A review on global solar radiation prediction with machine learning models in a comprehensive perspective
Y Zhou, Y Liu, D Wang, X Liu, Y Wang - Energy Conversion and …, 2021 - Elsevier
Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …
for economic and environmental considerations. However, because solar-radiation …
A state of art review on estimation of solar radiation with various models
Solar radiation is free, and very useful input for most sectors such as heat, health, tourism,
agriculture, and energy production, and it plays a critical role in the sustainability of …
agriculture, and energy production, and it plays a critical role in the sustainability of …
Development of a hybrid computational intelligent model for daily global solar radiation prediction
Providing an accurate and reliable solar radiation prediction is highly significant for optimal
design and management of thermal and solar photovoltaic systems. It is massively essential …
design and management of thermal and solar photovoltaic systems. It is massively essential …
A novel machine learning approach for solar radiation estimation
Solar irradiation (Rs) is the electromagnetic radiation energy emitted by the Sun. It plays a
crucial role in sustaining life on Earth by providing light, heat, and energy. Furthermore, it …
crucial role in sustaining life on Earth by providing light, heat, and energy. Furthermore, it …
Experimental validation of multi-stage optimal energy management for a smart microgrid system under forecasting uncertainties
S Gheouany, H Ouadi, F Giri, S El Bakali - Energy Conversion and …, 2023 - Elsevier
This paper proposes a Multi-stage Energy Management System (MS-EMS) for power
distribution in a smart microgrid comprising a photovoltaic system (PV), an Energy Storage …
distribution in a smart microgrid comprising a photovoltaic system (PV), an Energy Storage …
[HTML][HTML] Variational mode decomposition based random forest model for solar radiation forecasting: new emerging machine learning technology
Forecasting of solar radiation (Radn) can provide an insight vision for the amount of green
and friendly energy sources. Owing to the non-linearity and non-stationarity challenges …
and friendly energy sources. Owing to the non-linearity and non-stationarity challenges …
Short‐Term PV Power Forecasting Using a Hybrid TVF‐EMD‐ELM Strategy
R Khelifi, M Guermoui, A Rabehi… - … on Electrical Energy …, 2023 - Wiley Online Library
This paper discusses the efficient implementation of a new hybrid approach to forecasting
short‐term PV power production for four different PV plants in Algeria. The developed model …
short‐term PV power production for four different PV plants in Algeria. The developed model …
A comprehensive review of solar irradiation estimation and forecasting using artificial neural networks: data, models and trends
N El-Amarty, M Marzouq, H El Fadili… - … Science and Pollution …, 2023 - Springer
Solar irradiation data are imperatively required for any solar energy-based project. The non-
accessibility and uncertainty of these data can greatly affect the implementation …
accessibility and uncertainty of these data can greatly affect the implementation …
Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network
This paper aims to develop the long short-term memory (LSTM) network modelling strategy
based on deep learning principles, tailored for the very short-term, near-real-time global …
based on deep learning principles, tailored for the very short-term, near-real-time global …
Soft computing for solar radiation potential assessment in Algeria
M Guermoui, A Rabehi - International Journal of Ambient Energy, 2020 - Taylor & Francis
Precise estimation of solar radiation is a highly required parameter for the design and
assessment of solar energy applications. Over the past years, many machine learning …
assessment of solar energy applications. Over the past years, many machine learning …