Determining Probable Locations of Photovoltaic Modules Malfunctions
| dc.contributor.author | Rubanenko, Olena | |
| dc.contributor.author | Bělík, Milan | |
| dc.contributor.author | Rubanenko, Oleksandr | |
| dc.contributor.author | Bobba, Phaneendra Babu | |
| dc.contributor.author | Smaglo, Ivan | |
| dc.contributor.author | Lakshmi, G. Sree | |
| dc.date.accessioned | 2025-06-20T08:37:26Z | |
| dc.date.available | 2025-06-20T08:37:26Z | |
| dc.date.issued | 2024 | |
| dc.date.updated | 2025-06-20T08:37:26Z | |
| dc.description.abstract | This 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.format | 6 | |
| dc.identifier.doi | 10.1109/SEFET61574.2024.10717959 | |
| dc.identifier.isbn | 979-8-3503-8399-7 | |
| dc.identifier.obd | 43945042 | |
| dc.identifier.orcid | Rubanenko, Olena 0000-0002-2660-182X | |
| dc.identifier.orcid | Bělík, Milan 0000-0002-9907-5365 | |
| dc.identifier.uri | http://hdl.handle.net/11025/60491 | |
| dc.language.iso | en | |
| dc.publisher | IEEE | |
| dc.relation.ispartofseries | 4th IEEE International Conference on Sustainable Energy and Future Electric Transportation, SEFET 2024 | |
| dc.subject | malfunction | en |
| dc.subject | photovoltaic module | en |
| dc.subject | renewable energy sources | en |
| dc.subject | solar station | en |
| dc.title | Determining Probable Locations of Photovoltaic Modules Malfunctions | en |
| dc.type | Stať ve sborníku (D) | |
| dc.type | STAŤ VE SBORNÍKU | |
| dc.type.status | Published Version | |
| local.files.count | 1 | * |
| local.files.size | 1670645 | * |
| local.has.files | yes | * |
| local.identifier.eid | 2-s2.0-85208960097 |
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