Taxonomy research of artificial intelligence for deterministic solar power forecasting

H Wang, Y Liu, B Zhou, C Li, G Cao, N Voropai… - Energy Conversion and …, 2020 - Elsevier
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …

Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review

B Li, C Delpha, D Diallo, A Migan-Dubois - Renewable and Sustainable …, 2021 - Elsevier
The rapid development of photovoltaic (PV) technology and the growing number and size of
PV power plants require increasingly efficient and intelligent health monitoring strategies to …

[HTML][HTML] A review of automated solar photovoltaic defect detection systems: Approaches, challenges, and future orientations

U Hijjawi, S Lakshminarayana, T Xu, GPM Fierro… - Solar Energy, 2023 - Elsevier
The development of Photovoltaic (PV) technology has paved the path to the exponential
growth of solar cell deployment worldwide. Nevertheless, the energy efficiency of solar cells …

In-depth review of yolov1 to yolov10 variants for enhanced photovoltaic defect detection

M Hussain, R Khanam - Solar, 2024 - mdpi.com
This review presents an investigation into the incremental advancements in the YOLO (You
Only Look Once) architecture and its derivatives, with a specific focus on their pivotal …

Module defect detection and diagnosis for intelligent maintenance of solar photovoltaic plants: Techniques, systems and perspectives

W Tang, Q Yang, Z Dai, W Yan - Energy, 2024 - Elsevier
The energy production efficiency of photovoltaic (PV) systems can be degraded due to the
complicated operating environment. Given the huge installed capacity of large-scale PV …

Efficient deep feature extraction and classification for identifying defective photovoltaic module cells in Electroluminescence images

MY Demirci, N Beşli, A Gümüşçü - Expert Systems with Applications, 2021 - Elsevier
Electroluminescence (EL) imaging has become the standard test procedure for defect
detection throughout the production, installation and operation stages of solar modules …

[HTML][HTML] Application of artificial intelligence in marine corrosion prediction and detection

MMH Imran, S Jamaludin, AFM Ayob, AAIM Ali… - Journal of Marine …, 2023 - mdpi.com
One of the biggest problems the maritime industry is currently experiencing is corrosion,
resulting in short and long-term damages. Early prediction and proper corrosion monitoring …

Microstructure segmentation with deep learning encoders pre-trained on a large microscopy dataset

J Stuckner, B Harder, TM Smith - npj Computational Materials, 2022 - nature.com
This study examined the improvement of microscopy segmentation intersection over union
accuracy by transfer learning from a large dataset of microscopy images called MicroNet …

A lightweight network for photovoltaic cell defect detection in electroluminescence images based on neural architecture search and knowledge distillation

J Zhang, X Chen, H Wei, K Zhang - Applied Energy, 2024 - Elsevier
Nowadays, the rapid development of photovoltaic (PV) power stations requires increasingly
reliable maintenance and fault diagnosis of PV modules in the field. Due to the …

[HTML][HTML] Applications of artificial intelligence to photovoltaic systems: a review

HF Mateo Romero, MÁ González Rebollo… - Applied Sciences, 2022 - mdpi.com
This article analyzes the relationship between artificial intelligence (AI) and photovoltaic
(PV) systems. Solar energy is one of the most important renewable energies, and the …