Optimizing Solar Potential Analysis in Cuba: A Methodology for High-Resolution Regional Mapping

Javier Domínguez (), Carlo Bellini, Ana María Martín and Luis F. Zarzalejo ()
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Javier Domínguez: Renewable Energies Division, Centre for Energy, Environmental and Technological Research (CIEMAT), 28040 Madrid, Spain
Carlo Bellini: Department of Industrial Engineering, University of Padova, 35131 Padova, Italy
Ana María Martín: Renewable Energies Division, Centre for Energy, Environmental and Technological Research (CIEMAT), 28040 Madrid, Spain
Luis F. Zarzalejo: Renewable Energies Division, Centre for Energy, Environmental and Technological Research (CIEMAT), 28040 Madrid, Spain

Sustainability, 2024, vol. 16, issue 18, 1-19

Abstract: The development of solar energy at a regional scale necessitates a thorough understanding of available resources. Cuba, facing prolonged economic, environmental, and energy crises, urgently needs to enhance its sustainability through solar energy. Although solar resource mapping is widespread, Cuba lacks extensive field measurements, often relying on models that may not be ideally suited for large regions, like Matanzas province. Spanning over 12,000 km² with nearly 150 km between its northern and southern extremes, Matanzas presents challenges for high-resolution solar mapping. This study introduces a methodology that integrates various methods and databases to achieve the maximum resolution in the resulting solar map. This approach is designed for large areas, where conventional high-resolution models fall short. By optimizing calculation times and parameterizing the entire surface latitudinally, a high-resolution solar resource map for Matanzas has been developed. This map significantly enhances the understanding of solar resources in Cuba and enables the proposal of new methodologies for analyzing solar potential in similarly large regions.

Keywords: solar mapping; GIS; solar resources; solar radiation; renewable energies; rural electrification; sustainable development; high-resolution models (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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