| Issue |
EPJ Photovolt.
Volume 14, 2023
Special Issue on ‘EU PVSEC 2023: State of the Art and Developments in Photovoltaics’, edited by Robert Kenny and João Serra
|
|
|---|---|---|
| Article Number | 36 | |
| Number of page(s) | 10 | |
| Section | Modules and Systems | |
| DOI | https://doi.org/10.1051/epjpv/2023026 | |
| Published online | 20 November 2023 | |
- G.M. Tina, C. Ventura, Monitoring and diagnostic of photovoltaic power plants, Renew. Energ. Service Mankind 2, 505 (2016) [CrossRef] [Google Scholar]
- U. Pruthviraj, Y Kashyap, Solar photovoltaic hotspot inspection using unmanned aerial vehicle thermal images at a solar field in South India, Remote Sens. 15, 1914 (2023) [Google Scholar]
- K. Natarajan, B. Praveen Kumar, Fault detection of solar PV system using SVM and thermal image processing, Int. J. Renew. Energ. Res. 10, 2 (2020) [Google Scholar]
- L. Jiang, D. Maskell, Automatic fault detection and diagnosis for photovoltaic systems using combined artificial neural network and analytical based methods, in International Joint Conference on Neural Networks (IJCNN) (2015) [Google Scholar]
- B. Mekki, A. Mellit, H. Salhi, Artificial neural network-based modelling and fault detection of partial shaded photovoltaic modules, Simul. Model. Pract Theory 67, 1 (2016) [CrossRef] [Google Scholar]
- M. Dhimish, G. Badran, Photovoltaic hot-spots fault detection algorithm using fuzzy systems, IEEE Trans. Device Mater. Reliab. 19, 671 (2019) [CrossRef] [Google Scholar]
- M. Hussain, M. Dhimish, S. Titarenko, P. Mather, Artificial neural network based photovoltaic fault detection algorithm integrating two bi-directional input parameters, Renew. Energy 155, 1272 (2020) [CrossRef] [Google Scholar]
- Z. Yuan, G. Xiong, X. Fu, Artificial neural network for fault diagnosis of solar photovoltaic systems: a survey, Energies 15, 8693 (2022) [CrossRef] [Google Scholar]
- S. Spataru, D. Sera, Diagnostic method for photovoltaic systems based on light I-V measurements, Sol. Energy 119, 29 (2015) [CrossRef] [Google Scholar]
- A. Minuto, E. Celi, G. Timò, N. Panozzo, New maximum power point tracking MPPT algorithm based on research of a target voltage range and its implementation in a commercial inverter for photovoltaic systems, in Proceedings of the 37th EUPVSEC (2020), pp. 939–944 [Google Scholar]
- F. Wang, X. Lu, S. Mei, A satellite image data based ultra-short-term solar PV power forecasting method considering cloud information from neighboring plant, Energy 238, 121946 (2021) [PubMed] [Google Scholar]
- S. Krauter, J. Bendfeld, Deviations of results for energy yield from efficiency rankings of microinverters, in Proceedings of the 32nd EUPVSEC (2016) [Google Scholar]
- S. Krauter, J. Bendfeld, Update on rankings of conversion efficiencies and energy yield of micro-inverters, including inverters for two PV modules, in Proceedings of the 33rd EUPVSEC (2017), pp. 1477–1482 [Google Scholar]
- European patent N. EP 3249 492B1 [Google Scholar]
- M. Pravettoni, D. Poh, The effect of capacitance on high-efficiency photovoltaic modules: a review of testing methods and related uncertainties, J. Phys. D: Appl. Phys. 54, 193001 (2021) [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.