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Estimation of solar photovoltaic efficiency under the urban heat island effect

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  • Han, Jen-Yu
  • Li, Sin-Yi
  • Chen, Yi-Chien

Abstract

Onsite renewable energy supply is a crucial aspect of nearly zero-energy buildings (NZEBs). Understanding the amount and trend of potential electricity generation from local renewable sources is essential for planning and designing NZEBs. Given the urban heat island (UHI) effect, where temperatures are higher in urban areas than in less developed surroundings, the energy generated in urban areas may be lower than in rural areas as the conversion efficiency of solar cells decreases with increasing temperature. This research investigates the impact of the UHI effect on solar photovoltaic (PV) efficiency in densely built urban areas. The study integrates satellite-based solar irradiance data with local temperature measurements to account for thermal effects on PV efficiency. A random forest regressor was employed to model the nonlinear interactions between land cover variables—such as building density, vegetation, and road surface—and solar energy potential. Sensitivity analysis reveals that building height and density negatively affect solar energy generation. Notably, urban areas exhibit increased solar potential during winter as temperatures decrease. The findings underscore the importance of land composition in optimizing solar energy generation, with implications for promoting NZEBs in urban environments. This study offers insights into how urban morphology and regional climate variations influence solar efficiency.

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  • Han, Jen-Yu & Li, Sin-Yi & Chen, Yi-Chien, 2025. "Estimation of solar photovoltaic efficiency under the urban heat island effect," Renewable Energy, Elsevier, vol. 242(C).
    • Handle: RePEc:eee:renene:v:242:y:2025:i:c:s0960148125001545
    DOI: 10.1016/j.renene.2025.122492
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    1. Mohsin Ramzan & Zulfiqar Ahmad Saqib & Ejaz Hussain & Junaid Aziz Khan & Abid Nazir & Muhammad Yousif Sardar Dasti & Saqib Ali & Nabeel Khan Niazi, 2022. "Remote Sensing-Based Prediction of Temporal Changes in Land Surface Temperature and Land Use-Land Cover (LULC) in Urban Environments," Land, MDPI, vol. 11(9), pages 1-19, September.
    2. Villemin, Thomas & Claverie, Rémy & Sawicki, Jean-Paul & Parent, Gilles, 2022. "Thermal characterization of a photovoltaic panel under controlled conditions," Renewable Energy, Elsevier, vol. 198(C), pages 28-40.
    3. Freitas, S. & Catita, C. & Redweik, P. & Brito, M.C., 2015. "Modelling solar potential in the urban environment: State-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 915-931.
    4. Pan, Wei & Pan, Mi, 2019. "Opportunities and risks of implementing zero-carbon building policy for cities: Hong Kong case," Applied Energy, Elsevier, vol. 256(C).
    5. Han, Jen-Yu & Vohnicky, Petr, 2022. "An optimized approach for mapping solar irradiance in a mid-low latitude region based on a site-adaptation technique using Himawari-8 satellite imageries," Renewable Energy, Elsevier, vol. 187(C), pages 603-617.
    6. Zhang, Yuhu & Ren, Jing & Pu, Yanru & Wang, Peng, 2020. "Solar energy potential assessment: A framework to integrate geographic, technological, and economic indices for a potential analysis," Renewable Energy, Elsevier, vol. 149(C), pages 577-586.
    7. Zhu, Rui & Wong, Man Sing & You, Linlin & Santi, Paolo & Nichol, Janet & Ho, Hung Chak & Lu, Lin & Ratti, Carlo, 2020. "The effect of urban morphology on the solar capacity of three-dimensional cities," Renewable Energy, Elsevier, vol. 153(C), pages 1111-1126.
    8. Walch, Alina & Castello, Roberto & Mohajeri, Nahid & Scartezzini, Jean-Louis, 2020. "Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty," Applied Energy, Elsevier, vol. 262(C).
    9. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    10. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
    11. M. M. Hasan & Shakhawat Hossain & M. Mofijur & Zobaidul Kabir & Irfan Anjum Badruddin & T. M. Yunus Khan & Esam Jassim, 2023. "Harnessing Solar Power: A Review of Photovoltaic Innovations, Solar Thermal Systems, and the Dawn of Energy Storage Solutions," Energies, MDPI, vol. 16(18), pages 1-30, September.
    12. Narvaez, Gabriel & Giraldo, Luis Felipe & Bressan, Michael & Pantoja, Andres, 2021. "Machine learning for site-adaptation and solar radiation forecasting," Renewable Energy, Elsevier, vol. 167(C), pages 333-342.
    13. Andrea Saltelli, 2002. "Sensitivity Analysis for Importance Assessment," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 579-590, June.
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