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Sevillano, M., (2023). New insights on the empirical predictability of spectral indicators for PV performance [Pontificia Universidad Católica del Perú]. http://hdl.handle.net/20.500.12404/26169
Sevillano, M., New insights on the empirical predictability of spectral indicators for PV performance []. PE: Pontificia Universidad Católica del Perú; 2023. http://hdl.handle.net/20.500.12404/26169
@phdthesis{sunedu/3574657,
title = "New insights on the empirical predictability of spectral indicators for PV performance",
author = "Sevillano Bendezú, Miguel Ángel",
publisher = "Pontificia Universidad Católica del Perú",
year = "2023"
}
Title: New insights on the empirical predictability of spectral indicators for PV performance
Authors(s): Sevillano Bendezú, Miguel Ángel
Advisor(s): Palomino Töfflinger, Jan Amaru
OCDE field: https://purl.org/pe-repo/ocde/ford#1.03.00
Issue Date: 13-Oct-2023
Institution: Pontificia Universidad Católica del Perú
Abstract: La estimación precisa de la energía fotovoltaica producida es fundamental para las decisiones
comerciales en el marco de inversiones a largo plazo en proyectos fotovoltaicos. El rendimiento
de la energía fotovoltaica se ve afectado por las condiciones locales epecíficas. La variabilidad
de la distribución espectral después de la temperatura y la irradiación es una condición del sitio
que afecta las estimaciones de rendimiento energético. Uno de los desafíos al evaluar el
impacto de la variabilidad espectral es reducir la complejidad del cálculo. Esto implica realizar
una estimación precisa y rápida del impacto espectral con la mínima información requerida a
priori. Con este fin, la presente tesis busca analizar las interrelaciones entre los indicadores
espectrales energéticos dependientes e independientes del dispositivo fotovoltaico con datos
espectrales de varios climas y latitudes en todo el mundo. Debido al enfoque reduccionista que
proveen los indicadores espectrales, analizamos la dependencia de la distribución espectral
representada por la energía fotónica promedio con la latitud en diferentes escalas de tiempo
mensuales y anuales. Al analizar los indicadores espectrales dependientes del dispositivo, se
destaca el Spectral mismatch factor, que exhibe una relación lineal global con el la energía
fotónica promedio en una escala mensual. El análisis exhaustivo de esta relación con los datos
espectrales medidos también proporciona un carácter predictivo al permitir el cálculo del
impacto espectral anual a partir de la energía fotónica promedio anual, y por lo tanto tal relación
lineal propone ser un modelo empírico para el cálculo directo y sencillo del impacto espectral
anual. Adicionalmente, analizamos la validez de manera global de dos indicadores espectrales
dependientes del dispositivo, el Spectral Enhancement Factor y el Spectral Average Useful
Fraction para los sitios seleccionados. Con ello se busca ofrecer un catálogo multiclimático
integrado de las interrelaciones de indicadores espectrales en escala de tiempo anual y mensual.
Finalmente, se realizó una validación cualitativa del método propuesto utilizando datos
espectrales sintéticos de la National Solar Radiation Database. Las tendencias de los Spectral
mismatch factor y Average Photon Energy anuales basados en data espectral sintética siguen a
la regresión lineal experimental y por ende, dan una idea de la funcionalidad del método
propuesto, pese a las incertidumbres propias de la data espectral sintética.
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.
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.
Link to repository: http://hdl.handle.net/20.500.12404/26169
Discipline: Física
Grade or title grantor: Pontificia Universidad Católica del Perú. Escuela de Posgrado
Grade or title: Doctor en Física
Juror: Palomino Tofflinger, Jan Amaru; Rodrigo Cruz, Pedro Manuel; Guerra Torres, Jorge Andres
Register date: 13-Oct-2023; 13-Oct-2023
This item is licensed under a Creative Commons License