Determining Probable Locations of Photovoltaic Modules Malfunctions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F24%3A43974041" target="_blank" >RIV/49777513:23220/24:43974041 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10717959" target="_blank" >https://ieeexplore.ieee.org/document/10717959</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SEFET61574.2024.10717959" target="_blank" >10.1109/SEFET61574.2024.10717959</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Determining Probable Locations of Photovoltaic Modules Malfunctions

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Determining Probable Locations of Photovoltaic Modules Malfunctions

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2024 IEEE 4th International Conference on Sustainable Energy and Future Electric Transportation (SEFET) : proceedings

ISBN

979-8-3503-8399-7

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

—

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Hyderabad, India

Datum konání akce

31. 7. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—