Digital Accessibility of Solar Energy Variability Through Short-Term Measurements: Data Descriptor

Fernando Venâncio Mucomole (), Carlos Augusto Santos Silva and Lourenço Lázaro Magaia
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Fernando Venâncio Mucomole: CS-OGET—Center of Excellence of Studies in Oil and Gas Engineering and Technology, Faculty of Engineering, Eduardo Mondlane University, Mozambique Avenue Km 1.5, Maputo 257, Mozambique
Carlos Augusto Santos Silva: Department of Mechanical Engineering, Instituto Superior Técnico, University of Lisbon, 1600-214 Lisbon, Portugal
Lourenço Lázaro Magaia: Department of Mathematics and Informatics, Faculty of Sciences, Eduardo Mondlane University, Main Campus No. 3453, Maputo 257, Mozambique

Data, 2025, vol. 10, issue 10, 1-18

Abstract: A variety of factors, such as absorption, reflection, and attenuation by atmospheric elements, influence the quantity of solar energy that reaches the surface of the Earth. This, in turn, impacts photovoltaic (PV) power generation. In light of this, a digital assessment of solar energy variability through short-term measurements was conducted to enhance PV power output. The clear-sky index K t * methodology was employed, effectively eliminating any indications of solar energy obstruction and comparing the measured radiation to the theoretical clear-sky radiation. The solar energy data were gathered in Mozambique, specifically in the southern region at Maputo–1, Massangena, Ndindiza, and Pembe, in the mid-region at Chipera, Nhamadzi, Barue–1, and Barue–2, as well as in the northern region at Nipepe-1, Nipepe-2, Nanhupo-1, Nanhupo-2, and Chomba, over the period from 2005 to 2024, with measurement intervals ranging from 1 to 10 min and 1 h during the measurement campaigns conducted by FUNAE and INAM, with additional data sourced from the PVGIS, Meteonorm, NOAA, and NASA solar databases. The analysis indicates a K t * value with a density approaching 1 for clear days, while intermediate-sky days exhibit characteristics that lie between those of clear and cloudy days. It can be inferred that there exists a robust correlation among sky types, with values ranging from 0.95 to 0.89 per station, alongside correlated energies, which experience a regression with coefficients between 0.79 and 0.95. Based on the analysis of the sample, the region demonstrates significant potential for solar energy utilization, and similar sampling methodologies can be applied in other locations to optimize PV output and other solar energy projects.

Keywords: digital; spatio-temporal; solar energy; accessibility; variability; clear-sky index (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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