dc.contributor.author | Michail, Anna | en |
dc.contributor.author | Livera, Andreas | en |
dc.contributor.author | Tziolis, Georgios | en |
dc.contributor.author | Carús Candás, Juan Luis | en |
dc.contributor.author | Fernandez, Alberto | en |
dc.contributor.author | Antuña Yudego, Elena | en |
dc.contributor.author | Fernández Martínez, Diego | en |
dc.contributor.author | Antonopoulos, Angelos | en |
dc.contributor.author | Tripolitsiotis, Achilleas | en |
dc.contributor.author | Partsinevelos, Panagiotis | en |
dc.contributor.author | Koutroulis, Eftichis | en |
dc.contributor.author | Georghiou, George E. | en |
dc.contributor.editor | Heliyon, Elsevier | en |
dc.creator | Michail, Anna | en |
dc.creator | Livera, Andreas | en |
dc.creator | Tziolis, Georgios | en |
dc.creator | Carús Candás, Juan Luis | en |
dc.creator | Fernandez, Alberto | en |
dc.creator | Antuña Yudego, Elena | en |
dc.creator | Fernández Martínez, Diego | en |
dc.creator | Antonopoulos, Angelos | en |
dc.creator | Tripolitsiotis, Achilleas | en |
dc.creator | Partsinevelos, Panagiotis | en |
dc.creator | Koutroulis, Eftichis | en |
dc.creator | Georghiou, George E. | en |
dc.date.accessioned | 2024-01-11T10:30:46Z | |
dc.date.available | 2024-01-11T10:30:46Z | |
dc.date.issued | 2024-01-03 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/65941 | en |
dc.description.abstract | Accurate photovoltaic (PV) diagnosis is of paramount importance for reducing investment risk and increasing the bankability of the PV technology. The application of fault diagnostic solutions and troubleshooting on operating PV power plants is vital for ensuring optimal energy harvesting, increased power generation production and optimised field operation and maintenance (O&M)activities. This study aims to give an overview of the existing approaches for PV plant diagnosis, focusing on unmanned aerial vehicle (UAV)-based approaches, that can support PV plant di-agnostics using imaging techniques and data-driven analytics. This review paper initially outlines the different degradation mechanisms, failure modes and patterns that PV systems are subjected and then reports the main diagnostic techniques. Furthermore, the essential equipment and sensor’s requirements for diagnosing failures in monitored PV systems using UAV-based approaches are provided. Moreover, the study summarizes the operating conditions and the various failure types that can be detected by such diagnostic approaches. Finally, it provides recommendations and insights on how to develop a fully functional UAV-based diagnostic tool, capable of detecting and classifying accurately failure modes in PV systems, while also locating the exact position of faulty modules. | en |
dc.description.sponsorship | This work was funded by the AID4PV project, which is supported under the umbrella of SOLAR-ERA.NET Cofund 2 Additional Joint Call by the Centre for the Development of Industrial Technology (CDTI, IDI-20210170) in Spain, the General Secretariat for Research and Innovation (GSRI, Τ12ΕΡΑ5-00042) in Greece and the Research and Innovation Foundation (RIF, P2P/SOLAR/1019/0012) in Cyprus. The SOLAR-ERA.NET Cofund 2 Action is supported by funding from the European Union's HORIZON 2020 Research and Innovation Programme (Grant Agreement N° 786483). | en |
dc.language.iso | eng | en |
dc.publisher | Elsevier | en |
dc.relation | RIF, P2P/SOLAR/1019/0012 | en |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Greece | * |
dc.rights | info:eu-repo/semantics/openAccess | en |
dc.rights | Open Access | en |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/gr/ | * |
dc.source | Heliyon | en |
dc.source.uri | https://www.cell.com/heliyon/fulltext/S2405-8440(24)00014-8?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2405844024000148%3Fshowall%3Dtrue | en |
dc.subject | Fault diagnosis | en |
dc.subject | Image analysis | en |
dc.subject | Photovoltaic systems | en |
dc.subject | Unmanned aerial vehicles | en |
dc.title | A comprehensive review of unmanned aerial vehicle-based approaches to support photovoltaic plant diagnosis | en |
dc.type | info:eu-repo/semantics/article | en |
dc.identifier.doi | 10.1016/j.heliyon.2024.e23983 | |
dc.description.volume | 10 | |
dc.description.issue | 1 | |
dc.author.faculty | 007 Πολυτεχνική Σχολή / Faculty of Engineering | |
dc.author.department | Τμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών / Department of Electrical and Computer Engineering | |
dc.type.uhtype | Article | en |
dc.contributor.orcid | Michail, Anna [0000-0001-5139-6007] | |
dc.contributor.orcid | Livera, Andreas [0000-0002-3732-9171] | |
dc.contributor.orcid | Tziolis, Georgios [0000-0002-7241-3192] | |
dc.contributor.orcid | Antuña Yudego, Elena [0000-0001-5962-158X] | |
dc.contributor.orcid | Fernández Martínez, Diego [0009-0006-6908-3977] | |
dc.contributor.orcid | Antonopoulos, Angelos [0009-0002-9904-9383] | |
dc.contributor.orcid | Tripolitsiotis, Achilleas [0000-0003-4857-9237] | |
dc.contributor.orcid | Partsinevelos, Panagiotis [0000-0002-3792-953X] | |
dc.contributor.orcid | Koutroulis, Eftichis [0000-0003-1285-8840] | |
dc.contributor.orcid | Georghiou, George E. [0000-0002-5872-5851] | |
dc.type.subtype | SCIENTIFIC_JOURNAL | en |
dc.gnosis.orcid | 0000-0001-5139-6007 | |
dc.gnosis.orcid | 0000-0002-3732-9171 | |
dc.gnosis.orcid | 0000-0002-7241-3192 | |
dc.gnosis.orcid | 0000-0001-5962-158X | |
dc.gnosis.orcid | 0009-0006-6908-3977 | |
dc.gnosis.orcid | 0009-0002-9904-9383 | |
dc.gnosis.orcid | 0000-0003-4857-9237 | |
dc.gnosis.orcid | 0000-0002-3792-953X | |
dc.gnosis.orcid | 0000-0003-1285-8840 | |
dc.gnosis.orcid | 0000-0002-5872-5851 | |