Deconvolution approach for floating wind turbines
Abstract Green renewable energy is produced by floating offshore wind turbines (FOWT), a crucial component of the modern offshore wind energy industry. It is a safety concern to accurately evaluate excessive weights while the FOWT operates in adverse weather conditions. Under certain water condition...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-08-01
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| Series: | Energy Science & Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ese3.1485 |
| _version_ | 1797384215335010304 |
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| author | Zirui Liu Oleg Gaidai Jiayao Sun Yihan Xing |
| author_facet | Zirui Liu Oleg Gaidai Jiayao Sun Yihan Xing |
| author_sort | Zirui Liu |
| collection | DOAJ |
| description | Abstract Green renewable energy is produced by floating offshore wind turbines (FOWT), a crucial component of the modern offshore wind energy industry. It is a safety concern to accurately evaluate excessive weights while the FOWT operates in adverse weather conditions. Under certain water conditions, dangerous structural bending moments may result in operational concerns. Using commercial FAST software, the study's hydrodynamic ambient wave loads were calculated and converted into FOWT structural loads. This article suggests a Monte Carlo‐based engineering technique that, depending on simulations or observations, is computationally effective for predicting extreme statistics of either the load or the response process. The innovative deconvolution technique has been thoroughly explained. The suggested approach effectively uses the entire set of data to produce a clear but accurate estimate for severe response values and fatigue life. In this study, estimated extreme values obtained using a novel deconvolution approach were compared to identical values produced using the modified Weibull technique. It is expected that the enhanced new de‐convolution methodology may offer a dependable and correct forecast of severe structural loads based on the overall performance of the advised de‐convolution approach due to environmental wave loading. |
| first_indexed | 2024-03-08T21:32:12Z |
| format | Article |
| id | doaj.art-68d7638d19a54651bda8f2cf8c4b6102 |
| institution | Directory Open Access Journal |
| issn | 2050-0505 |
| language | English |
| last_indexed | 2024-03-08T21:32:12Z |
| publishDate | 2023-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Energy Science & Engineering |
| spelling | doaj.art-68d7638d19a54651bda8f2cf8c4b61022023-12-21T06:55:47ZengWileyEnergy Science & Engineering2050-05052023-08-011182742275010.1002/ese3.1485Deconvolution approach for floating wind turbinesZirui Liu0Oleg Gaidai1Jiayao Sun2Yihan Xing3College of Engineering Science and Technology Shanghai Ocean University Shanghai ChinaCollege of Engineering Science and Technology Shanghai Ocean University Shanghai ChinaSchool of Naval Architecture and Ocean Engineering Jiangsu University of Science and Technology Zhenjiang ChinaDepartment of Mechanical and Structural Engineering and Materials Science University of Stavanger Stavanger NorwayAbstract Green renewable energy is produced by floating offshore wind turbines (FOWT), a crucial component of the modern offshore wind energy industry. It is a safety concern to accurately evaluate excessive weights while the FOWT operates in adverse weather conditions. Under certain water conditions, dangerous structural bending moments may result in operational concerns. Using commercial FAST software, the study's hydrodynamic ambient wave loads were calculated and converted into FOWT structural loads. This article suggests a Monte Carlo‐based engineering technique that, depending on simulations or observations, is computationally effective for predicting extreme statistics of either the load or the response process. The innovative deconvolution technique has been thoroughly explained. The suggested approach effectively uses the entire set of data to produce a clear but accurate estimate for severe response values and fatigue life. In this study, estimated extreme values obtained using a novel deconvolution approach were compared to identical values produced using the modified Weibull technique. It is expected that the enhanced new de‐convolution methodology may offer a dependable and correct forecast of severe structural loads based on the overall performance of the advised de‐convolution approach due to environmental wave loading.https://doi.org/10.1002/ese3.1485environmental loadsfloating offshore wind turbinegreen energyrenewable energywind energy |
| spellingShingle | Zirui Liu Oleg Gaidai Jiayao Sun Yihan Xing Deconvolution approach for floating wind turbines Energy Science & Engineering environmental loads floating offshore wind turbine green energy renewable energy wind energy |
| title | Deconvolution approach for floating wind turbines |
| title_full | Deconvolution approach for floating wind turbines |
| title_fullStr | Deconvolution approach for floating wind turbines |
| title_full_unstemmed | Deconvolution approach for floating wind turbines |
| title_short | Deconvolution approach for floating wind turbines |
| title_sort | deconvolution approach for floating wind turbines |
| topic | environmental loads floating offshore wind turbine green energy renewable energy wind energy |
| url | https://doi.org/10.1002/ese3.1485 |
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