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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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A High-resolution Regional Wave Resource Characterization For The U.S. West Coast

Objectives/Scope: Wave resource characterization is a critical step for wave energy converter deployment in the coastal ocean and relies on long-term, high-resolution wave datasets. This study presents a detailed modeling study of the wave resource along the U.S. West Coast (Washington, Oregon, and California), a coastal region that was identified with high wave energy potential in earlier studies. Methods, Procedures, Process: The wave hindcast covers a 32-year period from 1979 to 2010 and is based on a multi-resolution, unstructured-grid SWAN model framework. Model configuration closely follows and meets the requirements recommended by the International Electrotechnical Commission Technical Specification (IEC TS) for wave energy resource assessment and characterization (Class 2 - feasibility study). The model domain covers the entire U.S. Exclusive Economic Zone (EEZ) in the West Coast and has a spatial resolution varying from ~300 m in the nearshore region (20 km from the shoreline) to ~2500 m within the EEZ and ~5000 m at the open boundary, which extends beyond the EEZ. The model was forced by hourly 2-D wave spectra produced by a two-way nested WaveWatch III model, which covers the global ocean domain and the broader U.S. West Coast region domain with spatial resolutions of 0.5 degree and 10 arc-minutes, respectively. Both wave models are forced by hourly, 0.5-degree wind forcing obtained from NCEP’s Climate Forecast System Reanalysis (CFSR) product. Results, Observations, Conclusions: The standard model output for the SWAN model includes 3-hourly output for the six IEC wave resource parameters (e.g., omnidirectional wave power) at each grid point and hourly 2-D spectra at more than 50 NDBC buoys. Extensive model validation was achieved by comparing the six model-predicted IEC parameters with those derived from field observations at representative NDBC buoys. The error statistics indicated the model’s satisfactory performance. Further analyses were conducted to systematically evaluate the temporal and spatial distributions of wave energy potential and wave climate along the U.S. West Coast. Results suggest that Washington and Oregon coasts have similar nearshore wave resource, which is significantly higher than resources in Southern California. Strong seasonal variations are also observed, e.g., high wave energy tends to occur in the winter months. In summary, this study produced the first high-resolution, comprehensive dataset on wave energy distribution along the U.S. West Coast. Novel/Additive Information: The results are being used by the National Renewable Energy Laboratory to update the MHK Atlas, which was originally derived from NOAA’s 4-arc-minute WaveWatch III model output. In addition, the monthly averaged wave energy climatology dataset can be readily shared to support a variety of research and application efforts within the EEZ of the U.S. West Coast.

Wang, Taiping↗

Ocean Thermal Extractable Energy Visualization (Final Technical Report)

The Ocean Thermal Extractable Energy Visualization (OTEEV) project focuses on assessing the Maximum Practicably Extractable Energy (MPEE) from the world's ocean thermal resources. MPEE is defined as being sustainable and technically feasible, given today's state-of-the-art ocean energy technology. Under this project the OTEEV team developed a comprehensive Geospatial Information System (GIS) dataset and software tool, and used the tool to provide a meaningful assessment of MPEE from the global and domestic U.S. ocean thermal resources. The OTEEV project leverages existing NREL renewable energy GIS technologies and integrates extractable energy estimated from quality-controlled data and projected optimal achievable energy conversion rates. Input data are synthesized from a broad range of existing in-situ measurements and ground-truthed numerical models with temporal and spatial resolutions sufficient to reflect the local resource. Energy production rates are calculated for regions based on conversion rates estimated for current technology, local energy density of the resource, and sustainable resource extraction. Plant spacing and maximum production rates are then estimated based on a default plant size and transmission mechanisms. The resulting data are organized, displayed, and accessed using a multi-layered GIS mapping tool, http://maps.nrel.gov/mhk_atlas with a user-friendly graphical user interface.

14 SOLAR ENERGY↗

Marine and Hydrokinetic (MHK) Databases and Systems

The online information resources included in this fact sheet were developed with support from the U.S. Department of Energy, and are designed to provide the public access to information pertaining to MHK technologies, projects, and research.

MHK databases, technology databases, OpenEI, Tethy↗