Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea
Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential i...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Amrutha, M. M. [verfasserIn] Kumar, V. Sanil [verfasserIn] Bhaskaran, Harsha [verfasserIn] Naseef, Muhammed [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Ocean dynamics - Berlin : Springer, 1948, 69(2019), 5 vom: 04. Apr., Seite 543-560 |
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| Übergeordnetes Werk: |
volume:69 ; year:2019 ; number:5 ; day:04 ; month:04 ; pages:543-560 |
| Links: |
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| DOI / URN: |
10.1007/s10236-019-01267-1 |
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| Katalog-ID: |
SPR009212787 |
|---|
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| 245 | 1 | 0 | |a Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea |
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| 520 | |a Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. The capacity factor of WaveStar is high (27–34%) for the study area compared with other technologies considered in the study. | ||
| 650 | 4 | |a Renewable energy |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Ocean energy |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Wave power potential |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a North Indian Ocean |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Resource assessment |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Wave energy converters |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Kumar, V. Sanil |e verfasserin |4 aut | |
| 700 | 1 | |a Bhaskaran, Harsha |e verfasserin |4 aut | |
| 700 | 1 | |a Naseef, Muhammed |e verfasserin |4 aut | |
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10.1007/s10236-019-01267-1 doi (DE-627)SPR009212787 (SPR)s10236-019-01267-1-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Amrutha, M. M. verfasserin aut Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. The capacity factor of WaveStar is high (27–34%) for the study area compared with other technologies considered in the study. Renewable energy (dpeaa)DE-He213 Ocean energy (dpeaa)DE-He213 Wave power potential (dpeaa)DE-He213 North Indian Ocean (dpeaa)DE-He213 Resource assessment (dpeaa)DE-He213 Wave energy converters (dpeaa)DE-He213 Kumar, V. Sanil verfasserin aut Bhaskaran, Harsha verfasserin aut Naseef, Muhammed verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 69(2019), 5 vom: 04. Apr., Seite 543-560 (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:69 year:2019 number:5 day:04 month:04 pages:543-560 https://dx.doi.org/10.1007/s10236-019-01267-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 69 2019 5 04 04 543-560 |
| spelling |
10.1007/s10236-019-01267-1 doi (DE-627)SPR009212787 (SPR)s10236-019-01267-1-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Amrutha, M. M. verfasserin aut Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. The capacity factor of WaveStar is high (27–34%) for the study area compared with other technologies considered in the study. Renewable energy (dpeaa)DE-He213 Ocean energy (dpeaa)DE-He213 Wave power potential (dpeaa)DE-He213 North Indian Ocean (dpeaa)DE-He213 Resource assessment (dpeaa)DE-He213 Wave energy converters (dpeaa)DE-He213 Kumar, V. Sanil verfasserin aut Bhaskaran, Harsha verfasserin aut Naseef, Muhammed verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 69(2019), 5 vom: 04. Apr., Seite 543-560 (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:69 year:2019 number:5 day:04 month:04 pages:543-560 https://dx.doi.org/10.1007/s10236-019-01267-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 69 2019 5 04 04 543-560 |
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10.1007/s10236-019-01267-1 doi (DE-627)SPR009212787 (SPR)s10236-019-01267-1-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Amrutha, M. M. verfasserin aut Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. The capacity factor of WaveStar is high (27–34%) for the study area compared with other technologies considered in the study. Renewable energy (dpeaa)DE-He213 Ocean energy (dpeaa)DE-He213 Wave power potential (dpeaa)DE-He213 North Indian Ocean (dpeaa)DE-He213 Resource assessment (dpeaa)DE-He213 Wave energy converters (dpeaa)DE-He213 Kumar, V. Sanil verfasserin aut Bhaskaran, Harsha verfasserin aut Naseef, Muhammed verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 69(2019), 5 vom: 04. Apr., Seite 543-560 (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:69 year:2019 number:5 day:04 month:04 pages:543-560 https://dx.doi.org/10.1007/s10236-019-01267-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 69 2019 5 04 04 543-560 |
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10.1007/s10236-019-01267-1 doi (DE-627)SPR009212787 (SPR)s10236-019-01267-1-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Amrutha, M. M. verfasserin aut Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. The capacity factor of WaveStar is high (27–34%) for the study area compared with other technologies considered in the study. Renewable energy (dpeaa)DE-He213 Ocean energy (dpeaa)DE-He213 Wave power potential (dpeaa)DE-He213 North Indian Ocean (dpeaa)DE-He213 Resource assessment (dpeaa)DE-He213 Wave energy converters (dpeaa)DE-He213 Kumar, V. Sanil verfasserin aut Bhaskaran, Harsha verfasserin aut Naseef, Muhammed verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 69(2019), 5 vom: 04. Apr., Seite 543-560 (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:69 year:2019 number:5 day:04 month:04 pages:543-560 https://dx.doi.org/10.1007/s10236-019-01267-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 69 2019 5 04 04 543-560 |
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10.1007/s10236-019-01267-1 doi (DE-627)SPR009212787 (SPR)s10236-019-01267-1-e DE-627 ger DE-627 rakwb eng 550 ASE 38.90 bkl Amrutha, M. M. verfasserin aut Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. The capacity factor of WaveStar is high (27–34%) for the study area compared with other technologies considered in the study. Renewable energy (dpeaa)DE-He213 Ocean energy (dpeaa)DE-He213 Wave power potential (dpeaa)DE-He213 North Indian Ocean (dpeaa)DE-He213 Resource assessment (dpeaa)DE-He213 Wave energy converters (dpeaa)DE-He213 Kumar, V. Sanil verfasserin aut Bhaskaran, Harsha verfasserin aut Naseef, Muhammed verfasserin aut Enthalten in Ocean dynamics Berlin : Springer, 1948 69(2019), 5 vom: 04. Apr., Seite 543-560 (DE-627)337809313 (DE-600)2063267-8 1616-7228 nnns volume:69 year:2019 number:5 day:04 month:04 pages:543-560 https://dx.doi.org/10.1007/s10236-019-01267-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 ASE AR 69 2019 5 04 04 543-560 |
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Enthalten in Ocean dynamics 69(2019), 5 vom: 04. Apr., Seite 543-560 volume:69 year:2019 number:5 day:04 month:04 pages:543-560 |
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Enthalten in Ocean dynamics 69(2019), 5 vom: 04. Apr., Seite 543-560 volume:69 year:2019 number:5 day:04 month:04 pages:543-560 |
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Renewable energy Ocean energy Wave power potential North Indian Ocean Resource assessment Wave energy converters |
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Ocean dynamics |
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Amrutha, M. M. @@aut@@ Kumar, V. Sanil @@aut@@ Bhaskaran, Harsha @@aut@@ Naseef, Muhammed @@aut@@ |
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Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. 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Amrutha, M. M. |
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Amrutha, M. M. ddc 550 bkl 38.90 misc Renewable energy misc Ocean energy misc Wave power potential misc North Indian Ocean misc Resource assessment misc Wave energy converters Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea |
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550 ASE 38.90 bkl Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea Renewable energy (dpeaa)DE-He213 Ocean energy (dpeaa)DE-He213 Wave power potential (dpeaa)DE-He213 North Indian Ocean (dpeaa)DE-He213 Resource assessment (dpeaa)DE-He213 Wave energy converters (dpeaa)DE-He213 |
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consistency of wave power at a location in the coastal waters of central eastern arabian sea |
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Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea |
| abstract |
Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. The capacity factor of WaveStar is high (27–34%) for the study area compared with other technologies considered in the study. |
| abstractGer |
Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. The capacity factor of WaveStar is high (27–34%) for the study area compared with other technologies considered in the study. |
| abstract_unstemmed |
Abstract Wave energy assessment at a regional scale is required for planning installation of wave energy converters. Based on continuously measured wave data at 14-m water depth in the central eastern Arabian Sea from January 2011 to December 2017, the temporal distribution of wave power potential is studied in detail along with statistical analysis of the wave power and wave parameters. Long-term variability in wave power is examined based on reanalysis data from 1979 to 2017. The study also evaluates the wave power technologies, such as Oyster, WaveDragon, and WaveStar for the study location. Significant inter-annual variations in the wave power are observed from June to September due to the fluctuations in the Indian summer monsoon. The annual mean wave power is 7.85 kW/m with year-to-year variability up to 13% from 2011 to 2017. During 24.7% of the time (~ 90 days) in a year, the wave power is more than 10 kW/m and is less than 5 kW/m during 68% of the time in a year. Most (90.4%) of the available wave power is from a narrow band between west and southwest. A spatial variability of ~ 12% in the annual mean wave power is observed along the central eastern Arabian Sea based on the measured wave data at three locations in 14–15-m water depth. The study shows that WaveDragon and WaveStar energy converter produces the electric power during 81 and 85% of the time in a year, whereas Oyster gives output during 59% of the time. The capacity factor of WaveStar is high (27–34%) for the study area compared with other technologies considered in the study. |
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| container_issue |
5 |
| title_short |
Consistency of wave power at a location in the coastal waters of central eastern Arabian Sea |
| url |
https://dx.doi.org/10.1007/s10236-019-01267-1 |
| remote_bool |
true |
| author2 |
Kumar, V. Sanil Bhaskaran, Harsha Naseef, Muhammed |
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Kumar, V. Sanil Bhaskaran, Harsha Naseef, Muhammed |
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| doi_str |
10.1007/s10236-019-01267-1 |
| up_date |
2024-07-04T01:08:11.027Z |
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| score |
7.3998156 |