南部非洲辐照度数据的自动化质量控制与综合分析

Pub Date : 2023-10-30 DOI:10.3390/solar3040032
Francisca Muriel Daniel-Durandt, Arnold Johan Rix
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引用次数: 0

摘要

对大型辐照度数据集的质量控制进行了审查,作为南部非洲大学辐射测量网络(SAURAN)数据库的一个案例研究。质量控制程序是自动化的,并应用于数据库中的24个站点,总共有848,189个小时数据点。在此基础上,分析了各台站的数据质量。评估验证了自动化方法,而不需要基于用户的数据审查。SAURAN数据库可以在推进太阳能和风能方面发挥重要作用;然而,离线站点的数量阻碍了这一进程。数据缺乏仍然是实现这些目标的障碍,因此,本文提出了解决这一问题的建议。提出了关于每个站点在时间序列和离散应用中的可用性的建议,这提供了SAURAN数据库辐照度测量质量的总体指示。在评估的24个测量站中,8个建议使用,11个建议谨慎使用,5个建议非常谨慎使用。这些建议基于多个因素,例如数据集是否有超过一年的数据,或者缺少最小的数据点。在此基础上,对台站辐照度相关性进行了研究。结果表明,不同站点的分组显示出高度相关的辐照度测量和相似的天气模式。如果拟议的可再生能源发电厂(如PV)属于一个集群,如果没有可用的数据,则可以使用SAURAN数据库的数据作为替代,那么这是有用的。SAURAN为南部非洲提供了一个机会来增加其在太阳能和风能方面的研究产出,并减少其对基于化石燃料的能源生产的依赖。
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Automating Quality Control of Irradiance Data with a Comprehensive Analysis for Southern Africa
A review of quality control for large irradiance datasets is applied as a case study for the Southern African Universities Radiometric Network (SAURAN) database. The quality control procedure is automated and applied to 24 stations from the database with a total of 848,189 hourly datapoints. From this, the individual station’s data quality is also analysed. The assessment validates the automated methodology without the need for a user-based review of the data. The SAURAN database can play a significant role in advancing solar and wind energy; however, the number of offline stations hinders this process. Data scarcity remains an obstacle to these goals, and therefore, recommendations are provided to address this. Recommendations regarding each site’s usability in time-series and discrete applications are made, which provides an overall indication of the SAURAN database’s irradiance measurement quality. Of the 24 measuring stations assessed, eight are recommended, 11 are recommended with cautious use, and five are recommended with extremely cautious use. These recommendations are based on multiple factors, such as whether a dataset has more than one full year of data or is missing minimal datapoints. Further, a study of the irradiance correlation between the stations was conducted. The results indicated groupings of different stations that showed highly correlated irradiance measurements and similar weather patterns. This is useful if a proposed renewable energy power plant, such as PV, falls within a cluster where the data from the SAURAN database can be used as a substitute if no data is available. SAURAN presents an opportunity for Southern Africa to increase its research outputs in solar and wind energy and lessen its dependency on fossil fuel-based energy production.
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