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Assessing the Impact of Solar Spectral Variability on the Performance of Photovoltaic Technologies Across European Climates

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  • Ivan Bevanda

    (Faculty of Mechanical Engineering, Computing and Electrical Engineering, University of Mostar, Matice hrvatske b.b., 88 000 Mostar, Bosnia and Herzegovina)

  • Petar Marić

    (Faculty of Mechanical Engineering, Computing and Electrical Engineering, University of Mostar, Matice hrvatske b.b., 88 000 Mostar, Bosnia and Herzegovina)

  • Ante Kristić

    (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Ruđera Boškovića 32, 21 000 Split, Croatia)

  • Tihomir Betti

    (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Ruđera Boškovića 32, 21 000 Split, Croatia)

Abstract

Precise photovoltaic (PV) performance modeling is essential for optimizing system design, operational monitoring, and reliable power forecasting—yet spectral correction is often overlooked, despite its significant impact on energy yield uncertainty. This study employs the FARMS-NIT model to assess the impact of spectral irradiance on eight PV technologies across 79 European sites, grouped by Köppen–Geiger climate classification. Unlike previous studies limited to clear-sky or single-site analysis, this work integrates satellite-derived spectral data for both all-sky and clear-sky scenarios, enabling hourly, tilt-optimized simulations that reflect real-world operating conditions. Spectral analyses reveal European climates exhibit blue-shifted spectra versus AM1.5 reference, only 2–5% resembling standard conditions. Thin-film technologies demonstrate superior spectral gains under all-sky conditions, though the underlying drivers vary significantly across climatic regions—a distinction that becomes particularly evident in the clear-sky analysis. Crystalline silicon exhibits minimal spectral sensitivity (<1.6% variations), with PERC/PERT providing highest stability. CZTSSe shows latitude-dependent performance with ≤0.7% variation: small gains at high latitudes and losses at low latitudes. Atmospheric parameters were analyzed in detail, revealing that air mass (AM), clearness index (K t ), precipitable water (W), and aerosol optical depth (AOD) play key roles in shaping spectral effects, with different parameters dominating in distinct climate groups.

Suggested Citation

  • Ivan Bevanda & Petar Marić & Ante Kristić & Tihomir Betti, 2025. "Assessing the Impact of Solar Spectral Variability on the Performance of Photovoltaic Technologies Across European Climates," Energies, MDPI, vol. 18(14), pages 1-24, July.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:14:p:3868-:d:1706008
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    References listed on IDEAS

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    1. Daxini, Rajiv & Wu, Yupeng, 2024. "Review of methods to account for the solar spectral influence on photovoltaic device performance," Energy, Elsevier, vol. 286(C).
    2. Daxini, Rajiv & Wilson, Robin & Wu, Yupeng, 2023. "Modelling the spectral influence on photovoltaic device performance using the average photon energy and the depth of a water absorption band for improved forecasting," Energy, Elsevier, vol. 284(C).
    3. Conde, Luis A. & Angulo, José R. & Sevillano-Bendezú, Miguel Á. & Nofuentes, Gustavo & Töfflinger, Jan A. & de la Casa, Juan, 2021. "Spectral effects on the energy yield of various photovoltaic technologies in Lima (Peru)," Energy, Elsevier, vol. 223(C).
    4. Kinsey, Geoffrey S. & Riedel-Lyngskær, Nicholas C. & Miguel, Alonso-Abella & Boyd, Matthew & Braga, Marília & Shou, Chunhui & Cordero, Raul R. & Duck, Benjamin C. & Fell, Christopher J. & Feron, Sarah, 2022. "Impact of measured spectrum variation on solar photovoltaic efficiencies worldwide," Renewable Energy, Elsevier, vol. 196(C), pages 995-1016.
    5. Daxini, Rajiv & Sun, Yanyi & Wilson, Robin & Wu, Yupeng, 2022. "Direct spectral distribution characterisation using the Average Photon Energy for improved photovoltaic performance modelling," Renewable Energy, Elsevier, vol. 201(P1), pages 1176-1188.
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