Short term solar radiation forecasting: Island versus continental sites

John Boland (1) , Mathieu David (2) , Philippe Lauret (2)

1 University of South Australia [Adelaide]
2 PIMENT - Physique et Ingénierie Mathématique pour l'Énergie, l'environnemeNt et le bâtimenT

Due its intermittency, the large-scale integration of solar energy into electricity grids is an issue and more specifically in an insular context. Thus, forecasting the output of solar energy is a key feature to efficiently manage the supply-demand balance. In this paper, three short term forecasting procedures are applied to island locations in order to see how they perform in situations that are potentially more volatile than continental locations. Two continental locations, one coastal and one inland are chosen for comparison. At the two time scales studied, ten minute and hourly, the island locations prove to be more difficult to forecast, as shown by larger forecast errors. It is found that the three methods, one purely statistical combining Fourier series plus linear ARMA models, one combining clear sky index models plus neural net models, and a third using a clear sky index plus ARMA, give similar forecasting results. It is also suggested that there is great potential of merging modelling approaches on different horizons.

Mots clés: Fourier series; ARMA; Artificial neural nets; Insular locations; Solar forecasting

Domaines: Systèmes désordonnés et réseaux de neurones [cond-mat.dis-nn]

John Boland, Mathieu David, Philippe Lauret. Short term solar radiation forecasting: Island versus continental sites. Energy, 2016, 113, ⟨10.1016/j.energy.2016.06.139⟩. ⟨hal-01352228⟩