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Title: A wave model test bed study for wave energy resource characterization

Abstract

This paper presents a test bed study conducted to evaluate best practices in wave modeling to characterize energy resources. The model test bed off the central Oregon Coast was selected because of the high wave energy and available measured data at the site. Two third-generation spectral wave models, SWAN and WWIII, were evaluated. A four-level nested-grid approach—from global to test bed scale—was employed. Model skills were assessed using a set of model performance metrics based on comparing six simulated wave resource parameters to observations from a wave buoy inside the test bed. Both WWIII and SWAN performed well at the test bed site and exhibited similar modeling skills. The ST4 package with WWIII, which represents better physics for wave growth and dissipation, out-performed ST2 physics and improved wave power density and significant wave height predictions. However, ST4 physics tended to overpredict the wave energy period. The newly developed ST6 physics did not improve the overall model skill for predicting the six wave resource parameters. Sensitivity analysis using different wave frequencies and direction resolutions indicated the model results were not sensitive to spectral resolutions at the test bed site, likely due to the absence of complex bathymetric and geometric features.

Authors:
ORCiD logo; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1406783
Report Number(s):
PNNL-SA-122388
Journal ID: ISSN 0960-1481; WC0101000
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Renewable Energy; Journal Volume: 114; Journal Issue: PA
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; wave energy; resource characterization; modeling; WaveWatch III; SWAN

Citation Formats

Yang, Zhaoqing, Neary, Vincent S., Wang, Taiping, Gunawan, Budi, Dallman, Annie R., and Wu, Wei-Cheng. A wave model test bed study for wave energy resource characterization. United States: N. p., 2017. Web. doi:10.1016/j.renene.2016.12.057.
Yang, Zhaoqing, Neary, Vincent S., Wang, Taiping, Gunawan, Budi, Dallman, Annie R., & Wu, Wei-Cheng. A wave model test bed study for wave energy resource characterization. United States. doi:10.1016/j.renene.2016.12.057.
Yang, Zhaoqing, Neary, Vincent S., Wang, Taiping, Gunawan, Budi, Dallman, Annie R., and Wu, Wei-Cheng. 2017. "A wave model test bed study for wave energy resource characterization". United States. doi:10.1016/j.renene.2016.12.057.
@article{osti_1406783,
title = {A wave model test bed study for wave energy resource characterization},
author = {Yang, Zhaoqing and Neary, Vincent S. and Wang, Taiping and Gunawan, Budi and Dallman, Annie R. and Wu, Wei-Cheng},
abstractNote = {This paper presents a test bed study conducted to evaluate best practices in wave modeling to characterize energy resources. The model test bed off the central Oregon Coast was selected because of the high wave energy and available measured data at the site. Two third-generation spectral wave models, SWAN and WWIII, were evaluated. A four-level nested-grid approach—from global to test bed scale—was employed. Model skills were assessed using a set of model performance metrics based on comparing six simulated wave resource parameters to observations from a wave buoy inside the test bed. Both WWIII and SWAN performed well at the test bed site and exhibited similar modeling skills. The ST4 package with WWIII, which represents better physics for wave growth and dissipation, out-performed ST2 physics and improved wave power density and significant wave height predictions. However, ST4 physics tended to overpredict the wave energy period. The newly developed ST6 physics did not improve the overall model skill for predicting the six wave resource parameters. Sensitivity analysis using different wave frequencies and direction resolutions indicated the model results were not sensitive to spectral resolutions at the test bed site, likely due to the absence of complex bathymetric and geometric features.},
doi = {10.1016/j.renene.2016.12.057},
journal = {Renewable Energy},
number = PA,
volume = 114,
place = {United States},
year = 2017,
month =
}
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