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Tesis de la Escuela de Posgrado y de la Escuela de Negocios de CENTRUM Católica

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search.filters.applied.f.advisor: search.filters.advisor.Palomino Töfflinger, Jan AmaruSubject: search.filters.subject.Análisis espectral

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    New insights on the empirical predictability of spectral indicators for PV performance
    (Pontificia Universidad Católica del Perú, 2023-10-13) Sevillano Bendezú, Miguel Ángel; Palomino Töfflinger, Jan Amaru
    Accurate produced PV energy estimation is critical to business decisions under long-term investments in PV on a utility scale. PV energy yield is affected by different sites' specific conditions. The variability of the spectral distribution after temperature and irradiation is a site condition that impacts energy yield estimates. Evaluating the impact of the spectral irradiance distribution on the PV performance generally requires accurate information about the PV device's spectral response and the site’s measured spectra. Detailed spectral and device information may not always be available. This study analyzes the interrelations between device-dependent and device-independent energetic spectral indicators with spectral data from nine sites with different climates and latitudes, aiming to relax the requirement for detailed device and spectral information. First, an apparent correlation of each site's spectral distributions' yearly Average Photon Energy with the corresponding latitude is observed. As the commonly applied device-dependent spectral indicator, it can be observed that the monthly mismatch factors of all nine sites exhibit a global linear relationship with the monthly average photon energies. This linear relationship with measured spectral data provides a predictive character for each PV device technology by allowing the estimation of the annual spectral impact from the annual Average Photon Energy, potentially for any site. This work also analyzes the validity of the Spectral Average Useful Fraction and the Spectral Enhancement Factor as alternative device-dependent spectral indicators. These require average spectra and, thus, would reduce the calculation complexity for spectral indicators. Finally, the proposed method was validated qualitatively using synthetic spectral data from the National Solar Radiation Database. The trends of the scatter plot between the synthetic Spectral Mismatch Factor and the Average Photon Energy that follow the experimental linear regression give an idea of the proposed method's functionality, despite the synthetic data's uncertainties.