How does heterogeneous industrial agglomeration affect the total factor energy efficiency of China's digital economy

H Peng, Y Lu, Q Wang - Energy, 2023 - Elsevier
Digital economy has raised hopes for enhancing total factor energy efficiency (TFEE). This
study constructs a comprehensive evaluation model in which, under the moderating effect of …

Comparative investigation of imaging techniques, pre-processing and visual fault diagnosis using artificial intelligence models for solar photovoltaic system–A …

GB Balachandran, M Devisridhivyadharshini… - Measurement, 2024 - Elsevier
Photovoltaic systems provide an eco-friendly key to meet our increasing energy demand
while mitigating the adverse impacts of conventional fossil fuel-based energy generation …

Exploring the interplay among energy dependence, CO2 emissions, and renewable resource utilization in developing nations: Empirical insights from Africa and the …

NR Kouyakhi - Energy, 2023 - Elsevier
As an indicator of a nation's reliance on foreign suppliers, Energy dependence is a
determining factor in the optimal utilization of fossil fuels, upon which developing countries' …

[HTML][HTML] Photovoltaic systems operation and maintenance: A review and future directions

H Abdulla, A Sleptchenko, A Nayfeh - Renewable and Sustainable Energy …, 2024 - Elsevier
The expansion of photovoltaic systems emphasizes the crucial requirement for effective
operations and maintenance, drawing insights from advanced maintenance approaches …

Photovoltaics plant fault detection using deep learning techniques

S Jumaboev, D Jurakuziev, M Lee - Remote Sensing, 2022 - mdpi.com
Solar energy is the fastest-growing clean and sustainable energy source, outperforming
other forms of energy generation. Usually, solar panels are low maintenance and do not …

Performance of Deep Learning Techniques for Forecasting PV Power Generation: A Case Study on a 1.5 MWp Floating PV Power Plant

N Khortsriwong, P Boonraksa, T Boonraksa… - Energies, 2023 - mdpi.com
Recently, deep learning techniques have become popular and are widely employed in
several research areas, such as optimization, pattern recognition, object identification, and …

[HTML][HTML] Machine learning in solar plants inspection automation

J Starzyński, P Zawadzki, D Harańczyk - Energies, 2022 - mdpi.com
The emergence of large photovoltaic farms poses a new challenge for quick and economic
diagnostics of such installations. This article presents this issue starting from a quantitative …

Artificial deep neural network in hybrid PV system for controlling the power management

S Sahoo, TM Amirthalakshmi, S Ramesh… - International Journal …, 2022 - Wiley Online Library
The analysis of different components of a grid‐linked hybrid energy system (HES)
comprising a photovoltaic (PV) system is presented in this work. Due to the increase of the …

PV system failures diagnosis based on multiscale dispersion entropy

C Lebreton, F Kbidi, A Graillet, T Jegado, F Alicalapa… - Entropy, 2022 - mdpi.com
Photovoltaic (PV) system diagnosis is a growing research domain likewise solar energy's
ongoing significant expansion. Indeed, efficient Fault Detection and Diagnosis (FDD) tools …

Performance assessment and root-cause analysis of a deteriorating On-Grid Industrial PV System for the identification of newly originating power degrading defect

RAT Khan, MF Abbas, AN Khan, N Ahmed… - Energy for Sustainable …, 2023 - Elsevier
Solar modules deployed in industrial areas have the potential to conserve a significant
quantity of national grid electricity; nevertheless, the accessibility of industrial contaminants …