PVF-package: Forecast of AC Power Produced by Grid-Connected PV Systems

Description Details Author(s) References See Also


This package implements methods for forecasting the AC power output of a PV following a nonparametric approach. It uses as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. It uses Quantile Regression Forests as the machine learning tool to generate forecasts with a confidence interval.


The package includes 4 main functions:


Marcelo Pinho Almeida and Oscar Perpinan Lamigueiro

Maintainer: Oscar Perpinan Lamigueiro <oscar.perpinan@gmail.com>


Meinshausen, N. (2006). Quantile regression forests. The Journal of Machine Learning Research, 7, 983-999.

Pinho Almeida, M., Perpiñán Lamigueiro, O., and Narvarte L., PV Power Forecast Using a Nonparametric Model, Solar Energy (under review)

See Also

meteoForecast-package, quantregForest, raster-package, zoo, calcSol

iesiee/PVF documentation built on May 9, 2019, 1:09 a.m.