The Performance Assessment of Six Global Horizontal Irradiance Clear Sky Models in Six Climatological Regions in South Africa

• Published in: Energies (Basel) Vol. 14; no. 9; p. 2583
• Main Authors: Mabasa, Brighton, Lysko, Meena D., Tazvinga, Henerica, Zwane, Nosipho, Moloi, Sabata J.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-05-2021
• Subjects: Accuracy; Atmosphere; Birds; clear sky model; Climate; Climate models; climatological regions; Clouds; Confidence; Datasets; European Organization for the Exploitation of Meteorological Satellites (EUMETSAT)’s Satellite Application Facility on Climate Monitoring (CM SAF); global horizontal irradiance; Irradiance; Mathematical models; Meteorological services; Performance assessment; performance evaluation; Quality control; Radiation; Sensors; Sky models; Solar energy; solar energy applications; Australia; Singapore
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en14092583

This study assesses the performance of six global horizontal irradiance (GHI) clear sky models, namely: Bird, Simple Solis, McClear, Ineichen–Perez, Haurwitz and Berger–Duffie. The assessment is performed by comparing 1-min model outputs to corresponding clear sky reference 1-min Baseline Surface Radiation Network quality controlled GHI data from 13 South African Weather Services radiometric stations. The data used in the study range from 2013 to 2019. The 13 reference stations are across the six macro climatological regions of South Africa. The aim of the study is to identify the overall best performing clear sky model for estimating minute GHI in South Africa. Clear sky days are detected using ERA5 reanalysis hourly data and the application of an additional 1-min automated detection algorithm. Metadata for the models’ inputs were sourced from station measurements, satellite platform observations, reanalysis and some were modelled. Statistical metrics relative Mean Bias Error (rMBE), relative Root Mean Square Error (rRMSE) and the coefficient of determination (R2) are used to categorize model performance. The results show that each of the models performed differently across the 13 stations and in different climatic regions. The Bird model was overall the best in all regions, with an rMBE of 1.87%, rRMSE of 4.11% and R2 of 0.998. The Bird model can therefore be used with quantitative confidence as a basis for solar energy applications when all the required model inputs are available.