Detection of photovoltaic panel parameters pulse light

How do PV systems detect faults?

PV systems are affected by environmental conditions, making visual inspection of faults easy. Electroluminescence (EL), infrared thermography (IRT), and photoluminescence (PL) technologies are used to visualize faults. DL algorithms have shown promising results in visual PV fault detection.

Should PV system fault detection methods be based on onsite fault detection?

Future research directions are recommended for both industry and academia to advance PV fault detection methods. PV systems are prone to external environmental conditions that affect PV system operations. Visual inspection of the impacts of faults on PV system is considered a better practice rather than onsite fault detection mechanisms.

How complex is solar PV fault identification using image processing techniques?

It is also concluded that the complexity of precise solar PV fault identification using image processing techniques is more than other statistical approached. Exploring deep learning models with different input features can help in future research regarding concurrent and complex PV faults detection.

Why do PV panels need a fault diagnosis tool?

Continuous determination of faults must be carried out to protect the PV system from different losses, so a fault diagnosis tool is essential to the reliability and durability of the PV panels. Fault detection and diagnosis (FDD) methodologies include three main approaches as shown in Fig. 3.

What is PV fault detection using DL?

PV fault detection using DL enables the algorithms to identify and classify specific anomalies based on the characteristics of the given dataset . In addition, it is possible to modify a particular algorithm's learning parameters for the specific fault detection.

What are the different types of PV fault detection methods?

In the existing literature, three fundamental PV fault detection approaches are proposed, that are, vision-based detection, image-based detection with classification, and data analytics-based detection [, , , ]. Vision- and imaging-based techniques have been widely used to detect visual PV faults .