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2018 | OriginalPaper | Buchkapitel

30 min-Ahead Gridded Solar Irradiance Forecasting Using Satellite Data

verfasst von : Todd Taomae, Lipyeow Lim, Duane Stevens, Dora Nakafuji

Erschienen in: Databases Theory and Applications

Verlag: Springer International Publishing

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Abstract

Solar irradiance forecasting is critical to balancing solar energy production and energy consumption in the electric grid; however, solar irradiance forecasting is dependent on meteorological conditions and, in particular, cloud cover, which are captured in satellite imagery. In this paper we present a method for short-term solar irradiance forecasting using gridded global horizontal irradiance (GHI) data estimated from satellite images. We use this data to first create a simple linear regression model with a single predictor variable. We then discuss various methods to extend and improve the model. We found that adding predictor variables and partitioning the data to create multiple models both reduced prediction errors under certain circumstances. However, both these techniques were outperformed by applying a data transformation before training the linear regression model.

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Titel: 30 min-Ahead Gridded Solar Irradiance Forecasting Using Satellite Data
verfasst von: Todd Taomae
Lipyeow Lim
Duane Stevens
Dora Nakafuji
Verlag: Springer International Publishing
Buch: Databases Theory and Applications
Print ISBN: 978-3-319-92012-2

Electronic ISBN: 978-3-319-92013-9

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-92013-9_15

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