The society and industry of today are in the continuous search of reduction of life and production costs, with the demands of using environmentally friendly practices to contribute to the current commitment of the TEC, the country and the world in the framework of Sustainable Development. Fortunately, photovoltaic (PV) generation technology manages to contribute in these aspects, implying that there are more and more generation facilities with a greater number of solar panels; aspect in which the TEC has joined prominently.

The use of the entire power generation system depends on its performance, which is maximum under optimal operating conditions; This has implied a one-day increase in maintenance practices that address the problems that arise undesirably. Due to this, extensive research has been developed for the detection of suboptimal conditions in PV systems, problems with the existence of a range of solar panel fault detection techniques. Each method has its capabilities and limitations, implying that PV installations must know how to select and use one or more techniques in their maintenance plans.

The project specifically aims to explore three of the most commonly used fault identification methods: visual inspection, infrared thermography, and analysis of electrical variables, to compare them with each other and provide scientific knowledge for the selection of each one. Also, knowing that they are different, a new method will be implemented that combines to achieve maximum use of the three. For this, the research aims to develop an experiment that takes advantage of the technology and infrastructure that TEC has, such as a large PV installation in operation with characteristics for research, unmanned vehicles (drones), meteorological instrumentation systems, among others