An Inspection Mode Based on Unmanned Aerial Vehicle for
Due to the limitations of the low efficiency of human inspection affected by geographical environment, and the difficulties in locating failure position caused by the lack of data support
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 diagnostics using imaging techniques and data-driven analytics.
Abstract: This article addresses the design of a fully automated photovoltaic (PV) power plant inspection process by a fleet of unmanned aerial and ground vehicles (UAVs/UGVs).
In their study, aerial data were taken using a UAV drone, collecting RGB images to build an orthophoto of the PV system and used it as an interactive map in the GIS application. In addition, thermal photos were captured and reviewed using ThermoViewer. On the other hand, ground data were acquired with I–V curve tests.
Multi-rotor cleaning drones for distributed PV stations are 40+ times more efficient than manual cleaning, using only 10% water and 1/3 cost, with >90% dust removal. This addresses manual inefficiency and cleaning difficulty, offering a new technical solution for specialized, refined distributed PV systems.
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