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Found 5 papers, 2 papers with code
Sky-image-based solar forecasting using deep learning with multi-location data: training models locally, globally or via transfer learning?
With more and more sky image datasets open sourced in recent years, the development of accurate and reliable deep learning-based solar forecasting methods has seen a huge growth in potential.
Omnivision forecasting: combining satellite observations with sky images for improved intra-hour solar energy predictions
In this study, we integrate these two complementary points of view on the cloud cover in a single machine learning framework to improve intra-hour (up to 60-min ahead) irradiance forecasting.
SPIN: Simplifying Polar Invariance for Neural networks Application to vision-based irradiance forecasting
Translational invariance induced by pooling operations is an inherent property of convolutional neural networks, which facilitates numerous computer vision tasks such as classification.
ECLIPSE : Envisioning CLoud Induced Perturbations in Solar Energy
Efficient integration of solar energy into the electricity mix depends on a reliable anticipation of its intermittency.
Benchmarking of Deep Learning Irradiance Forecasting Models from Sky Images -- an in-depth Analysis
A number of industrial applications, such as smart grids, power plant operation, hybrid system management or energy trading, could benefit from improved short-term solar forecasting, addressing the intermittent energy production from solar panels.
