bluuebunny/crossref_metadata_2025 huggingface dataset:
Turbine power loss during yaw-misaligned free field tests at different atmospheric conditions
Authors: Hulsman Paul , Sucameli Carlo , Petrović Vlaho , Rott Andreas , Gerds Alexander , Kühn Martin
Published: June 2022

This paper presents an analysis of the power loss of the upstream turbine for yaw misalignment depending on the inflow condition. High-quality experimental field data, obtained from a lidar wind profiler, met mast, GPS based yaw sensor, turbine data, and load data is used. To reduce the spreading of the power loss during yaw misalignment, the rotor effective wind speed is estimated using load data. Furthermore, the so-called power loss coefficient currently used in most engineering models, for yaw misalignment, is assessed at various inflow conditions. As main finding, the power loss coefficient increases for stronger vertical wind shear. In addition, there is an asymmetry with respect to the direction of the yaw misalignment that is enhanced by the wind shear exponent and the wind veer. Neglecting these two effects could result in in-conservative wake-steering decisions at stable stratification
A physics-, SCADA-based remaining useful life calculation approach for wind turbine drivetrains
Authors: Binsbergen Diederik van , Soares Marcelo Nesci , Pedersen Eilif , Nejad Amir R.
Published: June 2022

This paper describes the development of a physics-, SCADA-based model able to predict the expected lifetime for wind turbine drivetrains. A real-time coupled torsional gearbox-generator model is developed using the bond graph approach in the software 20SIM. The model uses SCADA data with a sampling frequency of one hertz to impose a load reference on the wind turbine for the simulation model. From the SCADA measurements, rotor torque is estimated and used as input load to the wind turbine rotor, while generator speed is used as reference in the control loop for maximum power point tracking. Shaft torsion is used to predict highspeed shaft radial and axial bearing loads from static equilibrium. The load amplitude and the number of stress cycles are calculated using the load duration distribution method and damage is calculated using Miner’s rule. Expected lifetime is predicted by linear extrapolation of the accumulated fatigue damage to the fatigue limit. Results show that the model can capture the torsional and electrical dynamics and that the model results agree with the reference input. The radial bearing loads match well with literature where additional sensors are used to determine the loads.
Reconstructing the bending moments time history of wind turbine tower from acceleration measurements using Gaussian processes
Authors: Pimenta Francisco , Pacheco João , Pereira Sérgio , Magalhães Filipe
Published: June 2022

The proper estimation of the fatigue damage accumulated over time for a given wind turbine is a key information when evaluating the remaining lifetime of the structure. While the most obvious way to do so is to instrument the structure with strain gauges, not only this is a demanding task, it also only provides information about the sections that are being monitored. In this work we propose a new methodology to estimate the fatigue damage in any section of the tower based on the accelerations time series and a single instrumented section with strain gauges. We argue that accelerations and displacements of a linear structure under stochastic loading share a well defined covariance structure. This conclusion allow us to define a Monte Carlo Markov Chain (MCMC) algorithm to constrain the parameters that best describe this structure, as well as to use all the machinery associated with gaussian processes to convert accelerations into displacements, and these into bending moments. Using artificial experimental data obtained from a previously validated numerical model as input to our method, we obtained a good agreement between the simulated and reconstructed response. The results concerning fatigue damage were also in reasonable agreement, although presenting higher deviations that must be analysed in future studies.
Model predictive control of wind turbine with aero-elastically tailored blades
Authors: Hussain R , Yue H , Recalde-Camacho L
Published: June 2022

The use of aero-elastically tailored blades (ATB) for large wind turbines has shown the benefit of mitigating blade loads, in a passive adaptive manner, with the design of bend-twist coupling (BTC) along the blades. The BTC design makes the blades torsionally flexible and capable of adapting to different wind speeds. However, such increased flexibility makes the turbine modeling computationally demanding and the real-time controller design more challenging. In this work, to include the ATB effect into the turbine model for control, a twofold modeling for ATB characteristics is proposed. First a static BTC distribution is added to the turbine aerodynamics to account for the blade’s pre-bend-twist design, next a second-order transfer function is introduced to approximate the blade structural dynamic response to wind speed variations. The nonlinear model of the whole ATB wind turbine is built up in Simulink, linearized and discretized into a state-space form. A model predictive controller (MPC) is developed with the actuator constraints considered. Simulation studies are conducted on a 5MW ATB wind turbine at a selected above-rated wind speed. The use of the simplified model for control is assessed and the performance of MPC is compared to the gain-scheduling baseline controller.
Flow Modelling for Wind Farm Control: 2D vs. 3D
Authors: van den Broek Maarten J. , Sanderse Benjamin , Wingerden Jan-Willem van
Published: June 2022

Control-oriented models provide a basis for wind farm control to improve power production and reduce structural loading. Wake steering is considered to be one of the most promising techniques to achieve this. Wind turbine wakes under yaw misalignment are deflected downstream and have been shown to produce a curled or kidney-shaped structure. A Navier-Stokes based code called FRED was developed to model wind farm flow in 2D to perform yaw control. To tackle the differences between 2D and 3D flow, this work introduces a generalised continuity correction and wind turbine force scaling terms to the FRED framework. The effectiveness of approximating 3D results is tested by comparison with 3D simulations in the same framework. The continuity correction is now applicable to general wind directions and effective in reducing wake width and speed-up effects. The magnitude of wake deflection can be tuned using a force scaling term. However, we show that there remains a qualitative difference in the deflection profile downstream, as well as a difference in the propagation of yaw effects over time. From this study we can conclude that there is a fundamental difference between 2D and 3D flow physics in spatial and temporal dynamics which makes the 2D modelling approach challenging for control without further empirical adjustments. The necessary corrections are likely to be complex and non-physical, leading to a departure from the first principles foundation that FRED is developed from.
Results of fatigue measurement campaign on XL monopiles and early predictive models
Authors: Santos Francisco d N , Noppe Nymfa , Weijtjens Wout , Devriendt Christof
Published: June 2022

In the present contribution, data from a measurement campaign on XL monopiles (with 9.5 MW turbines and water depths of up to 36 m) is presented. This campaign is based on data collected by three types of sensors: strain gauges (installed at the TP-tower interface), accelerations (taken at bottom, mid and upper levels of the tower) and SCADA data, comprising of wind speed, yaw angle, power, pitch angle and rpm. Additionally, wave and tidal data from a public Flemish maritime weather database is added. In a comparative analysis of XL monopiles’ and standard monopiles it was seen that the fatigue behaviour of the former radically departs from the latter, with side-to-side damage surpassing fore-aft for nominal operational conditions, and standstill fatigue damage generally being bigger than nominal. Furthermore, following a methodology described in previous OWI-Lab research, artificial neural network models are trained using the aforementioned sensor data to estimate the fore-aft and side-side tower bending moment damage equivalent loads (DEL), through the use of three months worth of data with a comparative analysis ensuing. Finally, the models’ performance is investigated for concrete operating conditions by correlating it with environmental and operating conditions (EOCs).
Effect of wind turbine size on load reduction with active flow control
Authors: Gupta Abhineet , Rotea Mario A. , Chetan Mayank , Sadman Sakib M. , Todd Griffith D.
Published: June 2022

Decades of wind turbine research, development and installation have demonstrated reductions in levelized cost of energy (LCOE) resulting from turbines with larger rotor diameters and increased hub heights. Further reductions in LCOE by up-scaling turbine size can be challenged by practical limitations due to a mass increase trend. On-blade, active flow control devices have the potential to disrupt this trend by allowing longer blades with less mass through an active load control system. Typically, these load control systems are developed for specific wind turbines, making it difficult to study load reduction trends with turbine size to gain further insights into the benefits and risks of this control technology. This paper quantifies the variation in load reduction, complexity, and robustness of load control systems with flow control actuators for three turbines of increasing size. It is shown that, under limited control authority, load reduction can increase with turbine size provided more elaborate control algorithms are used to preserve the bandwidth and robustness of the control system.
A data-driven approach for fault diagnosis of drivetrain system in a spar-type floating wind turbine based on the multi-point acceleration measurements
Authors: Dibaj Ali , Nejad Amir R. , Gao Zhen
Published: June 2022

This paper deals with the condition monitoring of a floating wind turbine drivetrain using multi-point acceleration measurements. Single sensor data obtained from drivetrain system may provide insufficient information about the health condition due to the complicated structure and applied loading on this system. As a result, multi-point measurements are required to be employed for reliable fault diagnosis. The shared information between the multi-point measurements can be used for identifying the system’s condition. In this study, the fault diagnosis of the floating wind turbine drivetrain system is performed using a data-driven approach. Fault cases are considered in bearings most likely to damage. A combined principal component analysis (PCA) and deep convolutional neural network (CNN) is proposed to extract common and fault-related information between the measurements on the one hand and to classify different health conditions of the drivetrain on the other. It will be demonstrated that PCA-based information provides more satisfactory fault diagnosis results than individual sensor data. The method is numerically validated using the acceleration responses obtained from a 5-MW reference drivetrain model installed on a spar-type floating wind turbine.
Multi-scale Navier-Stokes analysis of geometrically resolved erosion of wind turbine blade leading edges
Authors: Ortolani Andrea , Castorrini Alessio , Sergio Campobasso M
Published: June 2022

A multi-scale computational fluid dynamics analysis of wind turbine blade leading edge erosion is presented. The test case is a large set of eroded blade sections. These are obtained by fitting the resolved eroded leading edge geometry of the outboard part of a multi-megawatt offshore wind turbine to the NACA633-618 airfoil. The erosion geometry measured by a blade laser scan is geometrically resolved in the aerodynamic simulations, whereas the aerodynamic effects of unresolved lower-amplitude scales are accounted for by using distributed surface roughness models. The simulations also account for the laminar-to-turbulent transition of the blade boundary layers with and without distributed roughness. An existing semi-empirical model and simulations of the nominal airfoil enable one to estimate the roughness level needed to trip leading edge boundary layer transition at the considered Reynolds number of 9 million. It is found that a) the mean roughness heights of the observed geometry perturbations are well above the critical roughness height, and b) consideration of either large or small erosion scales in isolation results in underestimating the airfoil performance impairment.
Wind Turbine Rotor aerodynamic imbalance detection using CNN
Authors: Hübner G.R. , da Rosa L. D. , de Souza C. E. , Pinheiro H. , Franchi C.M. , Morim R.B. , Ekwaro-Osire S. , Dias J.P. , Dabetwar S.
Published: June 2022

This paper investigates the use of convolutional neural networks (CNN) to automatically detect aerodynamic imbalances in horizontal axis wind turbines (WTs). The database is assembled with low-frequency acquisition rates, similar to those obtained using supervisory control and data acquisition (SCADA) systems. The methodology considers imbalances caused by pitch errors only, which might occur due to installation faults or pitch control errors. The measured raw data is initially processed using traditional statistical techniques. Next, the Gramian Angular Field (GAF) method is used to transform the statistical data into images, and then, a CNN is trained to identify aerodynamic rotor imbalance. The proposed methodology is evaluated under numerical simulations of a 1.5 MW wind turbine, and the accuracy and feasibility of the method are demonstrated. The paper demonstrates that it is possible to detect an aerodynamic imbalance in wind turbine rotors from statistics descriptors of nacelle IMU translational accelerations and wind speeds, considering a sampling frequency of above 0.05 Hz, and using an artificial intelligence technique.
Continuous grid frequency support with variable synthetic inertia and feedforward pitch angle adjustment
Authors: Gloe Arne
Published: June 2022

Grid frequency support by wind turbines is increasingly demanded by grid operators around the globe. By meeting these requirements, the wind turbines leave their optimal operating point and may even be pushed out of their safe operating range during severe grid events. In the past years, the Wind Energy Technology Institute developed a controller for grid frequency support in collaboration with Suzlon Energy. This work seeks to improve this controller by adding a pitch angle adjustment depending on the operating point of the wind turbine and the power adjustment for grid support. The controller performance is analysed for three scenarios and for the whole operating range of the NREL 5 MW WT. Simulations show, that the adjustment lowers the risk for overspeed at the cost of an increased pitch rate. By contrast, the aerodynamic efficiency is not increased by the additional control loop. The effect on the tower depends heavily on the wind situation during and shortly after the grid frequency support event.
Economic nonlinear model predictive control of fatigue for a hybrid wind-battery generation system
Authors: Anand Abhinav , Loew Stefan , Bottasso Carlo L.
Published: June 2022

An economic nonlinear model predictive controller (ENMPC) is formulated for a wind turbine-battery hybrid generation system. The controller aims to maximize the operational profit of the generator by balancing between generated wind power and turbine tower fatigue as well as battery cyclic fatigue. Other than the tower fore-aft fatigue, tower side-side fatigue is also considered to assess impact on overall economic performance. A moving horizon estimator (MHE) is formulated to provide meaningful initialization to the ENMPC in presence of plant model mismatch.The formulated controller utilizes the parametric online rainflow counting (PORFC) approach for direct cyclic fatigue cost minimization within ENMPC. The closed-loop simulation shows significantly higher profit compared to a realistic base-case scenario and relatively higher profit compared to another economic controller.
Aeroelastic modal dynamics of floating wind turbines in anisotropic conditions based on Floquet analysis
Authors: Schinas P , Manolas D. I. , Riziotis V. A. , Voutsinas S. G.
Published: June 2022

A reduced order model of a floating wind turbine with 22 degrees of freedom has been implemented and validated in comparison to the multibody, hydro-servo-aero-elastic code hGAST. The multi-blade Coleman transformation is applied and Floquet stability analysis is performed. This allows on one hand, to verify the actual Floquet implementation against the standard Coleman-based eigenvalue analysis in cases the transformed dynamic system has constant coefficients and on the other hand to analyze the effects of different anisotropies on stability. Mass imbalance of the rotor and yaw misalignment have been specifically addressed. In the mass imbalance scenario, the homogeneous results are not substantially altered while in the wind yaw scenario, there is slight change of the flapwise natural frequencies and of the tower lateral frequency as well as of the corresponding damping characteristics.
Using The Helix Mixing Approach On Floating Offshore Wind Turbines
Authors: Berg Daniel van den , Tavernier Delphine de , Wingerden Jan-Willem van
Published: June 2022

In recent years dynamic induction control has shown great potential in reducing wake-to-turbine interaction by increasing the mixing in the wake. With these wake mixing methods the thrust force will vary in time. If applied to a floating offshore wind turbine, it will cause the platform to move. In this paper the effect of the Helix mixing approach on a DTU10MW turbine on the TripleSpar platform and its wake is evaluated. When the Helix mixing approach is applied at Strouhal equal to 0.25, the yaw movement is excited close to the eigenfrequency of the platform resulting in significant yaw angles for small blade pitch angles. To understand the impact of the motion on the wake, the yaw motion is simulated using the free wake vortex method as implemented in Qblade. Under laminar inflow, results show that the windspeed at a distance of 5 rotor diameters downstream can be increased by up to 10% compared to a fixed-bottom turbine.
Including installation logistics costs in the optimal sizing of semi-submersibles for floating wind farms
Authors: Baudino Bessone M , Zaaijer M , von Terzi D , Dykes K , Jump E , Viré A
Published: June 2022

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.
An Open-Source Frequency-Domain Model for Floating Wind Turbine Design Optimization
Authors: Hall Matthew , Housner Stein , Zalkind Daniel , Bortolotti Pietro , Ogden David , Barter Garrett
Published: June 2022

A new frequency-domain dynamics model has been developed that uses open-source components to efficiently represent a complete floating wind turbine system. The model, called RAFT (Response Amplitudes of Floating Turbines), incorporates quasi-static mooring reactions, strip-theory and potential-flow hydrodynamics, blade-element-momentum aerodynamics, and linear turbine control. The formulation is compatible with a wide variety of support structure configurations and no manual or time-domain preprocessing steps are required, making RAFT very practical in design and optimization workflows. The model is applied to three reference floating wind turbine designs and its predictions are compared with results from time-domain OpenFAST simulations. There is good agreement in mean offsets as well the statistics and spectra of the dynamic response, verifying RAFT’s general suitability for floating wind analysis. Follow-on work will include verification of potential-flow and turbine-control features and application to optimization problems.
A frequency-time domain method for annual energy production estimation in floating wind turbines
Authors: Amaral R , Laugesen K , Masciola M , von Terzi D , Deglaire P , Viré A
Published: June 2022

A new method is proposed to estimate a floating wind turbine’s annual energy production (AEP) using frequency and time-domain design techniques. The approach demonstrated herein estimates the AEP by performing a convolution between the floating platform response and the response power operators (RPOs) that map the average power produced by the turbine as a function of the amplitude and frequency of the platform motions. One advantage of this approach is that it can be performed early in the conceptual design phase to help discover design space trade-offs between the platform and rotor design. The methodology is applied to the IEA Wind 15 MW WindCrete spar-buoy model using OpenFAST. The RPOs are obtained by prescribing single-DOF platform motions to the turbine with a given amplitude and frequency. This methodology is then validated by comparing the AEP estimation from the RPOs with the AEP estimation from fully-coupled simulations. The results indicate that the method is able to estimate the value of AEP for a realistic sea-state and regular waves. However, further validation is needed as, in the first case, the turbine is moving too little and, in the second case, the contribution of the controller may be dominant.
Surging Wind Turbine Simulations with a Free Wake Panel Method
Authors: Ribeiro A F P , Casalino D , Ferreira C S
Published: June 2022

We investigate the aerodynamics of a surging wind turbine with numerical simulations based on a free wake panel method. We start by demonstrating the method’s capability to simulate a plunging airfoil, which provides some insights that are later used to interpret results of a surging rotor. We then validate the method on a non-surging wind turbine and discuss the strengths and weaknesses of our approach. Next, we focus on the UNAFLOW case: a surging wind turbine which was modelled experimentally and with various numerical methods. Good agreement with experimental data is observed for amplitude and phase of the thrust with surge motion. For the first time, we achieve numerical results of a wind turbine wake that accurately reproduce experimentally verified effects of surging motion. Finally, we extend our simulations beyond the frequency range of the UNAFLOW experiments and reach results that do not follow a quasi-steady response. Using the plunging airfoil data, we justify the behavior observed in the non-linear range. Our work seeks to contribute a different method to the pool of results for the UNAFLOW case, while extending the analysis to conditions that have not been simulated before.
Current simulation with Software in the Loop for floating offshore wind turbines
Authors: Otter A , Flannery B , Murphy J , Desmond C
Published: June 2022

The presence of current is an added source of hydrodynamic loading on the platforms of Floating Offshore Wind Turbines (FOWT). Not only will current add viscous loading on the platform and moorings of FOWTs, but it will also affect wave loadings due to the alteration of wave shapes caused by wave-current interactions. Although the effects of current on platform response, mooring tensions and fatigue life have been numerically investigated, they are mostly neglected during scale model experiments for FOWTs. This paper proposes a novel method to simulate current loading and wave-current interactions during scale model tests by using a dynamic winch which is controlled using a Software in the Loop (SIL) approach. The winch is used in combination with a Multi-Propeller Actuator (MPA), for combined wave/wind/current testing in laboratory basins. The proposed current simulation method has lower costs and is more versatile than traditional physical current generation in a basin, as it allows for a wider range of test conditions and can be applied in any wave basin. A description of the experimental procedure is provided along with numerical validation using both AQWA and FAST. Results show that the winch actuator is capable of reliably emulating the drag force exerted by a current on the platform over a range of test conditions.
Surrogate model for fast simulation of turbine loads in wind farms
Authors: Bossanyi Ervin
Published: June 2022

A surrogate model for turbine loading is presented which has been developed for predicting the fatigue loads on each turbine in a wind farm, taking full account of wake effects, for detailed site-specific load assessment and/or to predict the effects of wind farm control on the loads. The model has been implemented in the wind farm simulation code LongSim, where it can be used both for steady-state setpoint optimisation against a merit function which can include both power and turbine loads, and for dynamic time-domain simulations, for example to evaluate the effects of wind farm control on turbine loading. For this application, fatigue loads need to be evaluated much more rapidly than is possible with full aeroelastic turbine simulations. Surrogate models based on fatigue load interpolation from a database of pre-computed aeroelastic turbine simulations are unwieldy and likely to miss important wake effects. The key simplifying approximation of the new model is that the load contributions from different causes can be calculated separately and then combined. This makes it straightforward to account for all relevant effects, at the same time vastly reducing the number of aeroelastic simulations required to populate the model.
Uncertainty quantification of wind turbine airfoil aerodynamics with geometric uncertainty
Authors: Marepally Koushik , Su Jung Yong , Baeder James , Vijayakumar Ganesh
Published: June 2022

An artificial neural network based reduced order model (ROM) is developed to predict the load coefficients and performance of wind turbine airfoils. The model is trained using a representative database of 972 wind turbine airfoil shapes generated by perturbing the design parameters in each of 12 baseline airfoils defining commercially relevant modern wind turbines. The predictions from our ROM show excellent agreement with the CFD data, with a 99thpercentile maximum errors of 0.03 in lift-coefficient, 2 in lift-to-drag ratio and 0.002 in pitching moment coefficient. A Monte-Carlo based uncertainty quantification (UQ) and global sensitivity analysis (GSA) framework is developed using this computationally economical ROM. Using UQ, we observed the stall behavior to be very sensitive to geometric uncertainty, with more than 10% deviation in lift coefficient associated to 5% deviation in geometric features. Sobol’s analysis is used to identify the most influencing geometric feature for the stall behavior to be concentrated at the maximum thickness location on the airfoil suction surface.
Wind turbine blade design with airfoil shape control using invertible neural networks
Authors: Jasa John , Glaws Andrew , Bortolotti Pietro , Vijayakumar Ganesh , Barter Garrett
Published: June 2022

Wind turbine blade design is a highly multidisciplinary process that involves aerodynamics, structures, controls, manufacturing, costs, and other considerations. More efficient blade designs can be found by controlling the airfoil cross-sectional shapes simultaneously with the bulk blade twist and chord distributions. Prior work has focused on incorporating panel-based aerodynamic solvers with a blade design framework to allow for airfoil shape control within the design loop in a tractable manner. Including higher fidelity aerodynamic solvers, such as computational fluid dynamics, makes the design problem computationally intractable. In this work, we couple an invertible neural network trained on high-fidelity airfoil aerodynamic data to a turbine design framework to enable the design of airfoil cross sections within a larger blade design problem. We detail the methodology of this coupled framework and showcase its efficacy by aerostructurally redesigning the IEA 15-MW reference wind turbine blade. The coupled approach reduces the cost of energy by 0.9% compared to a more conventional design approach. This work enables the inclusion of high-fidelity aerodynamic data earlier in the design process, reducing cycle time and increasing certainty in the performance of the optimal design.
Farm wide sensitivity assessments of resonant frequencies of integrated offshore wind turbine finite element models
Authors: Fallais D J M , Winkler K , Sastre Jurado C , Weijtjens W , Stuyts B , Devriendt C
Published: June 2022

To date, despite advancements in the design of offshore wind turbines, the as-designed and identified as-built natural frequencies of offshore wind turbines still show discrepancies. These discrepancies are partially rooted in modelling uncertainties, as well as uncertain input parameters, related to e.g. aero-, fluid- or soil-structure interaction. The first objective of this article is to present a wind farm wide comparison of the first and second, modelled and identified, fore-aft natural frequencies for turbines in parked conditions for a wind farm located in the Belgian north sea. Secondly, the effect of different model parameters on the computed natural frequencies will be assessed using wind farm wide sensitivity studies, with the aim to describe the potential of each considered parametrization in reducing the discrepancy between modelled and measured resonance frequencies. The in-depth considered parametrizations are aimed at assessing the effect of the linearization of the p-y curves, soil stiffness, local scour as well as the mass of the rotor nacelle assembly, whereas results for wall thickness, marine growth, added mass coefficient and sea water level variations will be presented without further discussion. In order to perform this study, turbine specific finite element models have been prepared and verified based on detailed design documents; subsequently updated best-estimate soil data has been used to model the foundation for two different design scenarios. Furthermore, modal parameters have been identified for each turbine, based on vibration data collected in parked condition and state of the art operational modal analysis tools. The results show that the discrepancies between the modelled and identified first fore-aft natural frequencies could potentially be bridged by adjusting combination of the investigated parameters, whereas the discrepancies observed on the second natural frequency cannot be bridged by making changes to the investigated parameters. As such, future work will entail a more detailed investigation on modelling uncertainties.
A blade element momentum model for dual-rotor wind turbines considering inter-rotor velocity interferences
Authors: Yin F F , Chen J J , Li X K , Ye Z L , Tang W , Shen X , Guo X J
Published: June 2022

A blade element momentum model for predicting the aerodynamic performance of dual-rotor wind turbines (DRWTs) as an aerodynamic design tool is introduced in this paper. The model considers the inter-rotor axial velocity reduction and the tangential velocity components in the front rotor’s wake to model the inter-rotor velocity interferences for the inflow velocity as the input of the BEM theory. A DRWT with two NREL 5MW rotors is studied using the present model and CFD simulations. Results from the two methods show good agreements with each other in the trends of power, thrust, and aerodynamic loads on the blades despite the error in near-tip regions. The present DRWT configurations have lower optimum tip speed ratios and a wider range of high-CP
speeds. The maximum efficiency of the present turbine is improved by only 5%, indicating that a dedicated blade design for DRWT aerodynamics is required to enhance power output and lower the aerodynamic loads.
Optimum Turbine Design for Hydrogen Production from Offshore Wind
Authors: Mehta Mihir , Zaaijer Michiel , Terzi Dominic von
Published: June 2022

To limit the consequences of climate change, generation from renewables coupled with large scale electrification is necessary. However, the deployment of renewables has its own challenges and not all sectors can be electrified. Hydrogen production from wind energy emerges as a promising solution that can alleviate these challenges. The current costs of green hydrogen production are high due to the high costs of electricity used for electrolysis. This study looks into the benefits of optimizing a turbine specifically for hydrogen production and the reduction in the Levelized Cost of Hydrogen (LCoH) compared to the use of conventional Levelized Cost of Energy (LCoE) optimized turbine. The case presented shows that turbines designed specifically for hydrogen production tend to have a higher specific power but these provide only a marginal advantage over using LCoE-optimized turbines for hydrogen production. Oversizing the electrolyzer compared to the turbine was shown to be a good design strategy. In the future, designing turbines specifically for hydrogen production could have certain benefits, depending on how the electrolyzer efficiencies, hydrogen production costs and the hydrogen market evolve.
Sensitivity analysis of a Ground-Gen Airborne Wind Energy System design
Authors: Trevisi Filippo , Riboldi Carlo E.D. , Croce Alessandro
Published: June 2022

The architecture of a new multidisciplinary design and optimization framework for rigid wing Airborne Wind Energy Systems, named T-GliDe, is introduced and a Ground-Gen AWES is analyzed to illustrate the features of the design approach. T-GliDe features an optimization module and an uncertainty quantification module, allowing for a number of algorithm-based design techniques. T-GliDe performs an AWES design optimizing market-based objective functions, while satisfying constraints related to fight stability. The fight dynamics is modelled with analytical aerodynamic theories, allowing for fast and consistent design evaluations, without the use of time simulation codes and thus of active control. In this work, a reduced optimization problem is run to find optimal working-set points of a Ground-Gen AWES with respect to power production. The reel-out factor and the pitch angle as function of wind speed are considered as design variables and output trends are shown. A variance based sensitivity analysis is then run to investigate how the rigid body eigenvalues are influenced by a set of independent variables. Among the chosen independent variables, a sub-set of variables which bear an impact on the dynamics is identified and they will be considered in future design and optimization activities as design variables.
Techno-economic analysis of power smoothing solutions for pumping airborne wind energy systems
Authors: Joshi R , von Terzi D , Kruijff M , Schmehl R
Published: June 2022

In pumping airborne wind energy (AWE) systems, the kite is operated in repetitive crosswind patterns, pulling the tether from a winch that drives a generator on the ground. During the reel-out phase of its operation, it produces power, whereas, during the reel-in phase, it consumes a small fraction of the produced power. This leads to an oscillating power profile that requires smoothing before it can be supplied to the electricity grid. This paper proposes three drivetrain concepts as a solution to this power smoothing challenge. The three concepts are based on three different types of storage technologies: electrical, hydraulic and mechanical. Techno–economic models of the drivetrains were developed and a case-study on sizing and costing of the three drivetrain concepts for a MW–scale AWE system was performed. Conclusions were drawn that provide guidance to AWE developers for choosing a suitable drivetrain concept for their systems.
3D printed rotor blades for a research wind turbine: Aerodynamic and structural design and testing
Authors: Alber J , Assfalg L , Nayeri C N , Paschereit C O , Lahr M , Semmler L , Twele J , Fortmann J , Fischer J , Latoufis K , Dorn I
Published: June 2022

This study combines the design, the 3D printing and the testing of a small 3-bladed wind turbine rotor for research and teaching purposes. The objective is the additive manufacturing of a rotor with a radius of one meter, as an alternative to subtractive methods, such as computerized milling. The blade design is developed using freely available software packages. The aerodynamic considerations include the airfoil selection, the calculation of the blade geometry and the simulation of the ultimate load cases. The structural considerations are focussed on the printable materials, the infill structures and the retrofit of a load-carrying spar. The rotor blades are 3D printed with the BigRep One at the maker space of the TH Wildau. The structural integrity of the prototype blade is tested in terms of the ultimate root bending moments and the centrifugal forces at the HTW Berlin. The aerodynamic run-up tests are performed at the large wind tunnel of the TU Berlin measuring the power curves. The successful prototype paves the way for follow-up projects, such as open field tests and the 3D printing of larger rotor blades.
Using Small Wind Turbine Technology to Design an AntiFrost Fan
Authors: Sessarego Matias , Wood David
Published: June 2022

Anti-frost fans (AFFs) are widely used in agriculture to reduce the frost damage to crops. The small wind turbine rotor design code (SWRDC) was adapted to design the blades of an anti-frost fan to maximize the mass flow rate through the rotor while minimizing the blade mass and aerodynamic noise. Using a random sample set of 60 baseline designs, the design is iterated using a genetic algorithm to obtain an optimized design with a mass flow rate of 3.11 kg/s, a blade mass of 6.96 kg, and with a noise level of 72.8 dB.
Challenges and Possible Solutions in Aeroelastic Modeling for the Distributed Wind Industry
Authors: Damiani R , Davis D , Summerville B
Published: June 2022

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine; it provides an understanding of the impact of design parameters on turbine loading and power response before witnessing it in the field. Despite these advantages, the use of AM in the distributed wind technology (DWT) sector is limited. This article represents a short summary of an in-depth assessment by the authors of the status of AM and its role within the distributed wind technology design standards. The research gathered input and feedback from a large number of U.S. and international stakeholders, reviewed technical strengths and weaknesses of the current edition of the design standards, analyzed the minutes from recent industry workshops and meetings, collected publicly available AM templates, and provided an evaluation of the existing AM codes. Several goals were achieved including providing strategies for the load assessment categorization of turbines based on rotor swept area and archetype, and guidance for AM verification and validation. Recommendations within this study will advance the value and the ease-of-use of AM, thereby allowing the industry to better capitalize this underutilized tool, resulting in a more efficient design process, an easier path to certification, and overall better and more reliable distributed wind technology products.
Engineering a Reduction of the Levelized Cost of Energy of Distributed Wind Turbines via Rotor and Control Enhancements
Authors: Damiani R , Davis D
Published: June 2022

Distributed wind turbines (DWTs), with rated capacity less than 100 kW, are penalized by high balance-of-system costs that lead to a high levelized cost of energy (LCOE). As a result, to contain the capital expenditure and thus LCOE, traditional designs have avoided active control systems that are standard in larger machines, e.g., active yaw and pitch control. In this paper, we present the key results of a trade-off study between larger rotor diameter, loads abatement, and simplicity in the pitch design for a typical mid-sized DWT with the overarching goal of increasing performance and decreasing LCOE. We focused on the upgrade potential for a generic downwind, passive-yaw, stall-controlled turbine model with high-speed shaft (HSS) brake and rated capacity of ∼ 60kW.

A rotor and control redesign proved successful in increasing power capture through the deployment of a blade-root extender and an innovative, low-cost, independent pitch system for overspeed protection. The improvements remove the need for a mechanical brake and yield a significant decrease in LCOE. The loads in all components were kept under the target threshold by a combination of optimum blade extender length and rotor rotational velocity. The failsafe and redundant aerodynamic braking system is economical and can lend itself to retrofit applications to other turbine models.
Vibration damping of a vertical axis wind turbine in operating conditions
Authors: Castellani F , Natili F , Astolfi D , Hirschl A , Peppoloni M
Published: June 2022

Distributed power generation technologies have been, over the years, gaining more and more attention from the industry as well as from the academia, due to the global interest in the exploitation of renewable energy sources even in urban areas. From this perspective, small size wind turbines, often with vertical axis layout and a nominal power between 1-3 kW, are being installed in urban areas on rooftops of residential, commercial, industrial buildings and even on metallic carpentry towers. As wind turbines tend to produce noise and vibrations, especially in presence of vortexes, wakes and unsteadiness, efficient devices for mitigating the vibrations transmitted to the supporting structure have to be added in order to limit the generation of stresses. Actually, the social acceptance of the installation of small wind turbines in built environment is tightly connected to the acoustic comfort for the inhabitants. The present study has been developed thanks to a joint collaboration between the Department of Engineering of the University of Perugia (Italy) and FH Technikum Wien (Austria) within the participation to the IEA Wind-Task 41: “Distributed Wind”. The work aims at mechanically characterizing the vibration damping provided by a mechanical device installed on the top of the turbine tower support. The decoupler, specifically designed for this purpose, has been tested in different conditions (in field and laboratory) and with different approaches, in order to have an overall evaluation of its performance. At first, vibrations are measured in open field in a real test case scenario with two installation arrangements: on the rooftop of a small building and on a tubular tower. Subsequently, the decoupler has been removed from its original location and tested in laboratory with external excitation from shaker.
Deep Reinforcement Learning for Perception and Control of Autonomous Vehicles
Authors: Zhao Dongbin
Published: June 2022

Deep reinforcement learning is an effective combination of the decision-making ability of reinforcement learning and the perceptual ability of deep learning, which has achieved a series of milestones in the field of artificial intelligence in recent years. This method has also obtained many beneficial attempts in the field of intelligent driving, which has strongly promoted the development and progress of key technologies of autonomous vehicles. This report briefly reviews the development of deep reinforcement learning methods and specifically introduces the research progress of my team in perception and decision making of autonomous vehicles based on deep reinforcement learning methods.
Surface Defect Segmentation and Detection of Printing Roller Based on Improved FT Algorithm
Authors: Shuang Huang , Shaozhong Cao , Weijun Zhu , Chenyang Bao
Published: June 2022

The method based on machine vision is one of the important ways of printing roller defect detection. It has the advantage of intuitively reflecting the surface state of printing roller, but the effect of detecting the position where the surface defect of printing roller is not obvious is not ideal. Aiming at the problems of different printing roller surface defects and large interference of background texture, a printing roller surface defect detection algorithm based on improved frequency tuning significance and threshold segmentation is proposed. Firstly, the nonlocal mean filter method is used to preprocess the image to solve the influence of noise on the image; Then, the saliency map is extracted by converting the lab color space of FT algorithm to HSV color space, normalizing and weighting each eigenvalue respectively; Finally, the salient image is binarized by iterative threshold segmentation to obtain the final defect image. The experimental results show that the accuracy of the algorithm is 97.1%, which is better than other similar algorithms. It can accurately detect the roller image with different size of surface defects and texture background interference, and the comprehensive performance is outstanding.
Design and Implement of University Teachers’ Workload Management System
Authors: Liu Qian , Zhang Hui , Fan Lin , Li Tong-han , Jin Xue
Published: June 2022

In order to achieve the information management of the workload of university teachers and effectively raise the work efficiency of the staff, in this paper, we used platforms like Microsoft Visual Studio 2015 and Microsoft SQL Sever 2012, developed a professional management system based on C/S architecture, which aims to efficiently and informationally manage the scientific research and teaching work information of the university teachers. The system is easily to operate and it enables the functional improvement. Facilitate the statistics and rewards of the teachers’ workload, and also helps teachers to fully understand their own work and pave the way for the next work. It is of great significance to stimulate teachers’ work enthusiasm and improve work efficiency.