Wave energy resources along the Hawaiian Island chain
Hawaii's access to the ocean and remoteness from fuel supplies has sparked an interest in ocean waves as a potential resource to meet the increasing demand for sustainable energy. The wave resources include swells from distant storms and year-round seas generated by trade winds passing through...
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| Published in | Renewable energy Vol. 55; pp. 305 - 321 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Elsevier Ltd
01.07.2013
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0960-1481 1879-0682 |
| DOI | 10.1016/j.renene.2012.12.030 |
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| Abstract | Hawaii's access to the ocean and remoteness from fuel supplies has sparked an interest in ocean waves as a potential resource to meet the increasing demand for sustainable energy. The wave resources include swells from distant storms and year-round seas generated by trade winds passing through the islands. This study produces 10 years of hindcast data from a system of mesoscale atmospheric and spectral wave models to quantify the wind and wave climate as well as nearshore wave energy resources in Hawaii. A global WAVEWATCH III (WW3) model forced by surface winds from the Final Global Tropospheric Analysis (FNL) reproduces the swell and seas from the far field and a nested Hawaii WW3 model with high-resolution winds from the Weather Research Forecast (WRF) model capture the local wave processes. The Simulating Waves Nearshore (SWAN) model nested inside Hawaii WW3 provides data in coastal waters, where wave energy converters are being considered for deployment. The computed wave heights show good agreement with data from satellites and buoys. Bi-monthly median and percentile plots show persistent trade winds throughout the year with strong seasonal variation of the wave climate. The nearshore data shows modulation of the wave energy along the coastline due to the undulating volcanic island bathymetry and demonstrates its importance in selecting suitable sites for wave energy converters.
► Proven numerical models have produced 10 years of wind and wave data. ► Model data compare well with observations from satellites and buoys. ► Statistics reveal the wind, wave, and wave energy resource climate. ► Wave energy resources are quantified and optimal locations are identified. |
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| AbstractList | Hawaii is subject to direct approach of swells from distant storms as well as seas generated by trade winds all year round. The island chain creates a localized weather system that modifies the wave energy resources from the far field. Here, we implement a nested computational grid across the major Hawaiian Islands at 3-min resolution in the global WaveWatch3 (WW3) model and utilize the Weather Research Forecast (WRF) model to provide high-resolution mesoscale wind forcing over the Hawaii region. Two hindcast studies representative of the year-round conditions provide a quantitative assessment of the regional wind and wave patterns as well as the wave energy resources along the Hawaiian Island chain. These events of approximately two weeks each have a range of wind speeds, ground swells, and wind waves for validation of the modeling system with satellite and buoy measurements prior to its general application. Hawaii's access to the ocean and remoteness from fuel supplies has sparked an interest in ocean waves as a potential resource to meet the increasing demand for sustainable energy. The wave resources include swells from distant storms and year-round seas generated by trade winds passing through the islands. This study produces 10 years of hindcast data from a system of mesoscale atmospheric and spectral wave models to quantify the wind and wave climate as well as nearshore wave energy resources in Hawaii. A global WAVEWATCH III (WW3) model forced by surface winds from the Final Global Tropospheric Analysis (FNL) reproduces the swell and seas from the far field and a nested Hawaii WW3 model with high-resolution winds from the Weather Research Forecast (WRF) model capture the local wave processes. The Simulating Waves Nearshore (SWAN) model nested inside Hawaii WW3 provides data in coastal waters, where wave energy converters are being considered for deployment. The computed wave heights show good agreement with data from satellites and buoys. Bi-monthly median and percentile plots show persistent trade winds throughout the year with strong seasonal variation of the wave climate. The nearshore data shows modulation of the wave energy along the coastline due to the undulating volcanic island bathymetry and demonstrates its importance in selecting suitable sites for wave energy converters. Hawaii's access to the ocean and remoteness from fuel supplies has sparked an interest in ocean waves as a potential resource to meet the increasing demand for sustainable energy. The wave resources include swells from distant storms and year-round seas generated by trade winds passing through the islands. This study produces 10 years of hindcast data from a system of mesoscale atmospheric and spectral wave models to quantify the wind and wave climate as well as nearshore wave energy resources in Hawaii. A global WAVEWATCH III (WW3) model forced by surface winds from the Final Global Tropospheric Analysis (FNL) reproduces the swell and seas from the far field and a nested Hawaii WW3 model with high-resolution winds from the Weather Research Forecast (WRF) model capture the local wave processes. The Simulating Waves Nearshore (SWAN) model nested inside Hawaii WW3 provides data in coastal waters, where wave energy converters are being considered for deployment. The computed wave heights show good agreement with data from satellites and buoys. Bi-monthly median and percentile plots show persistent trade winds throughout the year with strong seasonal variation of the wave climate. The nearshore data shows modulation of the wave energy along the coastline due to the undulating volcanic island bathymetry and demonstrates its importance in selecting suitable sites for wave energy converters. Hawaii's access to the ocean and remoteness from fuel supplies has sparked an interest in ocean waves as a potential resource to meet the increasing demand for sustainable energy. The wave resources include swells from distant storms and year-round seas generated by trade winds passing through the islands. This study produces 10 years of hindcast data from a system of mesoscale atmospheric and spectral wave models to quantify the wind and wave climate as well as nearshore wave energy resources in Hawaii. A global WAVEWATCH III (WW3) model forced by surface winds from the Final Global Tropospheric Analysis (FNL) reproduces the swell and seas from the far field and a nested Hawaii WW3 model with high-resolution winds from the Weather Research Forecast (WRF) model capture the local wave processes. The Simulating Waves Nearshore (SWAN) model nested inside Hawaii WW3 provides data in coastal waters, where wave energy converters are being considered for deployment. The computed wave heights show good agreement with data from satellites and buoys. Bi-monthly median and percentile plots show persistent trade winds throughout the year with strong seasonal variation of the wave climate. The nearshore data shows modulation of the wave energy along the coastline due to the undulating volcanic island bathymetry and demonstrates its importance in selecting suitable sites for wave energy converters. ► Proven numerical models have produced 10 years of wind and wave data. ► Model data compare well with observations from satellites and buoys. ► Statistics reveal the wind, wave, and wave energy resource climate. ► Wave energy resources are quantified and optimal locations are identified. |
| Author | Chen, Yi-Leng Li, Ning Filipot, Jean-François Cheung, Kwok Fai Vega, Luis Stopa, Justin E. |
| Author_xml | – sequence: 1 givenname: Justin E. surname: Stopa fullname: Stopa, Justin E. email: stopa@hawaii.edu organization: Department of Ocean and Resources Engineering, University of Hawaii at Manoa, Honolulu, HI 96822, USA – sequence: 2 givenname: Jean-François surname: Filipot fullname: Filipot, Jean-François email: jean-francois.filipot@shom.fr organization: Department of Ocean and Resources Engineering, University of Hawaii at Manoa, Honolulu, HI 96822, USA – sequence: 3 givenname: Ning surname: Li fullname: Li, Ning email: ningli@hawaii.edu organization: Department of Ocean and Resources Engineering, University of Hawaii at Manoa, Honolulu, HI 96822, USA – sequence: 4 givenname: Kwok Fai surname: Cheung fullname: Cheung, Kwok Fai email: cheung@hawaii.edu organization: Department of Ocean and Resources Engineering, University of Hawaii at Manoa, Honolulu, HI 96822, USA – sequence: 5 givenname: Yi-Leng surname: Chen fullname: Chen, Yi-Leng email: yileng@hawaii.edu organization: Department of Meteorology, University of Hawaii at Manoa, Honolulu, HI 96822, USA – sequence: 6 givenname: Luis surname: Vega fullname: Vega, Luis email: luisvega@hawaii.edu organization: National Marine Renewable Energy Center, University of Hawaii at Manoa, Honolulu, HI 96822, USA |
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| Snippet | Hawaii's access to the ocean and remoteness from fuel supplies has sparked an interest in ocean waves as a potential resource to meet the increasing demand for... Hawaii is subject to direct approach of swells from distant storms as well as seas generated by trade winds all year round. The island chain creates a... |
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| SubjectTerms | Applied sciences Climate coastal water coasts Converters Direct power generation Energy energy conversion Exact sciences and technology fuels Hawaii HYDRO ENERGY Islands Mathematical models Mesoscale model Natural energy Oceans satellites Seas seasonal variation Spectral wave models storms Trade winds troposphere water power water waves Wave atlas Wave energy Wave energy resource Wave power |
| Title | Wave energy resources along the Hawaiian Island chain |
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