[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 …
Hybrid prediction method of solar irradiance applied to short-term photovoltaic energy generation
JN Maciel, JJG Ledesma, OHA Junior - Renewable and Sustainable …, 2024 - Elsevier
One of the most promising renewable energy sources used as a solution to supply the
increase in electricity consumption is photovoltaic solar energy. This source has intrinsic and …
increase in electricity consumption is photovoltaic solar energy. This source has intrinsic and …
[HTML][HTML] Improving cross-site generalisability of vision-based solar forecasting models with physics-informed transfer learning
Forecasting solar energy from cloud cover observations is crucial to truly anticipate future
changes in power supply. On an intra-hour timescale, ground-level sky cameras located …
changes in power supply. On an intra-hour timescale, ground-level sky cameras located …
Improving ultra-short-term photovoltaic power forecasting using a novel sky-image-based framework considering spatial-temporal feature interaction
H Zang, D Chen, J Liu, L Cheng, G Sun, Z Wei - Energy, 2024 - Elsevier
Accurate photovoltaic (PV) power forecasting is crucial to ensure the safety and stability of
power systems, given the penetration of solar energy. Extracting spatial-temporal features …
power systems, given the penetration of solar energy. Extracting spatial-temporal features …
[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] Sky image-based solar forecasting using deep learning with heterogeneous multi-location data: Dataset fusion versus transfer learning
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 available in …
uncertainty in solar power generation. With more and more sky image datasets available in …
Advances in Short-Term Solar Forecasting: A Review and Benchmark of Machine Learning Methods and Relevant Data Sources
Solar forecasting is becoming increasingly important due to the exponential growth in total
global solar capacity each year. More photovoltaic (PV) penetration in the grid poses …
global solar capacity each year. More photovoltaic (PV) penetration in the grid poses …
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 …
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 …