A high-resolution wave energy assessment of south-east Australia based on a 40-year hindcast
Jin Liu,
Alberto Meucci,
Qingxiang Liu,
Alexander V. Babanin,
Daniel Ierodiaconou,
Xingkun Xu and
Ian R. Young
Renewable Energy, 2023, vol. 215, issue C
Abstract:
In this study, a third-generation ocean wave model (WAVEWATCH III; WW3) implemented on a high-resolution unstructured grid was developed to investigate wave energy in the south-east of Australia over the 40-year period from 1981 to 2020. The simulated wave power shows good agreement with values estimated from multiplatform satellite data. Thus, the modeled data were used to study statistics (mean conditions, seasonality, extremes, and long-term trends) of wave power in the domain, which show impacts of Southern Ocean swell and protection provided by the land mass of Tasmania. The results indicate increasing wave power trends, with the largest values in the southeastern part of the domain over the 40-year period. These positive trends are mainly a result of an increase in significant wave height rather than peak wave period. By utilizing the simulated wave properties, we estimated regional annual electric power at 14 coastal locations using 9 typical wave energy converters (WECs). To do so, we conducted a comprehensive analysis (seasonal variations, wave power roses, probability distributions, and bivariate probability distributions) at these locations. The results demonstrate that the western and southwestern coasts of the domain are promising generation sites but with large seasonal variability. The central and eastern coasts are protected by Tasmania, and exhibit more stable conditions but are far less energetic for electricity production. This study has critical implications for the region, which provides a benchmark for coastal WEC deployment.
Keywords: Wave power; South-east Australia; WAVEWATCH III; Unstructured grid; Satellite altimeter; Wave energy converter (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (7)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:215:y:2023:i:c:s0960148123008492
DOI: 10.1016/j.renene.2023.118943
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