Comparative Study of Sky Diffuse Irradiance Models Applied to Photovoltaic Systems

The increasing energy demand and the search for greener energy resources are expanding interests on photovoltaic systems. These systems need an accurate climatic and irradiation data in order to precisely estimate the energy yield of PV systems. However, most of the available irradiance data, are on...

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Bibliographic Details
Published in:2019 International Conference on Smart Energy Systems and Technologies (SEST) pp. 1 - 5
Main Authors: da Silva, Michelle Kitayama, de Melo, Karen Barbosa, Costa, Tatiane Silva, Narvez, Dante Inga, de Bastos Mesquita, Daniel, Villalva, Marcelo Gradella
Format: Conference Proceeding
Language:English
Published: IEEE 01-09-2019
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Summary:The increasing energy demand and the search for greener energy resources are expanding interests on photovoltaic systems. These systems need an accurate climatic and irradiation data in order to precisely estimate the energy yield of PV systems. However, most of the available irradiance data, are only for the horizontal plane. The precise estimation of the total irradiance incident on the surface of photovoltaic modules is one of the most important steps in the performance analysis of PV systems. In order to estimate the irradiance on a tilted surface from the irradiance data on the horizontal plane, there are many models available in the literature, they can be classified in isotropic and anisotropic models. This study aims to access the performance of an isotropic and three anisotropic models, which are used by PV system simulation softwares, and the impact of each of them on the estimated energy generation. The results are compared with measured energy data collected at Politec®, Araçariguama in Brazil. Results showed that positioning the module at the correct tilted angle and facing north can optimise the global irradiance incident on the module's surface. Hay & Davies model presented the lowest Mean Bias Error and Root Mean Squared Error while also showing a correlation coefficient close to 1.
DOI:10.1109/SEST.2019.8849031