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Minute-Scale Models for the Diffuse Fraction of Global Solar Radiation Balanced between Accuracy and Accessibility
by
Paulescu, Eugenia
, Paulescu, Marius
in
Accuracy
/ clearness index
/ Datasets
/ diffuse fraction
/ diffuse solar irradiance
/ direct normal solar irradiance
/ Energy industry
/ Photovoltaic cells
/ Radiation
/ separation model
/ Solar energy
/ Time series
2023
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Minute-Scale Models for the Diffuse Fraction of Global Solar Radiation Balanced between Accuracy and Accessibility
by
Paulescu, Eugenia
, Paulescu, Marius
in
Accuracy
/ clearness index
/ Datasets
/ diffuse fraction
/ diffuse solar irradiance
/ direct normal solar irradiance
/ Energy industry
/ Photovoltaic cells
/ Radiation
/ separation model
/ Solar energy
/ Time series
2023
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Do you wish to request the book?
Minute-Scale Models for the Diffuse Fraction of Global Solar Radiation Balanced between Accuracy and Accessibility
by
Paulescu, Eugenia
, Paulescu, Marius
in
Accuracy
/ clearness index
/ Datasets
/ diffuse fraction
/ diffuse solar irradiance
/ direct normal solar irradiance
/ Energy industry
/ Photovoltaic cells
/ Radiation
/ separation model
/ Solar energy
/ Time series
2023
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Minute-Scale Models for the Diffuse Fraction of Global Solar Radiation Balanced between Accuracy and Accessibility
Journal Article
Minute-Scale Models for the Diffuse Fraction of Global Solar Radiation Balanced between Accuracy and Accessibility
2023
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Overview
The separation models are tools used in solar engineering to estimate direct normal (DNI) and diffuse horizontal (DHI) solar irradiances from measurements of global solar irradiance (GHI). This paper proposes two empirical separation models that stand out owing to their simple mathematical formulation: a rational polynomial equation. Validation of the new models was carried out against data from 36 locations, covering the four major climatic zones. Five current top minute-scale separation models were considered references. The tests were performed on the final products of the estimation: DNI and DHI. The first model (M1) operates with eight predictors (evaluated from GHI post-processed measurements and clear-sky counterpart estimates) and constantly outperforms the already established models. The second model (M2) operates with three predictors based only on GHI measurements, which gives it a high degree of accessibility. Based on a statistical linear ranking method according to the models’ performance at every station, M1 leads the hierarchy, ranking first in both DNI and DHI estimation. The high accessibility of the M2 does not compromise accuracy; it is proving to be a real competitor in the race with the best-performing current models.
Publisher
MDPI AG
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