基于同化了30 a卫星高度计有效波高的全球高分辨率海浪再分析数据,该文详细分析波浪能分布特征,针对海浪的可开发性,提出一种新的波浪能资源选址评估方法,并利用该评估方法对全球和中国近海的波浪能进行区划。主要结论有:波浪能最为丰富处位于西风带海域,约占全球总波浪能的67%;其中,印度洋西风带尤甚,平均能流密度达90 kW/m,西风带近岸海域波浪能可利用程度较高;中国周边海域波浪能资源相对匮乏,但台湾岛东南部、琉球群岛以及东沙群岛附近波浪能资源较为丰富,可利用程度较高,平均能流密度最高约为11 kW/m,该研究可为波浪能发展规划与开发利用提供参考。
Abstract
Based on the global high-resolution wave reanalysis data that has assimilated the significant wave height of the satellite altimeters over the past 30 years, the wave energy distribution characteristics are analyzed in detail. Aiming at the developability of ocean waves, a new method for location evaluation of wave energy resources is proposed and use this evaluation method to divide the wave energy of the global and offshore China. The main conclusions are as follows: westerlies have the most abundant wave energy resources, accounting for 67% of the total global wave energy resources. Among them, the coastal wave energy resources are most abundant in the Indian Ocean westerlies, with an average wave power density of 90 kW/m, and the extent of wave energy utilization in the coastal westerlies are high. The wave energy of the China adjacent seas is relatively scarce, but the southeastern part of Taiwan Island, the Ryukyu Islands and the Dongsha Islands are slightly high in wave energy resources and have a high degree of availability, with an average wave power density of up to 11 kW/m. This research can provide reference for wave energy development planning and utilization.
关键词
海浪 /
波浪能 /
资源评估 /
区划 /
再分析数据
Key words
wave /
wave energy /
resource valuation /
regional planning /
reanalysis data
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参考文献
[1] ZHENG C W, WANG Q, LI C Y.An overview of medium-to long-term predictions of global wave energy resources[J]. Renewable and sustainable energy reviews, 2017, 79: 1492-1502.
[2] LENEE-BLUHM P, PAASCH ROBERT, ÖZKAN-HALLER H T. Characterizing the wave energy resource of the US Pacific Northwest[J]. Renewable energy, 2011, 36(8): 2106-2119.
[3] YAAKOB O, HASHIM F E, OMAR K M, et al.Satellite-based wave data and wave energy resource assessment for South China Sea[J]. Renewable energy, 2016, 88: 359-371.
[4] WAN Y, ZHANG J, MENG J M, et al.A wave energy resource assessment in the China's seas based on multi-satellite merged radar altimeter data[J]. Acta oceanologica sinica, 2015, 34(3): 115-124.
[5] PENTON J, PATTIARATCHI C B.Accuracy of wave forecasts as a function of forecast time horizon in south-western Australia[C]//Proceedings of the 20th Australasian Coastal and Ocean Engineering Conference and the 13th Australasian Port and Harbour Conference, Perth, Australia, 2011.
[6] 郑崇伟, 李训强. 基于WAVEWATCH-Ⅲ模式的近22年中国海波浪能资源评估[J]. 中国海洋大学学报(自然科学版), 2011, 41(11): 5-12.
ZHENG C W, LI X Q.Wave energy resources assessment in the China sea during the last 22 years by using WAVEWATCH III wave model[J]. Periodical of Ocean University of China(Natural Science) , 2011, 41(11): 5-12.
[7] LAVIDAS G, VENUGOPAL V, FRIEDRICH D.Wave energy extraction in Scotland through an improved nearshore Wave Atlas[J]. International journal of marine energy, 2017, 17: 64-83.
[8] ZHENG C W, SHAO L T, SHI W L, et al.An assessment of global ocean wave energy resources over the last 45 a[J]. Acta oceanologica sinica, 2014, 33(1): 92-101.
[9] ARINAGA P A, CHEUNG K F.Atlas of global wave energy from 10 years of reanalysis and hindcast data[J]. Renewable energy, 2011, 39(1): 49-64.
[10] 梅婵娟, 赵栋梁, 史剑. 两种海浪模式对中国黄海海域浪高模拟能力的比较[J]. 海洋预报, 2008, 25(2): 92-98.
MEI C J, ZHAO D L, SHI J.The analysis of Yellow Sea with WAVEWATCH and SWAN models[J]. Marine forecast, 2008, 25(2): 92-98.
[11] YU H M, LI J Y, WU K J, et al.A global high-resolution ocean wave model improved by assimilating the satellite altimeter significant wave height[J]. International journal of applied earth observations and geoinformation, 2018, 70: 43-50.
[12] EARLE M D.Development of algorithms for separation of sea and swell, National Data Buoy Center Tech[R]. MEC-87-1, 1984.
[13] 郑崇伟, 李崇银. 海洋强国视野下的“海上丝绸之路”海洋新能源评估[J]. 哈尔滨工程大学学报, 2020, 41(2): 175-183.
ZHENG C W, LI C Y.Evaluation of new marine energy for the Maritime Silk Road from the perspective of maritime power[J]. Journal of Harbin Engineering University, 2020, 41(2): 175-183.
[14] 郑崇伟, 裴顺强, 李伟. “21世纪海上丝绸之路”:未来40年波浪能长期预估[J]. 哈尔滨工程大学学报, 2020, 41(7): 958-965.
ZHENG C W, PEI S Q, Li W.Projection of wave energy resource for the future 40 years in the 21st century Maritime Silk Road[J]. Journal of Harbin Engineering University, 2020, 41(7): 958-965.
[15] 郑崇伟, 贾本凯, 郭随平, 等. 全球海域波浪能资源储量分析[J]. 资源科学, 2013, 35(8): 1611-1616.
ZHENG C W, JIA B K, GUO S P, et al.Wave energy resource storage assessment in global ocean[J]. Resources science, 2013, 35(8): 1611-1616.
[16] 郑崇伟, 李崇银. 全球海域波浪能资源评估的研究进展[J]. 海洋预报, 2016, 33(3): 76-88.
ZHENG C W, LI C Y.Review on the global ocean wave energy resource[J]. Marine forecasts, 2016, 33(3): 76-88.
[17] 万勇, 张杰, 孟俊敏, 等. 基于ERA-Interim高分辨率数据的中国东海南海波浪能评估[J].太阳能学报, 2015, 36(5): 1259-1267.
WAN Y, ZHANG J, MENG J M, et al.Wave energy assessment in the East China Sea and South China Sea based on ERA-Interim high-resolution data[J]. Acta energiae solaris sinica, 2015, 36(5): 1259-1267.
[18] ZHENG C W, ZHUANG H, LI X, et al.Wind energy and wave energy resources assessment in the East China Sea and South China Sea[J]. Science China(technological sciences), 2012, 55(1): 163-173.
[19] 郑崇伟, 游小宝, 陈晓斌, 等. 西北太平洋海域风浪、涌浪、混合浪波浪能资源特征[J]. 气象科学, 2014, 34(4): 408-413.
ZHENG C W, YOU X B, CHEN X B, et al.Characteristics analysis on wave energy over Northwest Pacific Ocean in the last 44 years[J]. Journal of meteorological sciences, 2014, 34(4): 408-413.
[20] 郑崇伟. 21世纪海上丝绸之路: 斯里兰卡海域的波浪能评估及决策建议[J]. 哈尔滨工程大学学报, 2018, 39(4): 614-621.
ZHENG C W.21st Century Maritime Silk Road: wave energy evaluation and decision and proposal of the Sri Lankan waters[J]. Journal of Harbin Engineering University, 2018, 39(4): 614-621.
[21] ATAN R, GOGGINS J, HARNETT M, et al.Assessment of wave characteristics and resource variability at a 1/4-scale wave energy test site in Galway Bay using waverider and high frequency radar (CODAR)data[J]. Ocean engineering, 2016, 117: 272-291.
基金
国家重点基础研究发展计划(2018YFB1501901; 2018YFB1502801)