Reconstructing 10-km-resolution direct normal irradiance dataset through a hybrid algorithm

J Wu, J Niu, Q Qi, CA Gueymard, L Wang, W Qin… - … and Sustainable Energy …, 2024 - Elsevier
Evaluating, map**, and monitoring high-quality Direct Normal Irradiance (DNI) is crucial
for the design, financing, and operation of solar power plants, especially those utilizing …

[HTML][HTML] On vision transformer for ultra-short-term forecasting of photovoltaic generation using sky images

S Xu, R Zhang, H Ma, C Ekanayake, Y Cui - Solar Energy, 2024 - Elsevier
An accurate photovoltaic (PV) generation forecasting is important for grid scheduling and
dispatching. However, ultra-short-term PV generation forecasting is rather challenging …

Prediction of solar irradiance using convolutional neural network and attention mechanism-based long short-term memory network based on similar day analysis and …

X Hou, C Ju, B Wang - Heliyon, 2023 - cell.com
As one of the future's most promising clean energy sources, solar energy is the key to
develo** renewable energy. The randomness of solar irradiance can affect the efficiency …

Enhancing direct Normal solar Irradiation forecasting for heliostat field applications through a novel hybrid model

M Guermoui, T Arrif, A Belaid, S Hassani… - Energy Conversion and …, 2024 - Elsevier
This study addresses the critical need for precise Direct Normal Irradiation forecasting in
concentrating solar power systems to enhance performance and manage power generation …

A novel hybrid intelligent approach for solar photovoltaic power prediction considering UV index and cloud cover

R Aman, M Rizwan, A Kumar - Electrical Engineering, 2025 - Springer
The power generation from photovoltaic plants depends on varying meteorological
conditions. These meteorological conditions such as solar irradiance, temperature, and wind …

CloudSwinNet: A hybrid CNN-transformer framework for ground-based cloud images fine-grained segmentation

C Shi, Z Su, K Zhang, X **e, X Zhang - Energy, 2024 - Elsevier
Solar irradiance is the main factor affecting the output of a photovoltaic (PV) power station.
The dominant role of ground-based clouds on the variation of direct solar radiation in the …

[HTML][HTML] Using sky-classification to improve the short-term prediction of irradiance with sky images and convolutional neural networks

VAM Lopez, G van Urk, PJF Doodkorte, M Zeman… - Solar Energy, 2024 - Elsevier
Clouds moving in front or away from the sun are the leading cause of irradiance variability.
These variations have a repercussion on the electricity production of photovoltaic systems …

Model-based predictive control of a solar hybrid thermochemical reactor for high-temperature steam gasification of biomass

Y Karout, A Curcio, J Eynard, S Thil, S Rodat… - Clean …, 2023 - mdpi.com
The present paper deals with both the modeling and the dynamic control of a solar hybrid
thermochemical reactor designed to produce syngas through the high-temperature steam …

Combined ultra-short-term prediction method of PV power considering ground-based cloud images and chaotic characteristics

Y Wang, X Wang, D Hao, Y Sang, H Xue, Y Mi - Solar Energy, 2024 - Elsevier
To further improve the ultra-short-term prediction accuracy of photovoltaic (PV) power in
mutant irradiation scenarios caused by moving clouds, a combined ultra-short-term …

Prediction Method of Direct Normal Irradiance for Solar Thermal Power Plants Based on VMD-WOA-DELM

S Zhang, D Niu, Z Zhou, Y Duan… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The Direct Normal Irradiance (DNI), being the energy source for solar thermal power plants,
can remarkably impact the reliability and efficiency of these plants because of its inherent …