Abstract
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.
Highlights
The prediction of solar radiation has a significant role in several fields such as photovoltaic (PV) power production and micro grid management
In the objective to improve the accuracy of solar radiation prediction, we propose a combination of two models, Auto Regressive Moving Average (ARMA) and one type of Dynamic Neural Network (DNN)
A novel hybrid model composed of ARMA and Nonlinear Auto Regressive with eXogenous input (NARX) was proposed to predict the weekly solar radiation averages
Summary
The prediction of solar radiation has a significant role in several fields such as photovoltaic (PV) power production and micro grid management. PV power production is mainly based on solar radiation, it is completely absent at night and available during the day, it is low in winter and high in summer and for the same day it is likely to be fluctuating because it is influenced by some weather conditions. This is the cause of PV power production intermittence which causes several problems when integrating the micro grid [5]. The prediction of solar radiation on a given time is based on the created model
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