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Title: Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

Abstract

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived frommore » buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.« less

Authors:
ORCiD logo [1];  [1]; ORCiD logo [2];  [3]; ORCiD logo [4]; ORCiD logo [4];  [3]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Water Power Technologies
  2. Pennsylvania State Univ., State College, PA (United States)
  3. North Carolina State Univ., Raleigh, NC (United States)
  4. Pacific Northwest National Lab. (PNNL), Seattle, WA (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Water Power Technologies Office; USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1638491
Report Number(s):
PNNL-SA-152704
Journal ID: ISSN 2077-1312
Grant/Contract Number:  
AC05-76RL01830; NA0003525
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Marine Science and Engineering
Additional Journal Information:
Journal Volume: 8; Journal Issue: 4; Journal ID: ISSN 2077-1312
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
16 TIDAL AND WAVE POWER; Extreme significant wave height; wave hindcast; wave energy resource assessment; WEC design

Citation Formats

Neary, Vincent S., Ahn, Seongho, Seng, Bibiana E., Allahdadi, Mohammad Nabi, Wang, Taiping, Yang, Zhaoqing, and He, Ruoying. Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment. United States: N. p., 2020. Web. https://doi.org/10.3390/jmse8040289.
Neary, Vincent S., Ahn, Seongho, Seng, Bibiana E., Allahdadi, Mohammad Nabi, Wang, Taiping, Yang, Zhaoqing, & He, Ruoying. Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment. United States. https://doi.org/10.3390/jmse8040289
Neary, Vincent S., Ahn, Seongho, Seng, Bibiana E., Allahdadi, Mohammad Nabi, Wang, Taiping, Yang, Zhaoqing, and He, Ruoying. Sat . "Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment". United States. https://doi.org/10.3390/jmse8040289. https://www.osti.gov/servlets/purl/1638491.
@article{osti_1638491,
title = {Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment},
author = {Neary, Vincent S. and Ahn, Seongho and Seng, Bibiana E. and Allahdadi, Mohammad Nabi and Wang, Taiping and Yang, Zhaoqing and He, Ruoying},
abstractNote = {Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.},
doi = {10.3390/jmse8040289},
journal = {Journal of Marine Science and Engineering},
number = 4,
volume = 8,
place = {United States},
year = {2020},
month = {4}
}

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