Solar Radiation Modeling with Adaptive Approach
Year 2019,
Volume: 3 Issue: 2, 110 - 115, 10.10.2019
Emre Akarslan
,
Fatih Onur Hocaoglu
Abstract
The unsustainable formation of fossil fuels, increase the
interest on different resources and this
leads to greater emphasis on clean resources. Solar energy is one of the
popular sources among the renewables. Electricity generation from PV panels
directly related to the solar radiation value measured on surface of the panel.
Modeling of solar radiation is important due to manage the integration of
different sources to the grid. In this study, previously developed Adaptive
Approach method is used for modeling the solar radiation values. This method
combines linear prediction filter method with an empiric approach. Linear
prediction filter used in this study utilize the current value of the solar
radiation to predict next hour’s solar radiation value while the empiric
model utilize from the current value of the solar radiation and the deviation
on extraterrestrial radiation. One year solar radiation data belong to Van
region is used in this study. The accuracies of the forecasting results are
compared and discussed.
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Year 2019,
Volume: 3 Issue: 2, 110 - 115, 10.10.2019
Emre Akarslan
,
Fatih Onur Hocaoglu
References
- [1]. K. Benmouiza and A. Cheknane, “Forecasting hourly global solar radiation using hybrid k-means and nonlinear autoregressive neural network models,” Energy Convers. Manag., vol. 75, pp. 561–569, Nov. 2013.
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- [3]. Y. Kashyap, A. Bansal, and A. K. Sao, “Solar radiation forecasting with multiple parameters neural networks,” Renew. Sustain. Energy Rev., vol. 49, pp. 825–835, Sep. 2015.
- [4]. Y. Gala, Á. Fernández, J. Díaz, and J. R. Dorronsoro, “Hybrid machine learning forecasting of solar radiation values,” Neurocomputing, vol. 176, pp. 48–59, May 2015.
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