UAV photovoltaic panel testing

Can a UAV be used to inspect a photovoltaic plant?

For more information on the journal statistics, click here . Multiple requests from the same IP address are counted as one view. Because photovoltaic (PV) plants require periodic maintenance, using unmanned aerial vehicles (UAV) for inspections can help reduce costs. Usually, the thermal and visual inspection of PV installations works as follows.

Are aircraft-based inspections better than UAV surveys for solar PV plants?

Airplane-based inspections are more convenient than UAV surveys for PV plants > 40 MW. The continuous increase in the number and scale of solar photovoltaic power plants requires the implementation of reliable diagnostic tools for fault detection.

Can uav photogrammetry be used for Autonomous inspection of PV plants?

The autonomous inspection of PV plants through UAV photogrammetry has been explored in the literature , , , . The UAV is given a set of waypoints, usually arranged in such a way to cover a delimited area to ensure the required horizontal and vertical overlapping of images.

Can an autonomous UAV track a PV module without a GPS?

The article proposes a novel approach using an autonomous UAV with an RGB and a thermal camera for PV module tracking through segmentation and visual servoing, which does not require a GPS except for measuring the “small” relative displacement between a PV module row and the next one.

Can UAV-based approaches support PV plant diagnostics?

Focus was shed on UAV-based approaches, that can support PV plant diagnostics using imaging techniques and data analytics. In this context, the essential equipment needed and the sensor requirements (parameters and resolution) for the diagnosis of failures in monitored PV systems using UAV-based approaches were outlined.

Can UAV be used for fault diagnosis in PV systems?

Overview of the 51 investigated studies which used UAV for the acquisition of data for fault diagnosis in PV systems. Fault diagnosis methods used: EL, IRT, RGB images and combination of methods. 6. Conclusions Accurate fault identification is critical for reducing investment risk and increasing the PV technology's bankability.