<> "The repository administrator has not yet configured an RDF license."^^ .
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"PV power forecast using a nonparametric PV model"^^ .
"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%."^^ .
"2015-05" .
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"115" .
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"Elsevier"^^ .
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"Solar Energy"^^ .
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"0038092X" .
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"Marcelo Pinho"^^ .
"Almeida"^^ .
"Marcelo Pinho Almeida"^^ .
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"Luis"^^ .
"Narvarte Fernández"^^ .
"Luis Narvarte Fernández"^^ .
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"Oscar"^^ .
"Perpiñan Lamigueiro"^^ .
"Oscar Perpiñan Lamigueiro"^^ .
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"PV power forecast using a nonparametric PV model (PDF)"^^ .
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"Pinho_Perpinan_ea2014.pdf"^^ .
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"PV power forecast using a nonparametric PV model (Other)"^^ .
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"PV power forecast using a nonparametric PV model (Other)"^^ .
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"lightbox.jpg"^^ .
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"PV power forecast using a nonparametric PV model (Other)"^^ .
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"preview.jpg"^^ .
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"PV power forecast using a nonparametric PV model (Other)"^^ .
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"medium.jpg"^^ .
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"PV power forecast using a nonparametric PV model (Other)"^^ .
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