Framework for autonomous inspection of PV plants using IoT electronics on each PV panel and UAV collaboration
This article details an autonomous monitoring and inspection system for photovoltaic (PV) installations, leveraging Unmanned Aerial Vehicles (UAV) collaboration and Internet of Things (IoT) technology. The system is part of a project aimed at optimizing the real-time control and operation of solar P...
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Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2025-04-01
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Series: | Energy Conversion and Management: X |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2590174525000108 |
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Summary: | This article details an autonomous monitoring and inspection system for photovoltaic (PV) installations, leveraging Unmanned Aerial Vehicles (UAV) collaboration and Internet of Things (IoT) technology. The system is part of a project aimed at optimizing the real-time control and operation of solar PV systems. This autonomous inspection system consists of two layers: (i) anomaly detection by on-board electronics of PV panels (referred as IoT Modules) and (ii) infrared (IR) and visual red, green, and blue (RGB) inspection by UAVs. The IoT Modules run a fault detection algorithm to identify anomalous events. Upon detection, they alert a UAV fleet equipped with RGB and IR cameras to conduct visual and thermal inspections of the affected PV panels. The inspection data is then relayed back to the IoT Modules, triggering appropriate actions. This framework enhances detection algorithms by providing rapid identification of severe issues. UAVs can quickly pinpoint hot-spots through thermographic imaging, enabling prompt intervention. Additionally, UAVs help resolve ambiguities in the detection on certain faults. Moreover, in order to make this autonomous inspection possible, a multiprotocol architecture is developed to ensure effective communication and coordination between IoT Modules and UAVs, facilitating seamless data exchange and system integration. |
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ISSN: | 2590-1745 |