Prognostics and health management of photovoltaic systems based on deep learning: A state-of-the-art review and future perspectives

Z Chang, T Han - Renewable and Sustainable Energy Reviews, 2024 - Elsevier
As global photovoltaic (PV) power generation capacity rapidly expands, efficient and
effective health management of PV systems has emerged as a critical focal point. With the …

[HTML][HTML] Deep Learning approaches for visual faults diagnosis of photovoltaic systems: State-of-the-art review

M Jalal, IU Khalil, A ul Haq - Results in Engineering, 2024 - Elsevier
PV systems are prone to external environmental conditions that affect PV system operations.
Visual inspection of the impacts of faults on PV system is considered a better practice rather …

Artificial intelligence in photovoltaic fault identification and diagnosis: A systematic review

M Islam, MR Rashel, MT Ahmed, AKMK Islam… - Energies, 2023 - mdpi.com
Photovoltaic (PV) fault detection is crucial because undetected PV faults can lead to
significant energy losses, with some cases experiencing losses of up to 10%. The efficiency …

Optimizing solar power using array topology reconfiguration with regularized deep neural networks

V Narayanaswamy, R Ayyanar… - IEEE …, 2023 - ieeexplore.ieee.org
Reconfiguring photovoltaic (PV) array connections among different topologies such as
series-parallel, bridge-link, honeycomb, or total-cross-tied is a popular strategy to mitigate …

Belt Conveyor Idlers Fault Detection Using Acoustic Analysis and Deep Learning Algorithm with the YAMNet Pretrained Network

F Alharbi, S Luo, S Zhao, G Yang… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Belt conveyor systems are essential in industries like automotive, aerospace, power
generation, and heavy machinery, with idlers playing a crucial role in ensuring the smooth …

Quantum neural network parameter estimation for photovoltaic fault detection

G Uehara, S Rao, M Dobson… - … & Applications (IISA), 2021 - ieeexplore.ieee.org
In this paper, we describe solar array monitoring using various machine learning methods
including neural networks. We study fault detection using a quantum computer system and …

Detection, classification, and location of open-circuit and short-circuit faults in solar photovoltaic array: an approach using single sensor

SS Sakthivel, V Arunachalam… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Solar PV arrays are exponentially employed in all possible spheres, ranging from a few
hundred watts to megawatts. In this context, fault detection, classification, and location …

Leveraging dynamic power benchmarks and CUSUM charts for enhanced fault detection in distributed PV systems

B Meng, R Loonen, JLM Hensen - Energy Conversion and Management, 2024 - Elsevier
Faults in photovoltaic (PV) systems are common during their operational lifetime. Existing PV
fault detection methods, which are primarily designed for large-scale PV fields, struggle with …

Classification of Photovoltaic Faults Using PSO-Optimized Compact Convolutional Transformer

YY Hong, LF Chen, W Zhang - IEEE Access, 2023 - ieeexplore.ieee.org
Diagnosing photovoltaic (PV) farms has become increasingly complex due to their large-
scale presence in diverse environmental conditions. A comprehensive diagnosis process …

Fault Diagnosis in PV system using DWT and Ensembled k-NN Machine Learning Classifier

SRK Joga, C Saiprakash, A Mohapatra… - … and Computing for …, 2022 - ieeexplore.ieee.org
The output power of a photovoltaic (PV) system is dependent on the perfect operation of the
PV array. PV arrays may experience various fault conditions as a result of open circuit, short …