Artificial intelligence and internet of things to improve efficacy of diagnosis and remote sensing of solar photovoltaic systems: Challenges, recommendations and future …
A Mellit, S Kalogirou - Renewable and Sustainable Energy Reviews, 2021 - Elsevier
Currently, a huge number of photovoltaic plants have been installed worldwide and these
plants should be carefully protected and supervised continually in order to be safe and …
plants should be carefully protected and supervised continually in order to be safe and …
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 …
Remote sensing of photovoltaic scenarios: Techniques, applications and future directions
Develo** solar photovoltaic (PV) systems is an effective way to address the problems of
limited fossil fuel reserves, soaring world energy demand and global climate change. The …
limited fossil fuel reserves, soaring world energy demand and global climate change. The …
Aerial infrared thermography for low-cost and fast fault detection in utility-scale PV power plants
The uptime of utility-scale solar photovoltaic (PV) power plants is of utmost importance for
meeting contractual energy yields and expected capacity factors. Aerial Infrared …
meeting contractual energy yields and expected capacity factors. Aerial Infrared …
An embedded solution for fault detection and diagnosis of photovoltaic modules using thermographic images and deep convolutional neural networks
A Mellit - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
In this work, an embedded system for fault detection and diagnosis of photovoltaic (PV)
modules based on infrared thermographic images and deep conventional neural networks …
modules based on infrared thermographic images and deep conventional neural networks …
[HTML][HTML] Develo** a deep learning-based layer-3 solution for thermal infrared large-scale photovoltaic module inspection from orthorectified big UAV imagery data
The increasing adoption of photovoltaic (PV) technology highlights the need for efficient and
large-scale deployment-ready inspection solutions. In the thermal infrared imagery-based …
large-scale deployment-ready inspection solutions. In the thermal infrared imagery-based …
Automatic inspection of photovoltaic power plants using aerial infrared thermography: a review
In recent years, aerial infrared thermography (aIRT), as a cost-efficient inspection method,
has been demonstrated to be a reliable technique for failure detection in photovoltaic (PV) …
has been demonstrated to be a reliable technique for failure detection in photovoltaic (PV) …
[HTML][HTML] Photovoltaic systems operation and maintenance: A review and future directions
The expansion of photovoltaic systems emphasizes the crucial requirement for effective
operations and maintenance, drawing insights from advanced maintenance approaches …
operations and maintenance, drawing insights from advanced maintenance approaches …
[HTML][HTML] Machine learning for advanced characterisation of silicon photovoltaics: A comprehensive review of techniques and applications
Accurate and efficient characterisation techniques are essential to ensure the optimal
performance and reliability of photovoltaic devices, especially given the large number of …
performance and reliability of photovoltaic devices, especially given the large number of …
Machine learning-based condition monitoring for PV systems: State of the art and future prospects
To ensure the continuity of electric power generation for photovoltaic systems, condition
monitoring frameworks are subject to major enhancements. The continuous uniform delivery …
monitoring frameworks are subject to major enhancements. The continuous uniform delivery …