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Wave Resource Characterization Using an Unstructured Grid Modeling Approach

Author

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  • Wei-Cheng Wu

    (Pacific Northwest National Laboratory, 1100 Dexter Ave North, Ste 500, Seattle, WA 98109, USA)

  • Zhaoqing Yang

    (Pacific Northwest National Laboratory, 1100 Dexter Ave North, Ste 500, Seattle, WA 98109, USA)

  • Taiping Wang

    (Pacific Northwest National Laboratory, 1100 Dexter Ave North, Ste 500, Seattle, WA 98109, USA)

Abstract

This paper presents a modeling study conducted on the central Oregon coast for wave resource characterization, using the unstructured grid Simulating WAve Nearshore (SWAN) model coupled with a nested grid WAVEWATCH III ® (WWIII) model. The flexibility of models with various spatial resolutions and the effects of open boundary conditions simulated by a nested grid WWIII model with different physics packages were evaluated. The model results demonstrate the advantage of the unstructured grid-modeling approach for flexible model resolution and good model skills in simulating the six wave resource parameters recommended by the International Electrotechnical Commission in comparison to the observed data in Year 2009 at National Data Buoy Center Buoy 46050. Notably, spectral analysis indicates that the ST4 physics package improves upon the ST2 physics package’s ability to predict wave power density for large waves, which is important for wave resource assessment, load calculation of devices, and risk management. In addition, bivariate distributions show that the simulated sea state of maximum occurrence with the ST4 physics package matched the observed data better than with the ST2 physics package. This study demonstrated that the unstructured grid wave modeling approach, driven by regional nested grid WWIII outputs along with the ST4 physics package, can efficiently provide accurate wave hindcasts to support wave resource characterization. Our study also suggests that wind effects need to be considered if the dimension of the model domain is greater than approximately 100 km, or O (10 2 km).

Suggested Citation

  • Wei-Cheng Wu & Zhaoqing Yang & Taiping Wang, 2018. "Wave Resource Characterization Using an Unstructured Grid Modeling Approach," Energies, MDPI, vol. 11(3), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:605-:d:135490
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    References listed on IDEAS

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    Cited by:

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    5. Wu, Wei-Cheng & Wang, Taiping & Yang, Zhaoqing & García-Medina, Gabriel, 2020. "Development and validation of a high-resolution regional wave hindcast model for U.S. West Coast wave resource characterization," Renewable Energy, Elsevier, vol. 152(C), pages 736-753.
    6. Lokuliyana, R.L.K. & Folley, M. & Gunawardane, S.D.G.S.P. & Wickramanayake, P.N., 2020. "Sri Lankan wave energy resource assessment and characterisation based on IEC standards," Renewable Energy, Elsevier, vol. 162(C), pages 1255-1272.
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