Long-term trend analysis and wave energy assessment based on ERA5 wave reanalysis along the Chinese coastline

Peidong Sun, Bin Xu and Jichao Wang

Applied Energy, 2022, vol. 324, issue C, No S0306261922010030

Abstract: Assessing wave energy is of great importance to estimate the wave energy potential and site selection of wave energy converters. This paper aims to present the distributions of wave energy and long-term wave trend along the Chinese coastline. By using the high-accuracy wave data in ERA5 reanalysis for the 42-year period in 1979–2020, the spatiotemporal distributions of wave variations estimated by Theil-Sen Estimations and mean wave energy resources assessed by the implicit calculation equation are presented. Generally, annually mean wave heights increase in Yellow sea, East China Sea and South China Sea and decrease in Bohai sea. The wave energy assessment shows the great energy potential with annually mean wave energy density of major 6–12 kW/m. There is near Taiwan island and the northern parts of South China Sea that of higher energy density. The seasonal analysis reveals that winter and fall are more energetic with higher values around 20 kW/m. The wave power production in the selected locations was evaluated and provided based on the distribution of various wave states showing the East China Sea and South China Sea are the most suitable sea area for wave energy development.

Keywords: Along the Chinese coastline; ERA5 reanalysis; Long-term wave trend; Ocean wave energy (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261922010030
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:324:y:2022:i:c:s0306261922010030

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2022.119709

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().