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Day-Ahead Hourly Forecasting of Power Generation from Photovoltaic Plants

Authors :
Gigoni, Lorenzo
Betti, Alessandro
Crisostomi, Emanuele
Franco, Alessandro
Tucci, Mauro
Bizzarri, Fabrizio
Mucci, Debora
Source :
IEEE Transactions of Sustainable Energy, Vol. 9, Issue 2, pp. 831 - 842 (2018)
Publication Year :
2019

Abstract

The ability to accurately forecast power generation from renewable sources is nowadays recognised as a fundamental skill to improve the operation of power systems. Despite the general interest of the power community in this topic, it is not always simple to compare different forecasting methodologies, and infer the impact of single components in providing accurate predictions. In this paper we extensively compare simple forecasting methodologies with more sophisticated ones over 32 photovoltaic plants of different size and technology over a whole year. Also, we try to evaluate the impact of weather conditions and weather forecasts on the prediction of PV power generation.<br />Comment: Preprint of IEEE Transactions of Sustainable Energy, Vol. 9, Issue 2, pp. 831 - 842 (2018)

Details

Database :
arXiv
Journal :
IEEE Transactions of Sustainable Energy, Vol. 9, Issue 2, pp. 831 - 842 (2018)
Publication Type :
Report
Accession number :
edsarx.1903.06800
Document Type :
Working Paper
Full Text :
https://doi.org/10.1109/TSTE.2017.2762435