Details
| Original language | English |
|---|---|
| Publication status | Published - 9 Jul 2023 |
| Event | 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14) - Trinity College Dublin, Dublin, Ireland Duration: 9 Jul 2023 → 13 Jul 2023 |
Conference
| Conference | 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14) |
|---|---|
| Abbreviated title | ICASP14 |
| Country/Territory | Ireland |
| City | Dublin |
| Period | 9 Jul 2023 → 13 Jul 2023 |
Abstract
the computing time are, for example, the reduction of load cases or the use of meta-models. In this work, three different methods for lifetime reassessment of offshore wind turbines are investigated and compared to identify differences of the three methods and to find out, whether the use of meta-models for lifetime reassessment is suitable. The three methods are a full lifetime reassessment approach using
a Monte Carlo simulation, an approach according to the standard IEC 61400-3 and a meta-model based approach. The results show that it is possible to use meta-models instead of the original aero-elastic simulation model for the lifetime reassessment. The computing time can be signficantly reduced while maintaining a high approximation quality in the prediction of lifetime fatigue loads.
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
2023. Paper presented at 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland.
Research output: Contribution to conference › Paper › Research › peer review
}
TY - CONF
T1 - Lifetime reassessment of offshore wind turbines using meta-models
AU - Schmidt, Franziska
AU - Hübler, Clemens
AU - Rolfes, Raimund
PY - 2023/7/9
Y1 - 2023/7/9
N2 - At the end of the lifetime of offshore wind turbines, there are various options. One option is to continue operating beyond the theoretical lifetime of the offshore wind turbine. To enable this, first, the remaining lifetime must be determined with a lifetime reassessment. However, the difficulty here is the very high comping time required to determine the remaining lifetime. Possible options for reducingthe computing time are, for example, the reduction of load cases or the use of meta-models. In this work, three different methods for lifetime reassessment of offshore wind turbines are investigated and compared to identify differences of the three methods and to find out, whether the use of meta-models for lifetime reassessment is suitable. The three methods are a full lifetime reassessment approach usinga Monte Carlo simulation, an approach according to the standard IEC 61400-3 and a meta-model based approach. The results show that it is possible to use meta-models instead of the original aero-elastic simulation model for the lifetime reassessment. The computing time can be signficantly reduced while maintaining a high approximation quality in the prediction of lifetime fatigue loads.
AB - At the end of the lifetime of offshore wind turbines, there are various options. One option is to continue operating beyond the theoretical lifetime of the offshore wind turbine. To enable this, first, the remaining lifetime must be determined with a lifetime reassessment. However, the difficulty here is the very high comping time required to determine the remaining lifetime. Possible options for reducingthe computing time are, for example, the reduction of load cases or the use of meta-models. In this work, three different methods for lifetime reassessment of offshore wind turbines are investigated and compared to identify differences of the three methods and to find out, whether the use of meta-models for lifetime reassessment is suitable. The three methods are a full lifetime reassessment approach usinga Monte Carlo simulation, an approach according to the standard IEC 61400-3 and a meta-model based approach. The results show that it is possible to use meta-models instead of the original aero-elastic simulation model for the lifetime reassessment. The computing time can be signficantly reduced while maintaining a high approximation quality in the prediction of lifetime fatigue loads.
M3 - Paper
T2 - 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14)
Y2 - 9 July 2023 through 13 July 2023
ER -