10 citations · 23 across the 3 of their papers we have counts for
4 papers · 1 filter
Sky-image-based solar forecasting using deep learning with multi-location data: training models locally, globally or via transfer learning?
Yuhao Nie, Quentin Paletta, Andea Scott +5
Solar forecasting from ground-based sky images has shown great promise in reducing the uncertainty in solar power generation. With more and more sky image datasets open sourced in…
Open-Source Ground-based Sky Image Datasets for Very Short-term Solar Forecasting, Cloud Analysis and Modeling: A Comprehensive Survey
Yuhao Nie, Xiatong Li, Quentin Paletta +3
Sky-image-based solar forecasting using deep learning has been recognized as a promising approach in reducing the uncertainty in solar power generation. However, one of the biggest…
Benchmarking of Deep Learning Irradiance Forecasting Models from Sky Images -- an in-depth Analysis
Quentin Paletta, Guillaume Arbod, Joan Lasenby
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 forecastin…
Convolutional Neural Networks applied to sky images for short-term solar irradiance forecasting
Quentin Paletta, Joan Lasenby
Despite the advances in the field of solar energy, improvements of solar forecasting techniques, addressing the intermittent electricity production, remain essential for securing i…