LAPSE:2023.32042
Published Article

LAPSE:2023.32042
The Performance Assessment of Six Global Horizontal Irradiance Clear Sky Models in Six Climatological Regions in South Africa
April 19, 2023
Abstract
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.
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.
Record ID
Keywords
clear sky model, climatological regions, Copernicus Atmosphere Monitoring Service Aerosol Optical depth (CAMS-AOD), European Organization for the Exploitation of Meteorological Satellites (EUMETSAT)’s Satellite Application Facility on Climate Monitoring (CM SAF), Fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5), global horizontal irradiance, performance evaluation, solar energy applications, Solar Radiation Data (SoDa), statistical metrics
Suggested Citation
Mabasa B, Lysko MD, Tazvinga H, Zwane N, Moloi SJ. The Performance Assessment of Six Global Horizontal Irradiance Clear Sky Models in Six Climatological Regions in South Africa. (2023). LAPSE:2023.32042
Author Affiliations
Mabasa B: Research & Development Division, South African Weather Service, Pretoria 0001, South Africa; Department of Physics, University of South Africa, UNISA Preller Street, Muckleneuk, Pretoria 0001, South Africa [ORCID]
Lysko MD: Department of Physics, University of South Africa, UNISA Preller Street, Muckleneuk, Pretoria 0001, South Africa; Move Beyond Consulting (Pty) Ltd., Pretoria 0001, South Africa [ORCID]
Tazvinga H: Research & Development Division, South African Weather Service, Pretoria 0001, South Africa [ORCID]
Zwane N: Research & Development Division, South African Weather Service, Pretoria 0001, South Africa
Moloi SJ: Department of Physics, University of South Africa, UNISA Preller Street, Muckleneuk, Pretoria 0001, South Africa
Lysko MD: Department of Physics, University of South Africa, UNISA Preller Street, Muckleneuk, Pretoria 0001, South Africa; Move Beyond Consulting (Pty) Ltd., Pretoria 0001, South Africa [ORCID]
Tazvinga H: Research & Development Division, South African Weather Service, Pretoria 0001, South Africa [ORCID]
Zwane N: Research & Development Division, South African Weather Service, Pretoria 0001, South Africa
Moloi SJ: Department of Physics, University of South Africa, UNISA Preller Street, Muckleneuk, Pretoria 0001, South Africa
Journal Name
Energies
Volume
14
Issue
9
First Page
2583
Year
2021
Publication Date
2021-04-30
ISSN
1996-1073
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Original Submission
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PII: en14092583, Publication Type: Journal Article
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LAPSE:2023.32042
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https://doi.org/10.3390/en14092583
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