Estimation of fatigue and extreme load distributions from limited data with application to wind energy systems.

Fitzwater, LeRoy M.

doi:10.2172/918211

Cited by 8 publications

(4 citation statements)

References 25 publications

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“…The number of counts in the lowest amplitude bin in Fig. A significant amount of work has been devoted to the issue of fitting distributions to fatigue data (Veers and Winterstein, 1998;Thomsen, 1998;Manuel et al, 2001;Fitzwater, 2002;Moriarty, et al, 2002). The smallest amplitude cycles do not produce any appreciable damage and could be just as well ignored.…”

Section: Short-term Load Distributionmentioning

confidence: 99%

Fatigue loading of wind turbines

Veers

2011

Wind Energy Systems

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Section: Short-term Load Distributionmentioning

confidence: 99%

Fatigue loading of wind turbines

Veers

2011

Wind Energy Systems

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“…As far as we know, calculating the extreme loads according to the IEC [1] or GL [2] standard is extremely time consuming. Over the last decade, most researchers extrapolated the extreme loads by means of statistical methods which suppose that the distribution of extreme loads at different wind speed meet some statistical models [3][4][5][6][7][8][9][10][11][12][13][14][15]. Generally, it is reasonable to estimate the extreme loads that occur or a long duration based on the measured or simulated data gathered over a short period.…”

Section: Introductionmentioning

confidence: 99%

Predicting the Extreme Loads in Power Production of Large Wind Turbines Using an Improved PSO Algorithm

2019

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Predicting the extreme loads in power production for the preliminary-design of large-scale wind turbine blade is both important and time consuming. In this paper, a simplified method, called Particle Swarm Optimization-Extreme Load Prediction Model (PSO-ELPM), is developed to quickly assess the extreme loads. This method considers the extreme loads solution as an optimal problem. The rotor speed, wind speed, pitch angle, yaw angle, and azimuth angle are selected as design variables. The constraint conditions are obtained by considering the influence of the aeroelastic property and control system of the wind turbine. An improved PSO algorithm is applied. A 1.5 MW and a 2.0 MW wind turbine are chosen to validate the method. The results show that the extreme root load errors between PSO-ELPM and FOCUS are less than 10%, while PSO-ELPM needs much less computational cost than FOCUS. The distribution of flapwise bending moments are close to the results of FOCUS. By analyzing the loads, we find that the extreme flapwise bending moment of the blade root in chord coordinate (CMF_ROOT) is largely reduced because of the control system, with the extreme edgewise bending moment of the blade root in chord coordinate (CME_ROOT) almost unchanged. Furthermore, higher rotor speed and smaller pitch angle will generate larger extreme bending moments at the blade root.

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“…More recent work on wind turbines has focused on the prediction of actual loading curves, e.g., in the study of Manuel and Veers , limited to a wind speed range between 15 and 19 m/s. Fitzwater has studied fatigue and extreme loading for both operational and parked conditions by fitting quadratic Weibull models. Dong et al , used both two‐parameter Weibull and generalized Gamma functions for modeling long‐term fatigue damage.…”

Section: Introductionmentioning

confidence: 99%

Simplified fatigue load assessment in offshore wind turbine structural analysis

Zwick

Muskulus

2015

Wind Energy

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The estimation of fatigue lifetime for an offshore wind turbine support structure requires a large number of time-domain simulations. It is an important question whether it is possible to reduce the number of load cases while retaining a high level of accuracy of the results. We present a novel method for simplified fatigue load assessments based on statistical regression models that estimate fatigue damage during power production. The main idea is to predict the total fatigue damage only and not also the individual damage values for each load case . We demonstrate the method for a jacket-type support structure. Reducing the number of simulated load cases from 21 to 3, the total fatigue damage estimate exhibited a maximum error of about 6% compared with the complete assessment. As a consequence, a significant amount of simulation time can be saved, in the order of a factor of seven. This quick fatigue assessment is especially interesting in the application of structural optimization, with a large number of iterations.

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Estimation of fatigue and extreme load distributions from limited data with application to wind energy systems.

Cited by 8 publications

References 25 publications

Fatigue loading of wind turbines

Fatigue loading of wind turbines

Predicting the Extreme Loads in Power Production of Large Wind Turbines Using an Improved PSO Algorithm

Simplified fatigue load assessment in offshore wind turbine structural analysis

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