The role of clouds in improving the regression model for hourly values of diffuse solar radiation

Furlan, Claudia; Oliveira, Amauri Pereira de; Soares, Jacyra Ramos; Codato, Georgia; Escobedo, João Francisco

doi:10.1016/j.apenergy.2011.10.032

Cited by 105 publications

(59 citation statements)

References 70 publications

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“…Existen modelos empíricos (Gilani et al, 2011;Noorian, Moradi, & Kamali, 2008;Pandey & Soupir, 2012;Spokas & Forcella,Frank, 2006), métodos estadísticos (Ji, Chan, Loh, & Chen, 2009;Reikard, 2009), basados en regresión lineal y no lineal (Elminir, Azzam, & Younes, 2007;Furlan, De Oliveira, Soares, Codato, & Escobedo, 2012) y métodos basados en técnicas de inteligencia artificial (Sfetsos & Coonick, 2000), donde las Redes Neuronales Artificiales son las más utilizadas (Cao & Lin, 2008;Hernández-Travieso, Travieso, Alonso, & Dutta, 2014;Khatib, Mohamed, Sopian, & Mahmoud, 2012;Mellit, Eleuch, Benghanem, Elaoun, & Pavan, 2010;Sayago, Bocco, Ovando, & Willington, 2011). Muchos de estos métodos modelan la radiación solar a partir de diferentes variables y parámetros disponibles, desde los más simples que utilizan parámetros geográficos (latitud, longitud, altitud, etc.)…”

Section: Introductionunclassified

Estimación De Radiación Solar Horaria Utilizando Modelos Empíricos Y Redes Neuronales Artificiales.

Jimenez

Will

Rodríguez

2017

Ciencia Y Tecnología

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iii ResumenLa radiación solar es uno de los parámetros más importantes para el desarrollo de aplicaciones e investigaciones relacionadas a energías renovables. Sin embargo, la adquisición de mediciones de radiación solar no siempre es posible por diferentes motivos y es necesario contar con modelos que permitan estimarla. Estos modelos en su mayoría utilizan variables climáticas difíciles de medir y que no siempre están disponibles en todos los sitios. El objetivo de este trabajo es aplicar un método para estimar radiación solar horaria, basado en redes neuronales, utilizando como variables de entrada estimaciones de radiación solar obtenidas mediante un modelo matemático simple y variables climáticas de fácil adquisición: Temperatura, Presión y Humedad. Además, para comprobar que las redes neuronales son más adecuadas en estos casos se hizo una comparativa con estimaciones realizadas con regresión lineal. Los modelos generados fueron ajustados y validados con datos provenientes de cinco estaciones meteorológicas de la provincia de Tucumán, Argentina, logrando obtener en promedio un error de 11.0% (Root Mean Squared Error) con regresión lineal y 7.84% con redes neuronales.

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Section: Introductionunclassified

Estimación De Radiación Solar Horaria Utilizando Modelos Empíricos Y Redes Neuronales Artificiales.

Jimenez

Will

Rodríguez

2017

Ciencia Y Tecnología

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“…The reduced version of the two-parameter model of Reindl, Beckman and Duffie [3] is presented in Figure 3. Not classifiable as one-or two-parameter model is the noteworthy approach by Furlan et al [22] who developed a multi-parameter regression model for data from Sao Paolo, Brazil. Another important contribution was achieved by the model by Perez and Ineichen [23], which features a dynamic time-series approach to model the direct normal from the global irradiance based on the DISC model by Maxwell [10].…”

Section: Presentation Of Existing Modelsmentioning

confidence: 99%

A New Model for Estimating the Diffuse Fraction of Solar Irradiance for Photovoltaic System Simulations

Hofmann

Seckmeyer

2017

Energies

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Abstract:We present a new model for the calculation of the diffuse fraction of the global solar irradiance for solar system simulations. The importance of an accurate estimation of the horizontal diffuse irradiance is highlighted by findings that an inaccurately calculated diffuse irradiance can lead to significant over-or underestimations in the annual energy yield of a photovoltaic (PV) system by as much as 8%. Our model utilizes a time series of global irradiance in one-minute resolution and geographical information as input. The model is validated by measurement data of 28 geographically and climatologically diverse locations worldwide with one year of one-minute data each, taken from the Baseline Surface Radiation Network (BSRN). We show that on average the mean absolute deviation of the modelled and the measured diffuse irradiance is reduced from about 12% to about 6% compared to three reference models. The maximum deviation is less than 20%. In more than 80% of the test cases, the deviation is smaller 10%. The root mean squared error (RMSE) of the calculated diffuse fractions is reduced by about 18%.

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“…Due to the variability of sky cover conditions in Botucatu was considered only the isotropic behaviour given by equation 12 (CHWIEDUK, 2009;ESCOBEDO et al, 2009;FURLAN et al, 2012;), which in turn is dependent on surface albedo (α) considered as 0.23 for reference crop.…”

Section: Site and Measurementsmentioning

confidence: 99%

“…This is due to the costs involved in the acquisition and maintenance of specific instruments for measuring of attenuation and/or spectral components, thus justifying the existence of few solar radiometry stations installed in Brazil (CODATO et al, 2008;ESCOBEDO et al, 2009;VIANA et al, 2011;FURLAN et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

An Assessment of the Diffuse Radiation Models for Prediction on Hourly Global Radiation in Tilted Surface

Escobedo¹,

Souza²,

Martins³

2014

NATIVA

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ABSTRACT:The total solar irradiation incident on a tilted surface consists in three components including: direct, diffuse and reflected from the ground. The reflected radiation has a small effect and the direct radiation can be calculated with an isotropic model. The most difficulty depends on diffuse radiation by circumsolar variations, horizontal brightness, isotropic and anisotropic subcomponents. This study evaluated the influence of diffuse radiation estimate by different models for obtaining the incident global radiation on tilted surfaces at 12. [MI], that are indicated as the best models for estimating the diffuse radiation in the geographic and climatic local conditions. The increase of the inclination angle provides increased scattering between measured and estimated. The largest variations in the statistical residues were found for atmospheric transmissivity coefficients less than 0.15 and the best estimates occurred of cloudy skies due the low energy levels. Keywords: atmospheric transmissivity, statistical index, parameterized models. AVALIAÇÃO DE MODELOS DE

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The role of clouds in improving the regression model for hourly values of diffuse solar radiation

Cited by 105 publications

References 70 publications

Estimación De Radiación Solar Horaria Utilizando Modelos Empíricos Y Redes Neuronales Artificiales.

Estimación De Radiación Solar Horaria Utilizando Modelos Empíricos Y Redes Neuronales Artificiales.

A New Model for Estimating the Diffuse Fraction of Solar Irradiance for Photovoltaic System Simulations

An Assessment of the Diffuse Radiation Models for Prediction on Hourly Global Radiation in Tilted Surface

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