Determining Probable Locations of Photovoltaic Modules Malfunctions

dc.contributor.authorRubanenko, Olena
dc.contributor.authorBělík, Milan
dc.contributor.authorRubanenko, Oleksandr
dc.contributor.authorBobba, Phaneendra Babu
dc.contributor.authorSmaglo, Ivan
dc.contributor.authorLakshmi, G. Sree
dc.date.accessioned2025-06-20T08:37:26Z
dc.date.available2025-06-20T08:37:26Z
dc.date.issued2024
dc.date.updated2025-06-20T08:37:26Z
dc.description.abstractThis paper focuses on automation of processes applicable for fast and cheap diagnostics of PV plants. In general, there are some techniques commonly used for PV diagnostics (visual inspection, thermography, etc.). Main disadvantage of these methods is high time requirement and thus high labor costs. Smart usage of unmanned automated systems such as quadcopters can significantly increase the efficiency of the process and decrease the costs. But the process itself does not mean just the unmanned flight, but also the data acquisition. If we forget the legislative and technical complication of the flight and preflight preparation, the data analysis is the most complicated and time-consuming part. Particular steps of the analyses can be strongly optimized to decrease the time requirements but also affects technical aspects of the flight (UAS trajectory, operational time, battery consumption etc.). These aspects are being discusses and their influence on inspection methods is described. Application of these principles on single PV plant should decrease the time consumption and operational costs if compared to conventional diagnostic methods.en
dc.format6
dc.identifier.doi10.1109/SEFET61574.2024.10717959
dc.identifier.isbn979-8-3503-8399-7
dc.identifier.obd43945042
dc.identifier.orcidRubanenko, Olena 0000-0002-2660-182X
dc.identifier.orcidBělík, Milan 0000-0002-9907-5365
dc.identifier.urihttp://hdl.handle.net/11025/60491
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartofseries4th IEEE International Conference on Sustainable Energy and Future Electric Transportation, SEFET 2024
dc.subjectmalfunctionen
dc.subjectphotovoltaic moduleen
dc.subjectrenewable energy sourcesen
dc.subjectsolar stationen
dc.titleDetermining Probable Locations of Photovoltaic Modules Malfunctionsen
dc.typeStať ve sborníku (D)
dc.typeSTAŤ VE SBORNÍKU
dc.type.statusPublished Version
local.files.count1*
local.files.size1670645*
local.has.filesyes*
local.identifier.eid2-s2.0-85208960097

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