Examining the Potential of a Random Forest Derived Cloud Mask from GOES-R Satellites to Improve Solar Irradiance Forecasting

Examining the Potential of a Random Forest Derived Cloud Mask from GOES-R Satellites to Improve Solar Irradiance Forecasting

In order for numerical weather prediction (NWP) models to correctly predict solar irradiance reaching the earth’s surface for more accurate solar power forecasting, it is important to initialize the NWP model with accurate cloud information. Knowing where the clouds are located is the first step. Us...

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Bibliographic Details
Main Authors:	Tyler McCandless, Pedro Angel Jiménez
Format:	Article
Language:	English
Published:	MDPI AG 2020-04-01
Series:	Energies
Subjects:	solar power forecasting machine learning artificial intelligence random forests supervised learning remote sensing
Online Access:	https://www.mdpi.com/1996-1073/13/7/1671

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