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Estimation of 5-min time-step data of tilted solar global irradiation using ANN (Artificial Neural Network) model

Author

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  • Dahmani, Kahina
  • Dizene, Rabah
  • Notton, Gilles
  • Paoli, Christophe
  • Voyant, Cyril
  • Nivet, Marie Laure

Abstract

Converting measured horizontal global solar irradiance in tilted ones is a difficult task, particularly for a small time-step and for not-averaged data. Conventional methods (statistical, correlation, …) are not always efficient with time-step less than one hour; thus, we want to know if an ANN (Artificial Neural Network) is able to realize this conversion with a good accuracy when applied to 5-min solar radiation data of Bouzareah, Algeria. The ANN is developed and optimized using two years of solar data; the nRMSE (relative root means square error) is around 8% for the optimal configuration, which corresponds to a very good accuracy for such a short time-step.

Suggested Citation

  • Dahmani, Kahina & Dizene, Rabah & Notton, Gilles & Paoli, Christophe & Voyant, Cyril & Nivet, Marie Laure, 2014. "Estimation of 5-min time-step data of tilted solar global irradiation using ANN (Artificial Neural Network) model," Energy, Elsevier, vol. 70(C), pages 374-381.
    • Handle: RePEc:eee:energy:v:70:y:2014:i:c:p:374-381
    DOI: 10.1016/j.energy.2014.04.011
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