A comprehensive fatigue load set reduction study for offshore wind turbines with jacket substructures

Häfele, Jan; Hübler, Clemens; Gebhardt, Cristian Guillermo; Rolfes, Raimund

doi:10.1016/j.renene.2017.10.097

Cited by 33 publications

(28 citation statements)

References 12 publications

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“…The evaluation of fatigue limit state code checks requires many simulations considering DLC 1.2 and 6.4 production load 50 m water depth, FINO3 environmental conditions), the required number of design load cases with respect to uncertainty was analyzed in previous papers (Häfele et al, 2018b(Häfele et al, , 2017. A number of 128 turned out to be a good compromise between accuracy and numerical effort.…”

Section: Fatigue Limit Statementioning

confidence: 99%

“…Compared to the environmental conditions documented in the UpWind design basis , the FINO3 measurements are much more comprehensive and allow for a better estimation of probability density functions as inputs for the determination of probabilistic loads . The probabilistic load set, which is based on probability density functions of environmental state parameters and 25 reduced in size compared to full load sets used by industrial wind turbine designers, was described in recent studies (Häfele et al, 2018b(Häfele et al, , 2017. However, there are two drawbacks that have to be mentioned when using this data.…”

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confidence: 99%

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A comparison study on jacket substructures for offshore wind turbines based on optimization

Häfele¹,

Gebhardt²,

Rolfes³

2018

Preprint

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Abstract. The structural optimization problem of jacket substructures for offshore wind turbines is commonly considered as a pure tube dimensioning problem with given topology, minimizing the entire mass of the structure. However, this approach goes along with the assumption that the given topology is fixed in any case. The present work contributes to the improvement of the state of the art by utilizing more detailed models for geometry, costs, and structural design code checks. They are assembled in an optimization scheme, in order to consider the jacket optimization problem from a different point of view 5 that is closer to practical applications. The objective function is replaced by a sum term comprising several cost terms. To address the issue of high demand of numerical capacity, a machine learning approach based on Gaussian process regression is applied to reduce numerical cost and enhance the number of considered design load cases. The proposed approach is meant to provide decision guidance in the first phase of wind farm planning. A numerical example for a NREL 5 MW turbine under FINO3 environmental conditions is computed by two effective optimization methods (sequential quadratic programming and 10 an interior-point method), allowing for the estimation of characteristic design variables of a jacket substructure. In order to resolve the mixed-integer problem formulation, multiple subproblems with fixed integer design variables are solved. The approach shows reasonable and promising results, useful both for further research and technical applications.

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Section: Fatigue Limit Statementioning

confidence: 99%

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confidence: 99%

A comparison study on jacket substructures for offshore wind turbines based on optimization

Häfele¹,

Gebhardt²,

Rolfes³

2018

Preprint

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“…For this purpose, representative positions serving the load and response esti mation for a range of positions may be identified based on intelligent clustering strategies that divide the positions into groups with similar water depths, soil properties, frequencies, damping, etc. several attempts have been made to reduce the number of DLCs, see [3] or [4], for example; however, in general, these methods are based on tuning results from a full analysis and thus still require that all DLCs are simulated at least once.…”

Section: Introductionmentioning

confidence: 99%

State‐of‐the‐art framework for design of offshore wind jacket foundations

et al. 2019

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Nominated for the Bernt Johansson Outstanding Paper Awards at Nordic Steel 2019 A state‐of‐the‐art framework for the design of jacket foundations for offshore wind turbines is presented here. The article illustrates how an efficient, yet highly accurate, structural model can be achieved through a combination of a comprehensive beam finite element model and detailed shell/solid finite element models, where the former suffices for representing the overall global behaviour and the latter improves the representation of non‐trivial structural details such as the transition piece and tubular joints. This approach allows the verification of standard structural elements according to various design codes to be automated on beam element level, while the fatigue performance via the hot‐spot method as well as detailed stress and buckling analyses of relevant joints and details can be performed based on the detailed shell/solid finite element models readily available for stiffness representation. The computational framework ensures full consistency between the local and global description levels and an efficient cloud interface facilitates the thousands of design load cases that typically require consideration in order that a full detailed design can be simulated within a reasonable timeframe.

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“…This is why several research projects characterized environmental conditions at specific sites or entire areas and published statistical distributions as a reference. Examples for data bases of main conditions (wind speeds, wave height, wave period, and wind and wave directions) are the UPWIND design basis, the work of Stewart et al, the PSA‐OWT project, Häfele et al, or Hübler et al In this work, the data basis of Hübler et al is utilized, as it is—beside other advantages—the only one where additional environmental conditions, like the turbulence intensity or the wind shear, are considered in a statistical manner (see Table 2 for considered environmental conditions).…”

Section: Introductionmentioning

confidence: 99%

“…For the remainder of this work, the expression “uncertainty” always refers to the uncertainty due to finite sampling. The effect of finite sampling is even intensified, if scattering of other environmental conditions within each bin is included, as it is done by Häfele et al The authors show that even for 2048 overall simulations, distributed to the bins according to the statistical occurrence distribution of the wind speed, the error in the damage at an X‐joint of the OC4 jacket due to finite samples is more than 10% with a probability of 5% (95th percentile). This high error results from the inclusion of stochastic effects (random seeds) and probabilistic effects (scattering environmental conditions).…”

Section: Introductionmentioning

confidence: 99%

Methodologies for fatigue assessment of offshore wind turbines considering scattering environmental conditions and the uncertainty due to finite sampling

2018

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For substructures of offshore wind turbines, the fatigue limit state is in most cases a decisive design factor. However, to calculate the fatigue lifetime of wind turbines, numerous time domain simulations for different load cases with changing environmental conditions are necessary. According to the state of the art, wind speed bins (of 2 m s −1 ) are employed, while keeping all other environmental states constant. However, assuming constant parameters in each wind speed bin is an unfounded simplification. Therefore, in this study, methodologies for fatigue assessment considering scattering environmental conditions are investigated by assuming statistical distributions for environmental conditions for all wind speeds that are derived using real data measured at the North Sea research platform FINO3. These statistical distributions are used to conduct time domain simulations of an OC3 monopile-with a 5-MW wind turbine-using the aero-servo-hydro-elastic simulation framework FAST. The fatigue lifetime is calculated, and its uncertainty due to finite sampling is assessed. It is shown that if scattering environmental states in each wind speed bin are applied, the uncertainty due to finite sampling is significant. Furthermore, only some wind speed bins contribute to the overall fatigue damage. Based on these findings, in a last step, different Monte Carlo sampling concepts are investigated to reduce the number of simulations needed to calculate the fatigue lifetime with a defined uncertainty. By combining several wind speed bins and by sampling according to the damage distribution, it is proved that the number of simulations can be reduced by more than 30% without increasing the uncertainty. KEYWORDSfatigue limit state, offshore wind energy, scattering environmental conditions, simulation error, uncertainty INTRODUCTIONThe share of offshore wind energy in overall energy production has grown over the last years. However, the cost of offshore wind energy is still high compared with other renewable energies. 1 As it is forecast that substructure improvements can potentially reduce the overall turbine cost by more than 5%, 2 an accurate and reliable simulation of offshore wind turbine substructures is beneficial. For substructures made of steel, mainly the fatigue limit state is decisive. 3 To calculate the fatigue lifetime of wind turbines, numerous time domain simulations are necessary. Current standards 4 define that these simulations should mirror the changing environmental conditions at the precise site of a wind turbine. However, for research purposes, these data are scarcely available, and even in industrial projects, the data quality is frequently poor because information on some parameters or long-term data is missing. This is why several research projects characterized environmental conditions at specific sites or entire areas and published statistical distributions as a reference. Examples for data bases of main conditions (wind speeds, wave height, wave period, and wind and wave directions) are the UPWIND desi...

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A comprehensive fatigue load set reduction study for offshore wind turbines with jacket substructures

Cited by 33 publications

References 12 publications

A comparison study on jacket substructures for offshore wind turbines based on optimization

A comparison study on jacket substructures for offshore wind turbines based on optimization

State‐of‐the‐art framework for design of offshore wind jacket foundations

Methodologies for fatigue assessment of offshore wind turbines considering scattering environmental conditions and the uncertainty due to finite sampling

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