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 …

Fault detection and monitoring systems for photovoltaic installations: A review

A Triki-Lahiani, ABB Abdelghani… - … and Sustainable Energy …, 2018 - Elsevier
As any energy production system, photovoltaic (PV) installations have to be monitored to
enhance system performances and to early detect failures for more reliability. There are …

Graph-based semi-supervised learning for fault detection and classification in solar photovoltaic arrays

Y Zhao, R Ball, J Mosesian… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
Fault detection in solar photovoltaic (PV) arrays is an essential task for increasing reliability
and safety in PV systems. Because of PV's nonlinear characteristics, a variety of faults may …

Proton exchange membrane fuel cell degradation prediction based on adaptive neuro-fuzzy inference systems

RE Silva, R Gouriveau, S Jemei, D Hissel… - International Journal of …, 2014 - Elsevier
This paper studies the prediction of the output voltage reduction caused by degradation
during nominal operating condition of a PEM fuel cell stack. It proposes a methodology …

Monitoring, diagnosis, and power forecasting for photovoltaic fields: A review

S Daliento, A Chouder, P Guerriero… - International Journal …, 2017 - Wiley Online Library
A wide literature review of recent advance on monitoring, diagnosis, and power forecasting
for photovoltaic systems is presented in this paper. Research contributions are classified into …

A supervised ensemble learning method for fault diagnosis in photovoltaic strings

C Kapucu, M Cubukcu - Energy, 2021 - Elsevier
This study proposes a fault diagnosis method based on the use of a machine learning (ML)
technique called ensemble learning (EL) for photovoltaic (PV) systems. EL methods aim to …

Real time fault detection in photovoltaic systems

MH Ali, A Rabhi, A El Hajjaji, GM Tina - Energy Procedia, 2017 - Elsevier
In this paper, a method for real time monitoring and fault diagnosis in photovoltaic systems is
proposed. This approach is based on a comparison between the performances of a faulty …

Review of artificial intelligence-based failure detection and diagnosis methods for solar photovoltaic systems

A Abubakar, CFM Almeida, M Gemignani - Machines, 2021 - mdpi.com
In recent years, the overwhelming growth of solar photovoltaics (PV) energy generation as
an alternative to conventional fossil fuel generation has encouraged the search for efficient …

A taxonomical review on recent artificial intelligence applications to PV integration into power grids

C Feng, Y Liu, J Zhang - International Journal of Electrical Power & Energy …, 2021 - Elsevier
The exponential growth of solar power has been witnessed in the past decade and is
projected by the ambitious policy targets. Nevertheless, the proliferation of solar energy …

Scheme for predictive fault diagnosis in photo-voltaic modules using thermal imaging

ZA Jaffery, AK Dubey, A Haque - Infrared Physics & Technology, 2017 - Elsevier
Degradation of PV modules can cause excessive overheating which results in a reduced
power output and eventually failure of solar panel. To maintain the long term reliability of …