Current Status and Future Trends of the Evaluation of Solar Global Irradiation using Soft-Computing-Based Models

Fernando Antonanzas-Torres, Andres Sanz-Garcia, Javier Antonanzas-Torres, Oscar Perpiñán-Lamiguero, Francisco Javier Martínez-de-Pisón-Ascacibar

Forskningsoutput: Kapitel i bok/rapport/konferenshandlingKapitelVetenskaplig

Sammanfattning

Most of the research on estimating Solar Global Irradiation (SGI) is based on the development of parametric models. However, the use of methods based on the use of statistics and machine-learning theories can provide a significant improvement in reducing the prediction errors. The chapter evaluates the performance of different Soft Computing (SC) methods, such as support vector regression and artificial neural networks-multilayer perceptron, in SGI modeling against classical parametric and lineal models. SC methods demonstrate a higher generalization capacity applied to SGI modeling than classic parametric models. As a result, SC models suppose an alternative to satellite-derived models to estimate SGI in near-to-present time in areas in which no pyranometers are installed nearby.
Originalspråkengelska
Titel på gästpublikationSoft Computing Applications for Renewable Energy and Energy Efficiency
RedaktörerMaria del Socorro García Cascales, Juan Miguel Sánchez Lozano, Antonio David Masegosa Arredondo, Carlos Cruz Corona
Antal sidor22
FörlagIGI Global
Utgivningsdatum2015
Sidor1-22
ISBN (tryckt)9781466666313
DOI
StatusPublicerad - 2015
MoE-publikationstypB2 Del av bok eller annan forskningsbok

Vetenskapsgrenar

  • 113 Data- och informationsvetenskap
  • 317 Farmaci

Citera det här

Antonanzas-Torres, F., Sanz-Garcia, A., Antonanzas-Torres, J., Perpiñán-Lamiguero, O., & Martínez-de-Pisón-Ascacibar, F. J. (2015). Current Status and Future Trends of the Evaluation of Solar Global Irradiation using Soft-Computing-Based Models. I M. D. S. G. Cascales, J. M. S. Lozano, A. D. M. Arredondo, & C. C. Corona (Red.), Soft Computing Applications for Renewable Energy and Energy Efficiency (s. 1-22). IGI Global. https://doi.org/10.4018/978-1-4666-6631-3
Antonanzas-Torres, Fernando ; Sanz-Garcia, Andres ; Antonanzas-Torres, Javier ; Perpiñán-Lamiguero, Oscar ; Martínez-de-Pisón-Ascacibar, Francisco Javier. / Current Status and Future Trends of the Evaluation of Solar Global Irradiation using Soft-Computing-Based Models. Soft Computing Applications for Renewable Energy and Energy Efficiency. redaktör / Maria del Socorro García Cascales ; Juan Miguel Sánchez Lozano ; Antonio David Masegosa Arredondo ; Carlos Cruz Corona. IGI Global, 2015. s. 1-22
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abstract = "Most of the research on estimating Solar Global Irradiation (SGI) is based on the development of parametric models. However, the use of methods based on the use of statistics and machine-learning theories can provide a significant improvement in reducing the prediction errors. The chapter evaluates the performance of different Soft Computing (SC) methods, such as support vector regression and artificial neural networks-multilayer perceptron, in SGI modeling against classical parametric and lineal models. SC methods demonstrate a higher generalization capacity applied to SGI modeling than classic parametric models. As a result, SC models suppose an alternative to satellite-derived models to estimate SGI in near-to-present time in areas in which no pyranometers are installed nearby.",
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Antonanzas-Torres, F, Sanz-Garcia, A, Antonanzas-Torres, J, Perpiñán-Lamiguero, O & Martínez-de-Pisón-Ascacibar, FJ 2015, Current Status and Future Trends of the Evaluation of Solar Global Irradiation using Soft-Computing-Based Models. i MDSG Cascales, JMS Lozano, ADM Arredondo & CC Corona (red), Soft Computing Applications for Renewable Energy and Energy Efficiency. IGI Global, s. 1-22. https://doi.org/10.4018/978-1-4666-6631-3

Current Status and Future Trends of the Evaluation of Solar Global Irradiation using Soft-Computing-Based Models. / Antonanzas-Torres, Fernando; Sanz-Garcia, Andres; Antonanzas-Torres, Javier; Perpiñán-Lamiguero, Oscar; Martínez-de-Pisón-Ascacibar, Francisco Javier.

Soft Computing Applications for Renewable Energy and Energy Efficiency. red. / Maria del Socorro García Cascales; Juan Miguel Sánchez Lozano; Antonio David Masegosa Arredondo; Carlos Cruz Corona. IGI Global, 2015. s. 1-22.

Forskningsoutput: Kapitel i bok/rapport/konferenshandlingKapitelVetenskaplig

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AB - Most of the research on estimating Solar Global Irradiation (SGI) is based on the development of parametric models. However, the use of methods based on the use of statistics and machine-learning theories can provide a significant improvement in reducing the prediction errors. The chapter evaluates the performance of different Soft Computing (SC) methods, such as support vector regression and artificial neural networks-multilayer perceptron, in SGI modeling against classical parametric and lineal models. SC methods demonstrate a higher generalization capacity applied to SGI modeling than classic parametric models. As a result, SC models suppose an alternative to satellite-derived models to estimate SGI in near-to-present time in areas in which no pyranometers are installed nearby.

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Antonanzas-Torres F, Sanz-Garcia A, Antonanzas-Torres J, Perpiñán-Lamiguero O, Martínez-de-Pisón-Ascacibar FJ. Current Status and Future Trends of the Evaluation of Solar Global Irradiation using Soft-Computing-Based Models. I Cascales MDSG, Lozano JMS, Arredondo ADM, Corona CC, redaktörer, Soft Computing Applications for Renewable Energy and Energy Efficiency. IGI Global. 2015. s. 1-22 https://doi.org/10.4018/978-1-4666-6631-3