Photovoltaic (PV) generators have been established as one of the most important renewable energy sources in the last years and they will have a main role in the energy transition that is envisaged for the coming years according to the European Union Recovery Plan and the Green Deal. However, PV panels may suffer early degradation and failures that affect the PV system reliability and considerably reduce the energy production, not only on a specific panel but in the entire string to which the panel is connected. Therefore, it is important to develop diagnostic tools to improve energy yield, extend the lifetime of the panels, and improve the effectiveness of maintenance activities. Hence, this project aims to develop an online monitoring and diagnostic system, for PV panels, that uses the impedance spectrum (IS) to detect failures while they are operating at their maximum power point (MPP). Therefore, there isn’t a reduction in the power produced by the generator and the measurements can be performed within short time frames to detect the failures as soon as possible. The proposed diagnostic tool will be formed by an electronic device and a failure classification algorithm running on an embedded system. Hence, the project begins with the design and implementation of the electronic device to generate the signals and implement the measurements required to obtain the IS. Then, the project continues with the development of a failure classification algorithm from the analysis of the PV generator dynamic model parameters (DMP), which are estimated using the ISs obtained with the proposed electronic device. Finally, the diagnostic tool will be experimentally validated with PV panels of different technologies and with real failures.
