Quality control of solar radiation data within the South African Weather Service solar radiometric network

Author:

Ntsangwane LuckyORCID,Mabasa BrightonORCID,Sivakumar VenkataramanORCID,Zwane NosiphoORCID,Ncongwane KatlegoORCID,Botai JoelORCID

Abstract

This study reports on the performance results of the Baseline Surface Radiation Network (BSRN) quality control procedures applied to the solar radiation data, from September 2013 to December 2017, within the South African Weather Service radiometric network. The overall percentage performance of the SAWS solar radiation network based on BSRN quality control methodology was 97.79%, 93.64%, 91.60% and 92.23% for long wave downward irradiance (LWD), global horizontal irradiance (GHI), diffuse horizontal irradiance (DHI) and direct normal irradiance (DNI), respectively, with operational problems largely dominating the percentage of bad data. The overall average performance of the surface solar radiation dataset – Heliosat data records for the GHI estimation for all stations showed a mean bias deviation of 8.28 Wm-2, a mean absolute deviation of 9.06 Wm-2 and the root mean square deviation of 11.02 Wm-2. The correlation, quantified by the square of correlation coefficient (R2), between ground-based and Heliosat-derived GHI time series was ~0.98. The established network has the potential to provide high quality minute solar radiation data sets (GHI, DHI, DNI and LWD) and auxiliary hourly meteorological parameters vital for scientific and practical applications in renewable energy technologies.

Publisher

Academy of Science of South Africa

Subject

General Energy,General Computer Science

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Predicting surface solar radiation using a hybrid radiative Transfer–Machine learning model;Renewable and Sustainable Energy Reviews;2023-03

2. The Automation of Quality Control for Large Irradiance Datasets;2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME);2022-11-16

3. A Fast Quality Control of 0.5 Hz Temperature Data in China;Frontiers in Earth Science;2022-04-27

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