基于海洋模型SWAN建立广东近海海域高分辨率波浪数值模型,并利用波浪观测资料对模型进行验证,良好刻画了广东近海海域波浪能资源特征。选取粤东海上风电基地海域重点研究波浪能年际变化和方向分布,并探讨该处各季节风浪及涌浪有效波高和平均周期特性。结果表明:广东海域波浪能资源呈东南-西北递减趋势,具有较强的季节变化性,秋冬两季大部分海域波浪能功率密度大于6 kW/m,春夏两季多大于2 kW/m;平均周期冬季较大,大部分海域介于5.5~7.0 s,秋、春季次之,夏季偏小,多低于6.0 s。粤东海上风电基地全年波浪能来向主要为E-NE向区间,5、6、9月份平均有效波高值较小,中位值及平均值在0.7~0.9 m区间。冬季有效波高平均值在1.3~1.6 m范围内,其中12月份平均值最高,能量周期在5、6月份最小,平均值约5.1 s。此外,该处波浪冬季由风浪主导,夏季由涌浪主导,各季节平均周期涌浪较风浪高约3.0 s。
Abstract
Based on the ocean model SWAN, the validation results suggested that the model can effectively represent the wave energy characterization in this region. The sea area of Guangdong East Offshore Wind Power Base was selected to focus on the wave energy inter-annual variation and directional distribution, and to explore the significant wave height and mean period characteristics of wind waves and swell waves in all seasons. The results show that the wave energy resource in the study area show a decreasing trend from southeast to northwest with strong seasonal variability. The power density is more than 6 kW/m in most of the sea area in winter and fall, and more than 2 kW/m in spring and summer. The average period in winter is between 5.5-7.0 s in most of the study area, and mostly lower than 6.0 s in summer, which is the smallest. Guangdong East offshore wind power base is mainly in E-NE wave direction throughout the year, and the average effective wave height value is small in May, June and September, with the median and average value in the range of 0.7-0.9 m. and the energy period is the smallest in May-June, with an average value of about 5.1 s. In addition, the waves in this area are dominated by wind waves in winter and swell waves in summer, and the average period swell waves are about 3.0 s higher than wind waves in all seasons.
关键词
波浪能 /
资源评估 /
SWAN /
广东近海 /
风浪 /
浪涌
Key words
wave energy /
resource assessment /
SWAN model /
Guangdong offshore /
wind wave /
swell
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参考文献
[1] LI L, LIN J, WU N Y, et al.Review and outlook on the international renewable energy development[J]. Energy and built environment, 2022, 3(2): 139-157.
[2] GUILLOU N, LAVIDAS G, CHAPALAIN G.Wave energy resource assessment for exploitation: a review[J]. Journal of marine science and engineering, 2020, 8(9): 705.
[3] ZHANG Y X, ZHAO Y J, SUN W, et al.Ocean wave energy converters: technical principle, device realization, and performance evaluation[J]. Renewable and sustainable energy reviews, 2021, 141: 110764.
[4] HOU J C, ZHU X W, LIU P K.Current situation and future projection of marine renewable energy in China[J]. International journal of energy research, 2019, 43(2): 662-680.
[5] 胡聪, 毛海英, 尤再进, 等. 中国海域波浪能资源分布及波浪能发电装置适用性研究[J]. 海洋科学, 2018, 42(3): 142-148.
HU C, MAO H Y, YOU Z J, et al.Study on the distribution of wave energy resources in China and the applicability of wave energy generation device[J]. Marine sciences, 2018, 42(3): 142-148.
[6] 施伟勇, 王传崑, 沈家法. 中国的海洋能资源及其开发前景展望[J]. 太阳能学报, 2011, 32(6): 913-923.
SHI W Y, WANG C K, SHEN J F.Utilization and prospect of ocean energy resource in China[J]. Acta energiae solaris sinica, 2011, 32(6): 913-923.
[7] 张松, 刘富铀, 张滨, 等. 我国近海波浪能资源调查与评估[J]. 海洋技术, 2012, 31(3): 79-81, 85.
ZHANG S, LIU F Y, ZHANG B, et al.Investigation and assessment of wave energy in coastal area of China[J]. Ocean technology, 2012, 31(3): 79-81, 85.
[8] 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.
[9] 姜波, 丁杰, 方舣洲, 等. 涠洲岛海洋风能和波浪能资源评估[J]. 太阳能学报, 2023, 44(10): 461-466.
JIANG B, DING J, FANG Y Z, et al.Offshore wind energy and wave energy resource valuation in Weizhou island[J]. Acta energiae solaris sinica, 2023, 44(10): 461-466.
[10] 于建民, 纪棋严, 郑欢, 等. 基于SWAN模式的舟山海域波浪能资源的评估研究[J]. 海洋预报, 2020, 37(4): 38-49.
YU J M, JI Q Y, ZHENG H, et al.The investigation of wave energy in Zhoushan coastal area based on SWAN model[J]. Marine forecasts, 2020, 37(4): 38-49.
[11] 武贺, 方舣洲, 张松, 等. 南海岛礁海域波浪能资源分析及总量评估[J]. 太阳能学报, 2022, 43(9): 416-423.
WU H, FANG Y Z, ZHANG S, et al.Wave energy characterization and potential estimation for islands of South China Sea[J]. Acta energiae solaris sinica, 2022, 43(9): 416-423.
[12] 王奎, 岳显昌, 吴雄斌, 等. 台湾海峡有效波高的SWAN模式与ERA-Interim数据对比分析[J]. 海洋学报, 2021, 43(12): 15-25.
WANG K, YUE X C, WU X B, et al.Comparative analysis of SWAN model and ERA-Interim data on significant wave height in the Taiwan Strait[J]. Haiyang Xuebao, 2021, 43(12): 15-25.
[13] 杜文彦, 张旭日, 张丽丽, 等. 基于ERA5再分析数据的中国邻近海域极端波高特征分析[J]. 海洋与湖沼, 2022, 53(4): 1007-1014.
DU W Y, ZHANG X R, ZHANG L L, et al.Characteristics of extreme wave height in China’s marginal seas based on ERA5 reanalysis data[J]. Oceanologia et limnologia sinica, 2022, 53(4): 1007-1014.
[14] 路晴, 史宏达. 中国波浪能技术进展与未来趋势[J]. 海岸工程, 2022, 41(1): 1-12.
LU Q, SHI H D.Progress and future trend of wave energy technology in China[J]. Coastal engineering, 2022, 41(1): 1-12.
[15] 江森汇, 舒勰俊, 王青, 等. 基于长时间序列ERA-Interim再分析资料的广东沿海波浪能资源分布特征分析[J]. 海洋通报, 2021, 40(5): 550-558.
JIANG S H, SHU X J, WANG Q, et al.Evolution characteristics of wave energy resources in Guangdong coastal area based on long time series ERA-Interim reanalysis data[J]. Marine science bulletin, 2021, 40(5): 550-558.
[16] 江兴杰, 杨永增, 王道龙, 等. 浅水环境下波浪能能流密度计算方法研究[J]. 海洋学报, 2015, 37(9): 1-9.
JIANG X J, YANG Y Z, WANG D L, et al.Study of wave power density computation in finite depth[J]. Haiyang Xuebao, 2015, 37(9): 1-9.
基金
中国大唐集团有限公司科技项目(DTGD-2023-10174)