Basic techniques for failure diagnosis PV module undergoes several standard quality tests before it is supplied to customers. Those tests' primary objective is to determine the possible factors that cause a breakdown of the solar panel, which is the heart of a PV system.
The method includes as inputs the solar irradiation and module temperature of the PVM and then using this information together with the characteristics captured from the PV power generation system, provide fault diagnosis, including Pm, I m, V m and V oc of the PVA during operation. Investigated faults are reported in Table 8.
After the I–V curve measurement technique, IR imaging, EL imaging, EBIC imaging, visual inspection (VI) method, and CBC method represented 19%, 17%, 10%, 5%, and 2% of the reviewed PV module defect detection technique, respectively.
Moreover, to generalize the PV cell defect detection methods, this paper divide them into (i) imaging-based techniques, (ii) rapid visual inspection methods, and (iii) I–V curve measurements, which are the most powerful diagnostic tools for field-level testing.
A fault detection method for photovoltaic module under partially shaded conditions is introduced in . It uses an ANN in order to estimate the output photovoltaic current and voltage under variable working conditions. The results confirm the ability of the technique to correctly localise and identify the different types of faults.
This technique is typically used to identify defects in a PV module, such as structural defects that may arise from imperfect semiconductor processes, unmatched crystalline lattices, or faulty electrical connections [ 44 ].