| 近海及海上风资源时空特性研究 |
| 封宇1, 何焱2, 朱启昊1, 郭辰2, 冯笑丹2, 黄必清1 |
| 1. 清华大学 自动化系, 北京 100084; 2. 华能新能源股份有限公司, 北京 100036 |
| Temporal and spatial characteristics of offshore wind resources |
| FENG Yu1, HE Yan2, ZHU Qihao1, GUO Chen2, FENG Xiaodan2, HUANG Biqing1 |
| 1. Department of Automation, Tsinghua University, Beijing 100084, China; 2. Huaneng Renewables Corporation Limited, Beijing 100036, China |
摘要:
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| 摘要海洋蕴含的风能资源比陆地更加丰富。由于海上与陆地气象要素的差异, 在进行近海及海上风资源评估时, 通常需要考虑海上风资源时间特性和空间特性的影响。该文根据某公司海上测风塔和近海测风塔的实际测风资料, 研究了海上风资源在时间上的不同分布, 重点使用了EM(expectation-maximization)算法, 研究传统风资源评估方法几乎不考虑的风速在昼夜表现出的不同分布。同时, 基于实测数据, 应用机器学习算法, 结合Monin-Obukhov相似性理论、参数离散替代方案以及海面空气动力学粗糙度参数化方案, 对海上风资源的空间特性进行了分析研究, 有效地反映出海洋表面动力学粗糙度变化对于风速垂直变化的影响, 弥补了传统切变公式的不足。结果揭示了海上风资源的时空变化规律, 为近海及海上风资源评估和海上风电场的前期规划提供了依据。 | |||
| 关键词 ：风能,海上风资源,时空特性,风资源评估,Monin-Obukhov相似性理论,空气动力学粗糙度 | |||
| Abstract：Offshore wind energy resources are more abundant than on land. However, sea and land winds have different meteorological elements so offshore wind resource assessments need to take the impact of the temporal and spatial characteristics of the offshore wind resources into consideration. Data from an offshore wind measurement mast was used to study offshore wind distributions at different time scales. The EM (expectation-maximization) algorithm was used to study the differences in offshore wind distributions between day and night, which is normally not considered in traditional wind assessment methods. The spatial characteristics of offshore winds will than analyzing using a machine learning algorithm, Monin-Obukhov similarity theory, and a parameter replacement scheme in discrete calculations and in an ocean surface aerodynamic roughness model. This method efficiently reflects the impact of ocean surface aerodynamic roughness changes on the vertical variations of the wind speed that is not considered in traditional wind shear formula. The results show the temporal and spatial characteristics of the offshore wind resources as a basis for better offshore wind assessments for planning offshore wind farms. | |||
| Key words：wind energyoffshore wind resourcetemporal and spatial characteristicswind resource assessmentMonin-Obukhov similarity theorysurface aerodynamic roughness | |||
| 收稿日期: 2016-01-07 出版日期: 2016-05-19 | |||
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| 通讯作者:黄必清(1966-), 教授, E-mail: hbq@tsinghua.edu.cnE-mail: hbq@tsinghua.edu.cn | |||
| 引用本文: |
| 封宇, 何焱, 朱启昊, 郭辰, 冯笑丹, 黄必清. 近海及海上风资源时空特性研究[J]. 清华大学学报（自然科学版）, 2016, 65(5): 522-529. FENG Yu, HE Yan, ZHU Qihao, GUO Chen, FENG Xiaodan, HUANG Biqing. Temporal and spatial characteristics of offshore wind resources. Journal of Tsinghua University(Science and Technology), 2016, 65(5): 522-529. |
| 链接本文: |
| http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2016.25.011或 http://jst.tsinghuajournals.com/CN/Y2016/V65/I5/522 |
图表:
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| 图１ 海上风资源评估方法 |
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| 表１ 测风数据的完整率计算 |
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| 图２ 风速的单日变化曲线 |
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| 图３ 风速的月变化曲线 |
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| 图４ 风速的昼夜变化曲线 |
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| 表２ 海上风资源昼夜分布参数 |
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| 图５ Charnock模型对于风速垂直变化的拟合结果 |
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| 图６ Smith模型对于风速垂直变化的拟合结果 |
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| 表３ 不同风廓线拟合方法的均方根误差 |
参考文献:
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