Open Access
Issue |
Sci. Tech. Energ. Transition
Volume 79, 2024
|
|
---|---|---|
Article Number | 27 | |
Number of page(s) | 11 | |
DOI | https://doi.org/10.2516/stet/2024024 | |
Published online | 29 April 2024 |
- Osmani K., Haddad A., Lemenand T., Castanier B., Ramadan M. (2020) A review on maintenance strategies for PV systems, Sci. Total Environ. 746, 141753. [CrossRef] [Google Scholar]
- Khalil I.U., Ul-Haq A., Mahmoud Y., Jalal M., Aamir M., Ahsan M.U., Mehmood K. (2020) Comparative analysis of photovoltaic faults and performance evaluation of its detection techniques, IEEE Access 8, 26676–26700. [CrossRef] [Google Scholar]
- Prasanna R., Karthik C., Chowdhury S., Khan B. (2022) Comprehensive review on modelling, estimation, and types of faults in solar photovoltaic system, Int. J. Photoenergy 2022, 3053317. [CrossRef] [Google Scholar]
- Mellit A., Kalogirou S. (2022) Assessment of machine learning and ensemble methods for fault diagnosis of photovoltaic systems, Renew. Energy 184, 1074–1090. [CrossRef] [Google Scholar]
- Eldeghady G.S., Kamal H.A., Moustafa Hassan M.A. (2023) Fault diagnosis for PV system using a deep learning optimized via PSO heuristic combination technique, Electr. Eng. 105, 2287–2301. [CrossRef] [Google Scholar]
- Liu Y., Ding K., Zhang J., Lin Y., Yang Z., Chen X., Li Y., Chen X. (2022) Intelligent fault diagnosis of photovoltaic array based on variable predictive models and I-V curves, Solar Energy 237, 340–351. [CrossRef] [Google Scholar]
- Londoño C.D., Cano J.B., Jaramillo F., Valencia J.A., Velilla E. (2023) Outdoor and synthetic performance data for PV devices concerning the weather conditions and capacitor values of IV tracer, Data Brief 47, 109007. [CrossRef] [PubMed] [Google Scholar]
- Padilla A., Londoño C., Jaramillo F., Tovar I., Cano J.B., Velilla E. (2022) Photovoltaic performance assess by correcting the IV curves in outdoor tests, Solar Energy 237, 11–18. [CrossRef] [Google Scholar]
- Li B., Diallo D., Migan-Dubois A., Delpha C. (2022) Performance evaluation of IEC 60891:2021 procedures for correcting I-V curves of photovoltaic modules under healthy and faulty conditions, Prog. Photovolt. Res. Appl. 31, 474–493. [Google Scholar]
- Raj R.D.A., Bhattacharjee S. (2020) An Inclusive Investigation of Potential Faults in Solar Photovoltaic Array, in: 2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE), Kolkata, India, IEEE, pp. 1–6. [Google Scholar]
- Li B. (2021) Health monitoring of photovoltaic modules using electrical measurements, Dissertation, Université Paris-Saclay. [Google Scholar]
- Dhimish M., Chen Z. (2019) Novel open-circuit photovoltaic bypass diode fault detection algorithm, IEEE J. Photovol. 9, 1819–1827. [CrossRef] [Google Scholar]
- Ghazali S.N.A.M., Mohd A., Sujod M.Z. (2023) A comparative analysis of solar photovoltaic advanced fault detection and monitoring techniques, Electrica 23, 1, 137–148. [Google Scholar]
- Ibrahim A.L.W., Fang Z., Ameur K., Min D., Shafik M.B., Al-Muthanna G. (2021) Comparative study of solar PV system performance under partial shaded condition utilizing different control approaches, Indian J. Sci. Technol. 14, 1864–1893. [CrossRef] [Google Scholar]
- Delpha C., Migan-Dubois A., Diallo D. (2021) Fault diagnosis of photovoltaic panels using full I-V characteristics and machine learning techniques, Energy Convers. Manag. 248, 114785. [CrossRef] [Google Scholar]
- Lin P., Qian Z., Lu X., Lin Y., Lai Y., Cheng S., Chen Z., Wu L. (2022) Compound fault diagnosis model for Photovoltaic array using multi-scale SE-ResNet, Sustain. Energy Technol. Assess. 50, 101785. [Google Scholar]
- Sarikh S., Raoufi M., Bennouna A., Benlarabi A., Ikken B. (2020) Implementation of a plug and play IV curve tracer dedicated to characterization and diagnosis of PV modules under real operating conditions, Energy Convers. Manag. 209, 112613. [CrossRef] [Google Scholar]
- Koester L., Lindig S., Louwen A., Astigarraga A., Manzolini G., Moser D. (2022) Review of photovoltaic module degradation, field inspection techniques and techno-economic assessment, Renew. Sustain. Energy Rev. 165, 112616. [CrossRef] [Google Scholar]
- Thandaiah Prabu R., Parasuraman S., Sahoo S., Amirthalakshmi T.M., Ramesh S., Agnes Shifani S., Arockia Jayadhas S., Indra Reddy M., Al Obaid S., Alfarraj S., Kumar S.S. (2022) The numerical algorithms and optimization approach used in extracting the parameters of the single-diode and double-diode photovoltaic (PV) models, Int. J. Photoenergy 2022, 5473266. [Google Scholar]
- Edun A.S., LaFlamme C., Kingston S.R., Tetali H.V., Benoit E.J., Scarpulla M., Furse C.M., Harley J.B. (2020) Finding faults in PV systems: Supervised and unsupervised dictionary learning with SSTDR, IEEE Sens. J. 21, 4855–4865. [Google Scholar]
- Gutiérrez L., Patiño J., Duque-Grisales E. (2021) A comparison of the performance of supervised learning algorithms for solar power prediction, Energies 14, 4424. [CrossRef] [Google Scholar]
- Li N., Shepperd M., Guo Y. (2020) A systematic review of unsupervised learning techniques for software defect prediction, Inf. Softw. Technol. 122, 106287. [CrossRef] [Google Scholar]
- Humada A.M., Darweesh S.Y., Mohammed K.G., Kamil M., Mohammed S.F., Kasim N.K., Tahseen T.A., Awad O.I., Mekhilef S. (2020) Modeling of PV system and parameter extraction based on experimental data: review and investigation, Solar Energy 199, 742–760. [CrossRef] [Google Scholar]
- Ahmed R., Sreeram V., Mishra Y., Arif M.D. (2020) A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization, Renew. Sustain. Energy Rev. 124, 109792. [CrossRef] [Google Scholar]
- Dong X.-J., Shen J.-N., He G.-X., Ma Z.-F., He Y.-J. (2021) A general radial basis function neural network assisted hybrid modeling method for photovoltaic cell operating temperature prediction, Energy 234, 121212. [CrossRef] [Google Scholar]
- Kaloop M.R., Bardhan A., Kardani N., Samui P., Hu J.W., Ramzy A. (2021) Novel application of adaptive swarm intelligence techniques coupled with adaptive network-based fuzzy inference system in predicting photovoltaic power, Renew. Sustain. Energy Rev. 148, 111315. [CrossRef] [Google Scholar]
- Lazzaretti A.E., da Costa C.H., Rodrigues M.P., Yamada G.D., Lexinoski G., Moritz G.L., Oroski E., de Goes R.E., Linhares R.R., Stadzisz P.C., Omori J.S., dos Santos R.B. (2020) A monitoring system for online fault detection and classification in photovoltaic plants, Sensors 20, 17, 4688. [CrossRef] [PubMed] [Google Scholar]
- Ghaderzadeh M., Hosseini A., Asadi F., Abolghasemi H., Bashash D., Roshanpoor A. (2022) Automated detection model in classification of B-lymphoblast cells from normal B-lymphoid precursors in blood smear microscopic images based on the majority voting technique, Sci. Program. 2022, 1–8. [Google Scholar]
- Garavand A., Behmanesh A., Aslani N., Sadeghsalehi H., Ghaderzadeh M. (2023) Towards diagnostic aided systems in coronary artery disease detection: a comprehensive multiview survey of the state of the art, Int. J. Intell. Syst. 2023, 1–19. [CrossRef] [Google Scholar]
- Fasihfar Z., Rokhsati H., Sadeghsalehi H., Ghadezadeh M., Gheisari M. (2023) AI-driven malaria diagnosis: developing a robust model for accurate detection and classification of malaria parasites, Iran. J. Blood Cancer 15, 112–124. [CrossRef] [Google Scholar]
- Ghaderzadeh M., Asadi F., Ramezan Ghorbani N., Almasi S., Taami T. (2023) Toward artificial intelligence (AI) applications in the determination of COVID-19 infection severity: considering AI as a disease control strategy in future pandemics, Iran. J. Blood Cancer 15, 3, 93–111. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.