Hybrid deep learning models for multivariate forecasting of global horizontal irradiation

N Vakitbilir, A Hilal, C Direkoğlu - Neural Computing and Applications, 2022 - Springer
Increasing photovoltaic (PV) instalments could affect the stability of the electrical grid as the
PV produces weather-dependent electricity. However, prediction of the power output of the …

Comparative analysis of neural networks techniques to forecast Global Horizontal Irradiance

A Aliberti, D Fucini, L Bottaccioli, E Macii… - IEEE …, 2021 - ieeexplore.ieee.org
Due to the continuous increasing importance of renewable energy sources as an alternative
to fossil fuels, to contrast air pollution and global warming, the prediction of Global …

Sequence to sequence deep learning models for solar irradiation forecasting

BP Mukhoty, V Maurya… - 2019 IEEE Milan …, 2019 - ieeexplore.ieee.org
The energy output a photo voltaic (PV) panel is a function of solar irradiation and weather
parameters like temperature and wind speed etc. A general measure for solar irradiation …

A compound of feature selection techniques to improve solar radiation forecasting

M Castangia, A Aliberti, L Bottaccioli, E Macii… - Expert Systems with …, 2021 - Elsevier
Abstract The prediction of Global Horizontal Irradiance (GHI) allows to estimate in advance
the future energy production of photovoltaic systems, thus ensuring their full integration into …

Multi-step-ahead forecasting of daily solar radiation components in the Saharan climate

R Khelifi, M Guermoui, A Rabehi… - International Journal of …, 2020 - Taylor & Francis
Accurate estimation of renewable energy sources plays an important role in their integration
into the grid. An unexpected atmospheric change can produce a range of problems related …

Short term solar irradiance forecasting using artificial neural network for a semi-arid climate in Morocco

O El Alani, H Ghennioui… - … Conference on Wireless …, 2019 - ieeexplore.ieee.org
Knowledge of irradiance with high accuracy is of paramount importance for monitoring
planning and for better exploitation and distribution of photovoltaic (PV) energy. Different …

[HTML][HTML] Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction

D Markovics, MJ Mayer - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The increase of the worldwide installed photovoltaic (PV) capacity and the intermittent
nature of the solar resource highlights the importance of power forecasting for the grid …

Hyper‐parametric improved machine learning models for solar radiation forecasting

M Kumar, K Namrata, N Kumari - … and Computation: Practice …, 2022 - Wiley Online Library
Spatiotemporal solar radiation forecasting is extremely challenging due to its dependence
on metrological and environmental factors. Chaotic time‐varying and non‐linearity make the …

A flexible and robust deep learning-based system for solar irradiance forecasting

II Prado-Rujas, A García-Dopico, E Serrano… - IEEE …, 2021 - ieeexplore.ieee.org
Most studies about the solar forecasting topic do not analyze and exploit the temporal and
spatial components that are inherent to such a task. Furthermore, they mostly focus just on …

[PDF][PDF] Deep learning based models for solar energy prediction

I Jebli, FZ Belouadha, MI Kabbaj… - Advances in Science …, 2021 - academia.edu
Solar energy becomes widely used in the global power grid. Therefore, enhancing the
accuracy of solar energy predictions is essential for the efficient planning, managing and …