UAV-based decision-making and modular approach to support PV plant diagnosis using EL, RGB, IRT imagery, correlated with electrical data analysis and advanced reporting and geovisualization.

The AID4PV project aims to research, develop and demonstrate in an operational environment a modular solution based on unmanned aerial vehicles (UAVs) for PV plant monitoring and advanced diagnostics. The autonomous UAV platform will capture photographic (RGB), thermographic (IRT) and electroluminescence (EL) images to enable near real-time fault detection, leading to PV plant diagnostics in time and cost. The results will be presented in an advanced reporting and geo-visualisation platform including geospatial analysis and visualisation tools. Decision support capabilities will also be investigated, adding the possibility to perform some kind of predefined actions from the UAV platform, minimising the time from detection of an anomaly to corrective actions.

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AID4PV Project

The AID4PV project has been initiated to face the main challenges of the PV industry and to provide an unmanned aerial vehicle (UAV) platform for decision-making and modular approach to support PV plant diagnosis. The decision-making capabilities will be investigated, adding the possibility to perform predefined actuations by the UAV-platform to perform remedy actions minimizing the timing since an anomaly is detected and certain actions are carried out. The UAV platform will capture EL, RGB & IRT imagery that when integrated with electrical data analysis, near real-time fault detection will occur, leading to time and cost-efficient PV plant diagnosis. The system will be controlled by a user-friendly geo-visualization interface with advanced reporting and operational functionalities.

The project has a total budget of €825.832,00 and is coordinated by the TSK Information Technologies Division. For the successful implementation of the project and development of the UAV platform for PV plant monitoring and advanced diagnostics, the project will be executed by a transnational consortium comprising of the TSK Information Technologies Division (TSK - Spain), University of Cyprus (UCY – Cyprus) and Technical University of Crete (TUC – Greece).


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