Comparative study of nonparametric and parametric PV models to forecast AC power output of PV plants
Fecha
2015Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Contribución a congreso / Biltzarrerako ekarpena
Versión
Versión publicada / Argitaratu den bertsioa
Impacto
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nodoi-noplumx
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Resumen
In this paper, a comparison between two approaches to predict the AC power output of PV systems is carried out in terms of forecast performance. Each approach uses one of the two main types of PV modeling, parametric and nonparametric, and both use as inputs several forecasts of meteorological variables from a Numerical Weather Prediction model. Furthermore, actual AC power measurements of a PV p ...
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In this paper, a comparison between two approaches to predict the AC power output of PV systems is carried out in terms of forecast performance. Each approach uses one of the two main types of PV modeling, parametric and nonparametric, and both use as inputs several forecasts of meteorological variables from a Numerical Weather Prediction model. Furthermore, actual AC power measurements of a PV plant are used to train the nonparametric model, to adjust the parameters of the different PV components models used in the parametric approach and to assess the quality of the forecasts. The approaches presented similar behavior, although the nonparametric approach, based on Quantile Regression Forests, showed smaller biased errors due to the machine learning tool used. [--]
Materias
PV output power forecast,
Numerical weather prediction,
Parametric PV model,
Nonparametric PV model
Editor
EU PVSEC
Notas
Trabajo presentado a la 31st European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC). Hamburgo, 2015.Incluye póster
Departamento
Universidad Pública de Navarra. Departamento de Ingeniería Eléctrica y Electrónica /
Nafarroako Unibertsitate Publikoa. Ingeniaritza Elektrikoa eta Elektronikoa Saila
Versión del editor
Entidades Financiadoras
This work has been partially financed by the Seventh Framework Programme of the European Commission with the Project Photovoltaic Cost Reduction, Reliability, Operational Performance, Prediction and Simulation (PVCROPS—Grant Agreement No. 308468).