Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review
Meteorological changes urge engineering communities to look for sustainable and clean
energy technologies to keep the environment safe by reducing CO 2 emissions. The …
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
Abstract In modern Smart Grids (SGs) ruled by advanced computing and networking
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …
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
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 …
energy production. In parallel, machine learning has gained prominence because of a …
A systematic guide for predicting remaining useful life with machine learning
Prognosis and health management (PHM) are mandatory tasks for real-time monitoring of
damage propagation and aging of operating systems during working conditions. More …
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
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 …
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
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 …
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
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 …
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 …
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
Detecting shading in Photovoltaic panels (PV) is crucial for ensuring optimal energy
generation. This paper proposes a novel monitoring system that uses Artificial Neural …
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
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 …
degradation over time, resulting ultimately in module failure. This paper reports how the …