# Strategy Based on Two Stages for IR Thermographic Inspections of Photovoltaic Plants
## 1 Introduction  
The photovoltaic (PV) industry has experienced unprecedented growth in recent years as a consequence of the energy policies applied by many countries to drive the change to renewable energies and the decarbonisation of the economy. Despite the serious impact of the COVID-19 pandemic on the entire world, global accrued solar capacity had increased to 773.2 GW by 2020, representing a year-on-year increase of 22%, confirming the trend of recent years [1]. This growth in the PV sector has been particularly pronounced in the number of PV power plants and their installed capacity [2]. The PV plants constructed are increasingly larger and have increasingly larger installed power capacities. This situation requires specialised and efficient operation and maintenance (O&M) tasks, to ensure peak-performance operational continuity with the maximum energy use of systems to amortise the investments made [3, 4]. Large PV power plants are normally monitored and have an alert system for continuous supervision of their operations. The measurement and recording of electrical and atmospheric variables enable the intervention of the maintenance service before incidents and faults appear in the modules [5]. The monitoring systems can report possible failures if the measured amount of energy differs from the expected values [6]. The monitoring system should be adapted to the size of the PV system and user requirements. The largest and most costly photovoltaic systems are generally equipped with more monitoring points and sensors with greater precision than smaller and more economical photovoltaic systems [7]. Conducting infrared (IR) thermographic inspections for PV plant maintenance is an effective and reliable maintenance technique for detecting and locating incidents thatare thermal in nature [8,9]. IR imaging of PV modules permit the identification of early faults by non-contact surface temperature measurements [10,11]. The procedures for IR inspections of PV systems are well established in guides and technical specifications [12,13]. The growth in size of PV plants makes manual or ground-level thermographic inspections complex, due to the large areas and time involved in doing them. Further, the manual inspection can turn out to be extremely difficult in plants with trackers or modules with very slight tilt angles due to the height required. The use of unmanned aerial vehicles (UAVs) or drones to conduct these inspections can be done at great speed and reliability, making them a perfect tool for large plants [14,15]. Reducing inspection times entails a significant advantage for costs associated with PV plant operation and maintenance. Different studies have been executed in recent years to evaluate the potential of aerial IR thermography for inspecting photovoltaic systems. A comprehensive bibliographical review of different issues of aerial IR imaging is done in [16], where the authors conclude that this inspection technique for photovoltaic systems is still in its development phase. The evolution and technological development attained in the sensors and electronic instrumentation employed in aerial thermography has increased the possibilities of this technique [17]. The influence of image resolution on detecting faults in PV modules is studied in [18], with the results for different inspection heights compared. One study [19] on PV modules with hotspots compares thermographic results at the back and at different heights via aerial thermography. A general trend was observed of lower temperature measurements as the flight height increased. Automated planning of flight routes and fault detection in defective PV modules was studied in [20], proposing an automated algorithm for drone flight routes that eliminates the need to manually control the drones. The evaluation of faults by IR thermography-based orthomosaics is studied in [21,22], facilitating the location of faults. However, long flight times are required to create compound images and there is some spatial distortion.