基于ERA5数据的江苏海域风能资源评估

吉会峰, 刘吉堂, 宋心刚, 丁言者, 高清清

太阳能学报 ›› 2023, Vol. 44 ›› Issue (1) : 320-324.

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太阳能学报 ›› 2023, Vol. 44 ›› Issue (1) : 320-324. DOI: 10.19912/j.0254-0096.tynxb.2021-0952

基于ERA5数据的江苏海域风能资源评估

  • 吉会峰, 刘吉堂, 宋心刚, 丁言者, 高清清
作者信息 +

EVALUATION OF WIND ENERGY RESOURCES IN JIANGSU SEA AREA BASED ON ERA5 DATA

  • Ji Huifeng, Liu Jitang, Song Xin’gang, Ding Yanzhe, Gao Qingqing
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文章历史 +

摘要

利用欧洲中期天气预报中心(ECMWF)的ERA5风场数据,综合考虑风功率密度的时空分布、稳定性以及资源储量等要素,对江苏海域风能资源进行评估。结果表明,江苏海域多年平均风速和风功率密度总体呈现南高北低、离岸高近岸低的分布趋势。连云港近岸区域风功率密度等级小于2级,3级及以上区域主要分布在远海海域;盐城和南通除岸边潮间带滩涂区域外,大部分区域达到2级或3级,离岸约30 km可迅速提升至4级以上。风功率密度具有较明显的季节性分布特征;盐城南部和南通海域风能稳定性最好,连云港海域风能稳定性相对较差。南通和盐城南部风能资源有效储量最高,盐城北部次之,连云港最低。

Abstract

The wind energy resources in Jiangsu Sea area are evaluated based on the ERA5 surface wind data from the European Center for Medium-Range Weather Forecasts (ECMWF) considering the temporal and spatial distribution, stability and resource reserves of wind power density. The results show that the annual average of wind speed and wind power density in the south area is generally higher than the north and increase with the distance from the shore. The wind power density level of Lianyungang Nearshore Area is less than level 2, and level 3 and above are mainly distributed in offshore waters; while most areas in Yancheng and Nantong reach level 2 or level 3, and can be rapidly raised to level 4 or above about 30 km offshore, except for the coastal intertidal beach area. Wind power density shows obvious seasonal variation except in the coastal areas. The wind energy stability in the waters near Nantong and the south of Yancheng is the best, and relatively poor in the coastal area of Lianyungang. The effective reserves of wind energy resources in Nantong and southern Yancheng are the highest, followed by northern Yancheng, and the lowest in Lianyungang.

关键词

风能资源 / 再分析数据 / 风功率密度 / 有效储量 / 江苏海域

Key words

wind energy resource / reanalysis data / wind power density / effective reserves / Jiangsu Sea area

引用本文

导出引用
吉会峰, 刘吉堂, 宋心刚, 丁言者, 高清清. 基于ERA5数据的江苏海域风能资源评估[J]. 太阳能学报. 2023, 44(1): 320-324 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0952
Ji Huifeng, Liu Jitang, Song Xin’gang, Ding Yanzhe, Gao Qingqing. EVALUATION OF WIND ENERGY RESOURCES IN JIANGSU SEA AREA BASED ON ERA5 DATA[J]. Acta Energiae Solaris Sinica. 2023, 44(1): 320-324 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0952
中图分类号: P425.6   

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基金

国家重点研发计划(2018YFC1407005); 自然资源部东海局青年基金(2019011)

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