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Pinho_Perpinan_ea2014.pdf
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PV power forecast using a nonparametric PV model
PV power forecast using a nonparametric PV model (PDF)
PV power forecast using a nonparametric PV model (Other)
PV power forecast using a nonparametric PV model (Other)
PV power forecast using a nonparametric PV model (Other)
PV power forecast using a nonparametric PV model (Other)
PV power forecast using a nonparametric PV model (Other)
Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%.
115
2015-05
PV power forecast using a nonparametric PV model
Computer Science
Informática
Matemáticas
Mathematics
Energías Renovables
Renewable Energy
Elsevier
Almeida
Marcelo Pinho
Marcelo Pinho Almeida
Narvarte Fernández
Luis
Luis Narvarte Fernández
Perpiñan Lamigueiro
Oscar
Oscar Perpiñan Lamigueiro
0038092X
Solar Energy