Wave energy resources along the Hawaiian Island chain

• Published in: Renewable energy Vol. 55; pp. 305 - 321
• Main Authors: Stopa, Justin E., Filipot, Jean-François, Li, Ning, Cheung, Kwok Fai, Chen, Yi-Leng, Vega, Luis
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.07.2013; Elsevier
• Subjects: 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; Hawaii; Polynesia; Oceania; ISE, USA, Hawaii; Hawaii; Spectral wave models; Mesoscale model; Wave energy; Wave power; Wave atlas; Atlas; Energy resources; Renewable energy; Models; Island; Modeling
• ISSN: 0960-1481; 1879-0682
• DOI: 10.1016/j.renene.2012.12.030

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.