Deep learning models for solar irradiance forecasting: A comprehensive review
P Kumari, D Toshniwal - Journal of Cleaner Production, 2021 - Elsevier
The growing human population in this modern society hugely depends on the energy to
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …
[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 …
[HTML][HTML] A regional solar forecasting approach using generative adversarial networks with solar irradiance maps
The intermittent and stochastic nature of solar resource hinders the integration of solar
energy into modern power system. Solar forecasting has become an important tool for better …
energy into modern power system. Solar forecasting has become an important tool for better …
A review on neural network based models for short term solar irradiance forecasting
The accuracy of solar energy forecasting is critical for power system planning, management,
and operation in the global electric energy grid. Therefore, it is crucial to ensure a constant …
and operation in the global electric energy grid. Therefore, it is crucial to ensure a constant …
[HTML][HTML] SkyGPT: Probabilistic ultra-short-term solar forecasting using synthetic sky images from physics-constrained VideoGPT
The variability of solar photovoltaic (PV) power output, driven by rapidly changing cloud
dynamics, hinders the transition to reliable renewable energy systems. Information on future …
dynamics, hinders the transition to reliable renewable energy systems. Information on future …
[HTML][HTML] Systematic review of nowcasting approaches for solar energy production based upon ground-based cloud imaging
BJ Martins, A Cerentini, SL Mantelli, TZL Chaves… - Solar Energy …, 2022 - Elsevier
Nowcasting of solar energy considering clouds is important for photovoltaic solar plants and
distributed systems. Clouds present a challenge for modeling, due to constant changes in …
distributed systems. Clouds present a challenge for modeling, due to constant changes in …
A Review of Solar Forecasting Techniques and the Role of Artificial Intelligence
Solar energy forecasting is essential for the effective integration of solar power into electricity
grids and the optimal management of renewable energy resources. Distinguishing itself from …
grids and the optimal management of renewable energy resources. Distinguishing itself from …
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 …
[HTML][HTML] Solar radiation nowcasting based on geostationary satellite images and deep learning models
Y Cui, P Wang, JF Meirink, N Ntantis, JS Wijnands - Solar Energy, 2024 - Elsevier
Reliable solar radiation and photovoltaic power prediction is essential for the safe and
stable operation of electric power systems. Cloud cover is highly related with solar radiation …
stable operation of electric power systems. Cloud cover is highly related with solar radiation …