A Comparative Assessment of Annual Solar Irradiance Trends between Mpumalanga and Northern Cape Province in South Africa Using PVGIS
South Africa has committed to reducing its greenhouse emissions by sixty-five percent by 2030 in their National Integrated Energy Plan (NEIP). The lack of investment and development for renewable energy sources put the country on an uncertain trajectory in fulfilling its 2030 energy commitments. At...
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| Materyal Türü: | Makale |
| Dil: | English |
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MDPI AG
2023-09-01
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| Seri Bilgileri: | Energies |
| Konular: | |
| Online Erişim: | https://www.mdpi.com/1996-1073/16/18/6665 |
| _version_ | 1827726313176170496 |
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| author | Lennox Boateng Paidamwoyo Mhangara |
| author_facet | Lennox Boateng Paidamwoyo Mhangara |
| author_sort | Lennox Boateng |
| collection | DOAJ |
| description | South Africa has committed to reducing its greenhouse emissions by sixty-five percent by 2030 in their National Integrated Energy Plan (NEIP). The lack of investment and development for renewable energy sources put the country on an uncertain trajectory in fulfilling its 2030 energy commitments. At the same time, the country has been labeled as a region with one of the highest solar energy potentials. Provinces such as Mpumalanga and Northern Cape are on opposite ends of the matter, with Northern Cape is one of the leading provinces for renewal energy, while the Mpumalanga province remains the host to eighty-five per cent of the country’s coal plants. Solar energy is an abundant renewable energy source and can be assessed using Geographic Information Systems (GIS) techniques. In this paper, the geostatistical technique, Kriging, is employed to predict, estimate, and compare the regional distribution, potential, and variability of annual optimum solar energy (irradiance) between the Mpumalanga Province and Northern Cape Province. Spot-based radiation data are available for solar energy analyses from the GIS Web-based tool Photovoltaic Geographical Information Systems (PVGIS). Kriging was used to estimate the spatial variability of solar energy at an average error of 1.98505% for the Northern Cape Province and 2.32625% for the Mpumalanga Province. It was identified that the Northern Cape receives the highest annual optimum irradiation and has a low overall spatial variation in irradiation over its provincial area. Mpumalanga receives lesser amounts of irradiation but has high overall spatial variation over its provincial area. Most of Northern Cape’s central to northwestern regions have the highest annual optimum irradiation ranging from 2583 kWh/m<sup>2</sup> to 2638 kWh/m<sup>2</sup>, while Mpumalanga’s highest regions of annual irradiation occur primarily on its western and northwestern parts and ranges in highs of 2345 kWh/m<sup>2</sup> to 2583 kWh/m<sup>2</sup>. |
| first_indexed | 2024-03-10T22:49:15Z |
| format | Article |
| id | doaj.art-7182812e494e4c4dba6aaa4094e882e9 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T22:49:15Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-7182812e494e4c4dba6aaa4094e882e92023-11-19T10:28:23ZengMDPI AGEnergies1996-10732023-09-011618666510.3390/en16186665A Comparative Assessment of Annual Solar Irradiance Trends between Mpumalanga and Northern Cape Province in South Africa Using PVGISLennox Boateng0Paidamwoyo Mhangara1School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg 2050, South AfricaSchool of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg 2050, South AfricaSouth Africa has committed to reducing its greenhouse emissions by sixty-five percent by 2030 in their National Integrated Energy Plan (NEIP). The lack of investment and development for renewable energy sources put the country on an uncertain trajectory in fulfilling its 2030 energy commitments. At the same time, the country has been labeled as a region with one of the highest solar energy potentials. Provinces such as Mpumalanga and Northern Cape are on opposite ends of the matter, with Northern Cape is one of the leading provinces for renewal energy, while the Mpumalanga province remains the host to eighty-five per cent of the country’s coal plants. Solar energy is an abundant renewable energy source and can be assessed using Geographic Information Systems (GIS) techniques. In this paper, the geostatistical technique, Kriging, is employed to predict, estimate, and compare the regional distribution, potential, and variability of annual optimum solar energy (irradiance) between the Mpumalanga Province and Northern Cape Province. Spot-based radiation data are available for solar energy analyses from the GIS Web-based tool Photovoltaic Geographical Information Systems (PVGIS). Kriging was used to estimate the spatial variability of solar energy at an average error of 1.98505% for the Northern Cape Province and 2.32625% for the Mpumalanga Province. It was identified that the Northern Cape receives the highest annual optimum irradiation and has a low overall spatial variation in irradiation over its provincial area. Mpumalanga receives lesser amounts of irradiation but has high overall spatial variation over its provincial area. Most of Northern Cape’s central to northwestern regions have the highest annual optimum irradiation ranging from 2583 kWh/m<sup>2</sup> to 2638 kWh/m<sup>2</sup>, while Mpumalanga’s highest regions of annual irradiation occur primarily on its western and northwestern parts and ranges in highs of 2345 kWh/m<sup>2</sup> to 2583 kWh/m<sup>2</sup>.https://www.mdpi.com/1996-1073/16/18/6665photovoltaic geographical information systemsphotovoltaic technologyrenewable energyoptimum solar irradiationKrigingNorthern Cape |
| spellingShingle | Lennox Boateng Paidamwoyo Mhangara A Comparative Assessment of Annual Solar Irradiance Trends between Mpumalanga and Northern Cape Province in South Africa Using PVGIS Energies photovoltaic geographical information systems photovoltaic technology renewable energy optimum solar irradiation Kriging Northern Cape |
| title | A Comparative Assessment of Annual Solar Irradiance Trends between Mpumalanga and Northern Cape Province in South Africa Using PVGIS |
| title_full | A Comparative Assessment of Annual Solar Irradiance Trends between Mpumalanga and Northern Cape Province in South Africa Using PVGIS |
| title_fullStr | A Comparative Assessment of Annual Solar Irradiance Trends between Mpumalanga and Northern Cape Province in South Africa Using PVGIS |
| title_full_unstemmed | A Comparative Assessment of Annual Solar Irradiance Trends between Mpumalanga and Northern Cape Province in South Africa Using PVGIS |
| title_short | A Comparative Assessment of Annual Solar Irradiance Trends between Mpumalanga and Northern Cape Province in South Africa Using PVGIS |
| title_sort | comparative assessment of annual solar irradiance trends between mpumalanga and northern cape province in south africa using pvgis |
| topic | photovoltaic geographical information systems photovoltaic technology renewable energy optimum solar irradiation Kriging Northern Cape |
| url | https://www.mdpi.com/1996-1073/16/18/6665 |
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