Fatigue loading of wind turbines

Veers, P. S.

doi:10.1533/9780857090638.1.130

Cited by 9 publications

(6 citation statements)

References 18 publications

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“…To simplify this stage of the analysis, loads were obtained for the averaged flow conditions within each flow speed bin and this is combined with the flow speed occurrence to obtain long-term loading. This follows the approach of Veers [55] and provides a consistent approach to compare between alternative predictions and measurements. When the model through-life loading predictions are compared to the measurements, they underestimate the loads by 30-32% for the Telemac RANS and by 8-16% for the Telemac LES.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Model Predictions of the Unsteady Tidal Stream Resource and Turbine Fatigue Loads Relative to Multi-Point Flow Measurements at Raz Blanchard

Mullings,

Draycott,

Thiébot

et al. 2023

Energies

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The next stage of development of the tidal stream industry will see a focus on the deployment of tidal turbines in arrays of increasing device numbers and rated power. Successful array development requires a thorough understanding of the resource within potential deployment sites. This is predictable in terms of flow speeds, based upon tidal constituents. However, the operating environment for the turbine is more complex than the turbine experiencing a uniform flow, with turbulence, shear and wave conditions all affecting the loading on the turbine components. This study establishes the accuracy with which several alternative modelling tools predict the resource characteristics which define unsteady loading—velocity shear, turbulence and waves—and assesses the impact of the model choice on predicted damage equivalent loads. In addition, the predictions of turbulence are compared to a higher fidelity model and the occurrence of flow speeds to a Delft3D model for currents and waves. These models have been run for a specific tidal site, the Raz Blanchard, one of the major tidal stream sites in European waters. The measured resource and predicted loading are established using data collected in a recent deployment of acoustic Doppler current profilers (ADCPs) as part of the Interreg TIGER project. The conditions are measured at three locations across the site, with transverse spacing of 145.7 m and 59.3 m between each device. Turbine fatigue loading is assessed using measurements and model predictions based on an unsteady blade element momentum model applied to near-surface and near-bed deployment positions. As well as across-site spatial variation of loading, the through life loading over a 5-year period results in an 8% difference to measured loads for a near-surface turbine, using conditions purely defined from a resource model and to within 3% when using a combination of modelled shear with measured turbulence characteristics.

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Section: Discussionmentioning

confidence: 99%

Evaluation of Model Predictions of the Unsteady Tidal Stream Resource and Turbine Fatigue Loads Relative to Multi-Point Flow Measurements at Raz Blanchard

Mullings,

Draycott,

Thiébot

et al. 2023

Energies

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“…Joint random generation of multiple correlated stationary processes from their spectral representation dates back to the work of Shinozuka 13 and has become a standard method used in a variety of applications where multiple stochastic inputs are correlated in space, such as seismic vibrations or wind 14 . Veers 15 adapted it to wind energy, initiating the current approach of precomputing turbulent boxes propagated through the rotor at simulation time under Taylor's frozen‐turbulence assumption. The method relies on Cholesky factorisation and random phases to come up with a turbulent box realisation that satisfies spectral properties fitted from field measurements.…”

Section: The Veers Methodsmentioning

confidence: 99%

Synthetic turbulence modelling for offshore wind farm engineering models using coherence aggregation

Chabaud

2023

Wind Energy

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Turbulent wind fields are known to be a major driver for structural loads and power fluctuations on offshore wind turbines. At the single‐turbine scale, there exist well‐established design standards based on wind spectra and coherence functions calibrated from years of measurements, which are used to generate multiple 10‐min wind field realisations known as synthetic turbulence boxes, themselves used as input to turbine‐scale aero‐hydro‐servo elastic codes. These methods are however not directly applicable at farm scale. When analysing the dynamics of large offshore wind farms, measurements reveal the importance of large, low‐frequency turbulent vortices for power fluctuations and hence for wind farm control and grid integration. Also, farm‐scale wind fields are needed as input to farm‐scale aero‐servo‐elastic codes for the modelling of wake dynamics, affecting structural loads. These new concerns motivate an upgrade in the original turbine‐scale wind field representation: (1) spectral models need to be based on farm‐scale measurements, (2) the frozen‐turbulence assumption merging temporal and along‐wind coherence must be lifted, (3) simplifications are needed to reduce the number of degrees of freedom as the domain becomes excessively large. This paper suggests models and algorithms for aggregated farm‐wide corrrelated synthetic turbulence generation—lumping the wind field into space‐averaged quantities—adapted to the aero‐hydro‐servo elastic modelling of large offshore wind farms. Starting from the work of Sørensen et al. in the early 2000s for grid integration purposes, methods for structural load modelling (through wake meandering and high‐resolution wind field reconstruction) are introduced. Implementation and efficiency matters involving mathematical subtleties are then presented. Finally, numerical experiments are carried out to (1) verify the approach and implementation against a state‐of‐the‐art point‐based—as opposite to aggregated—synthetic turbulence generation code and (2) illustrate the benefit of turbulence aggregation for the modelling of large offshore wind farms.

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“…Two stall models are available in hGAST, the ONERA [7] and the Beddoes-Leishman [6] model. A separate module that provides turbulent inflow boxes is also available, formulated on the basis of Veers' model [21]. For the calculation of the turbulent inflow wind time series either the von Karman or the Kaimal spectra, specified in the IEC 61400-1 standard, can be used.…”

Section: Multibody Servo-aero-elastic Analysis Tool Hgastmentioning

confidence: 99%

Wind Turbine Blade Design Optimization for Reduced LCoE, Focusing on Design-Driving Loads Due to Storm Conditions

Serafeim

Manolas²,

Riziotis³

et al. 2022

Fluids

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Design modifications of the blade inner structure, targeted at reducing design-driving extreme loads due to storm conditions, are assessed in the present paper. Under survival wind speeds, the lack of sufficient aerodynamic damping in the edgewise direction is responsible for excessive stall-induced vibrations that usually drive wind turbine blade design loads. The modifications considered in the work are (i) a non-symmetric increase in the thickness of the uniaxial and tri-axial material on the suction and pressure side of the blade sections, (ii) a shift in the spar caps in opposite directions and (iii) the ply-angle re-orientation of the laminates on the spar caps. The first two design interventions aim at increasing the damping of the low-damped edgewise modes in the idling rotor, while the third aims at reducing the fatigue and ultimate loads in normal operation. The design parameters in the problem are determined on the basis of a multidisciplinary optimization (MDAO) process, which minimizes the levelized cost of energy (LCoE). The in-house integrated optimization tool employed in the present study combines: (i) a servo-aero-elastic analysis tool for calculating ultimate loads and power yield, (ii) a cross-sectional analysis tool for obtaining structural properties and stress distributions in the modified blades and (iii) a cost model of the overall wind turbine to evaluate the LCoE.

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Fatigue loading of wind turbines

Cited by 9 publications

References 18 publications

Evaluation of Model Predictions of the Unsteady Tidal Stream Resource and Turbine Fatigue Loads Relative to Multi-Point Flow Measurements at Raz Blanchard

Evaluation of Model Predictions of the Unsteady Tidal Stream Resource and Turbine Fatigue Loads Relative to Multi-Point Flow Measurements at Raz Blanchard

Synthetic turbulence modelling for offshore wind farm engineering models using coherence aggregation

Wind Turbine Blade Design Optimization for Reduced LCoE, Focusing on Design-Driving Loads Due to Storm Conditions

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