Analysis of the influence of climate change on the fatigue lifetime of offshore wind turbines using imprecise probabilities

Hübler, Clemens; Rolfes, Raimund

doi:10.1002/we.2572

Cited by 12 publications

(2 citation statements)

References 30 publications

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“…Even if the measurement period covers more than a year, yearly and/or long-term effects are not taken into account, e.g. varying damage due to climate change (Hübler and Rolfes, 2021).…”

Section: Simple Extrapolationmentioning

confidence: 99%

Probabilistic temporal extrapolation of fatigue damage of offshore wind turbine substructures based on strain measurements

Hübler

Rolfes

2022

Wind Energ. Sci.

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Abstract. Substructures of offshore wind turbines are becoming older and beginning to reach their design lifetimes. Hence, lifetime extensions for offshore wind turbines are becoming not only an interesting research topic but also a relevant option for industry. To make well-founded decisions on possible lifetime extensions, precise fatigue damage predictions are required. In contrast to the design phase, fatigue damage predictions can be based not only on aeroelastic simulations but also on strain measurements. Nonetheless, strain-measurement-based fatigue damage assessments for lifetime extensions have been rarely conducted so far. Simulation-based approaches are much more common, although current standards explicitly recommend the use of measurement-based approaches as well. For measurement-based approaches, the main challenge is that strain data are limited. This means that measurements are only available for a limited period and only at some specific hotspot locations. Hence, spatial and temporal extrapolations are required. Available procedures are not yet standardised and in most cases not validated. This work focusses on extrapolations in time. Several methods for the extrapolation of fatigue damage are assessed. The methods are intended to extrapolate fatigue damage calculated for a limited time period using strain measurement data to a longer time period or another time period, where no such data are available. This could be, for example, a future period, a period prior to the installation of strain gauges or a period after some sensors have failed. The methods are validated using several years of strain measurement data from the German offshore wind farm Alpha Ventus. The performance and user-friendliness of the various methods are compared. It is shown that fatigue damage can be predicted accurately and reliably for periods where no strain data are available. Best results are achieved if wind speed correlations are taken into account by applying a binning approach and if a least some winter months of strain data are available.

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“…Even if the measurement period covers more than a year, yearly and/or long-term effects are not taken into account, e.g. varying damage due to climate change (Hübler and Rolfes, 2021).…”

Section: Simple Extrapolationmentioning

confidence: 99%

Probabilistic temporal extrapolation of fatigue damage of offshore wind turbine substructures based on strain measurements

Hübler

Rolfes

2022

Wind Energ. Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Even if the measurement period covers more than a year, yearly and/or long-term effects are not taken into account, e.g. varying damage due to climate change (Hübler and Rolfes, 2021).…”

Section: Simple Extrapolationmentioning

confidence: 99%

Probabilistic Temporal Extrapolation of Fatigue Damage of Offshore Wind Turbine Substructures Based on Strain Measurements

Hübler

Rolfes

2022

Preprint

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Abstract. Substructures of offshore wind turbines are becoming older and beginning to reach their design lifetimes. Hence, lifetime extensions for offshore wind turbines are becoming not only an interesting research topic, but also a relevant option for industry. To make well-founded decisions on possible lifetime extensions, precise fatigue damage predictions are required. In contrast to the design phase, fatigue damage predictions cannot only be based on aero-elastic simulations but also on strain measurements. Nonetheless, strain measurement-based fatigue damage assessments for lifetime extensions have been rarely conducted so far. Simulation-based approaches are much more common, although current standards explicitly recommend the use of measurement-based approaches as well. For measurement-based approaches, the main challenge is that strain data are limited. This means that measurements are only available for a limited period and only at some specific hot-spot locations. Hence, spatial and temporal extrapolations are required. Available procedures are not yet standardised and in most cases not validated. This work focuses on extrapolations in time. Several methods for the extrapolation of fatigue damage are assessed. The methods are intended to extrapolate fatigue damage calculated for a limited time period using strain measurement data to a longer time period, or another time period, where no such data are available. This could be, for example, a future period, a period prior to the installation of strain gauges or a period after some sensors have failed. The methods are validated using several years of strain measurement data from the German offshore wind farm Alpha Ventus. The performance and user friendliness of the various methods are compared. It is shown that fatigue damage can be predicted accurately and reliably for periods where no strain data are available. Best results are achieved if wind speed correlations are taken into account by applying a binning approach, and if a least some winter months of strain data are available.

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Climate change effects on offshore wind turbines

James¹,

Haldar²,

Varghese³

et al. 2023

Wind Energy Engineering

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Analysis of the influence of climate change on the fatigue lifetime of offshore wind turbines using imprecise probabilities

Cited by 12 publications

References 30 publications

Probabilistic temporal extrapolation of fatigue damage of offshore wind turbine substructures based on strain measurements

Probabilistic temporal extrapolation of fatigue damage of offshore wind turbine substructures based on strain measurements

Probabilistic Temporal Extrapolation of Fatigue Damage of Offshore Wind Turbine Substructures Based on Strain Measurements

Climate change effects on offshore wind turbines

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