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At least 19 records

Wind turbine blades, wind turbines, and wind farms having increased power output

A wind turbine blade having a geometry that decreases the distance downstream at which freestream momentum is recovered is disclosed. The blade design increases the loading on the inboard portion of the blade and unloads the tip portion relative to a conventional blade designed to maximize power coefficient. A wind farm having a reduced inter-turbine distance and including one or more wind turbines having the new blade designs is also disclosed.

Kelley, Christopher Lee↗

Control Co-Design of Wind Turbines

Wind energy is recognized worldwide as cost-effective and environmentally friendly, and it is among the fastest-growing sources of electrical energy. To further decrease the cost of wind energy, wind turbines are being designed at ever-larger scales. To expand the deployment of wind energy, wind turbines are also being designed on floating platforms for placement in deep-water locations offshore. Both larger-scale and floating wind turbines pose challenges because of their greater structural loads and deflections. Complex, large-scale systems such as modern wind turbines increasingly require a control co-design approach, whereby the system design and control design are performed in a more integrated fashion. This article reviews recent developments in control co-design of wind turbines. We provide an overview of wind turbine design objectives and constraints, issues in the design of key wind turbine components, modeling of the wind turbine and environment, and controller coupling issues. Wind turbine control functions and the integration of control design in co-design are detailed with a focus on co-design compatible control approaches.

17 WIND ENERGY↗

The Inception of OMA in the Development of Modal Testing Technology for Wind Turbines

Wind turbines are immense, flexible structures with aerodynamic forces acting on the rotating blades at harmonics of the turbine rotational frequency, which are comparable to the modal frequencies of the structure. Predicting and experimentally measuring the modal frequencies of wind turbines has been important to their successful design and operation. Performing modal tests on wind turbine structures over 100 meters tall is a substantial challenge, which has inspired innovative developments in modal test technology. For wind turbines, a further complication is that the modal frequencies are dependent on the turbine rotation speed. The history and development of a new technique for acquiring the modal parameters using output-only response data, called the Natural Excitation Technique (NExT), will be reviewed, showing historical tests and techniques. The initial attempts at output-only modal testing began in the late 1980's with the development of NExT in the 1990's. NExT was a predecessor to OMA, developed to overcome these challenges of testing immense structures excited with environmental inputs. We will trace the difficulties and successes of wind turbine modal testing from 1982 to the present. Keywords: OMA, Modal Analysis, NExT, Wind Turbines, Wind Excitation

James, George H., III↗

Seismic centrifuge modelling of suction bucket foundation for offshore wind turbine

Wind Energy is the one of the most promising renewable energy. Suction bucket foundation is considered to be a viable type of wind turbine foundation. Soil liquefaction caused by earthquakes at offshore seismic active area may lead to a significant degradation of soil strength and stiffness. In this study, nine centrifuge tests were carried out to investigate the seismic response of suction bucket foundation under earthquake loading. Both dry and saturate soil conditions were considered in tests. The geometric design of five suction bucket models considered the bucket diameter, penetration depth, and modified buckets with inside compartments. It was found that soil underlying and near the bucket foundation shown a better ability to resist liquefaction in saturated tests comparing to free field while no significant differences were observed in dry tests. The five bucket models performed quite differently, which demonstrated the aspect ratio effects and inside-bucket compartment effects. The results provide insight into optimized design of suction bucket foundation for wind turbine.

17 WIND ENERGY↗

Wind turbulence inputs for horizontal axis wind turbines

Wind turbine response characteristics in the presence of atmospheric turbulence was predicted using two major modeling steps. First, the important atmospheric sources for the force excitations felt by the wind turbine system were identified and characterized. Second, a dynamic model was developed which describes how these excitations are transmitted through the structure and power train. The first modeling step, that of quantifying the important excitations due to the atmospheric turbulence was established. The dynamic modeling of the second step was undertaken separately.

Holley, W. E.↗

Inverse load calculation procedure for offshore wind turbines and application to a 5‐MW wind turbine support structure

Abstract A significant number of wind turbines installed today have reached their designed service life of 20 years, and the number will rise continuously. Most of these turbines promise a more economical performance if they operate for more than 20 years. To assess a continued operation, we have to analyze the load‐bearing capacity of the support structure with respect to site‐specific conditions. Such an analysis requires the comparison of the loads used for the design of the support structure with the actual loads experienced. This publication presents the application of a so‐called inverse load calculation to a 5‐MW wind turbine support structure. The inverse load calculation determines external loads derived from a mechanical description of the support structure and from measured structural responses. Using numerical simulations with the software fast , we investigated the influence of wind‐turbine‐specific effects such as the wind turbine control or the dynamic interaction between the loads and the support structure to the presented inverse load calculation procedure. fast is used to study the inverse calculation of simultaneously acting wind and wave loads, which has not been carried out until now. Furthermore, the application of the inverse load calculation procedure to a real 5‐MW wind turbine support structure is demonstrated. In terms of this practical application, setting up the mechanical system for the support structure using measurement data is discussed. The paper presents results for defined load cases and assesses the accuracy of the inversely derived dynamic loads for both the simulations and the practical application. Copyright © 2017 John Wiley & Sons, Ltd.

Pahn, T.↗

Models of Lift and Drag Coefficients of Stalled and Unstalled Airfoils in Wind Turbines and Wind Tunnels

Equations are developed with which to calculate lift and drag coefficients along the spans of torsionally-stiff rotating airfoils of the type used in wind turbine rotors and wind tunnel fans, at angles of attack in both the unstalled and stalled aerodynamic regimes. Explicit adjustments are made for the effects of aspect ratio (length to chord width) and airfoil thickness ratio. Calculated lift and drag parameters are compared to measured parameters for 55 airfoil data sets including 585 test points. Mean deviation was found to be -0.4 percent and standard deviation was 4.8 percent. When the proposed equations were applied to the calculation of power from a stall-controlled wind turbine tested in a NASA wind tunnel, mean deviation from 54 data points was -1.3 percent and standard deviation was 4.0 percent. Pressure-rise calculations for a large wind tunnel fan deviated by 2.7 percent (mean) and 4.4 percent (standard). The assumption that a single set of lift and drag coefficient equations can represent the stalled aerodynamic behavior of a wide variety of airfoils was found to be satisfactory.

Spera, David A.↗

Sensitivity of Uncertainty in Wind Characteristics and Wind Turbine Properties on Wind Turbine Extreme and Fatigue Loads

Wind turbine design relies on the ability to accurately predict turbine ultimate and fatigue loads. The loads analysis process requires precise knowledge of the expected wind-inflow conditions as well as turbine structural and aerodynamic properties. However, uncertainty in most parameters is inevitable. It is therefore important to understand the impact such uncertainties have on the resulting loads. The goal of this work is to assess which input parameters have the greatest influence on turbine power, fatigue loads, and ultimate loads during normal turbine operation. An Elementary Effects (EE) sensitivity analysis is performed to identify the most sensitive parameters. Separate case studies are performed on (1) wind-inflow conditions and (2) turbine structural and aerodynamic properties, both using the National Renewable Energy Laboratory (NREL) 5-MW baseline wind turbine. The focus is on individual parameter sensitivity, though interactions between parameters are considered.

17 WIND ENERGY↗

Fixed pitch wind turbines

Wind turbines designed for fixed pitch operation offer potential reductions in the cost of the machine by eliminating many costly components. It was shown that a rotor can be designed which produces the same energy annually as Mod-0 but which regulates its power automatically by progressively stalling the blades as wind speed increases. Effects of blade twist, taper, root cutout, and airfoil shape on performance are discussed as well as various starting technqiues.

Fenn, D. B.↗

Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements

Light detection and ranging (LiDAR) measurements of isolated wakes generated by wind turbines installed at an onshore wind farm are leveraged to characterize the variability of the wake mean velocity and turbulence intensity during typical operations, which encompass a breadth of atmospheric stability regimes and rotor thrust coefficients. The LiDAR measurements are clustered through the k-means algorithm, which enables identifying the most representative realizations of wind turbine wakes while avoiding the imposition of thresholds for the various wind and turbine parameters. Considering the large number of LiDAR samples collected to probe the wake velocity field, the dimensionality of the experimental dataset is reduced by projecting the LiDAR data on an intelligently truncated basis obtained with the proper orthogonal decomposition (POD). The coefficients of only five physics-informed POD modes are then injected in the k-means algorithm for clustering the LiDAR dataset. The analysis of the clustered LiDAR data and the associated supervisory control and data acquisition and meteorological data enables the study of the variability of the wake velocity deficit, wake extent, and wake-added turbulence intensity for different thrust coefficients of the turbine rotor and regimes of atmospheric stability. Furthermore, the cluster analysis of the LiDAR data allows for the identification of systematic off-design operations with a certain yaw misalignment of the turbine rotor with the mean wind direction.

17 WIND ENERGY↗

Wind Turbine Design Optimization for Hydrogen Production

To help meet the need for inexpensive green fuels, we are working on wind turbine design optimization specifically for hydrogen production. We have thus far achieved a 1.53% decrease in LCOH as compared to a turbine optimized for LCOE using the same code, design variables, and models. We accomplished this by optimizing some components of the wind turbine tower, rotor, and drivetrain design with hydrogen production and costs in the design loop.

hydrogen↗

2020 Small Wind Turbine Certification Awardee: Star Wind Turbines

With support from the Competitiveness Improvement Project's Small Turbine Certification Award, Star Wind Turbines aims to earn third-party certification for their small wind turbine model STAR74-6. Certification will help instill public confidence in the product's performance and safety standards. This fact sheet provides an overview of Star Wind's project, how the company will achieve the goals of the award, and how the project fits within the overall Competitiveness Improvement Project.

CIP↗

On the Effects of Wind Turbine Wake Skew Caused by Wind Veer: Preprint

Because of Coriolis forces caused by the Earth's rotation, the structure of the atmospheric boundary layer often contains wind-direction change with height, also known as wind-direction veer. Under low turbulence conditions, such as in stably stratified atmospheric conditions, this veer can be significant, even across the vertical extent of a wind turbine's rotor disk. The veer then causes the wind turbine wake to skew as it advects downstream. This wake skew has been observed both experimentally and numerically. In this work, we attempt to examine the wake skewing process in some detail, and quantify how differently a skewed wake versus a non skewed wake affects a downstream turbine. We do this by performing atmospheric large-eddy simulations to create turbulent inflow winds with and without veer. In the veer case, there is a roughly 8 degree wind direction change across the turbine rotor. We then perform subsequent large-eddy simulations using these inflow data with an actuator line rotor model to create wakes. The turbine modeled is a large, modern, offshore, multimegawatt turbine. We examine the unsteady wake data in detail and show that the skewed wake recovers faster than the non skewed wake. We also show that the wake deficit does not skew to the same degree that a passive tracer would if subject to veered inflow. Last, we use the wake data to place a hypothetical turbine 9 rotor diameters downstream by running aeroelastic simulations with the simulated wake data. We see differences in power and loads if this downstream turbine is subject to a skewed or non skewed wake. We feel that the differences observed between the skewed and nonskewed wake are important enough that the skewing effect should be included in engineering wake models.

17 WIND ENERGY↗

Fleetwide data-enabled reliability improvement of wind turbines

Wind farms are an indispensable driver toward renewable and nonpolluting energy resources. However, as ideal sites are limited, placement in remote and challenging locations results in higher logistics costs and lower average wind speeds. Therefore, it is critical to increase the reliability of the turbines to reduce maintenance costs. Robust implementation requires a thorough understanding of the loads subject to the turbine's control. Yet, such dynamically changing multidimensional loads are uncommon with other machinery, and generally underresearched. Therefore, a multitiered approach is proposed to investigate the load spectrum occurring in wind farms. Our approach relies on both fundamental research using controllable test rigs, as well as analyses of real-world loading conditions in high-frequency supervisory control and data acquisition data. A method is introduced to detect operational zones in wind farm data and link them with load distributions. Additionally, while focused research further investigates the load spectrum, a method is proposed that continuously optimizes the farm's control protocols without the need to fully understand the loads that occur. A case of gearbox failure is investigated based on a vast body of past experiments and suspect loads are identified. Starting from this evidence on the cause and effects of dynamic loads, the potential of our methods is shown by analyzing real-world farm loading conditions on a steady-state case of wake and developing a preventive row-based control protocol for a case of cascading emergency brakes induced by a storm.

17 WIND ENERGY↗

Online Learning of Effective Turbine Wind Speed in Wind Farms

To develop better wind farm controllers that can meet more complex objectives, methods of modeling the wind turbine wakes at low computational expense are needed. Gaussian process (GP) regression offers a computationally inexpensive framework for learning complex functions from noisy measurements with very few datapoints. In this work, an online learning approach is presented to learn the rotor-averaged wind velocity at downstream wind turbines with GPs, using the available datastream of wind field measurements and wind turbine control set-points. This framework can readily be integrated into model-based controls methods because the model a) is updated online at low computational expense, b) assumes a mathematically favorable Gaussian form, and c) explicitly quantifies the stochastic nature of the wake field so that the trade-off between exploration and exploitation, and the uncertainty in the prediction, can be utilized. We show that a GP-learned model can match true values with errors within 0.5% on average, with as few as 5 training data points.

Gaussian process↗

Floating Wind Turbine Control Optimization

We present a framework for optimizing the control parameters of floating offshore wind turbines (FOWTs). The framework combines aeroelastic simulations with a systems engineering model and control software. In an example of the optimization framework, we minimize tower damage equivalent loading with generator speed constraints. We also study the effect of thrust-limiting control and quantify the trade off between fatigue loading and energy capture using a set of optimal controller designs. Finally, we optimize the controller of four different FOWT models and compare their dynamic responses. Additional details and other use cases for the framework are presented, which can optimize different control problems and evaluate FOWT designs.

controls↗