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Deep learning prediction models for short-term solar photovoltaic power generation forecasting | Synapse
March 3, 2026
Open Access
Deep learning prediction models for short-term solar photovoltaic power generation forecasting
PS
Praveen K. Singh
University of Miami
AS
Amit Saraswat
Manipal University Jaipur
YG
Yogesh Gupta
BML Munjal University
Key Points
Power generation forecasting accuracy enhances with deep learning techniques, supporting better energy distribution.
The predictive model uses historical weather data to forecast solar power output over short timeframes.
Assessment using historical data reveals a significant reduction in forecasting errors compared to traditional methods.
Highlights the need for real-time prediction improvements in energy sector applications to enhance efficiency.
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Singh et al. (Tue,) studied this question.
synapsesocial.com/papers/69a7666dbadf0bb9e87dcecd
https://doi.org/https://doi.org/10.1016/j.nxener.2026.100531