[HTML][HTML] Advances in solar forecasting: Computer vision with deep learning
Renewable energy forecasting is crucial for integrating variable energy sources into the grid.
It allows power systems to address the intermittency of the energy supply at different …
It allows power systems to address the intermittency of the energy supply at different …
Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey
Sky image-based solar forecasting using deep learning has been recognized as a
promising approach in reducing the uncertainty of solar power generation. However, a major …
promising approach in reducing the uncertainty of solar power generation. However, a major …
Benchmarking of solar irradiance nowcast performance derived from all-sky imagers
Fluctuations of the incoming solar irradiance impact the power generation from photovoltaic
and concentrating solar thermal power plants. Accurate solar nowcasting becomes …
and concentrating solar thermal power plants. Accurate solar nowcasting becomes …
Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery
FJ Rodríguez-Benítez, M López-Cuesta… - Applied Energy, 2021 - Elsevier
This work proposes and evaluates methods for extending the forecasting horizon of all-sky
imager (ASI)-based solar radiation nowcasts and estimating the uncertainty of these …
imager (ASI)-based solar radiation nowcasts and estimating the uncertainty of these …
A physical model with meteorological forecasting for hourly rooftop photovoltaic power prediction
Y Zhi, T Sun, X Yang - Journal of Building Engineering, 2023 - Elsevier
Accurate photovoltaic power forecasting provides essential information for the flexible
control of building energy systems. This paper proposes a physical model with …
control of building energy systems. This paper proposes a physical model with …
[HTML][HTML] Applying self-supervised learning for semantic cloud segmentation of all-sky images
Semantic segmentation of ground-based all-sky images (ASIs) can provide high-resolution
cloud coverage information of distinct cloud types, applicable for meteorology-, climatology …
cloud coverage information of distinct cloud types, applicable for meteorology-, climatology …
A hybrid solar irradiance nowcasting approach: Combining all sky imager systems and persistence irradiance models for increased accuracy
The share of distributed solar power generation is continuously growing. This increase,
combined with the intermittent nature of the solar resource creates new challenges for all …
combined with the intermittent nature of the solar resource creates new challenges for all …
[HTML][HTML] 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. A promising approach to forecasting the temporal variability of solar …
of its intermittency. A promising approach to forecasting the temporal variability of solar …
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 …
convolutional neural networks, which facilitates numerous computer vision tasks such as …
Open-source ground-based sky image datasets for very short-term solar forecasting, cloud analysis and modeling: A comprehensive survey
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 …
promising approach in reducing the uncertainty in solar power generation. However, one of …