喀土穆气象桅杆站历史风速数据集。

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Data in Brief Pub Date : 2024-11-07 eCollection Date: 2024-12-01 DOI:10.1016/j.dib.2024.111115
Abubaker Younis, Hazim Elshiekh, Yassir Yassin, Ali Omer, Elfadil Biraima
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引用次数: 0

摘要

这里展示的数据演示文章展示了喀土穆市2017年6月至8月三个月的风速场记录。这些记录是从位于苏丹国家能源研究中心房地内的SOBA-D161094气象桅杆站获得的。采用双参数威布尔分布,矩量法估计该数据集的尺度和形状参数分别为4.175 m/s和2.099,决定系数为0.975,参见相关文献。利用NASA观测卫星编制的MERRA-2数据库中的空间风速信息验证了数据的准确性,发现地面和遥感数据集之间的均方根误差为0.385。此外,Kolmogorov-Smirnov检验表明,这两个样本来自相同的总体和统计分布。基于威布尔密度函数,风电输送的平均功率为103.45 W,风机可提取的最大平均功率为61.3 W。这项工作的主要目标是以一种格式提供数据,使其能够用作基准或在各种研究工作中重用。特别强调促进风速统计分布模型参数估计的研究。这种方法类似于RTC法国太阳能电池数据集的利用,该数据集通常用于等效电路模型的参数提取。这些数据的附加价值在于,它有可能提供信息,揭示国内风力发电未被认识到的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Historical wind speed dataset of meteorological mast station in Khartoum.

The data demonstration article presented here showcases three months of wind speed field records for Khartoum city from June to August 2017. These records were obtained from the SOBA-D161094 meteorological mast station, located within the premises of the National Energy Research Center of Sudan. Using the two-parameter Weibull distribution, the scale and shape parameters estimated by the method of moments for this dataset were 4.175 m/s and 2.099, respectively, with a coefficient of determination of 0.975, as provided in the associated literature. The accuracy of the data was verified using spatial wind speed information from the MERRA-2 database, compiled by a NASA observation satellite, with a root mean square error between the ground and remote sensing datasets found to be 0.385. Additionally, the Kolmogorov-Smirnov test suggests that the two samples are drawn from the same population and statistical distribution. Based on the Weibull density function, the mean power transported by wind and the maximum mean power that can be extracted by the turbine were 103.45 W and 61.3 W, respectively. The primary objective of this work is to provide the data in a format that enables its use as a benchmark or for reuse in various research endeavors. Special emphasis is placed on facilitating studies related to the parameter estimation of wind speed statistical distribution models. This approach is akin to the utilization of the RTC France solar cell dataset, which is commonly employed for parameter extraction in equivalent circuit models. The added value of this data lies in its potential to provide information that could reveal unrecognized opportunities for the domestic generation of wind power.

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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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