This paper compares multiple techniques to detect suboptimal conditions in the PV system. Detection of suboptimal conditions in the PV system is required to achieve optimal photovoltaic (PV) systems. Therefore, maintenance managers need to choose the most suitable techniques objectively. However, there is a lack of objective information comparing the effectiveness of the methods. This article calculates and compares the effectiveness of Infrared thermography (IRT), visual inspection (VI), and electrical analysis (EA) in detecting soiling, partial shadows, and electrical faults experimentally. The results showed that the VI was the best at detecting soiling and partial shading with 100% of effectiveness. IRT and EA had an effectiveness of 78% and 73%, respectively, detecting the three types of conditions under study. It was not possible to achieve maximum detection using only one of the techniques, but that VI must be combined with IR or EA. This research represents a significant contribution by achieving an objective comparison between techniques for detecting suboptimal conditions, being very useful to guide PV system maintainers and designers of fault detection techniques.

Large photovoltaic installations present faults that can reduce significantly their power yield. For instance, a protection fuse can compromise the performance of the array making that several solar modules stop generating. This work presents a fault detection system based on efficiency measurements of a solar array and its comparison to an expected theoretical efficiency which serves as a threshold that was modeled as a plane using parameters that can be obtained from the manufacturer’s data-sheet or by software simulation. A set of experiments were executed in order to validate the proposed fault detection algorithm under short-circuit, open-circuit and partial shadowing faults. The results show that this method could detect short circuits in bypass diodes, open circuits in protection fuses and shadows in the array in small solar systems.

This work proposes an automated reconfiguration system to manage two types of faults in any position inside the solar arrays. The faults studied are the short-circuit to ground and the open wires in the string. These faults were selected because they severely affect power production. By identifying the affected panels and isolating the faulty one, it is possible to recover part of the power loss. Among other types of faults that the system can detect and locate are: diode short-circuit, internal open-circuit, and the degradation of the internal parasitic serial resistance. The reconfiguration system can detect, locate the above faults, and switch the distributed commutators to recover most of the power loss. Moreover, the system can return automatically to the previous state when the fault has been repaired. A SIMULINK model has been built to prove this automatic system, and a simulated numerical experiment has been executed to test the system response to the faults mentioned. The results show that the recovery of power is more than 90%, and the diagnosis accuracy and sensitivity are both 100% for this numerical experiment.

In this paper a simple expression to calculate the efficiency as a function of the temperature and irradiance is presented. The proposed efficiency model has been validated and compared with other efficiency models reported in the scientific literature. Differently from the reported models, the proposed efficiency model only requires the data provided in the data sheet of photovoltaic modules and cells and it is not required to estimate parameters or perform measurements.