Solar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX

The prediction of solar radiation has a significant role in several fields such as photovoltaic (PV) power production and micro grid management. The interest in solar radiation prediction is increasing nowadays so efficient prediction can greatly improve the performance of these different applicatio...

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Autores principales: Ines Sansa, Zina Boussaada, Najiba Mrabet Bellaaj
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Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/0a1f9f6ce58540ddb47b32f9488e5fc8
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spelling oai:doaj.org-article:0a1f9f6ce58540ddb47b32f9488e5fc82021-11-11T15:45:06ZSolar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX10.3390/en142169201996-1073https://doaj.org/article/0a1f9f6ce58540ddb47b32f9488e5fc82021-10-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/21/6920https://doaj.org/toc/1996-1073The prediction of solar radiation has a significant role in several fields such as photovoltaic (PV) power production and micro grid management. The interest in solar radiation prediction is increasing nowadays so efficient prediction can greatly improve the performance of these different applications. This paper presents a novel solar radiation prediction approach which combines two models, the Auto Regressive Moving Average (ARMA) and the Nonlinear Auto Regressive with eXogenous input (NARX). This choice has been carried out in order to take the advantages of both models to produce better prediction results. The performance of the proposed hybrid model has been validated using a real database corresponding to a company located in Barcelona north. Simulation results have proven the effectiveness of this hybrid model to predict the weekly solar radiation averages. The ARMA model is suitable for small variations of solar radiation while the NARX model is appropriate for large solar radiation fluctuations.Ines SansaZina BoussaadaNajiba Mrabet BellaajMDPI AGarticlesolar radiationPV powerpredictionARMANARXhybrid modelTechnologyTENEnergies, Vol 14, Iss 6920, p 6920 (2021)
institution DOAJ
collection DOAJ
language EN
topic solar radiation
PV power
prediction
ARMA
NARX
hybrid model
Technology
T
spellingShingle solar radiation
PV power
prediction
ARMA
NARX
hybrid model
Technology
T
Ines Sansa
Zina Boussaada
Najiba Mrabet Bellaaj
Solar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX
description The prediction of solar radiation has a significant role in several fields such as photovoltaic (PV) power production and micro grid management. The interest in solar radiation prediction is increasing nowadays so efficient prediction can greatly improve the performance of these different applications. This paper presents a novel solar radiation prediction approach which combines two models, the Auto Regressive Moving Average (ARMA) and the Nonlinear Auto Regressive with eXogenous input (NARX). This choice has been carried out in order to take the advantages of both models to produce better prediction results. The performance of the proposed hybrid model has been validated using a real database corresponding to a company located in Barcelona north. Simulation results have proven the effectiveness of this hybrid model to predict the weekly solar radiation averages. The ARMA model is suitable for small variations of solar radiation while the NARX model is appropriate for large solar radiation fluctuations.
format article
author Ines Sansa
Zina Boussaada
Najiba Mrabet Bellaaj
author_facet Ines Sansa
Zina Boussaada
Najiba Mrabet Bellaaj
author_sort Ines Sansa
title Solar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX
title_short Solar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX
title_full Solar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX
title_fullStr Solar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX
title_full_unstemmed Solar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX
title_sort solar radiation prediction using a novel hybrid model of arma and narx
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/0a1f9f6ce58540ddb47b32f9488e5fc8
work_keys_str_mv AT inessansa solarradiationpredictionusinganovelhybridmodelofarmaandnarx
AT zinaboussaada solarradiationpredictionusinganovelhybridmodelofarmaandnarx
AT najibamrabetbellaaj solarradiationpredictionusinganovelhybridmodelofarmaandnarx
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