Wind and Wave Energy Resource Assessment and Combined Utilization
The utilization of marine renewable energy, such as wind and wave energy resources, has become a global trend. Wind energy, wave energy, and especially wind-wave combinations are becoming more promising for the development and utilization of marine renewable energy in the future. This reprint contai...
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| 格式: | Online |
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| 語言: | 英语 |
| 出版: |
MDPI - Multidisciplinary Digital Publishing Institute
2025
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| 主題: | |
| 在線閱讀: | ONIX_20250220_9783725825813_342 |
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| _version_ | 1869526524200222720 |
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| collection | Directory of Open Access Books |
| description | The utilization of marine renewable energy, such as wind and wave energy resources, has become a global trend. Wind energy, wave energy, and especially wind-wave combinations are becoming more promising for the development and utilization of marine renewable energy in the future. This reprint contains empirical studies and systematic reviews regarding the utilization of marine renewable energies. It includes a multi-floater wave energy converter (WEC), size optimization of WEC, optimized control of an ocean WEC System, machine learning and deep learning for modelling an offshore hybrid wind-wave energy system, and other topics. |
| format | Online |
| id | doab-20.500.12854ir-152978 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1529782025-02-20T13:22:32Z Wind and Wave Energy Resource Assessment and Combined Utilization He, Guanghua Sun, Liang Bao, Yan wind speed extrapolation power-law machine learning supervised learning mesoscale model wind energy energy production assessment new european wind atlas random forest support vector machines linear regression multi-floater WEC platform potential flow theory numerical simulation wave energy floating wind-wave power generation platform WEC wave power conversion efficiency viscous heaving damping correction motion model ocean wave energy buoy efficiency optimize control wind–wave combined current energy vortex-induced vibration cylindrical oscillator mass ratio renewable energy artificial intelligence comparative analysis wind turbine energy deep learning big data wave power offshore offshore wind energy site selection multi-criteria decision-making resource assessment restrictions evaluation criteria climate change wind speed wind trend clustering Ward’s method k-means ocean wave height data fitting predication method ocean wave energy conversion wingsail apparent wind angle camber thrust coefficient thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PG Astronomy, space and time The utilization of marine renewable energy, such as wind and wave energy resources, has become a global trend. Wind energy, wave energy, and especially wind-wave combinations are becoming more promising for the development and utilization of marine renewable energy in the future. This reprint contains empirical studies and systematic reviews regarding the utilization of marine renewable energies. It includes a multi-floater wave energy converter (WEC), size optimization of WEC, optimized control of an ocean WEC System, machine learning and deep learning for modelling an offshore hybrid wind-wave energy system, and other topics. 2025-02-20T13:22:30Z 2025-02-20T13:22:30Z 2024 book ONIX_20250220_9783725825813_342 9783725825813 9783725825820 https://directory.doabooks.org/handle/20.500.12854/152978 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/10192 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-2582-0 10.3390/books978-3-7258-2582-0 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725825813 9783725825820 198 Basel open access |
| spellingShingle | wind speed extrapolation power-law machine learning supervised learning mesoscale model wind energy energy production assessment new european wind atlas random forest support vector machines linear regression multi-floater WEC platform potential flow theory numerical simulation wave energy floating wind-wave power generation platform WEC wave power conversion efficiency viscous heaving damping correction motion model ocean wave energy buoy efficiency optimize control wind–wave combined current energy vortex-induced vibration cylindrical oscillator mass ratio renewable energy artificial intelligence comparative analysis wind turbine energy deep learning big data wave power offshore offshore wind energy site selection multi-criteria decision-making resource assessment restrictions evaluation criteria climate change wind speed wind trend clustering Ward’s method k-means ocean wave height data fitting predication method ocean wave energy conversion wingsail apparent wind angle camber thrust coefficient thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PG Astronomy, space and time Wind and Wave Energy Resource Assessment and Combined Utilization |
| title | Wind and Wave Energy Resource Assessment and Combined Utilization |
| title_full | Wind and Wave Energy Resource Assessment and Combined Utilization |
| title_fullStr | Wind and Wave Energy Resource Assessment and Combined Utilization |
| title_full_unstemmed | Wind and Wave Energy Resource Assessment and Combined Utilization |
| title_short | Wind and Wave Energy Resource Assessment and Combined Utilization |
| title_sort | wind and wave energy resource assessment and combined utilization |
| topic | wind speed extrapolation power-law machine learning supervised learning mesoscale model wind energy energy production assessment new european wind atlas random forest support vector machines linear regression multi-floater WEC platform potential flow theory numerical simulation wave energy floating wind-wave power generation platform WEC wave power conversion efficiency viscous heaving damping correction motion model ocean wave energy buoy efficiency optimize control wind–wave combined current energy vortex-induced vibration cylindrical oscillator mass ratio renewable energy artificial intelligence comparative analysis wind turbine energy deep learning big data wave power offshore offshore wind energy site selection multi-criteria decision-making resource assessment restrictions evaluation criteria climate change wind speed wind trend clustering Ward’s method k-means ocean wave height data fitting predication method ocean wave energy conversion wingsail apparent wind angle camber thrust coefficient thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PG Astronomy, space and time |
| topic_facet | wind speed extrapolation power-law machine learning supervised learning mesoscale model wind energy energy production assessment new european wind atlas random forest support vector machines linear regression multi-floater WEC platform potential flow theory numerical simulation wave energy floating wind-wave power generation platform WEC wave power conversion efficiency viscous heaving damping correction motion model ocean wave energy buoy efficiency optimize control wind–wave combined current energy vortex-induced vibration cylindrical oscillator mass ratio renewable energy artificial intelligence comparative analysis wind turbine energy deep learning big data wave power offshore offshore wind energy site selection multi-criteria decision-making resource assessment restrictions evaluation criteria climate change wind speed wind trend clustering Ward’s method k-means ocean wave height data fitting predication method ocean wave energy conversion wingsail apparent wind angle camber thrust coefficient thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PG Astronomy, space and time |
| url | ONIX_20250220_9783725825813_342 |