Deep learning for single-site solar irradiance forecasting using multi-station data

Deep learning for single-site solar irradiance forecasting using multi-station data

This study examines the integration of data from multiple stations for solar irradiance forecasting at a single site using advanced deep learning models, such as long-term memory (LSTM), deep modular attention (DeepMap), and graph convolutional networks (GC-LSTM). The research addresses an important...

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Bibliographic Details
Main Authors: Daniel Guatibonza, Gabriel Narvaez, Luis Felipe Giraldo
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Environmental Research Communications
Subjects:
solar irradiance forecasting
deep learning
multi-station
renewable energy
Online Access:https://doi.org/10.1088/2515-7620/adaf79
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https://doi.org/10.1088/2515-7620/adaf79

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