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A seasonal grade division of the global offshore wind energy resource

机译:全球海上风能资源的季节性等级划分

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摘要

Under the background of energy crisis, the development of renewable energy will significantly alleviate the energy and environmental crisis. On the basis of the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-interim) wind data, the annual and seasonal grade divisions of the global offshore wind energy are investigated. The results show that the annual mean offshore wind energy has great potential. The wind energy over the westerly oceans of the Northern and Southern Hemispheres is graded as Class 7 (the highest), whereas that over most of the mid-low latitude oceans are higher than Class 4. The wind energy over the Arctic Ocean (Class 4) is more optimistic than the traditional evaluations. Seasonally, the westerly oceans of the Northern Hemisphere with a Class 7 wind energy are found to be largest in January, followed by April and October, and smallest in July. The area of the Class 7 wind energy over the westerly oceans of the Southern Hemisphere are found to be largest in July and slightly smaller in the other months. In July, the wind energy over the Arabian Sea and the Bay of Bengal is graded as Class 7, which is obviously richer than that in other months. It is shown that in this data set in April and October, the majority of the northern Indian Ocean are regions of indigent wind energy resource.
机译:在能源危机的背景下,可再生能源的发展将大大缓解能源和环境危机。根据欧洲中距离天气预报中心(ECMWF)临时再分析(ERA-interim)风数据,研究了全球海上风能的年度和季节等级划分。结果表明,海上风能年均潜力巨大。北半球和南半球西风海洋上的风能等级为7级(最高),而中低纬度海洋上的大部分风能都高于4级。北冰洋上的风能(4级) )比传统评估更为乐观。季节性地,发现北半球的西风海洋具有7级风能,在1月最大,其次是4月和10月,7月最小。发现南半球西风的7级风能面积在7月最大,而在其他月份略小。 7月,阿拉伯海和孟加拉湾的风能被定为7级,这显然比其他月份要丰富。结果表明,在4月和10月的这一数据集中,印度洋北部大部分地区是贫困的风能资源地区。

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  • 来源
    《海洋学报(英文版)》 |2017年第3期|109-114|共6页
  • 作者单位

    College of Meteorology and Oceanography, People's Liberation Army University of Science and Technology, Nanjing 211101, China;

    National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;

    Dalian Naval Academy, People's Liberation Army, Dalian 116018, China;

    College of Meteorology and Oceanography, People's Liberation Army University of Science and Technology, Nanjing 211101, China;

    National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;

    Dalian Naval Academy, People's Liberation Army, Dalian 116018, China;

    College of Meteorology and Oceanography, People's Liberation Army University of Science and Technology, Nanjing 211101, China;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
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