures, to replace edition 1 content. These are described along with how this works with the IEC Renewable Energy certification scheme for wind turbines (IECRE-WE). The JWG recognized the interest in maintaining informative parts of edition 1 including annexes on wind turbine architecture and loads, bearing and gear arrangements, bearing selection, lubrication system descriptions and lubricant performance recommendations. This information was retained in two technical reports: IEC/TR 61400-4-2 Lubrication and IEC/TR 61400-4-3 Explanatory Notes. Additionally, a technical specification, IEC/TS 61400-4-1, was drafted to provide a reliability calculation method for comparing different design options or conditions. Salient elements of these documents are described. All four documents were recently distributed for IEC/ISO review, ballot, and comment. Publication is expected in 2023.
This Technology Commercialization Fund (TCF) CRADA involved demonstration of NREL modeling capability using OpenFAST (formerly known as FAST) to design the next generation of floating offshore wind turbines (FOTW) with Stiesdal’s TetraSpar design. The objective of the project was to enable the design and optimization of next generation FOWT that show promise to make FOWT cost-competitive with other energy technologies by upgrading, verifying, and validating improvements to OpenFAST. This objective was achieved by (1) upgrading OpenFAST to compute floating substructure flexibility and member-level loads, which is critical to enable the design of floating substructures—especially newer designs that are streamlined, flexible, and cost-effective; (2) verifying the new OpenFAST capabilities through model-to-model comparisons and validating the capabilities through comparisons to empirical data generated with wave-tank testing, using TetraSpar data provided by Stiesdal; and (3) making available the upgraded OpenFAST tool to the wind energy community to enable next-generation floating wind designs.
Current wind turbine blade materials may not be damage tolerant to the extent necessary to optimize the Levelized Cost of Energy (LCOE) of wind energy plants. Traditionally, wind turbine blades have been designed using a safe-life approach, but advances in inspection techniques and structural health monitoring solutions give rise to the opportunity to design wind turbine blades using a damage tolerant approach. Materials selection is a key element of da mage tolerant design, so the extent of the damage tolerance of alternative materials has been analyzed through a literature review and discussions with industry leaders. Fabrics and resin selection significantly affect the damage tolerance of composites. Changes to fabric architecture may include through-the-thickness (TTT) fibers, stretch-broken carbon fiber (SBCF) composites, and aligned discontinuous fiber reinforced composites (ADFRCs). Previous research has demonstrated that using TTT fibers in creases damage tolerance, but additional research is necessary to demonstrate the effectiveness of SBCFs and ADFRCs in mitigating damage. Several studies have demonstrated increased damage tolerance when toughened resin systems are used. In addition to toughened resin systems, thermoplastics have been shown to be tougher than thermosets. However, thermosets have been traditionally preferred in wind turbine blade manufacturing due to ease of manufacturing. Thermoplastic resin system s have been developed that can be used with conventional manufacturing methods but have yet to be studied for its damage tolerant capabilities. Furthermore, cost and stress analyses on where to effectively implement TTT fibers, SBCF composites, ADFRCs, and toughened resin systems must be executed prior to incorporating new materials into wind turbine blade manufacturing.
Within the rapidly growing wind energy sector, floating offshore wind turbines are expected to be the fastest growing portion. This is largely driven by the immense offshore wind resources that are mostly over deep water, where fixed-bottom concepts become cost prohibitive. However, compared to fixed-bottom wind turbines, floating wind turbines are more dynamic and exhibit potential instabilities, which requires advanced control technologies to ensure a safe and efficient operation. Beyond their existing objectives of maximizing power production while minimizing structural loads, floating wind turbine controllers must also avoid large platform oscillations and accommodate wave disturbances. This paper provides an overview of the challenges and opportunities in the control of floating offshore wind energy systems.
Wind turbine power production deviates from the reference power curve in real-world atmospheric conditions. Correctly predicting turbine power performance requires models to be validated for a wide range of wind turbines using inflow in different locations. The Share-3 exercise is the most recent intelligence-sharing exercise of the Power Curve Working Group, which aims to advance the modeling of turbine performance. The goal of the exercise is to search for modeling methods that reduce error and uncertainty in power prediction when wind shear and turbulence digress from design conditions. Herein, we analyze data from 55 wind turbine power performance tests from nine contributing organizations with statistical tests to quantify the skills of the prediction-correction methods. We assess the accuracy and precision of four proposed trial methods against the baseline method, which uses the conventional definition of a power curve with wind speed and air density at hub height. The trial methods reduce power-production prediction errors compared to the baseline method at high wind speeds, which contribute heavily to power production; however, the trial methods fail to significantly reduce prediction uncertainty in most meteorological conditions. For the meteorological conditions when a wind turbine produces less than the power its reference power curve suggests, using power deviation matrices leads to more accurate power prediction. We also determine that for more than half of the submissions, the data set has a large influence on the effectiveness of a trial method. Overall, this work affirms the value of data-sharing efforts in advancing power curve modeling and establishes the groundwork for future collaborations.
Visual impacts of wind turbines have been a persistent concern for wind energy development in the United States (US) for decades and remain a major source of project delays and cancellations. Assessments of visual impacts are frequently performed at a local scale for individual projects, but a comprehensive understanding of broader geographic patterns in visual impacts across the US is lacking. This paper presents a visual impact assessment of the existing land-based wind turbine fleet of the contiguous United States (CONUS). The assessment combines geographic information systems and 3D simulation methods to account for key factors driving the visual magnitude of impacts from the installed turbines. The results indicate that, despite the deployment of approximately 70,000 turbines and over 144 gigawatts of land-based wind in the CONUS, the visual impacts are very small when measured as a proportion of land area, population, and sensitive visual resources. Nonetheless, visual impacts are not evenly distributed: people experience a concentrated share in a small number of natural settings, primarily including plains, prairies, and deserts. Finally, we find that although increased density of wind development consistently leads to visual impacts across a greater proportion of land, it does not always lead to impacts to a greater share of the population. These findings suggest that visual impacts from wind energy are generally well-mitigated across the CONUS to date but also highlight the need for a deeper understanding of landscape sensitivity and individual perceptions of wind turbines in the most heavily impacted natural settings.
Patterns of bat activity and mortalities at wind energy facilities suggest that bats are attracted to wind turbines based on bat behavioral responses to wind turbines. For example, current monitoring efforts suggest that bat activity increases post-wind turbine construction, with bats making multiple passes near wind turbines. We separated the attraction hypothesis into five previously proposed explanations of bat interactions at or near wind turbines, including attraction based on noise, roost sites, foraging and water, mating behavior, and lights, and one new hypothesis regarding olfaction, and provide a state of the knowledge in 2022. Our review indicates that future research should prioritize attraction based on social behaviors, such as mating and scent-marking, as this aspect of the attraction hypothesis has many postulates and remains the most unclear. Relatively more data regarding attraction to wind turbines based on lighting and noise emission exist, and these data indicate that these are unlikely attractants. Analyzing attraction at the species-level should be prioritized because of differences in foraging, flight, and social behavior among bat species. Lastly, research assessing bat attraction at various scales, such as the turbine or facility scale, is lacking, which could provide important insights for both wind turbine siting decisions and bat mortality minimization strategies. Identifying the causes of bat interactions with wind turbines is critical for developing effective impact minimization strategies.
Lidar scanners are capable of taking measurements of a wind field upstream of a wind turbine. The wind turbine controller can use these measurements as a “preview” of future disturbances impacting the turbine. Such preview-enabled (or feedforward) controllers show superior performance to standard wind turbine control configurations based purely on a feedback architecture. To capitalize on the performance improvements that preview wind measurements can provide, feedforward control actions should be timed to coincide with the arrival of the wind field at the wind turbine location. However, the time of propagation of the wind field between the lidar measurement location and the wind turbine is not perfectly known. Moreover, the best time to take feedforward control action may not perfectly coincide with the true arrival time of the wind disturbance. This contribution presents results from an experiment where preview-enabled model predictive control was deployed on a fully-actuated, scaled model wind turbine operating in a wind tunnel testbed. In the study, we investigate the sensitivity of the controller performance to the assumed propagation delay using a range of wind input sequences. We find that the preview-enabled controller outperforms the feedback only case across a wide range of assumed propagation delays, demonstrating a level of robustness to the time alignment of the incoming disturbances.
Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.