Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

F Ahsan, NH Dana, SK Sarker, L Li… - … and Control of …, 2023 - ieeexplore.ieee.org
Meteorological changes urge engineering communities to look for sustainable and clean
energy technologies to keep the environment safe by reducing CO 2 emissions. The …

Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects

T Berghout, M Benbouzid, SM Muyeen - International Journal of Critical …, 2022 - Elsevier
Abstract In modern Smart Grids (SGs) ruled by advanced computing and networking
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …

Using machine learning in photovoltaics to create smarter and cleaner energy generation systems: A comprehensive review

A Sohani, H Sayyaadi, C Cornaro… - Journal of Cleaner …, 2022 - Elsevier
Photovoltaic (PV) technologies are expected to play an increasingly important role in future
energy production. In parallel, machine learning has gained prominence because of a …

A systematic guide for predicting remaining useful life with machine learning

T Berghout, M Benbouzid - Electronics, 2022 - mdpi.com
Prognosis and health management (PHM) are mandatory tasks for real-time monitoring of
damage propagation and aging of operating systems during working conditions. More …

Cloud computing and IoT based intelligent monitoring system for photovoltaic plants using machine learning techniques

M Emamian, A Eskandari, M Aghaei, A Nedaei… - Energies, 2022 - mdpi.com
This paper proposes an Intelligent Monitoring System (IMS) for Photovoltaic (PV) systems
using affordable and cost-efficient hardware and also lightweight software that is capable of …

A day-ahead photovoltaic power prediction via transfer learning and deep neural networks

SM Miraftabzadeh, CG Colombo, M Longo, F Foiadelli - Forecasting, 2023 - mdpi.com
Climate change and global warming drive many governments and scientists to investigate
new renewable and green energy sources. Special attention is on solar panel technology …

[HTML][HTML] A weighted ensemble learning-based autonomous fault diagnosis method for photovoltaic systems using genetic algorithm

A Eskandari, M Aghaei, J Milimonfared… - International Journal of …, 2023 - Elsevier
Conventional protection devices may not be able to diagnose the faults in Photovoltaic (PV)
systems due to the nonlinear behavior of PV characteristics, its dependency on the …

A review on machine learning applications for solar plants

E Engel, N Engel - Sensors, 2022 - mdpi.com
A solar plant system has complex nonlinear dynamics with uncertainties due to variations in
system parameters and insolation. Thereby, it is difficult to approximate these complex …

[HTML][HTML] Intelligent solar panel monitoring system and shading detection using artificial neural networks

FSM Abdallah, MN Abdullah, I Musirin, AM Elshamy - Energy Reports, 2023 - Elsevier
Detecting shading in Photovoltaic panels (PV) is crucial for ensuring optimal energy
generation. This paper proposes a novel monitoring system that uses Artificial Neural …

[HTML][HTML] Experimentally derived models to detect onset of shunt resistance degradation in photovoltaic modules

H Al Mahdi, PG Leahy, AP Morrison - Energy Reports, 2023 - Elsevier
It has been shown that a reduction in the shunt resistance can lead to solar module
degradation over time, resulting ultimately in module failure. This paper reports how the …